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Luo Y, Hu Q, Yu Y, Lyu W, Shen F. Experimental investigation of confinement effect in single molecule amplification via real-time digital PCR on a multivolume droplet array SlipChip. Anal Chim Acta 2024; 1304:342541. [PMID: 38637051 DOI: 10.1016/j.aca.2024.342541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Revised: 03/19/2024] [Accepted: 03/25/2024] [Indexed: 04/20/2024]
Abstract
BACKGROUND Digital polymerase chain reaction (digital PCR) is an important quantitative nucleic acid analysis method in both life science research and clinical diagnostics. One important hypothesis is that by physically constraining a single nucleic acid molecule in a small volume, the relative concentration can be increased therefore further improving the analysis performance, and this is commonly defined as the confinement effect in digital PCR. However, experimental investigation of this confinement effect can be challenging since it requires a microfluidic device that can generate partitions of different volumes and an instrument that can monitor the kinetics of amplification. (96). RESULTS Here, we developed a real-time digital PCR system with a multivolume droplet array SlipChip (Muda-SlipChip) that can generate droplet of 125 nL, 25 nL, 5 nL, and 1 nL by a simple "load-slip" operation. In the digital region, by reducing the volume, the relative concentration is increased, the amplification kinetic can be accelerated, and the time to reach the fluorescence threshold, or Cq value, can be reduced. When the copy number per well is much higher than one, the relative concentration is independent of the partition volume, thus the amplification kinetics are similar in different volume partitions. This system is not limited to studying the kinetics of digital nucleic acid amplification, it can also extend the dynamic range of the digital nucleic acid analysis by additional three orders of magnitude by combining a digital and an analog quantification algorithm. (140). SIGNIFICANCE In this study, we experimentally investigated for the first time the confinement effect in the community of digital PCR via a new real-time digital PCR system with a multivolume droplet array SlipChip (Muda-SlipChip). And a wider dynamic range of quantification methods compared to conventional digital PCR was validated by this system. This system provides emerging opportunities for life science research and clinical diagnostics. (63).
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Affiliation(s)
- Yang Luo
- School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Hua Shan Road, Shanghai, 200030, PR China
| | - Qixin Hu
- School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Hua Shan Road, Shanghai, 200030, PR China
| | - Yan Yu
- School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Hua Shan Road, Shanghai, 200030, PR China
| | - Weiyuan Lyu
- School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Hua Shan Road, Shanghai, 200030, PR China
| | - Feng Shen
- School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Hua Shan Road, Shanghai, 200030, PR China.
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Bratash O, Buhot A, Leroy L, Engel E. Optical fiber biosensors toward in vivo detection. Biosens Bioelectron 2024; 251:116088. [PMID: 38335876 DOI: 10.1016/j.bios.2024.116088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 01/19/2024] [Accepted: 01/28/2024] [Indexed: 02/12/2024]
Abstract
This review takes stock of the various optical fiber-based biosensors that could be used for in vivo applications. We discuss the characteristics that biosensors must have to be suitable for such applications and the corresponding transduction modes. In particular, we focus on optical fiber biosensors based on fluorescence, evanescent wave, plasmonics, interferometry, and Raman phenomenon. The operational principles, implemented solutions, and performances are described and debated. The different sensing configurations, such as the side- and tip-based fiber biosensors, are illustrated, and their adaptation for in vivo measurements is discussed. The required implementation of multiplexed biosensing on optical fibers is shown. In particular, the use of multi-fiber assemblies, one of the most optimal configurations for multiplexed detection, is discussed. Different possibilities for multiple localized functionalizations on optical fibers are presented. A final section is devoted to the practical in vivo use of fiber-based biosensors, covering regulatory, sterilization, and packaging aspects. Finally, the trends and required improvements in this promising and emerging field are analyzed and discussed.
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Affiliation(s)
- Oleksii Bratash
- Univ. Grenoble Alpes, CEA, CNRS, Grenoble INP, IRIG, SyMMES, 38000, Grenoble, France
| | - Arnaud Buhot
- Univ. Grenoble Alpes, CEA, CNRS, Grenoble INP, IRIG, SyMMES, 38000, Grenoble, France
| | - Loïc Leroy
- Univ. Grenoble Alpes, CEA, CNRS, Grenoble INP, IRIG, SyMMES, 38000, Grenoble, France
| | - Elodie Engel
- Univ. Grenoble Alpes, CEA, CNRS, Grenoble INP, IRIG, SyMMES, 38000, Grenoble, France.
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Li B, Li G, Liu J, Sun H, Wen C, Yang Y, Qiao A, Liu J, Liu Y. Deep-learning-based real-time individualization for reduce-order haemodynamic model. Comput Biol Med 2024; 174:108476. [PMID: 38636328 DOI: 10.1016/j.compbiomed.2024.108476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 03/18/2024] [Accepted: 04/11/2024] [Indexed: 04/20/2024]
Abstract
The reduced-order lumped parameter model (LPM) has great computational efficiency in real-time numerical simulations of haemodynamics but is limited by the accuracy of patient-specific computation. This study proposed a method to achieve the individual LPM modeling with high accuracy to improve the practical clinical applicability of LPM. Clinical data was collected from two medical centres comprising haemodynamic indicators from 323 individuals, including brachial artery pressure waveforms, cardiac output data, and internal carotid artery flow waveforms. The data were expanded to 5000 synthesised cases that all fell within the physiological range of each indicator. LPM of the human blood circulation system was established. A double-path neural network (DPNN) was designed to input the waveforms of each haemodynamic indicator and their key features and then output the individual parameters of the LPM, which was labelled using a conventional optimization algorithm. Clinically collected data from the other 100 cases were used as the test set to verify the accuracy of the individual LPM parameters predicted by DPNN. The results show that DPNN provided good convergence in the training process. In the test set, compared with clinical measurements, the mean differences between each haemodynamic indicator and the estimate calculated by the individual LPM based on the DPNN were about 10 %. Furthermore, DPNN prediction only takes 4 s for 100 cases. The DPNN proposed in this study permits real-time and accurate individualization of LPM's. When facing medical issues involving haemodynamics, it lays the foundation for patient-specific numerical simulation, which may be beneficial for potential clinical application.
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Affiliation(s)
- Bao Li
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
| | - Guangfei Li
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China.
| | - Jincheng Liu
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
| | - Hao Sun
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
| | - Chuanqi Wen
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
| | - Yang Yang
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
| | - Aike Qiao
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
| | - Jian Liu
- Department of Cardiology, Peking University People's Hospital, Beijing, China
| | - Youjun Liu
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
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Liang SGS, Fan ESL, Lam PK, Kwok WT, Ma CZH, Lam FMH. The effect of adding real-time postural feedback in balance and mobility training in older adults: A systematic review and meta-analysis. Arch Gerontol Geriatr 2024; 123:105439. [PMID: 38643641 DOI: 10.1016/j.archger.2024.105439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 03/26/2024] [Accepted: 04/05/2024] [Indexed: 04/23/2024]
Abstract
OBJECTIVES This study aimed to systematically review the additional value of providing real-time postural feedback during balance and mobility training in older people. METHODS PubMed, Embase, CINAHL, and Web-of-Science were searched from inception to August 2023. Studies comparing the effectiveness of feedback-based versus non-feedback-based postural balance or mobility training on balance or mobility outcomes were selected. Similar outcomes were pooled in meta-analyses using a random-effect model. The quality of evidence for available outcomes was rated by Grading of Recommendations Assessment, Development and Evaluation (GRADE). RESULTS Eight studies were identified with 203 subjects. Two studies showed that providing postural feedback immediately improved stability in static balance and gait. For the post-training effect, however, no significant change was found in trunk movement during single-leg standing (i.e., pitch angle, MD=0.65, 95 %CI=-0.77 to 2.07, low-quality; roll angle, MD=0.96, 95 %CI=-0.87 to 2.80, moderate-quality), in the Mini-BESTest (MD=1.88, 95 %CI=-0.05 to 3.80, moderate-quality), and in balance confidence (MD=0.29, 95 %CI=-3.43 to 4.2, moderate-quality). A worsened functional reach distance was associated with providing feedback during balance training (MD=-3.26, 95 %CI=-6.31 to -0.21, high-quality). Meta-analyses on mobility outcomes were mostly insignificant, except for the trunk-roll angle of walking (MD=0.87, 95 %CI=0.05 to 1.70, low-quality) and trunk-pitch angle of walking with head-turning (MD=1.87, 95 %CI=0.95 to 2.79, moderate-quality). CONCLUSION Adding real-time postural feedback to balance and mobility training might immediately improve stability in balance and mobility in older people. However, mixed results were reported for its post-training effect.
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Affiliation(s)
- Sam Guo-Shi Liang
- Department of Rehabilitation Sciences, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong
| | - Eva Si-Long Fan
- Department of Rehabilitation Sciences, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong
| | - Pik Kwan Lam
- Department of Rehabilitation Sciences, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong
| | - Wing Tung Kwok
- Department of Rehabilitation Sciences, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong
| | - Christina Zong-Hao Ma
- Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong
| | - Freddy Man-Hin Lam
- Department of Rehabilitation Sciences, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
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Wilms LM, Radke KL, Abrar DB, Frahm J, Voit D, Thelen S, Klee D, Grunz JP, Müller-Lutz A, Nebelung S. Dynamic assessment of scapholunate ligament status by real-time magnetic resonance imaging: an exploratory clinical study. Skeletal Radiol 2024; 53:791-800. [PMID: 37819279 PMCID: PMC10858828 DOI: 10.1007/s00256-023-04466-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 09/25/2023] [Accepted: 09/25/2023] [Indexed: 10/13/2023]
Abstract
OBJECTIVE Clinical-standard MRI is the imaging modality of choice for the wrist, yet limited to static evaluation, thereby potentially missing dynamic instability patterns. We aimed to investigate the clinical benefit of (dynamic) real-time MRI, complemented by automatic analysis, in patients with complete or partial scapholunate ligament (SLL) tears. MATERIAL AND METHODS Both wrists of ten patients with unilateral SLL tears (six partial, four complete tears) as diagnosed by clinical-standard MRI were imaged during continuous active radioulnar motion using a 1.5-T MRI scanner in combination with a custom-made motion device. Following automatic segmentation of the wrist, the scapholunate and lunotriquetral joint widths were analyzed across the entire range of motion (ROM). Mixed-effects model analysis of variance (ANOVA) followed by Tukey's posthoc test and two-way ANOVA were used for statistical analysis. RESULTS With the increasing extent of SLL tear, the scapholunate joint widths in injured wrists were significantly larger over the entire ROM compared to those of the contralateral healthy wrists (p<0.001). Differences between partial and complete tears were most pronounced at 5°-15° ulnar abduction (p<0.001). Motion patterns and trajectories were altered. Complete SLL deficiency resulted in complex alterations of the lunotriquetral joint widths. CONCLUSION Real-time MRI may improve the functional diagnosis of SLL insufficiency and aid therapeutic decision-making by revealing dynamic forms of dissociative instability within the proximal carpus. Static MRI best differentiates SLL-injured wrists at 5°-15° of ulnar abduction.
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Affiliation(s)
- Lena Marie Wilms
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, Moorenstrasse 5, D-40225, Dusseldorf, Germany.
| | - Karl Ludger Radke
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, Moorenstrasse 5, D-40225, Dusseldorf, Germany
| | - Daniel Benjamin Abrar
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, Moorenstrasse 5, D-40225, Dusseldorf, Germany
| | - Jens Frahm
- Biomedical NMR, Max Planck Institute for Multidisciplinary Sciences, D-37077, Goettingen, Germany
| | - Dirk Voit
- Biomedical NMR, Max Planck Institute for Multidisciplinary Sciences, D-37077, Goettingen, Germany
| | - Simon Thelen
- Department of Orthopaedics and Trauma Surgery, Medical Faculty, University Dusseldorf, D-40225, Dusseldorf, Germany
| | - Dirk Klee
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, Moorenstrasse 5, D-40225, Dusseldorf, Germany
- Department of General Pediatrics, University Dusseldorf, Medical Faculty, University Children's Hospital, Heinrich-Heine-University Dusseldorf, Moorenstrasse 5, Düsseldorf, Germany
| | - Jan-Peter Grunz
- Department of Diagnostic and Interventional Radiology, University Hospital Wurzburg, D-97080, Würzburg, Germany
| | - Anja Müller-Lutz
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, Moorenstrasse 5, D-40225, Dusseldorf, Germany
| | - Sven Nebelung
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, Moorenstrasse 5, D-40225, Dusseldorf, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Aachen, D-52074, Aachen, Germany
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Zrenner C, Ziemann U. Closed-Loop Brain Stimulation. Biol Psychiatry 2024; 95:545-552. [PMID: 37743002 PMCID: PMC10881194 DOI: 10.1016/j.biopsych.2023.09.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 08/24/2023] [Accepted: 09/18/2023] [Indexed: 09/26/2023]
Abstract
In the same way that beauty lies in the eye of the beholder, what a stimulus does to the brain is determined not simply by the nature of the stimulus but by the nature of the brain that is receiving the stimulus at that instant in time. Over the past decades, therapeutic brain stimulation has typically applied open-loop fixed protocols and has largely ignored this principle. Only recent neurotechnological advancements have enabled us to predict the nature of the brain (i.e., the electrophysiological brain state in the next instance in time) with sufficient temporal precision in the range of milliseconds using feedforward algorithms applied to electroencephalography time-series data. This allows stimulation exclusively whenever the targeted brain area is in a prespecified excitability or connectivity state. Preclinical studies have shown that repetitive stimulation during a particular brain state (e.g., high-excitability state), but not during other states, results in lasting modification (e.g., long-term potentiation) of the stimulated circuits. Here, we survey the evidence that this is also possible at the systems level of the human cortex using electroencephalography-informed transcranial magnetic stimulation. We critically discuss opportunities and difficulties in developing brain state-dependent stimulation for more effective long-term modification of pathological brain networks (e.g., in major depressive disorder) than is achievable with conventional fixed protocols. The same real-time electroencephalography-informed transcranial magnetic stimulation technology will allow closing of the loop by recording the effects of stimulation. This information may enable stimulation protocol adaptation that maximizes treatment response. This way, brain states control brain stimulation, thereby introducing a paradigm shift from open-loop to closed-loop stimulation.
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Affiliation(s)
- Christoph Zrenner
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Institute for Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada; Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany.
| | - Ulf Ziemann
- Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.
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Lin HC, Xiao SX. Achievement of Dynamic Tablet Defect Detection Mechanism Using Biaxial Slope Symmetry Algorithm. J Pharm Sci 2024:S0022-3549(24)00089-3. [PMID: 38484876 DOI: 10.1016/j.xphs.2024.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2023] [Revised: 03/06/2024] [Accepted: 03/07/2024] [Indexed: 03/24/2024]
Abstract
An inspection in tablet appearance integrity before bottling is regarded as a routine task in a pharmaceutical factory. Although some methods such as automated optical instrument, video or artificial intelligence (AI) are currently available in industry, it usually pays for a complex computational process as well as high cost. Based on the symmetry of tablet appearance in reality, this study develops a biaxial scanning slope symmetry algorithm to realize a dynamic real-time tablet defect detection with a simple arithmetic operation. First, the tablet is discretely scanned using image sensor in two axes, i.e. X and Y directions, simultaneously. Second, the analogy output signals generated from the sensor during the scanning process is discretely digitized and stored in an array. Third, the coordinate of center point in the series data array is identified from every line scanning. Fourth, every section slope between two nearby center points from the first to last lines is formulated and calculated sequentially. Finally, the square mean error (SME) is used to evaluate the shape defect situation according to all accumulated errors from every slope variation. The experimental results verify that the proposed algorithm can achieve both fast and accurate detection performance.
