Real-time dual-modal photoacoustic and fluorescence small animal imaging

By combining optical absorption contrast and acoustic resolution, photoacoustic imaging (PAI) has broken the barrier in depth for high-resolution optical imaging. Meanwhile, Fluorescence imaging (FLI), owing to advantages of high sensitivity and high specificity with abundant fluorescence agents and proteins, has always been playing a key role in live animal studies. Based on different optical contrast mechanisms, PAI and FLI can provide important complementary information to each other. In this work, we uniquely designed a Photoacoustic-Fluorescence (PA-FL) imaging system that provides real-time dual modality imaging, in which a half-ring ultrasonic array is employed for high quality PA tomography and a specially designed optical window allows simultaneous whole-body fluorescence imaging. The performance of this dual modality system was demonstrated in live animal studies, including real-time monitoring of perfusion and metabolic processes of fluorescent dyes. Our study indicates that the PA-FL imaging system has unique potential for live small animal research.

Multi-channel Small Animal Drug Metabolism Real-Time Monitoring Fluorescence System

PURPOSE

The data acquisition of drug metabolism analysis requires a lot of time and animal resources. However, there are often many deviations in the results of pharmacokinetic analysis. Conventional methods cannot measure the blood drug concentration data in multiple tissues at the same time, and the data is obtained by in vitro measurement, which produces time errors, in vitro data errors, and individual differences between animals. In the analysis of pharmacokinetic parameters, it will seriously affect the pass rate of clinical trials of R&D drugs and the accuracy of the dosing schedule. To the best of our knowledge, we have not found the study of in vivo blood drug concentration using multi-channel equipment. Therefore, the purpose of this paper is to build a set of multi-organ monitoring and analysis instruments for synchronously monitoring the metabolism of drugs in various tissues of small animals, so as to obtain real in vivo data of blood drug concentration in real time.

PROCEDURES

Using the fluorescence properties and laser-induced fluorescence principle of drugs, we designed six channels to monitor the changes of fluorescence-labeled drugs in their main metabolic organs, a multi-channel calibration method was proposed to improve the accuracy of the time-division multiplexing, the real-time collection of drug concentration in vivo is realized, and the drug metabolism curve in vivo can be observed.

RESULTS

The instrument satisfies the collection of small doses of drugs such as microgram; the detection sensitivity can reach 10 ng/ml, and can monitor and collect the drug metabolism of multiple small animal tissues at the same time, which greatly reduces the use of animals, reduces the differences between individuals, and reduces consumption cost and improve the detection efficiency of parameters, and obtain data information that is closer to the real biology.

CONCLUSION

The real-time continuous monitoring and data collection of the drug metabolism in the plasma of living small animals and the important organs such as kidney, liver, and spleen were realized. The research and development of new drugs and clinical research have higher practical value.

Toxoplasma gondii genotyping in AIDS patients using high resolution melt analysis (HRM analysis) in Khuzestan province, southwest Iran

Toxoplasmosis is a parasitic zoonotic disease caused by Toxoplasma gondii, a common protozoan in the Apicomplexa phylum. Several studies in Iran have demonstrated the presence of the parasite in various hosts, but no data on T. gondii genotyping in HIV patients in Khuzestan, Southwest Iran, is available. One hundred of blood samples from AIDS patients were collected and tested by real-time PCR High Resolution Melting analyses for T.gondii detection and genotyping. T. gondii was discovered in 8 out of 100 (8%) AIDS patients with dominant Type I. This study suggest that HRM method demonstrated excellent discriminating ability for T. gondii, and AIDS patients should be tested for Toxoplasma detection and genotyping to prevent parasite pathogenicity.

