BBDash: An Electron-based tool for analyzing blood product utilization

Blood transfusions can be associated with side effects ranging from occasional febrile reactions to extremely rare fatal reactions. Monitoring blood product orders and ensuring appropriate utilization is therefore an important strategy to ensure patient safety. However, data extracted from laboratory information systems can be difficult to interpret. We created BBDash, an Electron-based tool that reads Sunquest reports to create easy-to-interpret graphs related to blood product utilization.

A PDMS-encapsulated cylindrical non-closed-packed photonic crystals composite with Bragg-enhanced Fresnel reflectance for optical gain and spectral selection

According to the Fresnel theory, the reflectivity intensity of spherical and cylindrical convex surfaces decreases from their edge to center, and it is noteworthy and interesting for optical gain to study the enhancement of center reflectance. In this paper, a polydimethylsiloxane (PDMS) - encapsulated cylindrical non-closed-packed photonic crystals (NPCs) composite with Bragg-enhanced Fresnel reflectance was designed for spectral selectivity and optical gain. Theoretically and experimentally, the periodically ordered structure of NPCs achieved high-reflection of light in photonic bandgap and high-transmission in other bands, which enhanced Fresnel reflectivity of the convex center to specific bands. Furtherly, the cylindrical NPCs hydrogel with stretchability was applied for the dynamic tuning of optical signals. The reflection peak of the PDMS-encapsulated cylindrical NPCs composite blue-shifted from 608 nm to 413 nm with 50 % tensile strain and achieved a rapid transition of structural color from orange to blue-violet in 60 cycles. The new kind of photonic crystals composite for optical gain and spectral selection broke through the limitations of traditional Fresnel curved mirrors with the lowest central reflectivity and inability to perform spectral selectivity, and have great significance and application prospects in fields of signal transmission, optical measurement, and instrument design.

Recent advances in molecularly imprinted polymers (MIPs) for visual recognition and inhibition of α-dicarbonyl compound-mediated Maillard reaction products

α-Dicarbonyl compounds (α-DCs) are important intermediates and precursors of harmful Maillard reaction products (e.g., acrylamide and late glycosylation end-products), and they exist widely in thermoprocessed sugar- or fat-rich foods. α-DCs and their end-products are prone to accumulation in the human body and lead to the development of various chronic diseases. Therefore, detection of α-DCs and their associated hazards in food samples is crucial. This paper reviews the preparation of molecularly imprinted polymers (MIPs) enabling visual intelligent responses and the strategies for recognition and capture of α-DCs and their associated hazards, and provides a comprehensive summary of the development of visual MIPs, including integration strategies and applications with real food samples. The visual signal responses as well as the mechanisms for hazard recognition and capture are highlighted. Current challenges and prospects for visual MIPs with advanced applications in food, agricultural and environmental samples are also discussed. This review will open new horizons regarding visual MIPs for recognition and inhibition of hazards in food safety.

Porphyrin fluorescence imaging for real-time monitoring and visualization of the freshness of beef stored at different temperatures

This study presents a novel fluorescence imaging method for the real-time monitoring of beef quality deterioration and freshness. The fluorescence property of porphyrin in the form of heme can be used to characterize quality changes in beef during storage. Therefore, a fluorescence imaging system with an excitation light source of 440 nm and a CCD camera with a specific wavelength filter of 595 nm was constructed, and the porphyrin fluorescence images of beef samples stored at different temperatures were then collected. The quantitative model for predicting the microbial freshness indicator (TVC) of beef was built with the support vector machine regression (SVR) algorithm and produced satisfactory results with Rc2 and Rp2 of 0.858 and 0.812, respectively. The classification model based on the support vector machine (SVM) algorithm classified beef freshness into "fresh" and "spoiled", with calibration and prediction accuracy of 100 % and 90.9 %, respectively.

Visualization of phenanthrene effect on biochar colloids transport in porous media

Biochar colloids (BCs) can be used as adsorbent materials for remediation of phenanthrene due to their high specific surface area and other characteristics. Understanding the effects of phenanthrene on the transport of BCs contributes to facilitate the removal of phenanthrene in soil and water habitats. In this work, the influence of phenanthrene on the transport of BCs under different environmental factors (pH, ionic strength (IS), media size) in a one-dimensional sand column was firstly explored together with a real-time visualization system to explore the transport mechanism of BCs in two-dimensional sand tank. The results show that phenanthrene adsorbed on the surface of BCs, shielded its surface charge and reduced the mobility of BCs in porous media. Acidic conditions promoted the agglomeration of BCs and adsorption of phenanthrene, resulting in a 51.03 % decrease in the maximum breakthrough rate of BCs compared to alkaline conditions. The same was true for the high IS condition, where the maximum breakthrough rate of BCs was only 0.95 % at IS = 50. Additionally, there was a substantial and positive correlation between media particle size and BCs mobility. As the quartz sand particle size increased, the maximum breakthrough rates of BCs were 2.67 %, 33.28 %, and 52.27 % in the 1-D experiment, and 0, 13.88 %, and 13.10 % in the 2-D experiment, respectively. The contact area of BCs with the medium expands under the fine particle size condition, leading to a significant decrease in the mobility of BCs at low potentials influenced by phenanthrene. This finding is significant for biochar application in phenanthrene contaminated soil and groundwater remediation.

A new comprehensive quantitative index for the assessment of essential amino acid quality in beef using Vis-NIR hyperspectral imaging combined with LSTM

The quality of beef is usually predicted by measuring a single index rather than a comprehensive index. To precisely determine the essential amino acid (EAA) contents in 360 beef samples, the feasibility of optimized spectral detection techniques based on the comprehensive EAA index (CEI) and comprehensive weight index (CWI) constructed by factor analysis was explored. Two-dimensional correlation spectroscopy (2D-COS) was used to analyse the mechanisms of spectral peak shifts in complex disturbance systems with CEI and CWI contents, and 15 sensitive feature variables were extracted to establish a quantitative analysis model of a long short-term memory network (LSTM). The results indicated that 2D-COS had good predictive performance in both CEI-LSTM (R2P of 0.9095 and RPD of 2.76) and CWI-LSTM (R2P of 0.8449 and RPD of 2.45), which reduced data information by 88%. This indicates that utilizing 2D-COS can eliminate collinearity and redundant information among variables while achieving data dimensionality reduction and simplification of calibration models. Furthermore, a spatial distribution map of the comprehensive EAA content was generated by combining the optimal prediction model. This study demonstrated that the comprehensive index method furnishes a new approach to rapidly evaluate EAA content.

Research hotspots and development trends in volume management of peritoneal dialysis patients: a bibliometrics and visual analysis up to 2022

OBJECTIVES

Among different renal replacement therapies (RRTs), peritoneal dialysis (PD) is a family based treatment method with multiple advantages, which allowing patients to maintain autonomy, avoiding frequent hospital visits, and preventing the spread of the disease virus. To visually analyze the literatures related to volume management of PD patients through bibliometric methods, to explore research hotspots and development trends in this field.

METHODS

The relevant literatures of PD patient volume management in the Web of Science core collection database were retrieved with the terms of peritoneal dialysis, volume management, capacity management, fluid status, and volume overload. The retrieval time was from the establishment of the database to October 2022. CiteSpace 6.1.R3 software was used to visually analyze Country, Institution, Author, Keyword, and draw keyword clusters and keyword emergence maps.

RESULTS

A total of 788 articles were included in the analysis, and the annual number of papers was on the rise, with the American, China, and Brirain in the top three, and Peking University and University College London in the top. Keywords cluster analysis showed 11 clusters. In the keyword emergence analysis, the keywords with higher emergence intensity rank are continuous cyclic peritoneal dialysis, ambulatory peritoneal dialysis, and icodextrin. The current research hotspots and trends are in the evaluation of peritoneal dialysis patients' volume status, the selection and adjustment of dialysis prescriptions, and adverse health outcomes.

CONCLUSION

The research on peritoneal dialysis volume management in China started late, but it has developed rapidly, and has a firm grasp of current research hotspots. However, there is less cooperation with other countries, so international exchanges and cooperation should be strengthened. At present, the volume assessment methods and dialysis modes are still the research hotspots, paying more attention to the adverse health outcomes of patients.