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Affiliation(s)
- Hsiung-Cheng Lin
- Department of Electronic Engineering, National Chin-Yi University of Technology, Taichung, Taiwan.
| | - Sheng-Xi Xiao
- Department of Electronic Engineering, National Chin-Yi University of Technology, Taichung, Taiwan
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Dai Y, Shi X, Huang Z, Du W, Cheng J. Proposal of policies based on temporal-spatial dynamic characteristics and co-benefits of CO 2 and air pollutants from vehicles in Shanghai, China. J Environ Manage 2024; 351:119736. [PMID: 38064982 DOI: 10.1016/j.jenvman.2023.119736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 11/21/2023] [Accepted: 11/27/2023] [Indexed: 01/14/2024]
Abstract
In megacities, vehicle emissions face urgent challenges related to air pollution and CO2 control. To achieve the refinement of vehicle control policies for the co-control of air pollutants and CO2, this study established a vehicle emission inventory with high spatial and temporal resolution based on the hourly traffic flow in Shanghai and analyzed the spatial and temporal distribution characteristics of the real-time vehicle emissions. Meanwhile, a policy evaluation framework was constructed by combining pollutant emission predictions with quantitative co-control effect assessments. The results indicated that spatio-temporal variations in different air pollutants and CO2 could mainly be attributed to primary contributing vehicle types. The pollutants (CO2, CO and VOCs) primarily contributed by private cars exhibited a bimodal pattern in 24-h time series and their spatial distribution was concentrated in the urban city center. The spatial distribution of NOx and PM primarily contributed by heavy trucks was still obvious on non-urban center areas. Furthermore, the results of synergistic effect analysis revealed that the alternative energy replacement scenario demonstrated the most significant potential for the co-control. Based on temporal-spatial and co-benefit analysis, the precise control policy of vehicle emissions can be established through time-, region-, and model-control. This study provides references and research methods for the formulation of the vehicle refinement control policies in worldwide megacities.
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Affiliation(s)
- Yuntong Dai
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Xiahong Shi
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Zining Huang
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Weiyi Du
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jinping Cheng
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
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Zhu C, Zhang S, Shen L, Ye L, Zhan M, Cai S, Huang J, Wang Z, Chen H. Changes in the characteristics and outcomes of high-risk pregnant women who delivered prior to and after China's universal two-child policy: a real-world retrospective study, 2010-2021. BMC Public Health 2024; 24:336. [PMID: 38297279 PMCID: PMC10829306 DOI: 10.1186/s12889-024-17810-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 01/18/2024] [Indexed: 02/02/2024] Open
Abstract
BACKGROUND In 2016, the "universal two-child" policy, allowing each couple to have two children, was introduced in China. The characteristic change of the long-term period after the implementation of the universal two-child policy was unclear. We studied trends in the obstetric characteristics and their potential impact on the rates of cesarean section and preterm birth in the era of China's universal two-child policy. METHODS A tertiary center-based study (2010-2021) retrospectively focused single high-risk pregnancies who delivered from the one-child policy period (OCP, 2010-2015) to the universal two-child policy period (TCP, 2016-2021). A total of 39, 016 pregnancies were enrolled. Maternal demographics, complications, delivery mode and obstetric outcomes were analyzed. Furthermore, logistic regression analysis was used to explore the association between the cesarean section rate, preterm birth and implementation of the universal two-child policy, adjusting maternal age, parity, and fetal distress. RESULTS Ultimately a total of 39,016 pregnant women met the criteria and were included in this analysis. The proportion of women with advanced maternal age (AMA) increased from 14.6% in the OCP to 31.6% in the TCP. The number of multiparous women increased 2-fold in the TCP. In addition, the overall rate of cesarean section significantly decreased over the policy change, regardless of maternal age, whereas the risk of preterm birth significantly increased in the TCP. Adjusting for maternal age, parity and fetal distress, the universal two-child policy showed a significantly favorable impact on the cesarean section rate (RR 0.745, 95%CI (0.714-0.777), P < 0.001). Compared to the OCP group, a higher increase in fetal distress and premature rupture of membranes (PROM) were observed in the TCP group. In pregnancies with AMA, there was no increase in the risk of postpartum hemorrhage, whereas more women who younger than 35 years old suffered from postpartum hemorrhage in TCP. The logistic regression model showed that the universal two-child policy was positively associated with the risk of postpartum hemorrhage (RR: 1.135, 95%CI: 1.025-1.257, P = 0.015). CONCLUSIONS After the implementation of the universal two-child policy in China, the rate of the cesarean section significantly decreased, especially for women under 35 years old. However, the overall risk of postpartum hemorrhage increased in women under 35 years old, while there was no change in women with AMA. Under the new population policy, the prevention of postpartum hemorrhage in the young women should not be neglected.
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Affiliation(s)
- Caixia Zhu
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Shaofeng Zhang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Lixia Shen
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Lisha Ye
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Minjin Zhan
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Shiqin Cai
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Jingwan Huang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Zilian Wang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
| | - Haitian Chen
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
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Ali Y, Hussain F, Haque MM. Advances, challenges, and future research needs in machine learning-based crash prediction models: A systematic review. Accid Anal Prev 2024; 194:107378. [PMID: 37976634 DOI: 10.1016/j.aap.2023.107378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 10/29/2023] [Accepted: 11/08/2023] [Indexed: 11/19/2023]
Abstract
Accurately modelling crashes, and predicting crash occurrence and associated severities are a prerequisite for devising countermeasures and developing effective road safety management strategies. To this end, crash prediction modelling using machine learning has evolved over two decades. With the advent of big data that provides unprecedented opportunities to better understand the crash mechanism and its determinants, such efforts will likely be accelerated. To gear these efforts, understanding state-of-the-art machine learning-based crash prediction models becomes paramount to summarise the lessons learned from past efforts, which can assist in developing robust and accurate models. This review paper aims to address this gap by systematically reviewing the machine learning studies on crash modelling. Models are reviewed from three aspects of the application: (a) crash occurrence (or real-time crash) prediction, (b) crash frequency prediction, and (c) injury severity prediction. Further, model intricacies that impact model performance are identified and thoroughly reviewed. This comprehensive review highlights specific gaps and future research needs in three aforementioned model applications, such as improper selection of non-crash events for crash occurrence models, the inability of future forecasting of crash frequency models, and inconsistency in injury severity classes. Critical research needs relating to model development, evaluation, and application are also discussed. This review envisages methodological advancements in machine learning models for crash prediction modelling and leveraging big data to better link crashes with its determinants.
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Affiliation(s)
- Yasir Ali
- School of Architecture, Building, and Civil Engineering, Loughborough University, Leicestershire LE11 3TU, United Kingdom.
| | - Fizza Hussain
- Queensland University of Technology, School of Civil & Environment Engineering, Faculty of Engineering, Brisbane 4001, Australia.
| | - Md Mazharul Haque
- Queensland University of Technology, School of Civil & Environment Engineering, Faculty of Engineering, Brisbane 4001, Australia.
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11
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Vetter DE, Zrenner C, Belardinelli P, Mutanen TP, Kozák G, Marzetti L, Ziemann U. Targeting motor cortex high-excitability states defined by functional connectivity with real-time EEG-TMS. Neuroimage 2023; 284:120427. [PMID: 38008297 PMCID: PMC10714128 DOI: 10.1016/j.neuroimage.2023.120427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 09/19/2023] [Accepted: 10/25/2023] [Indexed: 11/28/2023] Open
Abstract
We tested previous post-hoc findings indicating a relationship between functional connectivity (FC) in the motor network and corticospinal excitability (CsE), in a real-time EEG-TMS experiment in healthy participants. We hypothesized that high FC between left and right motor cortex predicts high CsE. FC was quantified in real-time by single-trial phase-locking value (stPLV), and TMS single pulses were delivered based on the current FC. CsE was indexed by motor-evoked potential (MEP) amplitude in a hand muscle. Possible confounding factors (pre-stimulus μ-power and phase, interstimulus interval) were evaluated post hoc. MEPs were significantly larger during high FC compared to low FC. Post hoc analysis revealed that the FC condition showed a significant interaction with μ-power in the stimulated hemisphere. Further, inter-stimulus interval (ISI) interacted with high vs. low FC conditions. In summary, FC was confirmed to be predictive of CsE, but should not be considered in isolation from μ-power and ISI. Moreover, FC was complementary to μ-phase in predicting CsE. Motor network FC is another marker of real-time accessible CsE beyond previously established markers, in particular phase and power of the μ rhythm, and may help define a more robust composite biomarker of high/low excitability states of human motor cortex.
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Affiliation(s)
- David Emanuel Vetter
- Department of Neurology & Stroke, University of Tübingen, Tübingen, Baden-Württemberg, Germany; Hertie-Institute for Clinical Brain Research, Tübingen, Baden-Württemberg, Germany
| | - Christoph Zrenner
- Department of Neurology & Stroke, University of Tübingen, Tübingen, Baden-Württemberg, Germany; Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Institute for Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
| | - Paolo Belardinelli
- Department of Neurology & Stroke, University of Tübingen, Tübingen, Baden-Württemberg, Germany; CIMeC, Center for Mind/Brain Sciences, University of Trento, Trento, Trentino-Alto Adige, Italy
| | - Tuomas Petteri Mutanen
- Department of Neuroscience and Biomedical Engineering, Aalto Yliopisto, Espoo, Uusimaa, Finland
| | - Gábor Kozák
- Department of Neurology & Stroke, University of Tübingen, Tübingen, Baden-Württemberg, Germany; Hertie-Institute for Clinical Brain Research, Tübingen, Baden-Württemberg, Germany
| | - Laura Marzetti
- Imaging and Clinical Sciences, Department of Neuroscience, University of Chieti-Pescara, Chieti, Abruzzo, Italy; Institute for Advanced Biomedical Technologies, University of Chieti-Pescara, Chieti, Abruzzo, Italy
| | - Ulf Ziemann
- Department of Neurology & Stroke, University of Tübingen, Tübingen, Baden-Württemberg, Germany; Hertie-Institute for Clinical Brain Research, Tübingen, Baden-Württemberg, Germany.
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Meng J, Xin L, Zou B, Wang L, Zhao X, Gao J, Zhang R. A manual controlled theranostic nanoplatform with real-time photoacoustic quantification of drug release for chemophotothermal therapy. J Colloid Interface Sci 2023; 651:1020-1027. [PMID: 37586151 DOI: 10.1016/j.jcis.2023.07.150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 07/15/2023] [Accepted: 07/24/2023] [Indexed: 08/18/2023]
Abstract
The development of intelligent nanodrug delivery systems that can visually guide the on-demand quantitative control of drug release has received extensive attention. Herein, two chemotherapeutic drugs, gallic acid and 5-fluorouracil, and Fe(III) were selected to prepare nanomedicine GF-Fe via polyphenol-metal self-assembly and infinite coordination of drug-metal. GF-Fe has good biocompatibility, photothermal properties and photoacoustic (PA) signals. When deferoxamine (DFO) was artificially applied and interacted with GF-Fe, GF-Fe began to disassemble, gallic acid and 5-fluorouracil were gradually released, while the PA signal of the nanomedicine decayed synchronously. Based on this, the relationship between the intensity of the PA signal and the drug release amount was established, so as to realize the precise quantitative control of the drug release in real-time under the guidance of PA imaging. Besides, the combined effect of the two therapeutic drugs in combination with photothermal therapy (PTT) can improve the therapeutic effect, resulting in significant superadditiveness. This nanoplatform constructed by facile synthesis provided good clinical translation potential for the implementation of precise multimodal combination therapy strategies for tumors.
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Affiliation(s)
- Jian Meng
- The Radiology Department of First Hospital of Shanxi Medical University, Taiyuan, China; Shanxi Academy of Medical Sciences, Shanxi Medical University, Taiyuan, China; The Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Taiyuan, China
| | - Lei Xin
- Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China
| | - Bocheng Zou
- The Radiology Department of First Hospital of Shanxi Medical University, Taiyuan, China; Shanxi Academy of Medical Sciences, Shanxi Medical University, Taiyuan, China
| | - Lei Wang
- Shanxi Academy of Medical Sciences, Shanxi Medical University, Taiyuan, China; The Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Taiyuan, China
| | - Xuhui Zhao
- The Radiology Department of First Hospital of Shanxi Medical University, Taiyuan, China
| | - Jinfang Gao
- The Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Taiyuan, China
| | - Ruiping Zhang
- The Radiology Department of First Hospital of Shanxi Medical University, Taiyuan, China.
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Paterson C, Armitage L, Turner M. Current Landscape of Ecological Momentary Assessment ( Real-Time Data) Methodology in Cancer Research: A Systematic Review. Semin Oncol Nurs 2023; 39:151514. [PMID: 37865555 DOI: 10.1016/j.soncn.2023.151514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 09/18/2023] [Accepted: 09/20/2023] [Indexed: 10/23/2023]
Abstract
OBJECTIVE To critically synthesize and describe the use and methods of ecological momentary assessment (EMA) in cancer research. DATA SOURCES A systematic review was conducted and has been reported according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) Guideline. Electronic databases (APA PsycINFO, CINAHL, Cochrane Central Register of Controlled Trials, MEDLINE, Scopus, and Web of Science Core Collection) were searched using a variety of keywords and subject headings by an expert systematic review librarian. All publications were double screened by two reviewers using predetermined exclusion and inclusion criteria throughout the full review process. The review used Covidence Systematic Review Software. Methodological quality assessment and data extraction were performed. A narrative synthesis was conducted to examine the aim for EMA, the characteristics of the study samples, the EMA sampling procedures, EMA completion rates, outcome measures, and any implications of findings for survivorship care. CONCLUSION A total of 42 EMA studies in cancer were included. Most studies used an electronic mobile device to capture EMA data apart from several that used paper diaries. Existing studies were found to have significant heterogeneity in methods and widely varying approaches to design and self-report measurements. While EMA in cancer research holds significant promise to advance cancer care research into the future by increasing ecological validity and reducing retrospective bias and can capture the unique idiographic within-person change over time, in real-time, further research is needed to develop standardized EMA self-report questionnaires. IMPLICATIONS FOR NURSING PRACTICE This is the first comprehensive systematic review to describe the use and methods of EMA in cancer research. There is significant heterogeneity in methods and widely varying approaches to design and self-report measurements in EMA cancer research. People affected by cancer found taking part in EMA studies reported benefit from the experience. However, researchers must engage with cancer survivors in the development and co-design of future EMA questionnaires to ensure relevant and acceptability of EMA data collection protocols.