Improving Augmented Reality Through Deep Learning: Real-time Instrument Delineation in Robotic Renal Surgery

Several barriers prevent the integration and adoption of augmented reality (AR) in robotic renal surgery despite the increased availability of virtual three-dimensional (3D) models. Apart from correct model alignment and deformation, not all instruments are clearly visible in AR. Superimposition of a 3D model on top of the surgical stream, including the instruments, can result in a potentially hazardous surgical situation. We demonstrate real-time instrument detection during AR-guided robot-assisted partial nephrectomy and show the generalization of our algorithm to AR-guided robot-assisted kidney transplantation. We developed an algorithm using deep learning networks to detect all nonorganic items. This algorithm learned to extract this information for 65 927 manually labeled instruments on 15 100 frames. Our setup, which runs on a standalone laptop, was deployed in three different hospitals and used by four different surgeons. Instrument detection is a simple and feasible way to enhance the safety of AR-guided surgery. Future investigations should strive to optimize efficient video processing to minimize the 0.5-s delay currently experienced. General AR applications also need further optimization, including detection and tracking of organ deformation, for full clinical implementation.

A complex wireless sensors model (CWSM) for real time monitoring of dam temperature

The following work is based on real-time temperature monitoring during the construction and during the operation of a dam. For this purpose, we have proposed a sensing model named: the "complex wireless sensors model (CWSM)" for measuring the value of different factors like temperature, humidity and pressure on the dam. The installation of the proposed model has been discussed with its wireless networking. The model contains five types of sensors i.e. humidity, temperature, pressure, sun and irradiance sensors for measuring the variation of different factors. The computation modeling of CWSM has been discussed in the paper. 3-D Finite Element method is used for thermal analysis. As the result, it is concluded that the wireless network will be more suitable for measuring and analyzing the effects of temperature, humidity, water pressure and solar radiation on the dam.

Electrodeposition of dopamine onto carbon fiber microelectrodes to enhance the detection of Cu2+ via fast-scan cyclic voltammetry

The etiology of neurodegenerative diseases is poorly understood; however, studies have shown that heavy metals, such as copper, play a critical role in neurotoxicity, thus, adversely affecting the development of these diseases. Because of the limitations associated with classical metal detection tools to obtain accurate speciation information of ultra-low concentrations of heavy metals in the brain, analysis is primarily performed in blood, urine, or postmortem tissues, limiting the translatability of acquired knowledge to living systems. Inadequate and less accurate data obtained with such techniques provide little or no information for developing efficient therapeutics that aid in slowing down the deterioration of brain cells. In this study, we developed a biocompatible, ultra-fast, low-cost, and robust surface-modified electrode with carbon fibers by electrodepositing dopamine via fast-scan cyclic voltammetry (FSCV) to detect Cu²⁺ in modified tris buffer. We studied the surface morphology of our newly introduced sensors using high-resolution images by atomic force microscopy under different deposition conditions. The limit of detection (LOD) of our surface-modified sensor was 0.01 µM (0.64 ppb), and the sensitivity was 11.28 nA/µM. The LOD and sensitivity are fifty and two times greater, respectively, compared to those of a bare electrode. The sensor's response is not affected by the presence of dopamine in the matrix. It also exhibited excellent stability to multiple subsequent injections and repeated measurements of Cu²⁺ over a month, thus showing its strength to be developed into an accurate, fast, robust electrochemical tool to monitor ultra-low concentrations of heavy metals in the brain in real time.

Bedside Cerebral Blood Flow Quantification in Neonates

Measurement of blood flow to the brain in neonates would be a very valuable addition to the medical diagnostic armamentarium. Such conditions such as assessment of closure of a patent ductus arteriosus (PDA) would greatly benefit from such an evaluation. However, measurement of cerebral blood flow in a clinical setting has proven very difficult and, as such, is rarely employed. Present techniques are often cumbersome, difficult to perform and potentially dangerous for very low birth weight (VLBW) infants. We have been developing an ultrasound blood volume flow technique that could be routinely used to assess blood flow to the brain in neonates. By scanning through the anterior fontanelles of 10 normal, full-term newborn infants, we were able to estimate total brain blood flows that closely match those published in the literature using much more invasive and technically demanding methods. Our method is safe, easy to do, does not require contrast agents and can be performed in the baby's incubator. The method has the potential for monitoring and assessing blood flows to the brain and could be used to routinely assess cerebral blood flow in many different clinical conditions.