Genome-scale metabolic network models for industrial microorganisms metabolic engineering: Current advances and future prospects

The construction of high-performance microbial cell factories (MCFs) is the centerpiece of biomanufacturing. However, the complex metabolic regulatory network of microorganisms poses great challenges for the efficient design and construction of MCFs. The genome-scale metabolic network models (GSMs) can systematically simulate the metabolic regulation process of microorganisms in silico, providing effective guidance for the rapid design and construction of MCFs. In this review, we summarized the development status of 16 important industrial microbial GSMs, and further outline the technologies or methods that continuously promote high-quality GSMs construction from five aspects: I) Databases and modeling tools facilitate GSMs reconstruction; II) evolving gap-filling technologies; III) constraint-based model reconstruction; IV) advances in algorithms; and V) developed visualization tools. In addition, we also summarized the applications of GSMs in guiding metabolic engineering from four aspects: I) exploring and explaining metabolic features; II) predicting the effects of genetic perturbations on metabolism; III) predicting the optimal phenotype; IV) guiding cell factories construction in practical experiment. Finally, we discussed the development of GSMs, aiming to provide a reference for efficiently reconstructing GSMs and guiding metabolic engineering.

Visualization of water transfer channel in sludge dewatering conditioned with skeleton builders by X-ray micro-computed tomography

Skeleton builders were normally deemed to improve the high porosity and newly-generated permeability of sludge cakes by building water transfer channel during high pressure filtration, thus enhancing sludge dewaterability. However, currently a direct visualization proof of water transfer channel was still lacking. This study provided the direct proof for visualizing water transfer channel in dewatered sludge cakes conditioned with a typical skeleton builder (i.e., phosphogypsum (PG)) by X-ray micro-computed tomography (micro-CT) for the first time. After the addition of PG, the pixel value and image luminance increased significantly, indicating the presence of high density substances from both two-dimensional (2D) cross section and three-dimensional (3D) reconstruction CT images. Moreover, the CT numbers showed strong and negative correlations with specific resistance to filtration (SRF) (R = - 0.99, p < 0.05), capillary suction time (CST) (regression coefficient (R) = - 0.87, probability (p) < 0.05), and water content of the dewatered sludge cake (R = - 0.99, p < 0.05), respectively. These results indicated that the X-ray micro-CT could be a potential technique for analyzing the water distribution in sludge samples conditioned with skeleton builders.

The cardiovascular system at high altitude: A bibliometric and visualization analysis

BACKGROUND

When exposed to high-altitude environments, the cardiovascular system undergoes various changes, the performance and mechanisms of which remain controversial.

AIM

To summarize the latest research advancements and hot research points in the cardiovascular system at high altitude by conducting a bibliometric and visualization analysis.

METHODS

The literature was systematically retrieved and filtered using the Web of Science Core Collection of Science Citation Index Expanded. A visualization analysis of the identified publications was conducted employing CiteSpace and VOSviewer.

RESULTS

A total of 1674 publications were included in the study, with an observed annual increase in the number of publications spanning from 1990 to 2022. The United States of America emerged as the predominant contributor, while Universidad Peruana Cayetano Heredia stood out as the institution with the highest publication output. Notably, Jean-Paul Richalet demonstrated the highest productivity among researchers focusing on the cardiovascular system at high altitude. Furthermore, Peter Bärtsch emerged as the author with the highest number of cited articles. Keyword analysis identified hypoxia, exercise, acclimatization, acute and chronic mountain sickness, pulmonary hypertension, metabolism, and echocardiography as the primary research hot research points and emerging directions in the study of the cardiovascular system at high altitude.

CONCLUSION

Over the past 32 years, research on the cardiovascular system in high-altitude regions has been steadily increasing. Future research in this field may focus on areas such as hypoxia adaptation, metabolism, and cardiopulmonary exercise. Strengthening interdisciplinary and multi-team collaborations will facilitate further exploration of the pathophysiological mechanisms underlying cardiovascular changes in high-altitude environments and provide a theoretical basis for standardized disease diagnosis and treatment.

Ketamine and its enantiomers for depression: a bibliometric analysis from 2000 to 2023

Ketamine has demonstrated rapid and sustained antidepressant effects, marking its emergence as an innovative treatment of depression. Despite the growing number of preclinical and clinical studies exploring the antidepressant effects of ketamine and its enantiomers, a comprehensive bibliometric analysis in this field has yet to be conducted. This study employs bibliometric methods and visualization tools to examine the literature and identify key topics related to the antidepressant effects of ketamine and its enantiomers. We sourced publications on the antidepressant effects of ketamine and its enantiomers from the Web of Science Core Collection (WOSCC) database, covering the period from 2000 to 2023. Tools such as VOSviewer, CiteSpace and the R package "bibliometrix" were utilized for visual analysis. The study included 4,274 publications, with a notable increase in publications peaking in 2022. Co-occurrence analysis highlighted two primary research focal points: the efficacy and safety of ketamine and its enantiomers in treating depression, and the mechanisms behind their antidepressant effects. In conclusion, this analysis revealed a significant increase in research on the antidepressant effects of ketamine and its enantiomers over the past two decades, leading to the approval of esketamine nasal spray for treatment-resistant depression. The rapid antidepressant effects of ketamine have spurred further studies into its mechanisms of action and the search for new antidepressants with fewer side effects.

OmicNavigator: open-source software for the exploration, visualization, and archival of omic studies

BACKGROUND

The results of high-throughput biology ('omic') experiments provide insight into biological mechanisms but can be challenging to explore, archive and share. The scale of these challenges continues to grow as omic research volume expands and multiple analytical technologies, bioinformatic pipelines, and visualization preferences have emerged. Multiple software applications exist that support omic study exploration and/or archival. However, an opportunity remains for open-source software that can archive and present the results of omic analyses with broad accommodation of study-specific analytical approaches and visualizations with useful exploration features.

RESULTS

We present OmicNavigator, an R package for the archival, visualization and interactive exploration of omic studies. OmicNavigator enables bioinformaticians to create web applications that interactively display their custom visualizations and analysis results linked with app-derived analytical tools, graphics, and tables. Studies created with OmicNavigator can be viewed within an interactive R session or hosted on a server for shared access.

CONCLUSIONS

OmicNavigator can be found at https://github.com/abbvie-external/OmicNavigator.

Analyzing global research trends and focal points in the utilization of laser techniques for the treatment of urolithiasis from 1978 to 2022: visualization and bibliometric analysis

Laser lithotripsy is gaining global prominence and is a dynamically progressing field marked by a continual influx of new and comprehensive research each year. Recently, there has been a noticeable shift toward the adoption of various kinds of lasers, such as holmium: yttrium-aluminum-garnet (Ho:YAG) and thulium fiber (TFL) lasers. Consequently, we aim to conduct a bibliometric analysis to analyze key areas of research activity within scientific publications that center on the utilization of laser techniques in urolithiasis. A search of the literature spanning from 1978 to 2022 was carried out on 25 December 2023 using the Scopus database to explore research related to the application of laser techniques for urolithiasis treatment. Visualization analysis was performed using VOSviewer software (version 1.6.20). We examined 962 publications that met the specified criteria, 791 (82.22%) of which were original articles. The analysis of the retrieved publications indicated a consistent increase in research output from 1978 to 2022; a particularly noteworthy surge occurred after 2003. In particular, the U.S. claimed the leading position as the most productive country, contributing 211 articles (21.93%). However, India had the highest research productivity according to the adjustment index of 19.08. In the European region, 324 publications (33.68% of the total) originated from 25 countries. The Journal of Endourology contributed the most between 1978 and 2022 (n = 96, 9.98%). The most cited paper examined the effectiveness of holmium: yttrium-aluminum-garnet (Ho:YAG) lasers, while a subsequent study focused on the use of a thulium fiber laser (TFL), an emerging laser technology that has gained increased recognition. Co-occurrence analysis revealed three distinct clusters focusing on the types of laser technology, minimally invasive approaches, and success rate/postoperative complications. This comprehensive investigation delves into the global landscape of laser use for the treatment of urolithiasis. This review supports the emerging clinical concept of using various types of laser technology for urolithiasis treatment. Moreover, the hot issues that researchers should focus on based on the findings of this study are the use of different types of laser lithotripsy in view of the surgical approach, success rate and complications.

Ischemic stroke pathophysiology: A bibliometric and visualization analysis from 1990 to 2022

Background

Pathophysiology plays a significant role in the scientific study of ischemic stroke, and has attracted increasing interest from researchers in the field. However, a comprehensive bibliometric analysis is lacking in this field. The purpose of this study is to identify the current research status and hotspots of ischemic stroke pathophysiology from a bibliometric perspective.

Methods

The Web of Science Core Collection database was searched for articles published from 1990 to 2022. CiteSpace, VOSviewer, and R package "bibliometrix" software were used to analyze countries/regions, institutions, journals, authors, papers, and keywords to predict the latest trends in ischemic stroke pathophysiology research.