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Affiliation(s)
- C Paterson
- Caring Futures Institute, Flinders University, Australia; Central Adelaide Local Health Network, Adelaide; Robert Gordon University, Aberdeen, Scotland, UK; Faculty of Health, University of Canberra, Bruce, ACT, Australia.
| | - L Armitage
- Faculty of Health, University of Canberra, Bruce, ACT, Australia
| | - M Turner
- Faculty of Health, University of Canberra, Bruce, ACT, Australia
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Caffarelli M, Karukonda V, Aghaeeaval M, McQuillen PS, Numis AL, Mackay MT, Press CA, Wintermark M, Fox CK, Amorim E. A quantitative EEG index for the recognition of arterial ischemic stroke in children. Clin Neurophysiol 2023; 156:113-124. [PMID: 37918222 DOI: 10.1016/j.clinph.2023.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 09/22/2023] [Accepted: 10/02/2023] [Indexed: 11/04/2023]
Abstract
OBJECTIVE To describe and assess performance of the Correlate Of Injury to the Nervous system (COIN) index, a quantitative electroencephalography (EEG) metric designed to identify areas of cerebral dysfunction concerning for stroke. METHODS Case-control study comparing continuous EEG data from children with acute ischemic stroke to children without stroke, with or without encephalopathy. COIN is calculated continuously and compares EEG power between cerebral hemispheres. Stroke relative infarct volume (RIV) was calculated from quantitative neuroimaging analysis. Significance was determined using a two-sample t-test. Sensitivity, specificity, and accuracy were measured using logistic regression. RESULTS Average COIN values were -34.7 in the stroke cohort compared to -9.5 in controls without encephalopathy (p = 0.003) and -10.5 in controls with encephalopathy (p = 0.006). The optimal COIN cutoff to discriminate stroke from controls was -15 in non-encephalopathic and -18 in encephalopathic controls with >92% accuracy in strokes with RIV > 5%. A COIN cutoff of -20 allowed discrimination between strokes with <5% and >5% RIV (p = 0.027). CONCLUSIONS We demonstrate that COIN can identify children with acute ischemic stroke. SIGNIFICANCE COIN may be a valuable tool for stroke identification in children. Additional studies are needed to determine utility as a monitoring technique for children at risk for stroke.
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Affiliation(s)
- Mauro Caffarelli
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA.
| | - Vishnu Karukonda
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Mahsa Aghaeeaval
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Patrick S McQuillen
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Adam L Numis
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Mark T Mackay
- Royal Children's Hospital, Melbourne, Victoria, Australia; The Murdoch Children's Research Institute Melbourne, Victoria, Australia; The Department of Paediatrics, University of Melbourne, Victoria, Australia
| | - Craig A Press
- Departments of Pediatrics and Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Max Wintermark
- Department of Neuroradiology, University of Texas MD Anderson Center, Houston, TX, USA
| | - Christine K Fox
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Edilberto Amorim
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
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15
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Xiao H, Han X, Zhi S, Wong YL, Liu C, Li W, Liu W, Wang W, Zhang Y, Wu H, Lee HFV, Cheung LYA, Chang HC, Liao YP, Deng J, Li T, Cai J. Ultra-fast multi-parametric 4D-MRI image reconstruction for real-time applications using a downsampling-invariant deformable registration (D2R) model. Radiother Oncol 2023; 189:109948. [PMID: 37832790 DOI: 10.1016/j.radonc.2023.109948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 09/12/2023] [Accepted: 10/09/2023] [Indexed: 10/15/2023]
Abstract
BACKGROUND AND PURPOSE Motion estimation from severely downsampled 4D-MRI is essential for real-time imaging and tumor tracking. This simulation study developed a novel deep learning model for simultaneous MR image reconstruction and motion estimation, named the Downsampling-Invariant Deformable Registration (D2R) model. MATERIALS AND METHODS Forty-three patients undergoing radiotherapy for liver tumors were recruited for model training and internal validation. Five prospective patients from another center were recruited for external validation. Patients received 4D-MRI scans and 3D MRI scans. The 4D-MRI was retrospectively down-sampled to simulate real-time acquisition. Motion estimation was performed using the proposed D2R model. The accuracy and robustness of the proposed D2R model and baseline methods, including Demons, Elastix, the parametric total variation (pTV) algorithm, and VoxelMorph, were compared. High-quality (HQ) 4D-MR images were also constructed using the D2R model for real-time imaging feasibility verification. The image quality and motion accuracy of the constructed HQ 4D-MRI were evaluated. RESULTS The D2R model showed significantly superior and robust registration performance than all the baseline methods at downsampling factors up to 500. HQ T1-weighted and T2-weighted 4D-MR images were also successfully constructed with significantly improved image quality, sub-voxel level motion error, and real-time efficiency. External validation demonstrated the robustness and generalizability of the technique. CONCLUSION In this study, we developed a novel D2R model for deformation estimation of downsampled 4D-MR images. HQ 4D-MR images were successfully constructed using the D2R model. This model may expand the clinical implementation of 4D-MRI for real-time motion management during liver cancer treatment.
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Affiliation(s)
- Haonan Xiao
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China 999077; Department of Radiation Oncology and Physics, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250117, China.
| | - Xinyang Han
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China 999077
| | - Shaohua Zhi
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China 999077
| | - Yat-Lam Wong
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China 999077
| | - Chenyang Liu
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China 999077
| | - Wen Li
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China 999077
| | - Weiwei Liu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Beijing Cancer Hospital & Institute, Peking University Cancer Hospital & Institute, Beijing 100000, China
| | - Weihu Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Beijing Cancer Hospital & Institute, Peking University Cancer Hospital & Institute, Beijing 100000, China
| | - Yibao Zhang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Beijing Cancer Hospital & Institute, Peking University Cancer Hospital & Institute, Beijing 100000, China
| | - Hao Wu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Beijing Cancer Hospital & Institute, Peking University Cancer Hospital & Institute, Beijing 100000, China
| | - Ho-Fun Victor Lee
- Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China 999077
| | - Lai-Yin Andy Cheung
- Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China 999077
| | - Hing-Chiu Chang
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong, China 999077
| | - Yen-Peng Liao
- Department of Radiation Oncology's Division of Medical Physics & Engineering, University of Texas Southwestern Medical Center, Texas 75390, USA
| | - Jie Deng
- Department of Radiation Oncology's Division of Medical Physics & Engineering, University of Texas Southwestern Medical Center, Texas 75390, USA
| | - Tian Li
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China 999077.
| | - Jing Cai
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China 999077.
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Punia M, Maan S, Batra K, Chaudhary D, Devi B, Kumar A, Gahlawat SK, Maan NS. Development of real-time RT-PCR systems for detection and quantitation of bovine enteric viral pathogens. Anim Biotechnol 2023; 34:4658-4666. [PMID: 38347693 DOI: 10.1080/10495398.2023.2182314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
The enteric viruses in animals are responsible for severe and devastating losses to the livestock owners with a profound negative impact on animal, health, welfare, and productivity. These viruses are usually transmitted via the feco-oral route and primarily infect the digestive tract of the humans, bovines and different mammals as well as birds. Some of the important enteric viruses in ruminants are: Rotavirus A (RVA), Peste des petits virus (PPRV), Norovirus (NV), Bovine corona virus (BoCV) and Bluetongue virus (BTV). In the present study, sensitive, specific and reliable TaqMan probe-based RT-qPCRs were developed and standardized for the rapid detection and quantification of enteric viruses from fecal samples. The assays result in efficient amplification of the RVA, BTV and BoCV RNA with a limit of detection (LoD) of 5, 5 and 4 copies, respectively, which is 1000 times more sensitive than the traditional gel-based RT-PCR. The reproducibility of each assay was satisfactory, thus allowing for a sensitive and accurate measurement of the viral RNA load in clinical samples. In conclusion, real time PCR developed for these viruses are highly specific and sensitive technique for the detection of diarrheic viral pathogens of cattle and buffalo.
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Affiliation(s)
- Monika Punia
- Department of Biotechnology, Ch. Devi Lal University, Sirsa, India
| | - Sushila Maan
- College of Veterinary Sciences, Lala Lajpat Rai University of Veterinary and Animal Science (LUVAS), Hisar, India
| | - Kanisht Batra
- College of Veterinary Sciences, Lala Lajpat Rai University of Veterinary and Animal Science (LUVAS), Hisar, India
| | - Deepika Chaudhary
- College of Veterinary Sciences, Lala Lajpat Rai University of Veterinary and Animal Science (LUVAS), Hisar, India
| | - Bhanita Devi
- College of Veterinary Sciences, Lala Lajpat Rai University of Veterinary and Animal Science (LUVAS), Hisar, India
| | - Aman Kumar
- College of Veterinary Sciences, Lala Lajpat Rai University of Veterinary and Animal Science (LUVAS), Hisar, India
| | | | - Narender Singh Maan
- College of Veterinary Sciences, Lala Lajpat Rai University of Veterinary and Animal Science (LUVAS), Hisar, India
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Li H, Zhu Y, Wan C, Wang Z, Liu L, Tan M, Zhang F, Zeng Y, Huang J, Wu C, Huang Y, Kang Z, Guo X. Rapid detection of goose astrovirus genotypes 2 using real-time reverse transcription recombinase polymerase amplification. BMC Vet Res 2023; 19:232. [PMID: 37936127 PMCID: PMC10629041 DOI: 10.1186/s12917-023-03790-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 10/21/2023] [Indexed: 11/09/2023] Open
Abstract
BACKGROUND Goose astrovirus (GoAstV) is an important pathogen that causes joint and visceral gout in goslings. It has been circulating in many provinces of China since 2017. Goose astrovirus genotypes 2 (GoAstV-2) is the main epidemic strain, and its high morbidity and mortality have caused huge economic losses to the goose industry. An accurate point-of-care detection for GoAstV-2 is of great significance. In this study, we developed a real-time reverse transcription recombinase polymerase amplification (RT-RPA) method for the on-site detection of GoAstV-2 infection. RESULTS The real-time RT-RPA reaction was carried out at a constant temperature of 39 °C, and the entire detection time from nucleic acid preparation to the end of amplification was only 25 min using the portable device. The results of a specificity analysis showed that no cross-reaction was observed with other related pathogens. The detection limit of the assay was 100 RNA copies/μL. The low coefficient of variation value indicated excellent repeatability. We used 270 clinical samples to evaluate the performance of our established method, the positive concordance rates with RT-qPCR were 99.6%, and the linear regression analysis revealed a strong correlation. CONCLUSIONS The established real-time RT-RPA assay showed high rapidity, specificity and sensitivity, which can be widely applied in the laboratory, field and especially in the resource-limited settings for GoAstV-2 point-of-care diagnosis.
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Affiliation(s)
- Haiqin Li
- Institute of Animal Husbandry and Veterinary Medicine, Jiangxi Academy of Agricultural Sciences, Nanchang, 330200, Jiangxi, China
- Jiangxi Provincial Key Laboratory for Animal Health, College of Animal Science and Technology, Jiangxi AgriculturalUniversity, Nanchang, China
| | - Yujun Zhu
- Guangdong laboratory animals monitoring instituteand Guangdong Provincial Key Laboratory of Laboratory Animals, Guangzhou, 510633, China
| | - Chunhe Wan
- Institute of Animal Husbandry and Veterinary Medicine, Fujian Academy of Agricultural Sciences, Fuzhou, 350013, Fujian, China
| | - Zhangzhang Wang
- Xingguo County Agricultural Technology Extension Center, Ganzhou, 341000, Jiangxi, China
| | - Lei Liu
- XinyuYushui District Center for Agricultural Sciences, Xinyu, 338000, Jiangxi, China
| | - Meifang Tan
- Institute of Animal Husbandry and Veterinary Medicine, Jiangxi Academy of Agricultural Sciences, Nanchang, 330200, Jiangxi, China
| | - Fanfan Zhang
- Institute of Animal Husbandry and Veterinary Medicine, Jiangxi Academy of Agricultural Sciences, Nanchang, 330200, Jiangxi, China
| | - Yanbing Zeng
- Institute of Animal Husbandry and Veterinary Medicine, Jiangxi Academy of Agricultural Sciences, Nanchang, 330200, Jiangxi, China
| | - Jiangnan Huang
- Institute of Animal Husbandry and Veterinary Medicine, Jiangxi Academy of Agricultural Sciences, Nanchang, 330200, Jiangxi, China
| | - Chengcheng Wu
- Institute of Animal Husbandry and Veterinary Medicine, Jiangxi Academy of Agricultural Sciences, Nanchang, 330200, Jiangxi, China
| | - Yu Huang
- Institute of Animal Husbandry and Veterinary Medicine, Fujian Academy of Agricultural Sciences, Fuzhou, 350013, Fujian, China
| | - Zhaofeng Kang
- Institute of Animal Husbandry and Veterinary Medicine, Jiangxi Academy of Agricultural Sciences, Nanchang, 330200, Jiangxi, China.
| | - Xiaoqiao Guo
- Jiangxi Provincial Key Laboratory for Animal Health, College of Animal Science and Technology, Jiangxi AgriculturalUniversity, Nanchang, China.
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Lee YS. Real-Time Visualization of Thrombus during Suction Thrombectomy : Contrast-in-Stasis Technique. J Korean Neurosurg Soc 2023:jkns.2023.0158. [PMID: 37920905 DOI: 10.3340/jkns.2023.0158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 10/31/2023] [Indexed: 11/04/2023] Open
Abstract
This report introduces a simple method to visualize the captured thrombus in real-time during suction thrombectomy using "contrast-in-stasis technique". It enables visualization of the thrombus captured by a suction catheter as it is being retrieved through the tortuous course of the carotid artery eventually into the guiding catheter. It also offers visual identification of important findings such as fragmentation of thrombus into pieces or loss of thrombus during retrieval, and, therefore, helps clinicians to make further critical decisions during the procedure.
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Affiliation(s)
- Yoon-Soo Lee
- Department of Neurosurgery, Daegu Fatima Hospital, Daegu, Korea
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Vahedizade S, Emamjomehzadeh O, Kerachian R, Forouhar L. A real-time market-based framework for basin-wide surface water pricing and allocation considering the available water uncertainty. J Environ Manage 2023; 345:118767. [PMID: 37604106 DOI: 10.1016/j.jenvman.2023.118767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 07/23/2023] [Accepted: 08/09/2023] [Indexed: 08/23/2023]
Abstract
Market-based approaches are increasingly considered reallocating instruments that put water consumption at its highest economic value among competing water users. Setting up a water market can have a lot of environmental, social, economic, and legal complexities. One of the main issues is the uncertain nature of the available water, which can cause the failure of markets, especially during drought conditions. Therefore, there is a need for market mechanisms to consider and reduce the adverse impacts of available water uncertainty on market outcomes. Accordingly, this paper proposes a new real-time seasonal smart water market framework for basin-wide surface water pricing and allocation. The framework uses the results of the reservoir water allocation optimization models and ANFIS-based monthly river discharge forecasts to better assist the water users with their bidding. The market manager uses updated available information at the beginning of each season to provide users with a more accurate understanding of available water to adjust their tradings for the rest of the year. The applicability and efficiency of the proposed framework are evaluated by applying it to the Gorganrood River basin in Iran. According to the results, the framework increased users' benefits from 721 to 1050 billion rials, which is more efficient than an annual market. Water markets can use this framework to improve their ability to cope with the uncertainty of available water, increase their users' benefits, and encourage them to improve their efficiency. Furthermore, the proposed framework allows the decision-makers in water sectors (e.g., industrial, agricultural, etc.) to discover time and location specific water allocation and price for different water users.