Toxic gas detection using 3-channel spark-induced plasma spectroscopy for indoor air quality monitoring

This study explored the toxic gas detection using a set of two spark-induced plasma emission spectroscopy (SIPS) modules as an alternative to conventional chemical sensors. This opens up a new possibility for detecting toxic molecules (formaldehyde, acetaldehyde, acetic acid, toluene, and ammonia) in real-time (<3 s) at relatively high sensitivity (<5 ppm). An optimized electrical controller (Raspberry Pi), manufactured as a compact and economical 3-channel optical measuring device, was developed for handling the high-resolution time-resolved electrical signals from the plasma emissions. Subsequently, the findings of this research elucidate the usability of the 3-channel SIPS device for quantitative monitoring of toxic gases.

Real-time wear monitoring of hob cutter based on statistical analysis

Real-time wear monitoring of hob cutters is of great significance to the quality and efficiency of gear hobbing. To achieve this goal, a strategy based on statistical analysis is proposed in this paper. First, vibration signals during the entire life cycle of a hob cutter are collected. Then, a feature iterative integration method is proposed to integrate the initial features of vibration signals. The integrated features have obvious stages, reflecting the different wear status of hob cutters. Next, a probability tabular cumulative sum control chart method is established to monitor the wear status of hob cutters in real time. Finally, the verification results of two different data sets prove the effectiveness and transferability of the proposed methods.

A New Real-Time Analog Circuit of Ca2+ Li-Rinzel Astrocyte Model Based on Analytical Method

Different biological models are used to study physical behaviors in neural networks. So far, various models of neural network components such as neurons, synapses, and astrocytes have been proposed. An astrocyte is one of the crucial parts introduced in multiple models. A model of astrocytes used as a good reference in various papers is the Li-Rinzel calcium model. This paper presents a real-time analog circuit of the Li-Rinzel calcium model based on common-mode (CM) in 180nm CMOS technology. To the best of our knowledge, this work is the first report to introduce a real-time analog Li-Rinzel model. The careful design of equations and low power consumption are essential features of this circuit. The real-time behavior is also crucial compared with the accelerated time circuits presented so far.

PRETUS: A plug-in based platform for real-time ultrasound imaging research

We present PRETUS - a Plugin-based Real Time UltraSound software platform for live ultrasound image analysis and operator support. The software is lightweight; functionality is brought in via independent plug-ins that can be arranged in sequence. The software allows to capture the real-time stream of ultrasound images from virtually any ultrasound machine, applies computational methods and visualizes the results on-the-fly. Plug-ins can run concurrently without blocking each other. They can be implemented in C++ and Python. A graphical user interface can be implemented for each plug-in, and presented to the user in a compact way. The software is free and open source, and allows for rapid prototyping and testing of real-time ultrasound imaging methods in a manufacturer-agnostic fashion. The software is provided with input, output and processing plug-ins, as well as with tutorials to illustrate how to develop new plug-ins for PRETUS.

A Nondestructive, Real-Time Annexin V Apoptosis Assay

This chapter describes a simple, nondestructive, annexin V apoptosis detection method that can be employed in real time over a 48-h test exposure. The real-time functionality allows for temporal resolution of apoptotic and cell death responses during the test exposure and obviates the need for onerous sample preparation and time course protocols associated with other annexin V methods. Further, this technique is eminently accessible to a wide range of laboratories because it does not require flow cytometry or other cytometric methods. It was developed for use with a variety of microplate well densities and with standard multimodal plate readers. The central feature of this assay is that it continuously reports the residency status of phosphatidylserine (PS) on the exofacial surface of a cell as it is translocated from the inner membrane leaflet during the apoptotic process. This homogenous, no-wash assay is made possible by two optimized and distinct annexin V fusion proteins which contain complementing NanoBiT™ luciferase enzyme subunits, a time-released luciferase substrate, and a fluorescent membrane integrity reagent. During an apoptotic event, the luminescent signal arising from an assay well is proportional to the number of cells with PS exposure, and fluorescence intensity correlates with the degree of cell death (secondary necrosis). Conversely, untreated cells contribute negligible luminescent or fluorescent signals throughout the time course. The data collected from these assay measures provide for both standard potency determinations and kinetic characterization of dose- and agent-dependent apoptotic responses, from early through late phases.