Results

This analysis collected 7578 records of ischemic stroke pathophysiology. China and America emerged as the leading countries in this field, with Harvard University being the most active institution. Among journals and authors in this field, journal Stroke and author Gregory YH Lip published the most papers, while Nature Medicine was the journal with the highest citation per article. Keywords and co-citation clusters were closely related to "central nervous system", "mechanisms", "biochemistry & molecular biology" and "radiology, nuclear medicine & medical imaging", while other related fields, such as peripheral organs damage induced by the central nervous system and rehabilitation after ischemic stroke, require further research efforts.

Conclusion

This is the first bibliometric study that comprehensively mapped out the knowledge structure and development trends of ischemic stroke pathophysiology in recent 32 years, which may provide a reference for scholars to explore ischemic stroke pathophysiology.

Schiff base functionalized dialdehyde starch for enhanced removal of Cu (II): Preparation, performances, DFT calculations

Dialdehyde starch modified by 2-hydrazinopyridine (HYD-DAS) based on the reaction of dialdehyde starch (DAS) and 2-hydrazinopyridine was synthesized and characterized by FT-IR spectra, element analysis and SEM. HYD-DAS can efficiently adsorb Cu (II) ion to demonstrate visual color changes from yellow to dark brown in aqueous solutions. The influence on HYD-DAS to Cu (II) adsorption including pH value of solution, isotherm, kinetics, thermodynamics and possible mechanism had also been examined. Batch experiments indicate that HYD-DAS's to Cu (II) adsorption reaches equilibrium within 250 min, and its adsorption capacity and rate are 195.75 mg/g and 98.63 %, respectively. Moreover, HYD-DAS to Cu (II) adsorption remains robust and underscoring after five cycles to exhibit good selectivity and reusability. Kinetics studies suggest the absorption process follows a quasi-second-order with isotherms aligning to the Langmuir monolayer model, and thermodynamics reveals that it is a spontaneous endothermic nature of adsorption. Based on the analyses of XPS and DFT calculations, a possible mechanism for HYD-DAS to Cu (II) adsorption is that Cu (II) combined with nitrogen atoms from Schiff base and hydrazine pyridine ring in HYD-DAS.

Cavitation suppression and transformation of turbulence structure in the cross flow around a circular cylinder: Surface morphology and wettability effects

Passive methods of flow and cavitation control appear to offer some of the best prospects in the field of hydraulic engineering and marine applications. In this article, we aimed at an experimental examination of the effect of wall roughness/wettability on the occurrence of cavitation and turbulence structure in the cross flow around and in the wake of a circular cylinder in two characteristic regimes. For this, we used three test bodies with different surface morphologies: smooth (reference), micro-scale irregularities (rough) and regular large-scale (of the order of a millimeter) texture (finned). Using high-speed imaging to observe vapor cavities, we revealed that cavitation is noticeably suppressed by both types of roughness. Applying the method of vapor phase detection (Pervunin et al., 2021), this finding was then quantitatively confirmed through an in-depth analysis of an ensemble of instantaneous velocity fields measured by PIV, indicating that modification of wall morphology is an effective method of cavitation control. The procedure of statistical vector filtration (Heinz et al., 2004) allowed us to remove outliers from the velocity fields and, thus, calculate various turbulence characteristics, including higher-order moments (i.e., the coefficients of skewness and excess). Wall irregularities were found to significantly affect the turbulence structure of the wake flow, but the higher-order moments downstream of the modified-surface cylinders turned out to be unexpectedly insensitive to a change in the flow regime, as opposed to the smooth one. Regardless of the type of surface morphology, the influence of roughness on the mechanism of formation of large-scale vortices and their characteristics was weakened. However, it caused overall disorganization of liquid motion in the cylinder wake, thus making local flow conditions highly unsteady. In addition, this process became more chaotic with an increase in the scale of irregularities.

β-Galactosidase-triggered in situ synthesis of yellow emitting silicon nanoparticle and its application in visual detection of E. coli O157:H7 and drug susceptibility test

The sensitive detection of foodborne pathogenic and rapid antibiotic susceptibility testing (AST) is of great significance. This paper reports the enzyme-triggered in situ synthesis of yellow emitting silicon nanoparticles (SiNPs) and the detection of Escherichia coli (E. coli) O157:H7 in food samples and the rapid AST. The rapid counting of E. coli O157:H7 has been achieved through direct visual observation, equipment detection, and smartphone digitalization. A simple detection platform based on smartphone senses and cotton swabs has been established. Meanwhile, rapid AST based on enzyme-catalyzed SiNPs can intuitively obtain colorimetric samples. This paper established a system for bacterial enzyme-triggered in situ synthesis of SiNPs, with high responsiveness, luminescence ratio, and specificity. The detection limit for E. coli O157:H7 can reach 100 CFU/mL during 5 h, and the recovery efficiency ranges from 90.14% to 110.16%, which makes it a promising strategy for the rapid detection of E. coli O157:H7 and AST.

Molecularly imprinted ratiometric fluorescence sensor for visual detection of 17β-estradiol in milk: A generalized strategy toward imprinted ratiometric fluorescence construction

17β-Estradiol (E2) is the typical endocrine disruptor of steroidal estrogens and is widely used in animal husbandry and dairy processing. In the environment, even lower concentrations of E2 can cause endocrine dysfunction in organisms. Herein, we have developed a novel molecularly imprinted ratiometric fluorescent sensor based on SiO2-coated CdTe quantum dots (CdTe@SiO2) and 7-hydroxycoumarin with a post-imprint mixing strategy. The sensor selectively detected E2 in aqueous environments due to its two fluorescent signals with a self-correction function. The sensor has been successfully used for spiking a wide range of real water and milk samples. The results showed that the sensor exhibited good linearity over the concentration range 0.011-50 μg/L, obtaining satisfactory recoveries of 92.4-110.6% with precisions (RSD) < 2.5%. Moreover, this sensor obtained an ultra-low detection limit of 3.3 ng/L and a higher imprinting factor of 13.66. By using estriol (E3), as a supporting model, it was confirmed that a simple and economical ratiometric fluorescent construction strategy was provided for other hydrophobic substances.

Laparoscopy training of novices with complex curved instruments using 2D- and 3D-visualization

PURPOSE

Beside many advantages, disadvantages such as reduced degrees of freedom and poorer depth perception are still apparent in laparoscopic surgery. 3D visualization and the development of complex instruments are intended to counteract the disadvantages. We want to find out whether the use of complex instruments and 3D visualization has an influence on the performance of novices.

METHODS

48 medical students with no experience in laparoscopic surgery or simulator-based laparoscopy training were included. They were randomized in four groups according to a stratification assessment. During a structured training period they completed the FLS-Tasks "PEG Transfer", "Pattern Cut" and "Intracorporeal Suture" and a transfer task based on these three. Two groups used conventional laparoscopic instruments with 3D or 2D visualization, two groups used complex curved instruments. The groups were compared in terms of their performance.

RESULTS

In 2D laparoscopy there was a better performance with straight instruments vs. curved instruments in PEG Transfer and Intracorporeal Suture. In the transfer task, fewer errors were made with straight instruments. In 2D vs. 3D laparoscopy when using complex curved instruments there was an advantage in Intracorporeal Suture and PEG Transfer for 3D visualization. Regarding the transfer exercise, a better performance was observed and fewer errors were made in 3D group.

CONCLUSION

We could show that learning laparoscopic techniques with complex curved instruments is more difficult with standard 2D visualization and can be overcome using 3D optics. The use of curved instruments under 3D vision seems to be advantageous when working on more difficult tasks.

A Narrative Review on 3D Visualization Techniques in Neurosurgical Education, Simulation and Planning

INTRODUCTION

High-fidelity visualization of anatomical organs is crucial for neurosurgical education, simulation, and planning. This becomes much more important for minimally invasive neurosurgical procedures. Realistic anatomical visualization can allow resident surgeons to learn visual cues and orient themselves with the complex 3D anatomy. Achieving full fidelity in 3D medical visualization is an active area of research, however, the prior reviews focus on the application area and lack the underlying technical principles. Accordingly, the present study attempts to bridge this gap by providing a narrative review of the techniques used for 3D visualization.

MATERIALS AND METHODS

We conducted a literature review on 3D medical visualization technology from 2018 to 2023 using the PubMed and Google Scholar search engines. The cross-referenced manuscripts were extensively studied to find literature that discusses technology relevant to 3D medical visualization. We also compiled and ran software applications that were accessible to us in order to better understand them.

RESULTS

We present the underlying fundamental technology used in 3D medical visualization in the context of neurosurgical education, simulation, and planning. Further, we discuss and categorize a few important applications based on the 3D visualization techniques they use.