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Affiliation(s)
- Sajad Vahedizade
- Research Associate, Department of Civil Environmental and Geo-Engineering and the Saint Anthony Falls Laboratory, University of Minnesota, Minneapolis, MN, USA
| | - Omid Emamjomehzadeh
- Research Associate, School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Reza Kerachian
- Professor, School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran.
| | - Leila Forouhar
- Research Associate, Department of Infrastructure Engineering, University of Melbourne, Melbourne, Victoria, Australia
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Carvalho CR, Fernández JM, Del-Ama AJ, Oliveira Barroso F, Moreno JC. Review of electromyography onset detection methods for real-time control of robotic exoskeletons. J Neuroeng Rehabil 2023; 20:141. [PMID: 37872633 PMCID: PMC10594734 DOI: 10.1186/s12984-023-01268-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Accepted: 10/13/2023] [Indexed: 10/25/2023] Open
Abstract
BACKGROUND Electromyography (EMG) is a classical technique used to record electrical activity associated with muscle contraction and is widely applied in Biomechanics, Biomedical Engineering, Neuroscience and Rehabilitation Robotics. Determining muscle activation onset timing, which can be used to infer movement intention and trigger prostheses and robotic exoskeletons, is still a big challenge. The main goal of this paper was to perform a review of the state-of-the-art of EMG onset detection methods. Moreover, we compared the performance of the most commonly used methods on experimental EMG data. METHODS A total of 156 papers published until March 2022 were included in the review. The papers were analyzed in terms of application domain, pre-processing method and EMG onset detection method. The three most commonly used methods [Single (ST), Double (DT) and Adaptive Threshold (AT)] were applied offline on experimental intramuscular and surface EMG signals obtained during contractions of ankle and knee joint muscles. RESULTS Threshold-based methods are still the most commonly used to detect EMG onset. Compared to ST and AT, DT required more processing time and, therefore, increased onset timing detection, when applied on experimental data. The accuracy of these three methods was high (maximum error detection rate of 7.3%), demonstrating their ability to automatically detect the onset of muscle activity. Recently, other studies have tested different methods (especially Machine Learning based) to determine muscle activation onset offline, reporting promising results. CONCLUSIONS This study organized and classified the existing EMG onset detection methods to create consensus towards a possible standardized method for EMG onset detection, which would also allow more reproducibility across studies. The three most commonly used methods (ST, DT and AT) proved to be accurate, while ST and AT were faster in terms of EMG onset detection time, especially when applied on intramuscular EMG data. These are important features towards movement intention identification, especially in real-time applications. Machine Learning methods have received increased attention as an alternative to detect muscle activation onset. However, although several methods have shown their capability offline, more research is required to address their full potential towards real-time applications, namely to infer movement intention.
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Affiliation(s)
- Camila R Carvalho
- Neural Rehabilitation Group, Cajal Institute, Spanish National Research Council (CSIC), Madrid, Spain
| | - J Marvin Fernández
- Electronic Technology Department, Rey Juan Carlos University, Madrid, Spain
| | - Antonio J Del-Ama
- Electronic Technology Department, Rey Juan Carlos University, Madrid, Spain
| | - Filipe Oliveira Barroso
- Neural Rehabilitation Group, Cajal Institute, Spanish National Research Council (CSIC), Madrid, Spain.
| | - Juan C Moreno
- Neural Rehabilitation Group, Cajal Institute, Spanish National Research Council (CSIC), Madrid, Spain
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21
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Caetano G, Esteves I, Vourvopoulos A, Fleury M, Figueiredo P. NeuXus open-source tool for real-time artifact reduction in simultaneous EEG-fMRI. Neuroimage 2023; 280:120353. [PMID: 37652114 DOI: 10.1016/j.neuroimage.2023.120353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 08/21/2023] [Accepted: 08/28/2023] [Indexed: 09/02/2023] Open
Abstract
The simultaneous acquisition of electroencephalography and functional magnetic resonance imaging (EEG-fMRI) allows the complementary study of the brain's electrophysiology and hemodynamics with high temporal and spatial resolution. One application with great potential is neurofeedback training of targeted brain activity, based on the real-time analysis of the EEG and/or fMRI signals. This depends on the ability to reduce in real time the severe artifacts affecting the EEG signal acquired with fMRI, mainly the gradient and pulse artifacts. A few methods have been proposed for this purpose, but they are either slow, hardware-dependent, publicly unavailable, or proprietary software. Here, we present a fully open-source and publicly available tool for real-time EEG artifact reduction in simultaneous EEG-fMRI recordings that is fast and applicable to any hardware. Our tool is integrated in the Python toolbox NeuXus for real-time EEG processing and adapts to a real-time scenario well-established artifact average subtraction methods combined with a long short-term memory network for R peak detection. We benchmarked NeuXus on three different datasets, in terms of artifact power reduction and background signal preservation in resting state, alpha-band power reactivity to eyes closure, and event-related desynchronization during motor imagery. We showed that NeuXus performed at least as well as the only available real-time tool for conventional hardware setups (BrainVision's RecView) and a well-established offline tool (EEGLAB's FMRIB plugin). We also demonstrated NeuXus' real-time ability by reporting execution times under 250 ms. In conclusion, we present and validate the first fully open-source and hardware-independent solution for real-time artifact reduction in simultaneous EEG-fMRI studies.
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Affiliation(s)
- Gustavo Caetano
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal
| | - Inês Esteves
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal
| | - Athanasios Vourvopoulos
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal
| | - Mathis Fleury
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal
| | - Patrícia Figueiredo
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal.
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22
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Li Y, Gu W, Yue H, Lei G, Guo W, Wen Y, Tang H, Luo X, Tu W, Ye J, Hong R, Cai Q, Gu Q, Liu T, Miao B, Wang R, Ren J, Lei W. Real-time detection of laryngopharyngeal cancer using an artificial intelligence-assisted system with multimodal data. J Transl Med 2023; 21:698. [PMID: 37805551 PMCID: PMC10559609 DOI: 10.1186/s12967-023-04572-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 09/23/2023] [Indexed: 10/09/2023] Open
Abstract
BACKGROUND Laryngopharyngeal cancer (LPC) includes laryngeal and hypopharyngeal cancer, whose early diagnosis can significantly improve the prognosis and quality of life of patients. Pathological biopsy of suspicious cancerous tissue under the guidance of laryngoscopy is the gold standard for diagnosing LPC. However, this subjective examination largely depends on the skills and experience of laryngologists, which increases the possibility of missed diagnoses and repeated unnecessary biopsies. We aimed to develop and validate a deep convolutional neural network-based Laryngopharyngeal Artificial Intelligence Diagnostic System (LPAIDS) for real-time automatically identifying LPC in both laryngoscopy white-light imaging (WLI) and narrow-band imaging (NBI) images to improve the diagnostic accuracy of LPC by reducing diagnostic variation among on-expert laryngologists. METHODS All 31,543 laryngoscopic images from 2382 patients were categorised into training, verification, and test sets to develop, validate, and internal test LPAIDS. Another 25,063 images from five other hospitals were used as external tests. Overall, 551 videos were used to evaluate the real-time performance of the system, and 200 randomly selected videos were used to compare the diagnostic performance of the LPAIDS with that of laryngologists. Two deep-learning models using either WLI (model W) or NBI (model N) images were constructed to compare with LPAIDS. RESULTS LPAIDS had a higher diagnostic performance than models W and N, with accuracies of 0·956 and 0·949 in the internal image and video tests, respectively. The robustness and stability of LPAIDS were validated in external sets with the area under the receiver operating characteristic curve values of 0·965-0·987. In the laryngologist-machine competition, LPAIDS achieved an accuracy of 0·940, which was comparable to expert laryngologists and outperformed other laryngologists with varying qualifications. CONCLUSIONS LPAIDS provided high accuracy and stability in detecting LPC in real-time, which showed great potential for using LPAIDS to improve the diagnostic accuracy of LPC by reducing diagnostic variation among on-expert laryngologists.
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Affiliation(s)
- Yun Li
- Otorhinolaryngology Hospital, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China
| | - Wenxin Gu
- School of Computer Science and Engineering, Guangdong Province Key Lab of Computational Science, Sun Yat-Sen University, Guangzhou, 510006, Guangdong, China
| | - Huijun Yue
- Otorhinolaryngology Hospital, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China
| | - Guoqing Lei
- Otorhinolaryngology Hospital, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China
| | - Wenbin Guo
- Otorhinolaryngology Hospital, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China
| | - Yihui Wen
- Otorhinolaryngology Hospital, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China
| | - Haocheng Tang
- Department of Otolaryngology-Head and Neck Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Xin Luo
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Wenjuan Tu
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Jin Ye
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Ruomei Hong
- Department of Otolaryngology-Head and Neck, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Qian Cai
- Department of Otolaryngology-Head and Neck, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Qingyu Gu
- Department of Otorhinolaryngology-Head and Neck Surgery, The Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Tianrun Liu
- Department of Otorhinolaryngology-Head and Neck Surgery, The Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Beiping Miao
- Department of Otolaryngology-Head and Neck Surgery, Shenzhen Secondary Hospital and First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China
| | - Ruxin Wang
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Jiangtao Ren
- School of Computer Science and Engineering, Guangdong Province Key Lab of Computational Science, Sun Yat-Sen University, Guangzhou, 510006, Guangdong, China.
| | - Wenbin Lei
- Otorhinolaryngology Hospital, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China.
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Sprygin A, Mazloum A, Van Schalkwyk A, Krotova A, Bydovskaya O, Prokhvatilova L, Chvala I. Development and application of a real-time polymerase chain reaction assay to detect lumpy skin disease virus belonging to the Kenyan sheep and goat pox group. BMC Res Notes 2023; 16:247. [PMID: 37777780 PMCID: PMC10543856 DOI: 10.1186/s13104-023-06502-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Accepted: 09/05/2023] [Indexed: 10/02/2023] Open
Abstract
Lumpy skin disease (LSD) outbreaks in Southeast and South Asia are attributed to different lineages of LSD virus (LSDV). Variants belonging to the novel recombinant cluster 2.5 circulate in China and Thailand, while a Kenyan sheep and goat pox (KSGP) strain from cluster 1.1 circulates in India, Pakistan, and Bangladesh. The clusters representing these circulating strains are vastly different. However, if their distribution encroaches into each other's ranges, it will be impossible to differentiate between them due to the lack of suitable molecular tools. Thus, fit-for-purpose molecular tools are in demand to effectively and timeously diagnose and investigate the epidemiology of LSDVs in a region. These could significantly contribute to the phylogenetic delineation of LSDVs and the development of preventive measures against transboundary spillovers. This work aimed to develop a real-time polymerase chain reaction assay targeting open reading frame LW032, capable of specifically detecting KSGP-related isolates and recombinant LSDV strains containing the KSGP backbone. The analytical specificity was proven against the widest possible panel of recombinant vaccine-like LSDV strains known to date. The amplification efficiency was 91.08%, and the assay repeatability had a cycle threshold variation of 0.56-1.1 over five repetitions across three runs. This KSGP-specific assay is reliable and fast and is recommended for use in LSDV epidemiological studies where the accurate detection of KSGP genetic signatures is a priority, particularly in regions where KSGP-like and other lineages are circulating.
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Affiliation(s)
| | - Ali Mazloum
- Federal Center for Animal Health, Vladimir, Russia
| | - Antoinette Van Schalkwyk
- Agricultural Research Council-Onderstepoort Veterinary Institute, Onderstepoort, South Africa
- Department of Biotechnology, University of the Western Cape, Bellville, South Africa
| | | | | | | | - Ilya Chvala
- Federal Center for Animal Health, Vladimir, Russia
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24
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Huang J, Tong Y, Chen Y, Yang X, Wei X, Chen X, Li J, Li S. Highly sensitive and rapid determination of Mycobacterium leprae based on real-time multiple cross displacement amplification. BMC Microbiol 2023; 23:272. [PMID: 37770823 PMCID: PMC10537127 DOI: 10.1186/s12866-023-03004-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 09/05/2023] [Indexed: 09/30/2023] Open
Abstract
BACKGROUND Mycobacterium leprae (ML) is the pathogen that causes leprosy, which has a long history and still exists today. ML is an intracellular mycobacterium that dominantly induces leprosy by causing permanent damage to the skin, nerves, limbs and eyes as well as deformities and disabilities. Moreover, ML grows slowly and is nonculturable in vitro. Given the prevalence of leprosy, a highly sensitive and rapid method for the early diagnosis of leprosy is urgently needed. RESULTS In this study, we devised a novel tool for the diagnosis of leprosy by combining restriction endonuclease, real-time fluorescence analysis and multiple cross displacement amplification (E-RT-MCDA). To establish the system, primers for the target gene RLEP were designed, and the optimal conditions for E-RT-MCDA at 67 °C for 36 min were determined. Genomic DNA from ML, various pathogens and clinical samples was used to evaluate and optimize the E-RT-MCDA assay. The limit of detection (LoD) was 48.6 fg per vessel for pure ML genomic DNA, and the specificity of detection was as high as 100%. In addition, the detection process could be completed in 36 min by using a real-time monitor. CONCLUSION The E-RT-MCDA method devised in the current study is a reliable, sensitive and rapid technique for leprosy diagnosis and could be used as a potential tool in clinical settings.
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Affiliation(s)
- Junfei Huang
- Laboratory of Infectious Disease of Experimental Center, Guizhou Provincial Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, People's Republic of China
| | - Yi Tong
- Laboratory of Infectious Disease of Experimental Center, Guizhou Provincial Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, People's Republic of China
| | - Yijiang Chen
- Laboratory of Infectious Disease of Experimental Center, Guizhou Provincial Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, People's Republic of China
| | - Xinggui Yang
- Laboratory of Infectious Disease of Experimental Center, Guizhou Provincial Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, People's Republic of China
| | - Xiaoyu Wei
- Laboratory of Infectious Disease of Experimental Center, Guizhou Provincial Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, People's Republic of China
| | - Xu Chen
- The Second Affiliated Hospital, Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou, 550003, People's Republic of China
| | - Jinlan Li
- Tuberculosis Control Institute, Guizhou Provincial Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, People's Republic of China
| | - Shijun Li
- Laboratory of Infectious Disease of Experimental Center, Guizhou Provincial Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, People's Republic of China.
- School of Public Health, Guizhou Medical University, Guiyang, Guizhou, 550025, People's Republic of China.