Aptamer-modified biosensors to visualize neurotransmitter flux

Chemical biosensors with the capacity to continuously monitor various neurotransmitter dynamics can be powerful tools to understand complex signaling pathways in the brain. However, in vivo detection of neurochemicals is challenging for many reasons such as the rapid release and clearance of neurotransmitters in the extracellular space, or the low target analyte concentrations in a sea of interfering biomolecules. Biosensing platforms with adequate spatiotemporal resolution coupled to specific and selective receptors termed aptamers, demonstrate high potential to tackle such challenges. Herein, we review existing literature in this field. We first discuss nanoparticle-based systems, which have a simple in vitro implementation and easily interpretable results. We then examine methods employing near-infrared detection for deeper tissue imaging, hence easier translation to in vivo implementation. We conclude by reviewing live cell imaging of neurotransmitter release via aptamer-modified platforms. For each of these sensors, we discuss the associated challenges for translation to real-time in vivo neurochemical imaging. Realization of in vivo biosensors for neurotransmitters will drive future development of early prevention strategies, treatments, and therapeutics for psychiatric and neurodegenerative diseases.

Acquisition of enzymatic progress curves in real time by quenching-free ion exchange chromatography

We describe a quenching-free, 'online' ion exchange chromatography (oIEC) method for the quantitative analysis of enzymatic reactions in real-time. We show that separate quenching of the ongoing reaction performed conventionally is not required, since enzymatic reactions are interrupted upon immobilization of the reaction compounds by binding to the stationary phase of the ion exchange column. The reaction mix samples are directly injected into the column, thereby improving data consistency and allowing automation of the process. The method allows reliable and efficient acquisition of enzymatic progress curves by automatic loading of aliquots of an ongoing reaction at predefined timepoints. We demonstrate the applicability of this method for a variety of enzymatic reactions. SUBJECT: Enzymatic assays and analysis.

Home-Use and Real-Time Sleep-Staging System Based on Eye Masks and Mobile Devices with a Deep Learning Model

Purpose

Sleep is an important human activity. Comfortable sensing and accurate analysis in sleep monitoring is beneficial to many healthcare and medical applications. From 2020, owing to the COVID‑19 pandemic that spreads between people when they come into close physical contact with one another, the willingness to go to hospital for receiving care has reduced; care-at-home is the trend in modern healthcare. Therefore, a home-use and real-time sleep-staging system is developed in this paper.

Methods

We developed and implemented a real-time sleep staging system that integrates a wearable eye mask for high-quality electroencephalogram/electrooculogram measurement and a mobile device with MobileNETV2 deep learning model for sleep-stage identification. In the experiments, 25 all-night recordings were acquired, 17 of which were used for training, and the remaining eight were used for testing.

Results

The averaged scoring agreements for the wake, light sleep, deep sleep, and rapid eye movement stages were 85.20%, 87.17%, 82.87%, and 89.30%, respectively, for our system compared with the manual scoring of PSG recordings. In addition, the mean absolute errors of four objective sleep measurements, including sleep efficiency, total sleep time, sleep onset time, and wake after sleep onset time were 1.68%, 7.56 min, 5.50 min, and 3.94 min, respectively. No significant differences were observed between the proposed system and manual PSG scoring in terms of the percentage of each stage and the objective sleep measurements.

Conclusion

These experimental results demonstrate that our system provides high scoring agreements in sleep staging and unbiased sleep measurements owing to the use of EEG and EOG signals and powerful mobile computing based on deep learning networks. These results also suggest that our system is applicable for home-use real-time sleep monitoring.