CONCLUSIONS

The visualization of virtual human organs has not yet achieved a level of realism close to reality. This gap is largely due to the interdisciplinary nature of this research, population diversity, and validation complexities. With the advancements in computational resources and automation of 3D visualization pipelines, next-gen applications may offer enhanced medical 3D visualization fidelity.

An experimental study on the visual identification of Fritillaria ussuriensis based on LAMP and nucleic acid colloidal gold technique

Fritillaria ussuriensis Maxim is one of the traditional Chinese valuable herbs, which is the dried bulb of Fritillaria, a plant of the lily family. The identification of authenticity about F. ussuriensis is still technically challenging. In this study, visual identification was performed by ring-mediated isothermal amplification and nucleic acid colloidal gold techniques. Firstly, multiple sequence comparative analysis was performed by DNAMAN to find the differential sites of F. ussuriensis and its mixed pseudo-products, and the specific identification primers of F. ussuriensis were designed. Genomic DNA was extracted by the modified CTAB method, and the reaction system and reaction conditions were optimized to construct LAMP for the visual detection of F. ussuriensis, meanwhile, the genuine product was cloned and the extracted plasmid was sequenced. The specificity and sensitivity were detected, and also verified by nucleic acid colloidal gold method, and 20 commercially available samples were tested. The extracted DNA met the requirements of the experiment, and the genuine F. ussuriensis PCR product titrated on a test strip showed two bands on the T and C lines, while the counterfeit and negative control showed only one band on the C line, which matched the LAMP results. The specificity was 100 %, and the sensitivity of LAMP assay was up to 0.01 ng μL-1, while that of colloidal gold assay was 0.1 ng μL-1, thus the LAMP assay had high sensitivity. 14 out of 20 commercially available samples of F. ussuriensis were qualified, and 6 were unqualified, and the results of the two methods of identification were consistent. In this study, the combined detection method of LAMP and colloidal gold for nucleic acid was established to be specific, rapid, precise and visualized, which can provide a new technical idea for the detection of F. ussuriensis.

Botulinum toxin injection for abductor spasmodic dysphonia under cervical ultrasonography guidance

Ultrasound (US) imaging effectively provides real-time anatomical information for clinical examinations. In otolaryngology, US imaging can visualize laryngeal muscles as well as cervical muscles. Here we present the case where US imaging was used while injecting botulinum toxin (BT) for the treatment of abductor spasmodic dysphonia, which provided definite results. We could visualize not only the injection pathway but also the infiltration of the BT solution into the posterior cricoarytenoid muscles. Therefore, our laryngeal US imaging is useful for both improving the success rate and avoiding injection complications of BT.

oppHeatmap: Rendering Various Types of Heatmaps for Omics Data

Heatmaps are preferred visualization modes for biologists to display high-dimensional information from high-throughput omics data. Many software including website services and R packages are available to generate various types of customized heatmaps. Here, we describe oppHeatmap (omics pilot platform of heatmap), a new tool constructed to render different kinds of heatmaps through MATLAB. oppHeatmap is available for plotting ordinary heatmaps, hierarchical clustering, TreeMaps, microplates graph, sample correlation (full heatmap and upper and lower triangle parts), gene correlation (between columns or tables), and polar heatmaps. oppHeatmap can support the modification of borders, fonts, and colors to customize the final plots. oppHeatmap can not only read data from Microsoft Excel to generate specific heatmaps but also make Excel heatmaps by coloring each cell in Excel. The graphs can be stored in SVG (supported vector graph) format and modified by other SVG recognition software. oppHeatmap is designed by MATLAB AppDesigner with GUI (graphical user interface) operation. The program for oppHeatmap was available at https://github.com/HangZhouSheep/oppHeatmap .are diagramed by.

Visualizing the bibliometrics of the inflammatory mechanisms in intervertebral disc degeneration

OBJECTIVE

Intervertebral disc degeneration (IVDD) constitutes a crucial pathological foundation for spinal degenerative diseases (SDD) and stands as a primary contributor to both low back pain (LBP) and disability. The progression of IVDD is linked to structural and functional alterations in tissues, where an imbalance in the inflammatory microenvironment can induce extracellular matrix (ECM) degradation, senescence, and apoptosis. This imbalance is a key pathomechanism in the disease's development, gaining considerable attention in recent years. This study aims to conduct a bibliometric analysis of publications pertaining to the inflammatory mechanisms of IVDD to quantitatively assess current research hotspots and directions.

METHODS

In this study, we queried the Web of Science Core Collection (WOSCC) database covering the period from January 1, 2001, to November 7, 2023. Content in this area was analyzed and visualized using software such as Citespace, Vosviewer, and the bibliometrix package.

RESULTS

Findings indicate a consistent annual increase in the number of publications, highlighting the widespread attention garnered by research on the inflammatory mechanisms of IVDD. In terms of journal research, Spine emerged with the highest number of publications, along with significantly elevated total citations and average citations compared to other journals. Regarding country analysis, China led in the number of publications, while the USA claimed the highest number of citations and total link strength. Institutional analysis revealed Sun Yat-sen University as having the highest number of publications and total link strength, with Thomas Jefferson University securing the highest total citations. Author analysis identified Ohtori, S. with the highest number of publications, Risbud, M.V. with the highest number of citations, and Inoue, G. with the highest total link strength, all of whom have made significant contributions to the field's development. Citation and co-citation analyses indicated that highly cited documents primarily focused on classical studies exploring inflammatory mechanisms in IVDD pathogenesis. Keyword analysis showcased the ongoing research hotspot as the further investigation of mechanisms and treatment studies. Recent years have seen a shift towards exploring pyroptosis, necrotic apoptosis, autophagy, ferroptosis, oxidative stress, and bacterial infection, among other mechanisms. In terms of treatment, alongside traditional monomer, drug, and compound therapies for IVDD, research is increasingly concentrating on stem cell therapy, exosomes, hydrogels, and scaffolds.

CONCLUSION

This bibliometric analysis of research on inflammatory mechanisms in IVDD provides insights into the current status, hotspots, and potential future trends. These findings can serve as a valuable reference and guide for researchers in the field.

Anatomical quantitative evaluation of popliteal artery visualization during medial approach in supine position

PURPOSE

The medial approach to the popliteal artery has been less commonly used than the posterior approach in surgical repair of traumatic popliteal injury. This study was performed to quantitatively evaluate the visual field of the popliteal artery obtained by staged myotendotomy in the medial approach to the popliteal artery.

METHODS

Twenty legs of fresh-frozen adult cadavers were dissected using the medial approach to the popliteal artery. In stage 1, the popliteal artery was exposed between the vastus medialis and sartorius muscles without myotendotomy. In stage 2, the medial head of the gastrocnemius muscle was dissected. In stage 3, the tendons of the sartorius and semimembranosus muscles were dissected. In stage 4, the tendons of the gracilis and semitendinosus muscles were dissected to fully expose the popliteal artery. The length of the popliteal artery that could be visualized in each stage was measured.

RESULTS

The anatomical length of the popliteal artery from the hiatus of the adductor magnus to the tendinous arch of soleus muscle ranged from 15 to 20 cm (mean, 16.3 cm). On average, 45%, 59%, 72%, and 100% of the popliteal artery were visualized in stage 1, 2, 3, and 4, respectively.

CONCLUSIONS

The medial approach to the popliteal artery has the advantage of being performed in the supine position, but it requires multiple myotendotomies around the knee. The results of this study may serve as a reference for myotendotomy depending on the site of injury to the popliteal artery.

Development of fluorescent GO-AgNPs-Eu3+ nanoparticles based paper visual sensor for foodborne spores detection

Foodborne spores are ubiquitous with extremely strong resistance, and pose a serious threat to food safety and human health. Therefore, rapid, sensitive, and selective detection of spores are crucial. In this study, a fluorescent probe was developed based on lanthanide ion (Eu3+)-labeled nano-silver-modified graphene oxide (GO-AgNPs-Eu3+) for the detection of 2,6-dipicolinic acid (DPA), a biomarker unique to spores, to allow quantitative spores detection. The GO-AgNPs-Eu3+ nano-fluorescent probe was loaded onto a polyvinylidene fluoride microfiltration membrane, and a smartphone-assisted portable GO-AgNPs-Eu3+ nanoparticles-based paper visual sensor was designed for rapid on-site quantitative and real-time online detection of spores. The results indicated that the developed probe achieved equilibrium binding with DPA within 5 min, and enhanced fluorescence emission through antenna effect. The fluorescence detection presented a good linear relationship in the DPA concentration range of 0-45 μM, with a DPA detection limit of 4.62 nM and spore detection limit of 104 cfu/mL. The developed sensor showed a change in fluorescence from blue to red with increasing DPA concentration, and this color change was quantitatively detected through smartphone RGB variations, with a detection limit of 13.1 μM for DPA and 6.3 cfu/mL for Bacillus subtilis spores. Subsequently, the sensitivity and selectivity of the developed sensor were verified using actual milk and water samples spiked with B. subtilis spores. The results of this study provided objective technological support for rapid detection of spores, which is important for reducing the occurrence of foodborne diseases and improving food safety.