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25
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Gennari F, Pagano M, Toncelli A, Lisanti MT, Paoletti R, Roversi PF, Tredicucci A, Giaccone M. Terahertz imaging for non-invasive classification of healthy and cimiciato-infected hazelnuts. Heliyon 2023; 9:e19891. [PMID: 37809509 PMCID: PMC10559270 DOI: 10.1016/j.heliyon.2023.e19891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 09/04/2023] [Accepted: 09/05/2023] [Indexed: 10/10/2023] Open
Abstract
The development of new non-invasive approaches able to recognize defective food is currently a lively field of research. In particular, a simple and non-destructive method able to recognize defective hazelnuts, such as cimiciato-infected ones, in real-time is still missing. This study has been designed to detect the presence of such damaged hazelnuts. To this aim, a measurement setup based on terahertz (THz) radiation has been developed. Images of a sample of 150 hazelnuts have been acquired in the low THz range by a compact and portable active imaging system equipped with a 0.14 THz source and identified as Healthy Hazelnuts (HH) or Cimiciato Hazelnut (CH) after visual inspection. All images have been analyzed to find the average transmission of the THz radiation within the sample area. The differences in the distribution of the two populations have been used to set up a classification scheme aimed at the discrimination between healthy and injured samples. The performance of the classification scheme has been assessed through the use of the confusion matrix on 50 samples. The False Positive Rate (FPR) and True Negative Rate (TNR) are 0% and 100%, respectively. On the other hand, the True Positive Rate (TPR) and False Negative Rate (FNR) are 75% and 25%, respectively. These results are relevant from the perspective of the development of a simple, automatic, real-time method for the discrimination of cimiciato-infected hazelnuts in the processing industry.
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Affiliation(s)
- Fulvia Gennari
- Dipartimento di Fisica “E. Fermi”, Università di Pisa, Largo B. Pontecorvo 3, 56127, Pisa, Italy
| | - Mario Pagano
- Institute of Research on Terrestrial Ecosystems (IRET), National Research Council (CNR), Via Madonna del Piano 10, 50019, Sesto Fiorentino, Italy
| | - Alessandra Toncelli
- Dipartimento di Fisica “E. Fermi”, Università di Pisa, Largo B. Pontecorvo 3, 56127, Pisa, Italy
- Centro per l’Integrazione della Strumentazione dell’Università di Pisa (CISUP), Lungarno Pacinotti 43/44, 56126, Pisa, Italy
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Largo B. Pontecorvo 3, 56127, Pisa, Italy
- Istituto Nanoscienze – CNR, Piazza S. Silvestro 12, 56127, Pisa, Italy
| | - Maria Tiziana Lisanti
- Università degli Studi di Napoli Federico II, Dipartimento di Agraria, Sezione di Scienze della Vigna e del Vino, viale Italia 60, 83100, Avellino, Italy
| | - Riccardo Paoletti
- Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Largo B. Pontecorvo 3, 56127, Pisa, Italy
- Dipartimento di Scienze Fisiche, della Terra e dell’Ambiente, Sezione di Fisica, Università di Siena, via Roma 56, 53100, Siena, Italy
| | - Pio Federico Roversi
- CREA, Research Centre for Plant Protection and Certification, 50125, Firenze, Italy
| | - Alessandro Tredicucci
- Dipartimento di Fisica “E. Fermi”, Università di Pisa, Largo B. Pontecorvo 3, 56127, Pisa, Italy
- Centro per l’Integrazione della Strumentazione dell’Università di Pisa (CISUP), Lungarno Pacinotti 43/44, 56126, Pisa, Italy
- Istituto Nanoscienze – CNR, Piazza S. Silvestro 12, 56127, Pisa, Italy
| | - Matteo Giaccone
- Institute for Mediterranean Agricultural and Forestry Systems, National Research Council, 80055 P.le Enrico, Fermi 1 - Loc. Porto del Granatello, 80055, Portici, Naples, Italy
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26
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Moya-Esteban A, Durandau G, van der Kooij H, Sartori M. Real-time lumbosacral joint loading estimation in exoskeleton-assisted lifting conditions via electromyography-driven musculoskeletal models. J Biomech 2023; 157:111727. [PMID: 37499430 DOI: 10.1016/j.jbiomech.2023.111727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 06/13/2023] [Accepted: 07/14/2023] [Indexed: 07/29/2023]
Abstract
Lumbar joint compression forces have been linked to the development of chronic low back pain, which is specially present in occupational environments. Offline methodologies for lumbosacral joint compression force estimation are not commonly integrated in occupational or medical applications due to the highly time-consuming and complex post-processing procedures. Hence, applications such as real-time adjustment of assistive devices (i.e., back-support exoskeletons) for optimal modulation of compression forces remains unfeasible. Here, we present a real-time electromyography (EMG)-driven musculoskeletal model, capable of estimating accurate lumbosacral joint moments and plausible compression forces. Ten participants performed box-lifting tasks (5 and 15 kg) with and without the Laevo Flex back-support exoskeleton using squat and stoop lifting techniques. Lumbosacral kinematics and EMGs from abdominal and thoracolumbar muscles were used to drive, in real-time, subject-specific EMG-driven models, and estimate lumbosacral joint moments and compression forces. Real-time EMG-model derived moments showed high correlations (R2 = 0.76 - 0.83) and estimation errors below 30% with respect to reference inverse dynamic moments. Compared to unassisted lifting conditions, exoskeleton liftings showed mean lumbosacral joint moments and compression forces reductions of 11.9 - 18.7 Nm (6 - 12% of peak moment) and 300 - 450 N (5 - 10%), respectively. Our modelling framework was capable of estimating in real-time, valid lumbosacral joint moments and compression forces in line with in vivo experimental data, as well as detecting the biomechanical effects of a passive back-support exoskeleton. Our presented technology may lead to a new class of bio-protective robots in which personalized assistance profiles are provided based on subject-specific musculoskeletal variables.
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Affiliation(s)
- A Moya-Esteban
- Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands.
| | - G Durandau
- Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands
| | - H van der Kooij
- Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands; Department of Biomechanical Engineering, Delft University of Technology, Delft, The Netherlands
| | - M Sartori
- Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands
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27
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Chen X, Ning H, Guo L, Diao D, Zhou X, Zhang X. Epidemic monitoring in real-time based on dynamic grid search and Monte Carlo numerical simulation algorithm. PeerJ Comput Sci 2023; 9:e1479. [PMID: 37547412 PMCID: PMC10403190 DOI: 10.7717/peerj-cs.1479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 06/12/2023] [Indexed: 08/08/2023]
Abstract
Building upon the foundational principles of the grid search algorithm and Monte Carlo numerical simulation, this article introduces an innovative epidemic monitoring and prevention plan. The plan offers the capability to accurately identify the sources of infectious diseases and predict the final scale and duration of the epidemic. The proposed plan is implemented in schools and society, utilizing computer simulation analysis. Through this analysis, the plan enables precise localization of infection sources for various demographic groups, with an error rate of less than 3%. Additionally, the plan allows for the estimation of the epidemic cycle duration, which typically spans around 14 days. Notably, higher population density enhances fault tolerance and prediction accuracy, resulting in smaller errors and more reliable simulation outcomes. Overall, this study provides highly valuable theoretical guidance for effective epidemic prevention and control efforts.
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Affiliation(s)
- Xin Chen
- College of Civil Architecture, Henan University of Science and Technology, Luoyang, China
| | - Huijun Ning
- College of Civil Architecture, Henan University of Science and Technology, Luoyang, China
| | - Liuwang Guo
- School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang, China
| | - Dongming Diao
- College of Civil Architecture, Henan University of Science and Technology, Luoyang, China
| | - Xinru Zhou
- School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai, China
| | - Xiaoliang Zhang
- College of Civil Architecture, Henan University of Science and Technology, Luoyang, China
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28
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Nhat PTH, Van Hao N, Tho PV, Kerdegari H, Pisani L, Thu LNM, Phuong LT, Duong HTH, Thuy DB, McBride A, Xochicale M, Schultz MJ, Razavi R, King AP, Thwaites L, Van Vinh Chau N, Yacoub S, Gomez A. Clinical benefit of AI-assisted lung ultrasound in a resource-limited intensive care unit. Crit Care 2023; 27:257. [PMID: 37393330 PMCID: PMC10314555 DOI: 10.1186/s13054-023-04548-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 06/24/2023] [Indexed: 07/03/2023] Open
Abstract
BACKGROUND Interpreting point-of-care lung ultrasound (LUS) images from intensive care unit (ICU) patients can be challenging, especially in low- and middle- income countries (LMICs) where there is limited training available. Despite recent advances in the use of Artificial Intelligence (AI) to automate many ultrasound imaging analysis tasks, no AI-enabled LUS solutions have been proven to be clinically useful in ICUs, and specifically in LMICs. Therefore, we developed an AI solution that assists LUS practitioners and assessed its usefulness in a low resource ICU. METHODS This was a three-phase prospective study. In the first phase, the performance of four different clinical user groups in interpreting LUS clips was assessed. In the second phase, the performance of 57 non-expert clinicians with and without the aid of a bespoke AI tool for LUS interpretation was assessed in retrospective offline clips. In the third phase, we conducted a prospective study in the ICU where 14 clinicians were asked to carry out LUS examinations in 7 patients with and without our AI tool and we interviewed the clinicians regarding the usability of the AI tool. RESULTS The average accuracy of beginners' LUS interpretation was 68.7% [95% CI 66.8-70.7%] compared to 72.2% [95% CI 70.0-75.6%] in intermediate, and 73.4% [95% CI 62.2-87.8%] in advanced users. Experts had an average accuracy of 95.0% [95% CI 88.2-100.0%], which was significantly better than beginners, intermediate and advanced users (p < 0.001). When supported by our AI tool for interpreting retrospectively acquired clips, the non-expert clinicians improved their performance from an average of 68.9% [95% CI 65.6-73.9%] to 82.9% [95% CI 79.1-86.7%], (p < 0.001). In prospective real-time testing, non-expert clinicians improved their baseline performance from 68.1% [95% CI 57.9-78.2%] to 93.4% [95% CI 89.0-97.8%], (p < 0.001) when using our AI tool. The time-to-interpret clips improved from a median of 12.1 s (IQR 8.5-20.6) to 5.0 s (IQR 3.5-8.8), (p < 0.001) and clinicians' median confidence level improved from 3 out of 4 to 4 out of 4 when using our AI tool. CONCLUSIONS AI-assisted LUS can help non-expert clinicians in an LMIC ICU improve their performance in interpreting LUS features more accurately, more quickly and more confidently.
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Affiliation(s)
- Phung Tran Huy Nhat
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam.
- School of Biomedical Engineering Imaging Sciences, King's College London, London, UK.
| | - Nguyen Van Hao
- Mahidol Oxford Tropical Medicine Research Unit, Bangkok, Thailand
- Hospital of Tropical Diseases, Ho Chi Minh City, Vietnam
- University of Medicine and Pharmacy, Ho Chi Minh City, Vietnam
| | - Phan Vinh Tho
- Hospital of Tropical Diseases, Ho Chi Minh City, Vietnam
| | - Hamideh Kerdegari
- School of Biomedical Engineering Imaging Sciences, King's College London, London, UK
| | - Luigi Pisani
- Mahidol Oxford Tropical Medicine Research Unit, Bangkok, Thailand
| | | | - Le Thanh Phuong
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | | | | | - Angela McBride
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Miguel Xochicale
- School of Biomedical Engineering Imaging Sciences, King's College London, London, UK
| | - Marcus J Schultz
- Mahidol Oxford Tropical Medicine Research Unit, Bangkok, Thailand
| | - Reza Razavi
- School of Biomedical Engineering Imaging Sciences, King's College London, London, UK
| | - Andrew P King
- School of Biomedical Engineering Imaging Sciences, King's College London, London, UK
| | - Louise Thwaites
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK
| | | | - Sophie Yacoub
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK
| | - Alberto Gomez
- School of Biomedical Engineering Imaging Sciences, King's College London, London, UK
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Yan X, Zuo C, Li Z, Chen HW, Jiang Y, He B, Liu H, Chen J, Shi W. Cooperative simultaneous inversion of satellite-based real-time PM 2.5 and ozone levels using an improved deep learning model with attention mechanism. Environ Pollut 2023; 327:121509. [PMID: 36967005 DOI: 10.1016/j.envpol.2023.121509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 02/28/2023] [Accepted: 03/22/2023] [Indexed: 06/18/2023]
Abstract
Ground-level fine particulate matter (PM2.5) and ozone (O3) are air pollutants that can pose severe health risks. Surface PM2.5 and O3 concentrations can be monitored from satellites, but most retrieval methods retrieve PM2.5 or O3 separately and disregard the shared information between the two air pollutants, for example due to common emission sources. Using surface observations across China spanning 2014-2021, we found a strong relationship between PM2.5 and O3 with distinct spatiotemporal characteristics. Thus, in this study, we propose a new deep learning model called the Simultaneous Ozone and PM2.5 inversion deep neural Network (SOPiNet), which allows for daily real-time monitoring and full coverage of PM2.5 and O3 simultaneously at a spatial resolution of 5 km. SOPiNet employs the multi-head attention mechanism to better capture the temporal variations in PM2.5 and O3 based on previous days' conditions. Applying SOPiNet to MODIS data over China in 2022, using 2019-2021 to construct the network, we found that simultaneous retrievals of PM2.5 and O3 improved the performance compared with retrieving them independently: the temporal R2 increased from 0.66 to 0.72 for PM2.5, and from 0.79 to 0.82 for O3. The results suggest that near-real time satellite-based air quality monitoring can be improved by simultaneous retrieval of different but related pollutants. The codes of SOPiNet and its user guide are freely available online at https://github.com/RegiusQuant/ESIDLM.
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Affiliation(s)
- Xing Yan
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China
| | - Chen Zuo
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China
| | - Zhanqing Li
- Department of Atmospheric and Oceanic Science and ESSIC, University of Maryland, College Park, MD, 20740, USA
| | - Hans W Chen
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden; Department of Space, Earth and Environment, Chalmers University of Technology, Gothenburg, 41296, Sweden.
| | - Yize Jiang
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China
| | - Bin He
- College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China
| | - Huiming Liu
- Satellite Environment Center, Ministry of Environmental Protection, Beijing, 100094, China
| | - Jiayi Chen
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China
| | - Wenzhong Shi
- Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, China
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30
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Chen YC, Wang JL, Chang CY, Chuang MT, Chou CCK, Pan XX, Ho YJ, Ou-Yang CF, Liu WT, Chang CC. Using drone soundings to study the impacts and compositions of plumes from a gigantic coal-fired power plant. Sci Total Environ 2023:164709. [PMID: 37301392 DOI: 10.1016/j.scitotenv.2023.164709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 05/20/2023] [Accepted: 06/04/2023] [Indexed: 06/12/2023]
Abstract
The immense impacts of coal-fired power plant plumes on the atmospheric environment have caused great concern linked to climate and health issues. However, studies on the field observations of aerial plumes are relatively limited, mainly due to the lack of suitable plume observation tools and techniques. In this study, we use a multicopter unmanned aerial vehicle (UAV) sounding technique to study the influences of the aerial plumes of the world's fourth-largest coal-fired power plant on the atmospheric physical/chemical conditions and air quality. A set of species, including 106 volatile organic compounds (VOCs), CO, CO2, CH4, PM2.5, and O3, and meteorological variables of temperature (T), specific humidity (SH), and wind data, are collected by the UAV sounding technique. The results reveal that the large-scale plumes of the coal-fired power plant cause local temperature inversion and humidity changes, and even affect the dispersion of pollutants below. The chemical compositions of coal-fired power plant plumes are significantly different from those of another ubiquitous vehicular source. High fractions of ethane, ethene, and benzene and low fractions of n-butane and isopentane found in plumes could serve as the key features to help distinguish the influences of coal-fired power plant plumes from other pollution sources in a particular area. By taking the ratios of pollutants (e.g., PM2.5, CO, CH4, and VOCs) to CO2 in plumes and the CO2 emission amounts of the power plant into calculation, we enable the easy quantification of the specific pollutant emissions released from power plant plumes to the atmosphere. In summary, observation by using drone soundings dissecting the aerial plumes provides a new methodology that allows aerial plumes to be readily detected and characterized. Furthermore, the influences of the plumes on the atmospheric physical/chemical conditions and air quality can be assessed rather straightforwardly, which was not easily achievable in the past.