Deep artifact suppression for spiral real-time phase contrast cardiac magnetic resonance imaging in congenital heart disease

PURPOSE

Real-time spiral phase contrast MR (PCMR) enables rapid free-breathing assessment of flow. Target spatial and temporal resolutions require high acceleration rates often leading to long reconstruction times. Here we propose a deep artifact suppression framework for fast and accurate flow quantification.

METHODS

U-Nets were trained for deep artifact suppression using 520 breath-hold gated spiral PCMR aortic datasets collected in congenital heart disease patients. Two spiral trajectories (uniform and perturbed) and two losses (Mean Absolute Error -MAE- and average structural similarity index measurement -SSIM-) were compared in synthetic data in terms of MAE, peak SNR (PSNR) and SSIM. Perturbed spiral PCMR was prospectively acquired in 20 patients. Stroke Volume (SV), peak mean velocity and edge sharpness measurements were compared to Compressed Sensing (CS) and Cartesian reference.

RESULTS

In synthetic data, perturbed spiral consistently outperformed uniform spiral for the different image metrics. U-Net MAE showed better MAE and PSNR while U-Net SSIM showed higher SSIM based metrics. In-vivo, there were no significant differences in SV between any of the real-time reconstructions and the reference standard Cartesian data. However, U-Net SSIM had better image sharpness and lower biases for peak velocity when compared to U-Net MAE. Reconstruction of 96 frames took ~59 s for CS and 3.9 s for U-Nets.

CONCLUSION

Deep artifact suppression of complex valued images using an SSIM based loss was successfully demonstrated in a cohort of congenital heart disease patients for fast and accurate flow quantification.

Optimizing cryoballoon pulmonary vein isolation: lessons from >1000 procedures- the Frankfurt approach

AIMS

Cryoballoon (CB) pulmonary vein isolation (PVI) is an accepted ablation strategy for rhythm control in atrial fibrillation (AF). We describe efficacy and safety in a high volume centre with a long experience in the use of the second-generation CB (CB2).

METHODS AND RESULTS

Consecutive paroxysmal AF (PAF) or persistent AF (persAF) patients undergoing CB2-PVI were enrolled. Procedural data, efficacy, and safety issues were systematically collected. The 28 mm CB2 was used in combination with an inner lumen spiral catheter, a luminal oesophageal temperature (LET) probe was used with a cut-off of 15°C, the phrenic nerve (PN) monitored during septal PVs ablation. Freeze duration was mainly set at 240 s with a bonus application in case of delayed time-to-isolation (TTI > 75 s). A total of 1017 CB2 procedures were analysed (58% male, 66 ± 12 years old, 70% with PAF). 3964 PVs were identified, 99.8% PVs isolated using solely the 28 mm CB. Mean procedure time was 69 ± 25 min, TTI during the first application was recorded in 77% of PVs after a mean of 48 ± 31 s. We recorded 0.2% cardiac tamponade, 4.8% PN injury (1.6% of PN palsy), and 19% of LET < 15°C. Among 725 patients with follow-up data, 84% with PAF and 75% with persAF were in stable SR at 1 year. Shorter freezing duration and longer TTI were procedural predictors for recurrence.

CONCLUSION

Cryoballoon procedures are fast and associated with a benign safety profile. Shorter TTI and longer freeze durations are associated with sinus rhythm during follow-up.

One-step, multiplex, dual-function oligonucleotide of loop-mediated isothermal amplification assay for the detection of pathogenic Burkholderia pseudomallei