Are realistic details important for learning with visualizations or can depth cues provide sufficient guidance?

The optimal choice of the level of realism in instructional visualizations is a difficult task. Previous studies suggest that realism can overwhelm learners, but a growing body of research demonstrates that realistic details can enhance learning. In the first experiment (n = 107), it was assessed whether learning using realistic visualizations can be distracting and therefore particularly benefits from pre-training. Participants learned the anatomy of the parotid gland using labeled visualizations. While pre-training did not have an effect, a more realistic visualization enhanced learning compared to a schematic visualization. In the second experiment (n = 132), a schematic diagram was compared to a more realistic style featuring basic depth cues, and a highly realistic visualization containing a detailed surface. Regarding retention performance, no significant differences were found. However, an interesting pattern regarding subjective cognitive load ratings emerged: the schematic version received the highest cognitive load ratings, while the version featuring simplified shading was rated as least demanding. The version containing simplified depth cues also elicited lower cognitive load ratings than the detailed visualization. The two experiments demonstrate that fears concerning a detrimental effect of realistic details should not be over-generalized. While schematic visualizations may be easier to visually process in some cases, extracting depth information from contour drawings adds cognitive demands to a learning task. Thus, it is advisable that computer-generated visualizations contain at least simplified forms of shading, while the addition of details does not appear to have a strong positive effect.

Cell4D: a general purpose spatial stochastic simulator for cellular pathways

BACKGROUND

With the generation of vast compendia of biological datasets, the challenge is how best to interpret 'omics data alongside biochemical and other small-scale experiments to gain meaningful biological insights. Key to this challenge are computational methods that enable domain-users to generate novel hypotheses that can be used to guide future experiments. Of particular interest are flexible modeling platforms, capable of simulating a diverse range of biological systems with low barriers of adoption to those with limited computational expertise.

RESULTS

We introduce Cell4D, a spatial-temporal modeling platform combining a robust simulation engine with integrated graphics visualization, a model design editor, and an underlying XML data model capable of capturing a variety of cellular functions. Cell4D provides an interactive visualization mode, allowing intuitive feedback on model behavior and exploration of novel hypotheses, together with a non-graphics mode, compatible with high performance cloud compute solutions, to facilitate generation of statistical data. To demonstrate the flexibility and effectiveness of Cell4D, we investigate the dynamics of CEACAM1 localization in T-cell activation. We confirm the importance of Ca2+ microdomains in activating calmodulin and highlight a key role of activated calmodulin on the surface expression of CEACAM1. We further show how lymphocyte-specific protein tyrosine kinase can help regulate this cell surface expression and exploit spatial modeling features of Cell4D to test the hypothesis that lipid rafts regulate clustering of CEACAM1 to promote trans-binding to neighbouring cells.

CONCLUSIONS

Through demonstrating its ability to test and generate hypotheses, Cell4D represents an effective tool to help integrate knowledge across diverse, large and small-scale datasets.

A bibliometric analysis of Kawasaki disease from 1974 to 2022

Objective

To analyse the research history, development trends and current status of relevant literature in the field of Kawasaki disease, and to provide the basis for future directions in Kawasaki disease (KD) research.

Methods

Literature on Kawasaki disease published between January 1974 and December 2022 was searched for in the Web of Science database, and CiteSpace was used to perform visual analyses.

Results

The search yielded a total of 6950 articles. The number of publications related to Kawasaki disease showed an increasing trend. A collaborative network analysis revealed that the United States, Japan and mainland China were the most influential countries in this field. The University of California system contributed the most publications and the journal with the most publications was Circulation. JW Newburger was an authoritative author in this field. "Coronary artery lesion", "Intravenous immunoglobulin" (IVIG) and "Risk factor" were three prominent keywords. Keyword bursts changed from "TNF" and "IVIG", which focused on aetiology and treatment, to "Long term management", which emphasized the recovery period, and to "Kawasaki-like disease" and "Multisystem inflammatory syndrome" during the novel coronavirus pandemic. Trends of highly cited references indicated that landmark articles in different periods focused on Kawasaki disease guidelines, gene polymorphisms and multisystem inflammatory syndrome caused by the novel coronavirus.

Conclusion

The aetiology of Kawasaki disease remains unclear, but viral infection is likely to play an important role. The combination of evolving sequencing technologies, large-scale epidemiological investigations and prospective cohort studies is likely to be important in exploring Kawasaki disease and improving its prognosis in future.

CFViSA: A comprehensive and free platform for visualization and statistics in omics-data

INTRODUCTION

The rapid growth of omics technologies has led to the use of bioinformatics as a powerful tool for unravelling scientific puzzles. However, the obstacles of bioinformatics are compounded by the complexity of data processing and the distinct nature of omics data types, particularly in terms of visualization and statistics.

OBJECTIVES

We developed a comprehensive and free platform, CFViSA, to facilitate effortless visualization and statistical analysis of omics data by the scientific community.

METHODS

CFViSA was constructed using the Scala programming language and utilizes the AKKA toolkit for the web server and MySQL for the database server. The visualization and statistical analysis were performed with the R program.

RESULTS

CFViSA integrates two omics data analysis pipelines (microbiome and transcriptome analysis) and an extensive array of 79 analysis tools spanning simple sequence processing, visualization, and statistics available for various omics data, including microbiome and transcriptome data. CFViSA starts from an analysis interface, paralleling a demonstration full course to help users understand operating principles and scientifically set the analysis parameters. Once analysis is conducted, users can enter the task history interface for figure adjustments, and then a complete series of results, including statistics, feature tables and figures. All the graphic layouts were printed with necessary statistics and a traceback function recording the options for analysis and visualization; these statistics were excluded from the five competing methods.

CONCLUSION

CFViSA is a user-friendly bioinformatics cloud platform with detailed guidelines for integrating functions in multi-omics analysis with real-time visualization adjustment and complete series of results provision. CFViSA is available at http://www.cloud.biomicroclass.com/en/CFViSA/.

Fast quantitative analysis and chemical visualization of amylopectin and amylose in sweet potatoes via merging 1D spectra and 2D image

The quantitative analysis and spatial chemical visualization of amylopectin and amylose in different varieties of sweet potatoes were studied by merging spectral and image information. Three-dimensional (3D) hyperspectral images carrying 1D spectra and 2D images of hundreds of the samples (amylopectin, n = 644; amylose, n = 665) in near-infrared (NIR) range of 950-1650 nm (426 wavelengths) were acquired. The NIR spectra were mined to correlate with the values of the two indexes using a linear algorithm, generating a best performance with correlation coefficients and root mean square error of prediction (rP and RMSEP) of 0.983 and 0.847 g/100 mg for amylopectin, and 0.975 and 0.500 g/100 mg for amylose, respectively. Then, 14 % of the wavelengths (60 for amylopectin, 61 for amylopectin) were selected to simplify the prediction with rP and RMSEP of 0.970 and 1.103 g/100 mg for amylopectin, and 0.952 and 0.684 g/100 mg for amylose, respectively, comparable to those of full-wavelength models. By transferring the simplified model to original images, the color chemical maps were created and the differences of the two indexes in spatial distribution were visualized. The integration of NIR spectra and 2D image could be used for the more comprehensive evaluation of amylopectin and amylose concentrations in sweet potatoes.

Directional vector visualization of scattered rays in mobile c-arm fluoroscopy

Previous radiation protection-measure studies for medical staff who perform X-ray fluoroscopy have employed simulations to investigate the use of protective plates and their shielding effectiveness. Incorporating directional information enables users to gain a clearer understanding of how to position protective plates effectively. Therefore, in this study, we propose the visualization of the directional vectors of scattered rays. X-ray fluoroscopy was performed; the particle and heavy-ion transport code system was used in Monte Carlo simulations to reproduce the behavior of scattered rays in an X-ray room by reproducing a C-arm X-ray fluoroscopy system. Using the calculated results of the scattered-ray behavior, the vectors of photons scattered from the phantom were visualized in three dimensions. A model of the physician was placed on the directional vectors and dose distribution maps to confirm the direction of the scattered rays toward the physician when the protective plate was in place. Simulation accuracy was confirmed by measuring the ambient dose equivalent and comparing the measured and calculated values (agreed within 10%). The directional vectors of the scattered rays radiated outward from the phantom, confirming a large amount of backscatter radiation. The use of a protective plate between the patient and the physician's head part increased the shielding effect, thereby enhancing radiation protection for the physicians compared to cases without the protective plate. The use of directional vectors and the surrounding dose-equivalent distribution of this method can elucidate the appropriate use of radiation protection plates.