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Affiliation(s)
- Yen-Chen Chen
- Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
| | - Jia-Lin Wang
- Department of Chemistry, National Central University, Chungli 320, Taiwan
| | - Chih-Yuan Chang
- Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
| | - Ming-Tung Chuang
- Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
| | - Charles C-K Chou
- Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
| | - Xiang-Xu Pan
- Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
| | - Yu-Jui Ho
- Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
| | - Chang-Feng Ou-Yang
- Department of Chemistry, National Central University, Chungli 320, Taiwan; Department of Atmospheric Sciences, National Central University, Chungli 320, Taiwan
| | - Wen-Tzu Liu
- Department of Chemistry, Chung Yuan University, Chungli 320, Taiwan
| | - Chih-Chung Chang
- Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan.
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31
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Lobato I, De Backer A, Van Aert S. Real-time simulations of ADF STEM probe position-integrated scattering cross-sections for single element fcc crystals in zone axis orientation using a densely connected neural network. Ultramicroscopy 2023; 251:113769. [PMID: 37279607 DOI: 10.1016/j.ultramic.2023.113769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 05/08/2023] [Accepted: 05/26/2023] [Indexed: 06/08/2023]
Abstract
Quantification of annular dark field (ADF) scanning transmission electron microscopy (STEM) images in terms of composition or thickness often relies on probe-position integrated scattering cross sections (PPISCS). In order to compare experimental PPISCS with theoretically predicted ones, expensive simulations are needed for a given specimen, zone axis orientation, and a variety of microscope settings. The computation time of such simulations can be in the order of hours using a single GPU card. ADF STEM simulations can be efficiently parallelized using multiple GPUs, as the calculation of each pixel is independent of other pixels. However, most research groups do not have the necessary hardware, and, in the best-case scenario, the simulation time will only be reduced proportionally to the number of GPUs used. In this manuscript, we use a learning approach and present a densely connected neural network that is able to perform real-time ADF STEM PPISCS predictions as a function of atomic column thickness for most common face-centered cubic (fcc) crystals (i.e., Al, Cu, Pd, Ag, Pt, Au and Pb) along [100] and [111] zone axis orientations, root-mean-square displacements, and microscope parameters. The proposed architecture is parameter efficient and yields accurate predictions for the PPISCS values for a wide range of input parameters that are commonly used for aberration-corrected transmission electron microscopes.
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Affiliation(s)
- I Lobato
- EMAT, University of Antwerp, Department of Physics, Groenenborgerlaan 171, B-2020 Antwerp, Belgium; NANOlab Center of Excellence, University of Antwerp, Department of Physics, Groenenborgerlaan 171, B-2020 Antwerp, Belgium.
| | - A De Backer
- EMAT, University of Antwerp, Department of Physics, Groenenborgerlaan 171, B-2020 Antwerp, Belgium; NANOlab Center of Excellence, University of Antwerp, Department of Physics, Groenenborgerlaan 171, B-2020 Antwerp, Belgium
| | - S Van Aert
- EMAT, University of Antwerp, Department of Physics, Groenenborgerlaan 171, B-2020 Antwerp, Belgium; NANOlab Center of Excellence, University of Antwerp, Department of Physics, Groenenborgerlaan 171, B-2020 Antwerp, Belgium
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32
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Rahman MH, Jannat MKA, Islam MS, Grossi G, Bursic S, Aktaruzzaman M. Real-time face mask position recognition system based on MobileNet model. Smart Health (Amst) 2023; 28:100382. [PMID: 36743719 PMCID: PMC9886393 DOI: 10.1016/j.smhl.2023.100382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 12/23/2022] [Accepted: 01/27/2023] [Indexed: 02/01/2023]
Abstract
COVID-19 is a highly contagious disease that was first identified in 2019, and has since taken more than six million lives world wide till date, while also causing considerable economic, social, cultural and political turmoil. As a way to limit its spread, the World Health Organization and medical experts have advised properly wearing face masks, social distancing and hand sanitization, besides vaccination. However, people wear masks sometimes uncovering their mouths and/or noses consciously or unconsciously, thereby lessening the effectiveness of the protection they provide. A system capable of automatic recognition of face mask position could alert and ensure that an individual is wearing a mask properly before entering a crowded public area and putting themselves and others at risk. We first develop and publicly release a dataset of face mask images, which are collected from 391 individuals of different age groups and gender. Then, we study six different architectures of pre-trained deep learning models, and finally propose a model developed by fine tuning the pre-trained state of the art MobileNet model. We evaluate the performance (accuracy, F1-score, and Cohen's Kappa) of this model on the proposed dataset and MaskedFace-Net, a publicly available synthetic dataset created by image editing. Its performance is also compared to other existing methods. The proposed MobileNet is found as the best model providing an accuracy, F1-score, and Cohen's Kappa of 99.23%, 99.22%, and 99.19%, respectively for face mask position recognition. It outperforms the accuracy of the best existing model by about 2%. Finally, an automatic face mask position recognition system has been developed, which can recognize if an individual is wearing a mask correctly or incorrectly. The proposed model performs very well with no drop in recognition accuracy from real images captured by a camera.
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Affiliation(s)
- Md Hafizur Rahman
- Department of Electrical and Electronic Engineering, Islamic University, Kushtia 7003, Bangladesh
| | | | - Md Shafiqul Islam
- Department of Computer Science and Engineering, The People's University of Bangladesh, Dhaka 1207, Bangladesh
| | - Giuliano Grossi
- Dipartimento di Informatica, Università degli Studi di Milano, Milan, Italy
| | - Sathya Bursic
- Dipartimento di Informatica, Università degli Studi di Milano, Milan, Italy
| | - Md Aktaruzzaman
- Department of Computer Science and Engineering, Islamic University, Kushtia 7003, Bangladesh
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33
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Huttinga NRF, Bruijnen T, van den Berg CAT, Sbrizzi A. Gaussian Processes for real-time 3D motion and uncertainty estimation during MR-guided radiotherapy. Med Image Anal 2023; 88:102843. [PMID: 37245435 DOI: 10.1016/j.media.2023.102843] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 05/11/2023] [Accepted: 05/15/2023] [Indexed: 05/30/2023]
Abstract
Respiratory motion during radiotherapy causes uncertainty in the tumor's location, which is typically addressed by an increased radiation area and a decreased dose. As a result, the treatments' efficacy is reduced. The recently proposed hybrid MR-linac scanner holds the promise to efficiently deal with such respiratory motion through real-time adaptive MR-guided radiotherapy (MRgRT). For MRgRT, motion-fields should be estimated from MR-data and the radiotherapy plan should be adapted in real-time according to the estimated motion-fields. All of this should be performed with a total latency of maximally 200 ms, including data acquisition and reconstruction. A measure of confidence in such estimated motion-fields is highly desirable, for instance to ensure the patient's safety in case of unexpected and undesirable motion. In this work, we propose a framework based on Gaussian Processes to infer 3D motion-fields and uncertainty maps in real-time from only three readouts of MR-data. We demonstrated an inference frame rate up to 69 Hz including data acquisition and reconstruction, thereby exploiting the limited amount of required MR-data. Additionally, we designed a rejection criterion based on the motion-field uncertainty maps to demonstrate the framework's potential for quality assurance. The framework was validated in silico and in vivo on healthy volunteer data (n=5) acquired using an MR-linac, thereby taking into account different breathing patterns and controlled bulk motion. Results indicate end-point-errors with a 75th percentile below 1 mm in silico, and a correct detection of erroneous motion estimates with the rejection criterion. Altogether, the results show the potential of the framework for application in real-time MR-guided radiotherapy with an MR-linac.
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Affiliation(s)
- Niek R F Huttinga
- Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, The Netherlands; Computational Imaging Group for MR diagnostics & therapy, Center for Image Sciences, University Medical Center Utrecht, The Netherlands.
| | - Tom Bruijnen
- Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, The Netherlands; Computational Imaging Group for MR diagnostics & therapy, Center for Image Sciences, University Medical Center Utrecht, The Netherlands
| | - Cornelis A T van den Berg
- Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, The Netherlands; Computational Imaging Group for MR diagnostics & therapy, Center for Image Sciences, University Medical Center Utrecht, The Netherlands
| | - Alessandro Sbrizzi
- Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, The Netherlands; Computational Imaging Group for MR diagnostics & therapy, Center for Image Sciences, University Medical Center Utrecht, The Netherlands
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Olvera-Toscano CM, Ríos-Solís YÁ, Ríos-Mercado RZ, Sánchez Nigenda R. Holding times to maintain quasi-regular headways and reduce real-time bus bunching. Public Transp 2023; 15:1-34. [PMID: 38625127 PMCID: PMC10188328 DOI: 10.1007/s12469-023-00326-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 04/16/2023] [Indexed: 04/17/2024]
Abstract
Real-time control strategies deal with the day's dynamics in bus rapid transit systems. This work focuses on minimizing the number of buses of the same line cruising head-to-tail or arriving at a stop simultaneously by implementing bus holding times at the stops as a control strategy. We propose a new mathematical model to determine the bus holding times. It has quadratic constraints but a linear objective function that minimizes the bus bunching penalties. We also propose a beam-search heuristic to reduce computational solution time to solve large instances. Experimental results on a bus rapid transit system simulation in Monterrey, Mexico, show a bus bunching reduction of 45% compared to the case without optimization. Moreover, passenger waiting times are reduced by 30% in some scenarios. For real-world instances with 60 buses, the beam-search approach provides solutions with an optimality gap of less than 5% in less than 3 s.
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Affiliation(s)
- Citlali M. Olvera-Toscano
- Graduate Program in Systems Engineering, Universidad Autonoma de Nuevo Leon, Av. Universidad s/n, 66455 San Nicolas de los Garza, NL Mexico
| | - Yasmín Á. Ríos-Solís
- Engineering and Sciences Department, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501, 64700 Monterrey, NL Mexico
| | - Roger Z. Ríos-Mercado
- Graduate Program in Systems Engineering, Universidad Autonoma de Nuevo Leon, Av. Universidad s/n, 66455 San Nicolas de los Garza, NL Mexico
| | - Romeo Sánchez Nigenda
- Graduate Program in Systems Engineering, Universidad Autonoma de Nuevo Leon, Av. Universidad s/n, 66455 San Nicolas de los Garza, NL Mexico
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35
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de Assis Vilela F, Times VC, de Campos Bernardi AC, de Paula Freitas A, Ciferri RR. A non-intrusive and reactive architecture to support real-time ETL processes in data warehousing environments. Heliyon 2023; 9:e15728. [PMID: 37215774 PMCID: PMC10196447 DOI: 10.1016/j.heliyon.2023.e15728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 05/24/2022] [Accepted: 04/19/2023] [Indexed: 05/24/2023] Open
Abstract
Nowadays, organizations are very interested to gather data for strategic decision-making. Data are disposable in operational sources, which are distributed, heterogeneous, and autonomous. These data are gathered through ETL processes, which occur traditionally in a pre-defined time, that is, once a day, once a week, once a month or in a specific period of time. On the other hand, there are special applications for which data needs to be obtained in a faster way and sometimes even immediately after the data are generated in the operation data sources, such as health systems and digital agriculture. Thus, the conventional ETL process and the disposable techniques are incapable of making the operational data delivered in real-time, providing low latency, high availability, and scalability. As our proposal, we present an innovative architecture, named Data Magnet, to cope with real-time ETL processes. The experimental tests performed in the digital agriculture domain using real and synthetic data showed that our proposal was able to deal in real-time with the ETL process. The Data Magnet provided great performance, showing an almost constant elapsed time for growing data volumes. Besides, Data Magnet provided significant performance gains over the traditional trigger technique.
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Maya-Manzano JM, Tummon F, Abt R, Allan N, Bunderson L, Clot B, Crouzy B, Daunys G, Erb S, Gonzalez-Alonso M, Graf E, Grewling Ł, Haus J, Kadantsev E, Kawashima S, Martinez-Bracero M, Matavulj P, Mills S, Niederberger E, Lieberherr G, Lucas RW, O'Connor DJ, Oteros J, Palamarchuk J, Pope FD, Rojo J, Šaulienė I, Schäfer S, Schmidt-Weber CB, Schnitzler M, Šikoparija B, Skjøth CA, Sofiev M, Stemmler T, Triviño M, Zeder Y, Buters J. Towards European automatic bioaerosol monitoring: Comparison of 9 automatic pollen observational instruments with classic Hirst-type traps. Sci Total Environ 2023; 866:161220. [PMID: 36584954 DOI: 10.1016/j.scitotenv.2022.161220] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 12/15/2022] [Accepted: 12/23/2022] [Indexed: 06/17/2023]
Abstract
To benefit allergy patients and the medical practitioners, pollen information should be available in both a reliable and timely manner; the latter is only recently possible due to automatic monitoring. To evaluate the performance of all currently available automatic instruments, an international intercomparison campaign was jointly organised by the EUMETNET AutoPollen Programme and the ADOPT COST Action in Munich, Germany (March-July 2021). The automatic systems (hardware plus identification algorithms) were compared with manual Hirst-type traps. Measurements were aggregated into 3-hourly or daily values to allow comparison across all devices. We report results for total pollen as well as for Betula, Fraxinus, Poaceae, and Quercus, for all instruments that provided these data. The results for daily averages compared better with Hirst observations than the 3-hourly values. For total pollen, there was a considerable spread among systems, with some reaching R2 > 0.6 (3 h) and R2 > 0.75 (daily) compared with Hirst-type traps, whilst other systems were not suitable to sample total pollen efficiently (R2 < 0.3). For individual pollen types, results similar to the Hirst were frequently shown by a small group of systems. For Betula, almost all systems performed well (R2 > 0.75 for 9 systems for 3-hourly data). Results for Fraxinus and Quercus were not as good for most systems, while for Poaceae (with some exceptions), the performance was weakest. For all pollen types and for most measurement systems, false positive classifications were observed outside of the main pollen season. Different algorithms applied to the same device also showed different results, highlighting the importance of this aspect of the measurement system. Overall, given the 30 % error on daily concentrations that is currently accepted for Hirst-type traps, several automatic systems are currently capable of being used operationally to provide real-time observations at high temporal resolutions. They provide distinct advantages compared to the manual Hirst-type measurements.