This study highlights the development of a multiplex real-time loop-mediated isothermal amplification assay. The developed assay employed a dual-function oligonucleotide (DFO) which simultaneously monitors the emitted amplification signals and accelerates the amplification process. The DFO was a modification of loop primer (LP); the 5'-end and 3'-end of the LP was tagged with fluorophore and quencher, respectively. The DFO was quenched in its unbound state and fluoresces only when it anneals to the specific target during the amplification process. With the same working mechanism as LP, DFO allowed the detection of target genes in less than 1 h in a real time monitoring system. We demonstrated this detection platform with Burkholderia pseudomallei, the causative agent of melioidosis. An internal amplification control (IAC) was incorporated in the assay to rule out false negative result and to demonstrate that the assay was successfully developed in a multiplex system. The assay was 100% specific when it was evaluated against 96 B. pseudomallei clinical isolates and 48 other bacteria species. The detection limit (sensitivity) of the developed assay was 1 fg/μl of B. pseudomallei genomic DNA and 18.2 CFU/ml at the bacterial cell level. In spiked blood samples, the assay's detection limit was 14 CFU/ml. The assay's diagnostic evaluation showed 100% diagnostic sensitivity, diagnostic specificity, positive predictive value, and negative predictive value. An integrated multiplex LAMP and real-time monitoring system was successfully developed, simplifying the workflow for the rapid and specific nucleic acid diagnostic test.

Real-time assessment of temporomandibular joint using HASTE sequences: feasibility and comparison with standard static sequences

OBJECTIVE

To test real-time MRI (rtMRI) using HASTE sequences in patients with suspected internal disk derangement (IDD) of temporomandibular joint (TMJ) and to compare these sequences with standard static sequences.

METHODS AND MATERIALS

99 TMJ were studied with both standard sequences (fat-saturated proton density) and HASTE sequences with high temporal resolution. Image quality was assessed using a 4-point Likert scale. Two radiologists analysed both standard and rtMRI sequences separately, randomly and blinded (by a third operator) to patients' names in order to assess inter-observer repeatability. One of the radiologists performed the analysis twice for assessing intra-observer repeatability. The same radiologists evaluated randomly and blinded to the previous assessment both the sequences and decided in consensus which was the most credible. Qualitative scores were compared using Friedman's test while concordance between radiologists and sequences was evaluated using the concordance correlation coefficient.

RESULTS

At image quality analysis, mean score was 3.41 for static MRI and 3.82 for rtMRI, with a statistically significant difference in favour of rtMRI (p < 0.0001). Inter-rater concordance between operator 1 (Op1) and operator 2 (Op2) with regard to the same sequence was high for both static and rtMRI sequences (0.824 and 0.888, respectively). Inter-rater variability of Op1 and Op2 between static and rtMRI sequences was lower (0.647 for Op1 and 0.633 for Op2). Among 71 discordances between sequences, 60 were judged in favour of rtMRI, while 11 were in favour of static MRI.

CONCLUSION

rtMRI with HASTE sequences is a robust technique and provide additional information in assessing IDD compared to static sequences.

Bilateral attention decoder: A lightweight decoder for real-time semantic segmentation

The encoder-decoder structure has been introduced into semantic segmentation to improve the spatial accuracy of the network by fusing high- and low-level feature maps. However, recent state-of-the-art encoder-decoder-based methods can hardly attain the real-time requirement due to their complex and inefficient decoders. To address this issue, in this paper, we propose a lightweight bilateral attention decoder for real-time semantic segmentation. It consists of two blocks and can fuse different level feature maps via two steps, i.e., information refinement and information fusion. In the first step, we propose a channel attention branch to refine the high-level feature maps and a spatial attention branch for the low-level ones. The refined high-level feature maps can capture more exact semantic information and the refined low-level ones can capture more accurate spatial information, which significantly improves the information capturing ability of these feature maps. In the second step, we develop a new fusion module named pooling fusing block to fuse the refined high- and low-level feature maps. This fusion block can take full advantages of the high- and low-level feature maps, leading to high-quality fusion results. To verify the efficiency of the proposed bilateral attention decoder, we adopt a lightweight network as the backbone and compare our proposed method with other state-of-the-art real-time semantic segmentation methods on the Cityscapes and Camvid datasets. Experimental results demonstrate that our proposed method can achieve better performance with a higher inference speed. Moreover, we compare our proposed network with several state-of-the-art non-real-time semantic segmentation methods and find that our proposed network can also attain better segmentation performance.