Exoscope Efficacy and Feasibility in Pediatric Spinal Neurosurgery: A Single-Institution Cohort Case Series

BACKGROUND

The exoscope has emerged as an efficacious microscope in adult spinal neurosurgery providing improved operative field visibility and surgeon ergonomics. However, outcome data and feasibility are underrepresented in the pediatric literature. We present the largest case series aimed at assessing operative and clinical outcomes in pediatric patients undergoing various exoscope-assisted spinal surgeries.

METHODS

A retrospective review was conducted on all consecutive pediatric (age <18 years) spinal surgeries performed with the use of an exoscope by 3 senior surgeons at a single institution from 2020-2023. Demographics and clinical and operative outcomes were reviewed and analyzed.

RESULTS

Ninety-six exoscope-assisted pediatric spine surgeries were performed on 89 unique patients, 41 (42.7%) of which were male. The mean age at surgery was 12 (±5.3) years. Spinal cord detethering (55.8%) was the most common procedure performed. The overall mean operative time for all procedures was 155 (±86) minutes, and the mean estimated blood loss was 18 (±41) mL. The mean length of stay was 5.4 (±6.5) days. There were 14 (14.6%) patients with complications in this cohort. At final follow-up, 64 (83.1%) of symptomatic patients reported neurologic symptom improvement.

CONCLUSIONS

Using the exoscope in a variety of pediatric spinal surgeries resulted in an acceptable average operative time, estimated blood loss, length of stay, and rate of neurologic symptom improvement. The exoscope appears to be an efficacious option for pediatric neurosurgical spinal procedures.

Intelligent mine safety risk based on knowledge graph: hotspots and frontiers

The safety of mining has always been a concern. The occurrence of safety accidents not only endangers human health, but also causes serious damage to the ecological environment. With the continuous upgrade and improvement of mining technology, most mines are undergoing intelligent construction and transformation. In order to analyze security risks that should be focused on the construction of intelligent mines and the technical challenges that will be faced, we used the Web of Science (WOS) Core Collection to identify 283 publications on the field of security risks in intelligent mines from 2013 to 2022. We combined the Vosviewer, CiteSpace, and Bibliometrix R software packages to conduct an in-depth analysis and exquisite visualization of the literature, including the authors, journals, countries, hot topics, and research frontiers. This paper can help scholars comprehensively and quickly understand the research status and hotspots in the field of intelligent mine safety and risk, and it provides theoretical support for further research and exploration in the future.

Non-destructive detection of egg white and yolk morphology transformation and salt content of salted duck eggs in salting by hyperspectral imaging

Salt content is a crucial indicator of the maturity and internal quality of salted duck eggs (SDEs) during the pickling process. However, there is currently no valid and rapid method available for accurately detecting salt content. In the present study, we utilized hyperspectral imaging to no-destructively determine the salt content in egg yolks, egg whites, and whole eggs during the curing period. Firstly, principal component analysis was applied to explain the characteristics of egg yolk and white morphology transformation of SDEs with different maturities during curing. Secondly, sensitive spectral factors representative of changes in the salt content of SDEs were extracted by three spectral transformations (Savitzky-Golay SG, continuum removal CR, and first-order derivation FD) and three approaches of selecting characteristic wavelengths (successive projection algorithm SPA, uninformative variables elimination UVE and competitive adaptive reweighting sampling algorithm CARS). The results of the PLSR model suggested that the optimal models for predicting salt content in egg yolks, whites, and whole eggs were SG-UVE-PLSR (predicted coefficient of determination Rp2=0.912, predicted standard deviation SEp=0.151, residual prediction deviation RPD = 3.371), CR-CARS-PLSR (Rp2=0.873, SEp=0.862, RPD = 2.806), and CR-UVE-PLSR (Rp2=0.877, SEp=0.680, RPD = 2.851), respectively. Eventually, the optimal prediction model for the salt content of the whole egg was employed to a pixel spectral matrix to calculate the salt content values of pixel points on the hyperspectral image of SDEs. Additionally, pseudo-color techniques were employed to visualize the spatial distribution of predicted salt content. This work will provide a theoretical foundation for rapidly detecting maturity and enabling high-throughput quality sorting of SDEs.

The role of short-chain fatty acids in central nervous system diseases: A bibliometric and visualized analysis with future directions

Background

Short-chain fatty acids (SCFAs) are thought to play a key role in the microbe-gut-brain axis and involve in the pathogenesis of a variety of neurological diseases. This study aimed to identify research hotspots and evolution trends in SCFAs in central nervous diseases (CNS) and examine current research trends.

Methods

The bibliometric analysis was performed using CiteSpace, and the results were visualized via network maps.

Results

From 2002 to 2022, 480 publications in the database met the criteria. On the country level, China produced the highest number of publications, while the United States had the highest centrality. On the institutional level, University College Cork contributed to the most publications, and John F. Cryan from this university was the key researcher with considerable academic influence. The article, the role of short-chain fatty acids in microbiota-gut-brain, written by Boushra Dalile et al., in 2019 was the most cited article. Furthermore, the journal Nutrients had the maximum number of publications, while Plos One was the most cited journal. "Gut microbiome", "SCFAs", and "central nervous system" were the three most frequent keywords. Among them, SCFAs had the highest centrality. "Animal model" was the keyword with the highest burst strength, with the latest burst keywords being "social behavior", "pathogenesis", and "insulin sensitive". In addition, the research topics on SCFAs in CNS diseases from 2002 to 2022 mainly focused on following aspects: SCFAs plays a key role in microbe-gut-brain crosstalk; The classification and definition of SCFAs in the field of CNS; Several CNS diseases that are closely related to SCFAs research; Mechanism and translational studies of SCFAs in the CNS diseases. And the hotspots over the past 5 years have gradually increased the attention to the therapeutic potential of SCFAs in the CNS diseases.

Conclusion

The research of SCFAs in CNS diseases is attracting growing attention. However, there is a lack of cooperation between countries and institutions, and additional measures are required to promote cooperation. The current evidence for an association between SCFAs and CNS diseases is preliminary and more work is needed to pinpoint the precise mechanism. Moreover, large-scale clinical trials are needed in the future to define the therapeutic potential of SCFAs in CNS diseases.

P2X7 receptors: a bibliometric review from 2002 to 2023

For many years, there has been ongoing research on the P2X7 receptor (P2X7R). A comprehensive, systematic, and objective evaluation of the scientific output and status of P2X7R will be instrumental in guiding future research directions. This study aims to present the status and trends of P2X7R research from 2002 to 2023. Publications related to P2X7R were retrieved from the Web of Science Core Collection database. Quantitative analysis and visualization tools were Microsoft Excel, VOSviewer, and CiteSpace software. The analysis content included publication trends, literature co-citation, and keywords. 3282 records were included in total, with the majority of papers published within the last 10 years. Based on literature co-citation and keyword analysis, neuroinflammation, neuropathic pain, gastrointestinal diseases, tumor microenvironment, rheumatoid arthritis, age-related macular degeneration, and P2X7R antagonists were considered to be the hotspots and frontiers of P2X7R research. Researchers will get a more intuitive understanding of the status and trends of P2X7R research from this study.

NnU-Net versus mesh growing algorithm as a tool for the robust and timely segmentation of neurosurgical 3D images in contrast-enhanced T1 MRI scans

PURPOSE

This study evaluates the nnU-Net for segmenting brain, skin, tumors, and ventricles in contrast-enhanced T1 (T1CE) images, benchmarking it against an established mesh growing algorithm (MGA).

METHODS

We used 67 retrospectively collected annotated single-center T1CE brain scans for training models for brain, skin, tumor, and ventricle segmentation. An additional 32 scans from two centers were used test performance compared to that of the MGA. The performance was measured using the Dice-Sørensen coefficient (DSC), intersection over union (IoU), 95th percentile Hausdorff distance (HD95), and average symmetric surface distance (ASSD) metrics, with time to segment also compared.