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Affiliation(s)
- José M Maya-Manzano
- Center of Allergy & Environment (ZAUM), Member of the German Center for Lung Research (DZL), Technical University and Helmholtz Center Munich, Munich, Germany.
| | - Fiona Tummon
- Federal Office of Meteorology and Climatology (MeteoSwiss), Payerne, Switzerland.
| | | | | | | | - Bernard Clot
- Federal Office of Meteorology and Climatology (MeteoSwiss), Payerne, Switzerland.
| | - Benoît Crouzy
- Federal Office of Meteorology and Climatology (MeteoSwiss), Payerne, Switzerland.
| | | | - Sophie Erb
- Federal Office of Meteorology and Climatology (MeteoSwiss), Payerne, Switzerland.
| | | | | | - Łukasz Grewling
- Laboratory of Aerobiology, Department of Systematic and Environmental Botany, Adam Mickiewicz University, Poznan, Poland
| | - Jörg Haus
- Helmut Hund Wetzlar, Wetzlar, Germany.
| | | | | | | | - Predrag Matavulj
- BioSense Institute Research Institute for Information Technologies in Biosystems, University of Novi Sad, Novi Sad, Serbia.
| | - Sophie Mills
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, United Kingdom.
| | | | - Gian Lieberherr
- Federal Office of Meteorology and Climatology (MeteoSwiss), Payerne, Switzerland.
| | | | - David J O'Connor
- School of Chemical Sciences, Dublin City University, Dublin, Ireland.
| | - Jose Oteros
- Department of Botany, Ecology and Plant Physiology, University of Cordoba, Cordoba, Spain.
| | | | - Francis D Pope
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, United Kingdom.
| | - Jesus Rojo
- Department of Pharmacology, Pharmacognosy and Botany, Complutense University of Madrid, Madrid, Spain.
| | | | | | - Carsten B Schmidt-Weber
- Center of Allergy & Environment (ZAUM), Member of the German Center for Lung Research (DZL), Technical University and Helmholtz Center Munich, Munich, Germany.
| | | | - Branko Šikoparija
- BioSense Institute Research Institute for Information Technologies in Biosystems, University of Novi Sad, Novi Sad, Serbia.
| | - Carsten A Skjøth
- Department of Environmental Science, Aarhus University, Aarhus, Denmark; School of Science and the Environment, University of Worcester, Worcester, United Kingdom
| | | | | | - Marina Triviño
- Center of Allergy & Environment (ZAUM), Member of the German Center for Lung Research (DZL), Technical University and Helmholtz Center Munich, Munich, Germany
| | | | - Jeroen Buters
- Center of Allergy & Environment (ZAUM), Member of the German Center for Lung Research (DZL), Technical University and Helmholtz Center Munich, Munich, Germany.
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Tang W, Zhang L, Chen Q, Han M, Chen C, Liu W. Determination of monophenolase activity based on backpropagation neural network analysis of three-dimensional fluorescence spectroscopy. J Biotechnol 2023; 365:11-19. [PMID: 36775069 DOI: 10.1016/j.jbiotec.2023.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 01/11/2023] [Accepted: 02/07/2023] [Indexed: 02/12/2023]
Abstract
Tyrosinase is pivotal for melanin formation. Measuring monophenolase activity is of great importance for both fundamental research and industrial applications. For the first time, a backpropagation (BP) artificial neural network with three-dimensional fluorescence spectroscopy was applied for the real-time determination of tyrosinase monophenolase activity. Principal component analysis (PCA) was utilized for the dimension reduction of three-dimensional fluorescence data. The four principal components served as inputs for the neural network. Network parameters were optimized using a genetic algorithm (GA). BP learning algorithm was applied to train the network model to determine tyrosine levels in a binary mixture containing tyrosine and L-DOPA without any chemical separation. The time course of tyrosine consumption by monophenolase was determined to calculate the initial velocity of the enzymatic reaction. The limit of detection of the monophenolase assay was 0.0615 U·mL-1. This combined strategy of PCA, GAs, and BP artificial neural networks for three-dimensional fluorescence spectroscopy was efficient for the real-time and in-situ determination of monophenolase activity in a cascade reaction.
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Affiliation(s)
- Weikang Tang
- Department of Pharmaceutical and Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Ling Zhang
- Department of Pharmaceutical and Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Qinfei Chen
- Department of Pharmaceutical and Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Mengqi Han
- Department of Pharmaceutical and Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Chan Chen
- Department of Pharmaceutical and Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Wenbin Liu
- Department of Pharmaceutical and Biological Engineering, School of Chemical Engineering, Sichuan University, Chengdu 610065, China.
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Dong S, Fan Z, Chen Y, Chen K, Qin M, Zeng M, Lu X, Zhou G, Gao X, Liu JM. Performance estimation for the memristor-based computing-in-memory implementation of extremely factorized network for real-time and low-power semantic segmentation. Neural Netw 2023; 160:202-215. [PMID: 36657333 DOI: 10.1016/j.neunet.2023.01.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 12/05/2022] [Accepted: 01/09/2023] [Indexed: 01/15/2023]
Abstract
Nowadays many semantic segmentation algorithms have achieved satisfactory accuracy on von Neumann platforms (e.g., GPU), but the speed and energy consumption have not meet the high requirements of certain edge applications like autonomous driving. To tackle this issue, it is of necessity to design an efficient lightweight semantic segmentation algorithm and then implement it on emerging hardware platforms with high speed and energy efficiency. Here, we first propose an extremely factorized network (EFNet) which can learn multi-scale context information while preserving rich spatial information with reduced model complexity. Experimental results on the Cityscapes dataset show that EFNet achieves an accuracy of 68.0% mean intersection over union (mIoU) with only 0.18M parameters, at a speed of 99 frames per second (FPS) on a single RTX 3090 GPU. Then, to further improve the speed and energy efficiency, we design a memristor-based computing-in-memory (CIM) accelerator for the hardware implementation of EFNet. It is shown by the simulation in DNN+NeuroSim V2.0 that the memristor-based CIM accelerator is ∼63× (∼4.6×) smaller in area, at most ∼9.2× (∼1000×) faster, and ∼470× (∼2400×) more energy-efficient than the RTX 3090 GPU (the Jetson Nano embedded development board), although its accuracy slightly decreases by 1.7% mIoU. Therefore, the memristor-based CIM accelerator has great potential to be deployed at the edge to implement lightweight semantic segmentation models like EFNet. This study showcases an algorithm-hardware co-design to realize real-time and low-power semantic segmentation at the edge.
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Affiliation(s)
- Shuai Dong
- Institute for Advanced Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, China; Guangdong Provincial Key Laboratory of Optical Information Materials and Technology, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, China
| | - Zhen Fan
- Institute for Advanced Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, China; Guangdong Provincial Key Laboratory of Optical Information Materials and Technology, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, China.
| | - Yihong Chen
- Institute for Advanced Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, China
| | - Kaihui Chen
- Institute for Advanced Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, China
| | - Minghui Qin
- Institute for Advanced Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, China
| | - Min Zeng
- Institute for Advanced Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, China
| | - Xubing Lu
- Institute for Advanced Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, China
| | - Guofu Zhou
- Guangdong Provincial Key Laboratory of Optical Information Materials and Technology, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, China; National Center for International Research on Green Optoelectronics, South China Normal University, Guangzhou, 510006, China
| | - Xingsen Gao
- Institute for Advanced Materials, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, China
| | - Jun-Ming Liu
- Laboratory of Solid State Microstructures and Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, China
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Gupta S, Kumar P, Tekchandani R. A multimodal facial cues based engagement detection system in e-learning context using deep learning approach. Multimed Tools Appl 2023; 82:1-27. [PMID: 36789011 PMCID: PMC9911959 DOI: 10.1007/s11042-023-14392-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 11/20/2022] [Indexed: 06/18/2023]
Abstract
Due to the COVID-19 crisis, the education sector has been shifted to a virtual environment. Monitoring the engagement level and providing regular feedback during e-classes is one of the major concerns, as this facility lacks in the e-learning environment due to no physical observation of the teacher. According to present study, an engagement detection system to ensure that the students get immediate feedback during e-Learning. Our proposed engagement system analyses the student's behaviour throughout the e-Learning session. The proposed novel approach evaluates three modalities based on the student's behaviour, such as facial expression, eye blink count, and head movement, from the live video streams to predict student engagement in e-learning. The proposed system is implemented based on deep-learning approaches such as VGG-19 and ResNet-50 for facial emotion recognition and the facial landmark approach for eye-blinking and head movement detection. The results from different modalities (for which the algorithms are proposed) are combined to determine the EI (engagement index). Based on EI value, an engaged or disengaged state is predicted. The present study suggests that the proposed facial cues-based multimodal system accurately determines student engagement in real time. The experimental research achieved an accuracy of 92.58% and showed that the proposed engagement detection approach significantly outperforms the existing approaches.
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Affiliation(s)
- Swadha Gupta
- Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, 147001 Punjab India
| | - Parteek Kumar
- Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, 147001 Punjab India
| | - Rajkumar Tekchandani
- Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, 147001 Punjab India
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Li N, Dong L. Real-time digital data of international passengers will shine in the precaution of epidemics. Intell Med 2023; 3:44-45. [PMID: 36312891 PMCID: PMC9595419 DOI: 10.1016/j.imed.2022.10.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 09/27/2022] [Accepted: 10/10/2022] [Indexed: 11/05/2022]
Abstract
International movement plays an important role in spatial spread of infectious diseases. Here, we share two successful COVID-19 interventions based on real-time digital information collected from international passengers, which have been performed in Greece and China respectively. Both of the interventions demonstrated good performance and showed the potential of real-time digital data in containing the spread. However, several key points should not be ignored when we promote similar strategies.
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Affiliation(s)
- Naizhe Li
- MOE Key Laboratory For Biodiversity Science And Ecological Engineering, College of Life Sciences, Beijing Normal University, Beijing 100091, China.,State Key Laboratory of Remote Sensing Science, Center for Global Change and Public Health, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100091, China
| | - Lu Dong
- MOE Key Laboratory For Biodiversity Science And Ecological Engineering, College of Life Sciences, Beijing Normal University, Beijing 100091, China
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Junior FA, Suharjito. Video based oil palm ripeness detection model using deep learning. Heliyon 2023; 9:e13036. [PMID: 36711312 PMCID: PMC9873703 DOI: 10.1016/j.heliyon.2023.e13036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 01/11/2023] [Accepted: 01/12/2023] [Indexed: 01/19/2023] Open
Abstract
Research on oil palm detection has been carried out for years, but there are only a few research that have conducted research using video datasets and only focus on development using non-sequential image. The use of the video dataset aims to adjust to the detection conditions carried out in real time so that it can automatically harvest directly from oil palm trees to increase efficiency in harvesting. To solve this problem, in this research, we develop an object detection model using a video dataset in training and testing. We used the 3 series YOLOv4 architecture to develop the model using video. Model development is done by means of hyperparameter tuning and frozen layer with data augmentation consisting of photometric and geometric augmentation experiment. To validate the outcomes of the YOLOv4 model development, a comparison of SSD-MobileNetV2 FPN and EfficientDet-D0 was performed. The results obtained show that YOLOv4-Tiny 3L is the most suitable architecture for use in real time object detection conditions with an mAP of 90.56% for single class category detection and 70.21% for multi class category detection with a detection speed of almost 4× faster than YOLOv4-CSPDarknet53, 5× faster than SSD-MobileNetV2 FPN, and 9× faster than EfficientDet-D0.
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Affiliation(s)
- Franz Adeta Junior
- Computer Science Department, BINUS Graduate Program – Master of Computer Science, Bina Nusantara University, Jakarta, 10480, Indonesia
| | - Suharjito
- Industrial Engineering Department, BINUS Graduate Program – Master of Industrial Engineering, Bina Nusantara University, Jakarta, 11480, Indonesia,Corresponding author.
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Bang E, Oh S, Cho HW, Park DH, Chang HE, Park JS, Lee H, Song KH, Kim ES, Kim HB, Suh YH, Park KU. Development of diagnostic tests for pathogen identification and detection of antimicrobial resistance on WHO global priority pathogens using modular real-time nucleic acid amplification test. Int Microbiol 2023:10.1007/s10123-023-00321-9. [PMID: 36646920 DOI: 10.1007/s10123-023-00321-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 12/17/2022] [Accepted: 01/04/2023] [Indexed: 01/18/2023]
Abstract
BACKGROUND Concerns regarding antimicrobial resistance (AMR) have resulted in the World Health Organization (WHO) designating so-called global priority pathogens (GPPs). However, little discussion has focused on the diagnosis of GPPs. To enable the simultaneous identification of pathogens and AMR, we developed a modular real-time nucleic acid amplification test (MRT-NAAT). METHODS Sequence-specific primers for each modular unit for MRT-NAAT pathogen identification and AMR sets were designed. The composition of the reaction mixture and the real-time PCR program were unified irrespective of primer type so to give MRT-NAAT modularity. Standard strains and clinical isolates were used to evaluate the performance of MRT-NAAT by real-time PCR and melting curve analysis. Probit analysis for the MRT-NAAT pathogen identification set was used to assess the limit of detection (LoD). RESULTS The MRT-NAAT pathogen identification set was made up of 15 modular units 109-199 bp in product size and with a Tms of 75.5-87.5 °C. The LoD was < 15.548 fg/μL, and nine modular units successfully detected the target pathogens. The MRT-NAAT AMR set included 24 modular units 65-785 bp in product size with a Tms of 75.5-87.5 °C; it showed high performance for detecting GPP target genes and variants. CONCLUSIONS MRT-NAAT enables pathogen identification and AMR gene detection and is time-effective. By unifying the reaction settings of each modular unit, the modularity where combinations of primers can be used according to need could be achieved. This would greatly help in reflecting the researcher's need and the AMR status of a certain region while successfully detecting pathogens and AMR genes.
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Affiliation(s)
- Eunsik Bang
- Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Sujin Oh
- Department of Laboratory Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Hee Won Cho
- Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Da-Ha Park
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | | | - Jeong Su Park
- Department of Laboratory Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Laboratory Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Hyunju Lee
- Department of Pediatrics, Seoul National University Bundang Hospital and Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Kyoung-Ho Song
- Department of Internal Medicine, Seoul National University Bundang Hospital and Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Eu Suk Kim
- Department of Internal Medicine, Seoul National University Bundang Hospital and Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Hong Bin Kim
- Department of Internal Medicine, Seoul National University Bundang Hospital and Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Young Ho Suh
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Kyoung Un Park
- Department of Laboratory Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea. .,Department of Laboratory Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
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Kovalyov A, Patel K, Panahi I. DSENet: Directional Signal Extraction Network for Hearing Improvement on Edge Devices. IEEE Access 2023; 11:4350-4358. [PMID: 37621739 PMCID: PMC10448805 DOI: 10.1109/access.2023.3235948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/26/2023]
Abstract
In this paper, we propose a directional signal extraction network (DSENet). DSENet is a low-latency, real-time neural network that, given a reverberant mixture of signals captured by a microphone array, aims at extracting the reverberant signal whose source is located within a directional region of interest. If there are multiple sources situated within the directional region of interest, DSENet will aim at extracting a combination of their reverberant signals. As such, the formulation of DSENet circumvents the well-known crosstalk problem in beamforming while providing an alternative and perhaps more practical approach to other spatially constrained signal extraction methods proposed in the literature. DSENet is based on a computationally efficient and low-distortion linear model formulated in the time domain. As a result, an important application of our work is hearing improvement on edge devices. Simulation results show that DSENet outperforms oracle beamformers, as well as state-of-the-art in low-latency causal speech separation, while incurring a system latency of only 4 ms. Additionally, DSENet has been successfully deployed as a real-time application on a smartphone.