Imaging VOC distribution in cities and tracing VOC emission sources with a novel mobile proton transfer reaction mass spectrometer

Volatile organic compounds (VOCs) are important precursors of ozone (O₃) and secondary organic aerosols (SOAs). Tracing VOC pollution sources is important for controlling VOC emissions and reducing O₃ and SOAs. We built a novel mobile proton transfer reaction mass spectrometry (M-PTR-MS) instrument to image the distribution of VOCs and trace their emission sources in cities and industrial parks. The M-PTR-MS is composed of a vibration-resistant proton transfer reaction mass spectrometry (PTR-MS) with a global positioning system receiver, modified box vehicle, and geographic information system (GIS) software. The PTR-MS, mounted on a vehicle, sends VOC data and vehicle position information to the GIS software. These data are used to image the space distribution of VOCs in real time while the vehicle platform is in motion and the VOC sources are precisely traced using the GIS. The spatial data resolution of the M-PTR-MS is typically 0.8 m. The limits of detection, sensitivity, and repeatability of the M-PTR-MS are 43.5 ppt, 347 counts ppb^-1, and 2.4% (RSD, n = 5), respectively. The intensity of reagent ions is stable over 8 h (RSD = 0.45%). Compared with commercial PTR-MS equipment, the M-PTR-MS demonstrated high consistency, with a correlation coefficient of 92.665%. Several field experiments were conducted in China using the M-PTR-MS. In one field experiment, the VOC distribution along three different routes was surveyed; the navigation monitoring lasted 1.8 h over a distance of 26.7 km at an average speed of 15 km h^-1. The VOC sources in an industrial park were identified by analyzing the components near different factories. The main species from a VOC source in an underground garage was related to paint. The M-PTR-MS instrument can be used by environmental protection agencies to trace VOC pollution sources in real time, and by researchers to survey VOC emissions in regions of concern.

Real-time continuous monitoring of injection pressure during peripheral nerve blocks in fresh cadavers

BACKGROUND

The incidence of unintentional intraneural injection while performing peripheral nerve block has been estimated to be 15% under real-time ultrasound guidance. Injection pressure increase may detect an intraneural injection. Real-time injection pressure changes throughout an entire nerve block procedure in relationship with needle tip location have never been reported.

METHODS

A new method was developed to precisely monitor the injection pressure curve during nerve blocks, based on a miniaturised Fabbri-Perrot pressure sensor. We tested in three fresh cadavers the ability of continuous pressure monitoring to discriminate between different tissues, as the injection pressure curve ascending slope, shape and plateau pressure value depend on tissue compliance. Injections of saline were performed by an electronic syringe pump with three different constant flow rates. Pressure was measured simultaneously at the tip and in the tubing of the needle.

RESULTS

At 10 mL/min injection flow, median peak injection pressure in the intraneural group at the needle tip was 315 mmHg, while at the perineural location it was 100 mmHg (p < 0.05). Median injection pressure was 95 mmHg in the intramuscular locations group, and 819 mmHg when a muscular fascia was indented (p < 0.05). A significant difference was noted for pressure measurements between the proximal port of the needle and the tip, 625 and 417 respectively.

CONCLUSIONS

Based on significant differences in injection pressure values and curve shapes, the system was able to discriminate between four needle tip locations. This may help with needle tracking while performing a peripheral nerve block.

Diagnostic performance of conventional ultrasound and quantitative and qualitative real-time shear wave elastography in musculoskeletal soft tissue tumors

BACKGROUND

To explore the feasibility to identify malignant musculoskeletal soft tissue tumors using real-time shear wave elastography (rtSWE).

METHODS

One hundred fifteen musculoskeletal soft tissue tumors in 92 consecutive patients were examined using both conventional ultrasonography (US) and rtSWE. For each patient, the rtSWE parameters including maximum elasticity (E_max), mean elasticity (E_mean), minimum elasticity (E_min), standard deviation of the elasticity (E_sd), and rtSWE image pattern were obtained. Eighty-one histopathologically confirmed tumors from 73 patients were subjected to analysis.