RESULTS

The nnU-Net models significantly outperformed the MGA (p < 0.0125) with a median brain segmentation DSC of 0.971 [95CI: 0.945-0.979], skin: 0.997 [95CI: 0.984-0.999], tumor: 0.926 [95CI: 0.508-0.968], and ventricles: 0.910 [95CI: 0.812-0.968]. Compared to the MGA's median DSC for brain: 0.936 [95CI: 0.890, 0.958], skin: 0.991 [95CI: 0.964, 0.996], tumor: 0.723 [95CI: 0.000-0.926], and ventricles: 0.856 [95CI: 0.216-0.916]. NnU-Net performance between centers did not significantly differ except for the skin segmentations Additionally, the nnU-Net models were faster (mean: 1139 s [95CI: 685.0-1616]) than the MGA (mean: 2851 s [95CI: 1482-6246]).

CONCLUSIONS

The nnU-Net is a fast, reliable tool for creating automatic deep learning-based segmentation pipelines, reducing the need for extensive manual tuning and iteration. The models are able to achieve this performance despite a modestly sized training set. The ability to create high-quality segmentations in a short timespan can prove invaluable in neurosurgical settings.

CytoPipeline and CytoPipelineGUI: a Bioconductor R package suite for building and visualizing automated pre-processing pipelines for flow cytometry data

BACKGROUND

With the increase of the dimensionality in flow cytometry data over the past years, there is a growing need to replace or complement traditional manual analysis (i.e. iterative 2D gating) with automated data analysis pipelines. A crucial part of these pipelines consists of pre-processing and applying quality control filtering to the raw data, in order to use high quality events in the downstream analyses. This part can in turn be split into a number of elementary steps: signal compensation or unmixing, scale transformation, debris, doublets and dead cells removal, batch effect correction, etc. However, assembling and assessing the pre-processing part can be challenging for a number of reasons. First, each of the involved elementary steps can be implemented using various methods and R packages. Second, the order of the steps can have an impact on the downstream analysis results. Finally, each method typically comes with its specific, non standardized diagnostic and visualizations, making objective comparison difficult for the end user.

RESULTS

Here, we present CytoPipeline and CytoPipelineGUI, two R packages to build, compare and assess pre-processing pipelines for flow cytometry data. To exemplify these new tools, we present the steps involved in designing a pre-processing pipeline on a real life dataset and demonstrate different visual assessment use cases. We also set up a benchmarking comparing two pre-processing pipelines differing by their quality control methods, and show how the package visualization utilities can provide crucial user insight into the obtained benchmark metrics.

CONCLUSION

CytoPipeline and CytoPipelineGUI are two Bioconductor R packages that help building, visualizing and assessing pre-processing pipelines for flow cytometry data. They increase productivity during pipeline development and testing, and complement benchmarking tools, by providing user intuitive insight into benchmarking results.

Aggregation-induced emission activity of sensor TBM-C1 hybrid of methoxy-triphenylamine (OMe-TPA) and dicyanovinyl for cyanide detection in aqueous THF: Mechanistic insights and potential applications

A series fluorescent probes (TBM-Cx (x = 1, 4, 8)) were designed based on embedding various alkoxy chains on the electron donor of triphenylamine (TPA)-based dicyanovinyl (MT) compound with an electron-deficient benzothiadiazole (BTD) for sensitive, selective, and visualizing detection of cyanide in aqueous solution. Due to the nucleophilic addition of CN-, the intramolecular charge transfer (ICT) of these probes was inhibited by the destroyed conjugated structure, exhibiting excellent "turn-on" fluorescence response toward cyanide anion (CN-) in tetrahydrofuran (THF). However, the alkoxy chains with different lengths embedded in TPA not only enhance the sensitivity and solubility, but also regulate the emission behavior from ICT to aggregation-induced emission (AIE) characteristics. The binding mechanism and AIE sensing performances between the probes and CN- have been investigated and compared in THF/water mixture by spectral tools and theoretical calculations. The results showed that the ICT-based TBM-C1 probe with methoxy chain showed significantly turn-on fluorescence response to CN- as low as 0.077 μM in THF/water solution at high water fraction (90 %). Due to the AIE sensing process, TBM-C1 was successfully employed to determine CN- in food and water samples, image CN- in living cells and BALB/c mice, and prepare test kits for visualizing cyanide.

Teaching computer architecture by designing and simulating processors from their bits and bytes

Teaching computer architecture (Comp-Arch) courses in undergraduate curricula is becoming more of a challenge as most students prefer software-oriented courses. In some computer science/engineering departments, Comp-Arch courses are offered without the lab component due to resource constraints and differing pedagogical priorities. This article demonstrates how students working in teams are motivated to study the Comp-Arch course and how instructors can increase student motivation and knowledge by taking advantage of hands-on practices. The teams are asked to design and implement a 16-bit MIPS-like processor with constraints as a specific instruction set, and limited data and instruction memory. Student projects include following three phases, namely, design, desktop simulator implementation, and verification using hardware description language (HDL). In the design phase, teams develop their Comp-Arch to implement specified instructions. A range of designs resulted, e.g., (a) a processor with extensive user-defined instructions resulting in longer cycle times (b) a processor with a minimal instruction set but with a faster clock cycle time. Next, teams developed a desktop simulator in any programming language to execute instructions on the architecture. Finally, students engage in Verilog Hardware Description Language (HDL) projects to simulate and verify the data-path designed during the initial phase. Student feedback and their current understanding of the project were collected through a questionnaire featuring varying Likert scale questions, some with a ten-point scale, and others with a five-point scale. Results of the survey show that the hands-on approach increases students' motivation and knowledge in the Comp-Arch course, which is centered around computer system design principles. This approach can also be effectively extended to related courses, such as Microprocessor Design, which delves into the intricacies of creating and implementing microprocessors or central processing units (CPUs) at the hardware level. Furthermore, the present study demonstrates that interactions, specifically through peer reviews and public presentations, between students in each phase increases their knowledge and perspective on designing custom processors.

Design of urban innovation space system using artificial intelligence technology and internet of things

The goal of this paper is to integrate artificial intelligence (AI) and Internet of things (IoT) technology into urban innovation space systems while expediting the construction of urban informatization. The core of the paper is to build an innovation space system, which is developed around three key components: innovation elements, innovation networks and innovation bases. First, the definition of innovation space is investigated in detail, and the essence of innovation space is understood to ensure that the key elements in the innovation process can be accurately captured and analyzed in the follow-up research. Second, it is clear that Chengdu is a representative city in Sichuan Province. Through the research in this area, people can deeply understand the specific background and characteristics of urban innovation space system. Then, the innovation space system is constructed, which is supported by innovation elements, innovation networks and innovation bases. These three components are intertwined, which together constitute the key elements of urban innovation space. Furthermore, the Internet worm technology is integrated with the IoT technology, and the system is visually inspected with the help of AI. The application of IoT technology helps to realize the automation and information sharing of the system, while the use of AI provides a deep insight into the system structure and operation. Through this research process, people can fully understand the construction process of Chengdu innovation space system, and provide deeper insight and support for urban innovation through the application of IoT and AI technology. The results show that while Chengdu's entrepreneurship and innovation enterprises are dispersed throughout all of the city's districts and counties, the city's academic talent and the bulk of its higher education institutions are concentrated in the city's core. There are 275 entrepreneurship and innovation enterprises in the High-tech District of Chengdu, which is the most densely distributed area. An urban innovation space network is being built by eight distinct research and higher education establishments. As urban innovation spaces are being built, emphasis should be given to the regional aggregation features of talents, higher education and research institutions, as well as entrepreneurship and innovation business enterprises. The innovation space system based on Internet worm technology of the IoT shows excellent performance in real-time identification of innovation elements, network connection quality, sensor monitoring, AI visual monitoring and so on. The system performs well in real-time monitoring of new enterprises and projects, and the real-time recognition rate reaches 98 %. The communication quality of the innovation network is relatively stable, and the connection quality reaches 92 %. The accuracy of sensor status monitoring in the IoT is high, reaching 99 %. The coverage of AI vision monitoring system reaches 96 %, effectively monitoring the areas involved in innovative space systems. Generally speaking, through the combination of theory and practice, this paaper provides comprehensive and specific guidance for the construction of urban innovation space system, promotes the research progress in this field, and makes beneficial contributions to the sustainable development of urban innovation and informatization.

Current and emerging 3D visualization technologies in radiology

As the field of three-dimensional (3D) visualization rapidly advances, how healthcare professionals perceive and interact with real and virtual objects becomes increasingly complex. Lack of clear vocabulary to navigate the changing landscape of 3D visualization hinders clinical and scientific advancement, particularly within the field of radiology. In this article, we provide foundational definitions and illustrative examples for 3D visualization in clinical care, with a focus on the pediatric patient population. We also describe how understanding 3D visualization tools enables better alignment of hardware and software products with intended use-cases, thereby maximizing impact for patients, families, and healthcare professionals.