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Affiliation(s)
- Anton Kovalyov
- Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Kashyap Patel
- Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Issa Panahi
- Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, TX 75080, USA
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Eggert S, Stetsenko S, Wiest J. Cellasys #8: A Microphysiometric Assay for Real-Time Cell Analysis Within 24 Hours. Methods Mol Biol 2023; 2644:303-311. [PMID: 37142930 DOI: 10.1007/978-1-0716-3052-5_19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Traditional biochemical assays present a vital toolbox to identify the effects of a test substance on cells. However, current assays are single-point measurements, only reveal one parameter at a time, and introduce potential interferences with labels and fluorescent lights. We have addressed these limitations by introducing the cellasys #8 test which is a microphysiometric assay for real-time cell analysis. Within 24 h, the cellasys #8 test is able to identify not only the effect of a test substance but also measure recovery effects. Due to the multi-parametric read-out, the test provides insights into metabolic as well as morphological changes in real-time. The following protocol provides a detailed introduction to the materials as well as a step-by-step description to support scientists with protocol adoption. The automated and standardized assay opens up manifold new application areas for scientists to study biological mechanisms, develop new therapeutic approaches, and validate serum-free media formulation.
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Affiliation(s)
| | | | - Joachim Wiest
- cellasys GmbH, Kronburg, Germany
- Technical University of Munich, Heinz Nixdorf Chair of Biomedical Electronics, TranslaTUM, Munich, Germany
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45
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Pongpech WA. A Distributed Data Mesh Paradigm for an Event-based Smart Communities Monitoring Product. Procedia Comput Sci 2023; 220:584-591. [PMID: 37089762 PMCID: PMC10110347 DOI: 10.1016/j.procs.2023.03.074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
The recent pandemic events in Thailand, Covid-19 in 2018, demonstrated the need for an event-based smart monitoring system. While a distributed multi-level architecture has emerged as an architecture of choice for a larger-scale smart event-based system that requires better latency, security, scalability, and reliability, a recently introduced data mesh paradigm can add a few additional benefits. The paradigm enables each district to become an event-based smart monitoring mesh and handle its analytics and monitoring workload. Districts can form a set of domains in a network of event-based smart community monitoring systems and provide data products for others during a crisis. This paper presents a distributed data mesh paradigm for an event-based smart monitoring product in a given community with predefined domains. The paper presents smart monitoring as a data product between domains. Key considerations for designing an event-based smart monitoring data product are given. The author introduces three possible domains necessary for creating a smart monitoring system in each community. Each domain creates a data product for a given domain and shares data between domains. Finally, a three-layer analytics architecture for a smart monitoring product in each domain and a use case is presented.
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Lavikainen J, Vartiainen P, Stenroth L, Karjalainen PA. Open-source software library for real-time inertial measurement unit data-based inverse kinematics using OpenSim. PeerJ 2023; 11:e15097. [PMID: 37038471 PMCID: PMC10082569 DOI: 10.7717/peerj.15097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 02/28/2023] [Indexed: 04/12/2023] Open
Abstract
Background Inertial measurements (IMUs) facilitate the measurement of human motion outside the motion laboratory. A commonly used open-source software for musculoskeletal simulation and analysis of human motion, OpenSim, includes a tool to enable kinematics analysis of IMU data. However, it only enables offline analysis, i.e., analysis after the data has been collected. Extending OpenSim's functionality to allow real-time kinematics analysis would allow real-time feedback for the subject during the measurement session and has uses in e.g., rehabilitation, robotics, and ergonomics. Methods We developed an open-source software library for real-time inverse kinematics (IK) analysis of IMU data using OpenSim. The software library reads data from IMUs and uses multithreading for concurrent calculation of IK. Its operation delays and throughputs were measured with a varying number of IMUs and parallel computing IK threads using two different musculoskeletal models, one a lower-body and torso model and the other a full-body model. We published the code under an open-source license on GitHub. Results A standard desktop computer calculated full-body inverse kinematics from treadmill walking at 1.5 m/s with data from 12 IMUs in real-time with a mean delay below 55 ms and reached a throughput of more than 90 samples per second. A laptop computer had similar delays and reached a throughput above 60 samples per second with treadmill walking. Minimal walking kinematics, motion of lower extremities and torso, were calculated from treadmill walking data in real-time with a throughput of 130 samples per second on the laptop and 180 samples per second on the desktop computer, with approximately half the delay of full-body kinematics. Conclusions The software library enabled real-time inverse kinematical analysis with different numbers of IMUs and customizable musculoskeletal models. The performance results show that subject-specific full-body motion analysis is feasible in real-time, while a laptop computer and IMUs allowed the use of the method outside the motion laboratory.
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Laganà MM, Di Tella S, Ferrari F, Pelizzari L, Cazzoli M, Alperin N, Jin N, Zacà D, Baselli G, Baglio F. Blood and cerebrospinal fluid flow oscillations measured with real-time phase-contrast MRI: breathing mode matters. Fluids Barriers CNS 2022; 19:100. [PMID: 36517859 PMCID: PMC9749305 DOI: 10.1186/s12987-022-00394-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 09/12/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Cervical blood and cerebrospinal fluid (CSF) flow rates can be quantified with Phase-contrast (PC) MRI, which is routinely used for clinical studies. Previous MRI studies showed that venous and CSF flow alterations are linked to various pathological conditions. Since it is well known that, besides the heart beating, the thoracic pump influences the blood and CSF dynamics, we studied the effect of different respiration modes on blood and CSF flow rates using a real-time (RT)-PC prototype. METHODS Thirty healthy volunteers were examined with a 3 T scanner. A RT-PC sequence was acquired at the first cervical level to quantify the flow rates of internal carotid arteries, internal jugular veins (IJVs) and CSF. Each RT-PC acquisition was repeated three times, while the subjects were asked to breathe in three different ways for 60 s each: freely (F), with a constant rate (PN) and with deep and constant respiration rate (PD). The average flow rates were computed, they were removed from the respective signals and integrated in the inspiratory and expiratory phases (differential volumes). Finally, the power spectral density was computed for each detrended flow rate. High- and very-high frequency peaks were identified on the spectra while their frequencies were compared to the respiratory and cardiac frequencies estimated using a thoracic belt and a pulse oximeter. The area under the spectra was computed in four 0.5 Hz-wide ranges, centered on the high-frequency peak, on very-high frequency peak and its 2nd and 3rd harmonics, and then they were normalized by the flow rate variance. The effect of breathing patterns on average flow rates, on systolic and diastolic peaks, and on the normalized power was tested. Finally, the differential volumes of inspiration were compared to those of expiration. RESULTS The frequencies of the high- and very-high spectral peaks corresponded to the respiratory and cardiac frequencies. The average flow rate progressively decreased from F to PN to PD breathing, and the cardiac modulations were less predominant especially for the IJVs. The respiratory modulation increased with PD breathing. The average volumes displaced in the inspiratory phases were not significantly different from those of the expiratory one. CONCLUSIONS The spectral analyses demonstrated higher respiratory modulations in PD compared to free breathing, even prevailing the cardiac modulation in the IJVs, showing an increment of the thoracic pump affecting the flow rate shape.
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Affiliation(s)
- Maria Marcella Laganà
- grid.418563.d0000 0001 1090 9021IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Sonia Di Tella
- grid.418563.d0000 0001 1090 9021IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy ,grid.8142.f0000 0001 0941 3192Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy
| | - Francesca Ferrari
- grid.4643.50000 0004 1937 0327Department of Electronics, Information, and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Laura Pelizzari
- grid.418563.d0000 0001 1090 9021IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Marta Cazzoli
- grid.418563.d0000 0001 1090 9021IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Noam Alperin
- grid.26790.3a0000 0004 1936 8606University of Miami, Miami, USA
| | - Ning Jin
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc, Cleveland, OH USA
| | | | - Giuseppe Baselli
- grid.4643.50000 0004 1937 0327Department of Electronics, Information, and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Francesca Baglio
- grid.418563.d0000 0001 1090 9021IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
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Eckert JA, Rosenberg M, Rhen M, Choong FX, Richter-Dahlfors A. An optotracer-based antibiotic susceptibility test specifically targeting the biofilm lifestyle of Salmonella. Biofilm 2022; 4:100083. [PMID: 36117547 PMCID: PMC9474290 DOI: 10.1016/j.bioflm.2022.100083] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 08/26/2022] [Accepted: 08/29/2022] [Indexed: 11/25/2022] Open
Abstract
Antimicrobial resistance is a medical threat of global dimensions. Proper antimicrobial susceptibility testing (AST) for drug development, patient diagnosis and treatment is crucial to counteract ineffective drug use and resistance development. Despite the important role of bacterial biofilms in chronic and device-associated infections, the efficacy of antibiotics is determined using planktonic cultures. To address the need for antibiotics targeting bacteria in the biofilm lifestyle, we here present an optotracing-based biofilm-AST using Salmonella as model. Our non-disruptive method enables real-time recording of the extracellular matrix (ECM) components, providing specific detection of the biofilm lifestyle. Biofilm formation prior to antibiotic challenge can thus be confirmed and pre-treatment data collected. By introducing Kirby-Bauer discs, we performed a broad screen of the effects of antibiotics representing multiple classes, and identified compounds with ECM inhibitory as well as promoting effects. These compounds were further tested in agar-based dose-response biofilm-AST assays. By quantifying the ECM based on the amount of curli, and by visualizing the biofilm size and morphology, we achieved new information directly reflecting the treated biofilm. This verified the efficacy of several antibiotics that were effective in eradicating pre-formed biofilms, and it uncovered intriguing possible resistance mechanisms initiated in response to treatments. By providing deeper insights into the resistances and susceptibilities of microbes, expanded use of the biofilm-AST will contribute to more effective treatments of infections and reduced resistance development.
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Affiliation(s)
- Johannes A Eckert
- AIMES - Center for the Advancement of Integrated Medical and Engineering Sciences, Karolinska Institutet and KTH Royal Institute of Technology, Stockholm, Sweden.,Department of Neuroscience, Karolinska Institutet, Solnavägen 9, SE-171 77, Stockholm, Sweden
| | - Ming Rosenberg
- AIMES - Center for the Advancement of Integrated Medical and Engineering Sciences, Karolinska Institutet and KTH Royal Institute of Technology, Stockholm, Sweden.,Department of Neuroscience, Karolinska Institutet, Solnavägen 9, SE-171 77, Stockholm, Sweden
| | - Mikael Rhen
- AIMES - Center for the Advancement of Integrated Medical and Engineering Sciences, Karolinska Institutet and KTH Royal Institute of Technology, Stockholm, Sweden.,Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Solnavägen 9, SE-171 77, Stockholm, Sweden
| | - Ferdinand X Choong
- AIMES - Center for the Advancement of Integrated Medical and Engineering Sciences, Karolinska Institutet and KTH Royal Institute of Technology, Stockholm, Sweden.,Department of Neuroscience, Karolinska Institutet, Solnavägen 9, SE-171 77, Stockholm, Sweden
| | - Agneta Richter-Dahlfors
- AIMES - Center for the Advancement of Integrated Medical and Engineering Sciences, Karolinska Institutet and KTH Royal Institute of Technology, Stockholm, Sweden.,Department of Neuroscience, Karolinska Institutet, Solnavägen 9, SE-171 77, Stockholm, Sweden
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49
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Ji X, Qin R, Shi C, Yang L, Yao L, Deng S, Qu G, Yin Y, Hu L, Shi J, Jiang G. Dynamic landscape of multi-elements in PM 2.5 revealed by real-time analysis. Environ Int 2022; 170:107607. [PMID: 36332492 DOI: 10.1016/j.envint.2022.107607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 10/12/2022] [Accepted: 10/26/2022] [Indexed: 06/16/2023]
Abstract
Metal components in fine particulate matter (PM2.5) are closely associated with many adverse health outcomes. Dynamic changes of metals in PM2.5 are critical for risk assessment due to their temporal variations. Herein, an online method for real-time determination of multi-elements (As, Cd, Cs, Cu, Fe, Mg, Mn, Pb, Rb, Sn, Tl, and V) in PM2.5 was established by directly introducing air samples into inductively coupled plasma mass spectrometry (ICPMS). Meanwhile, a quantified method using metal standard aerosols (Cr, Mo, and W) and high time resolution for 3.3 min online measurement was developed and validated. The limits of detection were in the range of 0.001-6.30 ng/m3 for different metals. Subsequently, the real-time contents of multi-elements in PM2.5 for 12 h over 33 days were measured at different air qualities. Temporal variations of crustal elements like Fe, Mg are similar to PM2.5, whereas toxic elements (Pb, As and Cd) have upward trends at dusk. This denoted the association with various emission sources and different exposure concentrations of metals. In addition to the acquisition of real-time information, online analysis of multi-elements in PM2.5 is beneficial for atmospheric monitoring and provides critical insights into the different exposure risks of metals in PM2.5 at varying times.
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Affiliation(s)
- Xiaomeng Ji
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Shandong Key Laboratory of Environmental Processes and Health, School of Environmental Science and Engineering, Shandong University, Qingdao 266237, China
| | - Ruiliang Qin
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; School of Water Resources and Environment, China University of Geosciences (Beijing), Beijing 100083, China
| | - Chunzhen Shi
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; College of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Lin Yang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Linlin Yao
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Shenxi Deng
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Guangbo Qu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310000, China
| | - Yongguang Yin
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310000, China
| | - Ligang Hu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310000, China
| | - Jianbo Shi
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310000, China; State Environmental Protection Key Laboratory of Source Apportionment and Control of Aquatic Pollution, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China.
| | - Guibin Jiang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310000, China
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50
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Haller JD, Bodor A, Luy B. Pure shift amide detection in conventional and TROSY-type experiments of 13C, 15N-labeled proteins. J Biomol NMR 2022; 76:213-221. [PMID: 36399207 PMCID: PMC9712348 DOI: 10.1007/s10858-022-00406-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 10/24/2022] [Indexed: 06/16/2023]
Abstract
Large coupling networks in uniformly 13C,15N-labeled biomolecules induce broad multiplets that even in flexible proteins are frequently not recognized as such. The reason is that given multiplets typically consist of a large number of individual resonances that result in a single broad line, in which individual components are no longer resolved. We here introduce a real-time pure shift acquisition scheme for the detection of amide protons which is based on 13C-BIRDr,X. As a result the full homo- and heteronuclear coupling network can be suppressed at low power leading to real singlets at substantially improved resolution and uncompromised sensitivity. The method is tested on a small globular and an intrinsically disordered protein (IDP) where the average spectral resolution is increased by a factor of ~ 2 and higher. Equally important, the approach works without saturation of water magnetization for solvent suppression and exchanging amide protons are not affected by saturation transfer.
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Affiliation(s)
- Jens D. Haller
- Institute of Organic Chemistry and Institute for Biological Interfaces 4 – Magnetic Resonance, Karlsruhe Institute of Technology (KIT), Hermann-Von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
| | - Andrea Bodor
- Institute of Chemistry, Analytical and BioNMR Laboratory, ELTE –Eötvös Loránd University, Pázmány Péter Sétány 1/A, 1117 Budapest, Hungary
| | - Burkhard Luy
- Institute of Organic Chemistry and Institute for Biological Interfaces 4 – Magnetic Resonance, Karlsruhe Institute of Technology (KIT), Hermann-Von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
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