Enhancing grain drying methods with hyperspectral imaging technology: A visualanalysis

This study proposes a recognition model for different drying methods of grain using hyperspectral imaging technology (HSI) and multivariate analysis. Fresh harvested grain samples were dried using three different methods: rotating ventilation drying, mechanical drying, and natural drying. Hyperspectral images of the samples were collected within the 388-1065 nm band range. The spectral features of the samples were extracted using principal component analysis (PCA), while the texture features were extracted using second-order probability statistical filtering. Partial least squares regression (PLSR) drying models with different characteristics were established. At the same time, a BPNN (Back-propagation neural network, BPNN) based on spectral texture fusion features was established to compare the recognition effects of different models. Texture analysis indicated that the mean-image had the clearest contour, and the texture characteristics of mechanical drying were smaller than those of rotating ventilation drying and natural drying. The BPNN model established using spectral-texture feature variables showed the best performance in distinguishing grain in different drying modes, with a prediction model obtained based on the correlation coefficients of special variables. The spectral and texture feature values were fused for pseudo-color visualization expression, and the three drying methods of grain showed different colors. This study provides a reference for non-destructive and rapid detection of grain with different drying methods.

Experimental study on the freezing process of water droplets for ice air jet technology

Ice air jet technology is one non-destructive, residue-free and environmentally friendly machining process. It is an efficient method to form ice particles by atomizing water droplets in ultra-low temperature environment. The freezing characteristics of water droplets in cryogenic gas and liquid nitrogen environment are visually analyzed, and the effects of droplet volume, ambient temperature are also studied. The results show that when water droplets freeze in a cryogenic gas environment, four distinct stages are observed, namely pre-cooling stage, recalescence stage, solidification stage, and deep cooling stage. However, when water droplets freeze in liquid nitrogen, the recalescence stage cannot be observed. For a 5 µl water droplet, it takes 68 s for water droplets to freeze into ice particles at - 20.36 °C, while it takes only 1.7 s in liquid nitrogen. During the freezing process, the water droplets form an ice shell outside and freeze inwardly. Ice particles may break up due to differences in solubility and density. With the increase of volume the time spent on pre-cooling stage and freezing stage both increases. For the large latent heat of water phase transformation, the solidification stage time is greatly affected by the volume of water droplets. When the ambient temperature drops from - 10.67 °C to - 24.68 °C, the freezing time of 5 µl water droplets decreases by 45.5%, indicating that the ambient temperature has a great influence on the freezing time. The results of the study can significantly contribute to the development of ice air jet technology.

Bibliometric review of carbon peak with CiteSpace: evolution, trends, and framework

In the context of global climate change, countries around the world are actively implementing carbon peak and carbon neutrality goals. In-depth research on carbon peak can help improve environmental conditions and achieve a harmonious coexistence between economic development and environmental protection. However, a comprehensive review of the current status of research in this area is scarce. Therefore, this article explores the current research evolution and hotspots of "carbon peak" with the help of CiteSpace visualization software, predicts the future development trends, and builds a knowledge network framework. A comprehensive analysis of the research on carbon peak from multiple perspectives is presented. The results show that the number of papers published on carbon peak is increasing every year, and that carbon peak has become a widely participated research area. Publications from various institutions and journals have also attracted widespread attention. The research hotspots of carbon peak have constantly changed with time, resulting in many theoretical and technological innovations. The knowledge framework of the field is constructed on this basis, which gives readers a clearer understanding of the development and trends in the field and provides some reference and help for future researchers.

Assumption-checking rather than (just) testing: The importance of visualization and effect size in statistical diagnostics

Statistical methods generally have assumptions (e.g., normality in linear regression models). Violations of these assumptions can cause various issues, like statistical errors and biased estimates, whose impact can range from inconsequential to critical. Accordingly, it is important to check these assumptions, but this is often done in a flawed way. Here, I first present a prevalent but problematic approach to diagnostics-testing assumptions using null hypothesis significance tests (e.g., the Shapiro-Wilk test of normality). Then, I consolidate and illustrate the issues with this approach, primarily using simulations. These issues include statistical errors (i.e., false positives, especially with large samples, and false negatives, especially with small samples), false binarity, limited descriptiveness, misinterpretation (e.g., of p-value as an effect size), and potential testing failure due to unmet test assumptions. Finally, I synthesize the implications of these issues for statistical diagnostics, and provide practical recommendations for improving such diagnostics. Key recommendations include maintaining awareness of the issues with assumption tests (while recognizing they can be useful), using appropriate combinations of diagnostic methods (including visualization and effect sizes) while recognizing their limitations, and distinguishing between testing and checking assumptions. Additional recommendations include judging assumption violations as a complex spectrum (rather than a simplistic binary), using programmatic tools that increase replicability and decrease researcher degrees of freedom, and sharing the material and rationale involved in the diagnostics.

A generic scope actuation system for flexible endoscopes

BACKGROUND

A scope actuation system assists a surgeon in steering a scope for navigating an operative field during an interventional or diagnostic procedure. Each system is tailored for a specific surgical procedure. The development of a generic scope actuation system could assist various laparoscopic and endoscopic procedures. This has the potential to reduce the deployment and maintenance costs for a hospital, making it more accessible for clinical usage.

METHODS

A modular actuation system (for maneuvering rigid laparoscopes) was adapted to enable incorporation of flexible endoscopes. The design simplifies the installation and disassembly processes. User studies were conducted to assess the ability of the system to focus onto a diagnostic area, and to navigate during a simulated esophagogastroduodenoscopy procedure. During the studies, the endoscope was maneuvered with (robotic mode) and without (manual mode) the actuation system to navigate the endoscope's focus on a predefined track.

RESULTS

Results show that the robotic mode performed better than the manual mode on all the measured performance parameters including (a) the total duration to traverse a track, (b) the percentage of time spent outside a track while traversing, and (c) the number of times the scope focus shifts outside the track. Additionally, robotic mode also reduced the perceived workload based on the NASA-TLX scale.

CONCLUSIONS

The proposed scope actuation system enhances the maneuverability of flexible endoscopes. It also lays the groundwork for future development of modular and generic scope assistant systems that can be used in both laparoscopic and endoscopic procedures.

Explainable machine learning model based on clinical factors for predicting the disappearance of indeterminate pulmonary nodules

BACKGROUND

During lung cancer screening, indeterminate pulmonary nodules (IPNs) are a frequent finding. We aim to predict whether IPNs are resolving or non-resolving to reduce follow-up examinations, using machine learning (ML) models. We incorporated dedicated techniques to enhance prediction explainability.

METHODS

In total, 724 IPNs (size 50-500 mm3, 575 participants) from the Dutch-Belgian Randomized Lung Cancer Screening Trial were used. We implemented six ML models and 14 factors to predict nodule disappearance. Random search was applied to determine the optimal hyperparameters on the training set (579 nodules). ML models were trained using 5-fold cross-validation and tested on the test set (145 nodules). Model predictions were evaluated by utilizing the recall, precision, F1 score, and the area under the receiver operating characteristic curve (AUC). The best-performing model was used for three feature importance techniques: mean decrease in impurity (MDI), permutation feature importance (PFI), and SHAPley Additive exPlanations (SHAP).

RESULTS

The random forest model outperformed the other ML models with an AUC of 0.865. This model achieved a recall of 0.646, a precision of 0.816, and an F1 score of 0.721. The evaluation of feature importance achieved consistent ranking across all three methods for the most crucial factors. The MDI, PFI, and SHAP methods highlighted volume, maximum diameter, and minimum diameter as the top three factors. However, the remaining factors revealed discrepant ranking across methods.

CONCLUSION

ML models effectively predict IPN disappearance using participant demographics and nodule characteristics. Explainable techniques can assist clinicians in developing understandable preliminary assessments.

Knowledge mapping on the sun-induced chlorophyll fluorescence technology research: a scientometric and visualization analysis

The sun-induced chlorophyll fluorescence (SIF) has received increasing attention over the past few years. This scientometric study analyzed the SIF research field, based on publications available in Web of Science Core Collection visualization, and cluster analysis enabled us to map the knowledge domain and intellectual landscape of this field and identify thematic trends, landmark articles, and emerging research themes. In this study, the software VOSviewer and CiteSpace were used to identify the intellectual base and research front using visualization and analysis. Then, we analyzed synthesized networks of co-authorship (author, institution, and country), co-citation (author, document, and journal), and co-occurring keywords. SIF has increased its publication output steadily since 2002. This study provided a visual knowledge map of the major research domains of SIF. Also, explanations and implications of the findings were explored, and the emerging trends were identified. This report provides a thorough overview of the current state and growth trends of SIF research, and it helps researchers and practitioners understand the major areas of attention in this area and provides insights into prospective areas for further study.