RESULTS

The 81 lesions included in the study were histopathologically classified as malignant (n = 21) or benign (n = 60). The statistically significant differences between benign and malignant lesions were found in conventional US characters including size, depth, margin, echogenicity, mass texture, and power Doppler signal. Meanwhile, the significant differences were also found in quantitative rtSWE findings including E_max, E_mean, E_min, and E_sd values and in qualitative rtSWE parameter named rtSWE image pattern. Multivariate analysis showed that infiltrative margin (OR, 4.470), and size (OR, 1.046) were independent predictors for malignancy in US findings, while E_sd value (OR, 9.047) was independent predictors for malignancy in quantitative rtSWE parameters. Areas under the ROC curve (Azs) for US features, E_sd value, and rtSWE image pattern were 0.851, 0.795, and 0.792, respectively.

CONCLUSIONS

Conventional US and quantitative and qualitative rtSWE parameters are useful for malignancy prediction of musculoskeletal soft tissue tumors. rtSWE can be used to supplement conventional US to diagnose musculoskeletal soft tissue tumors.

Bayesian spatiotemporal modeling with sliding windows to correct reporting delays for real-time dengue surveillance in Thailand

Background

The ability to produce timely and accurate estimation of dengue cases can significantly impact disease control programs. A key challenge for dengue control in Thailand is the systematic delay in reporting at different levels in the surveillance system. Efficient and reliable surveillance and notification systems are vital to monitor health outcome trends and early detection of disease outbreaks which vary in space and time.

Methods

Predicting the trend in dengue cases in real-time is a challenging task in Thailand due to a combination of factors including reporting delays. We present decision support using a spatiotemporal nowcasting model which accounts for reporting delays in a Bayesian framework with sliding windows. A case study is presented to demonstrate the proposed nowcasting method using weekly dengue surveillance data in Bangkok at district level in 2010.

Results

The overall real-time estimation accuracy was 70.69% with 59.05% and 79.59% accuracy during low and high seasons averaged across all weeks and districts. The results suggest the model was able to give a reasonable estimate of the true numbers of cases in the presence of delayed reports in the surveillance system. With sliding windows, models could also produce similar accuracy to estimation with the whole data.

Conclusions

A persistent challenge for the statistical and epidemiological communities is to transform data into evidence-based knowledge that facilitates policy making about health improvements and disease control at the individual and population levels. Improving real-time estimation of infectious disease incidence is an important technical development. The effort in this work provides a template for nowcasting in practice to inform decision making for dengue control.

[Patient tracking with beacon technology : Pilot project in a radiological practice]

Waiting times are still assumed to be unavoidable in medicine. However, waiting time is an essential factor of patient satisfaction. Because patient expectations are increasing, medical institutions should address the issue. Above all, this requires transparency about the current processes in the facilities. Conventional information systems often do not offer sufficient solutions to ensure this in real time combined with helpful visualization. In a pilot project in a radiological practice, the use of a patient tracking system based on beacon technology was tested. The aim was to track the actual location of the patients in the practice, to determine the patient status (e.g. patient waiting) and to display the entire processes on a smart dashboard. The successful pilot project has shown that the technology meets all requirements, that patients accept the system and that staff are familiar with the new processes after some time. For the first time, patient flows, including waiting times, were displayed clearly and in real time on a dashboard. This made it possible to control processes and waiting times that had previously never been recorded in a structured manner and were usually only recognized in the event of complaints. From a technical point of view, the system is arbitrarily scalable, whereby the connection to different information systems will be a challenge. If this succeeds, however, the possibilities are manifold. The created transparency makes it possible to reduce waiting times and to actively inform patients about waiting times and thus contribute to increasing patient satisfaction.

Online monitoring of heavy metal-related toxicity using flow-through and floating microbial fuel cell biosensors

Elevated concentrations of heavy metals in water caused by mining activities create significant risks to the environment. Traditional biological methods used to assess heavy metal-related toxicity in aquatic environments are lengthy and labor intensive. Real-time biomonitoring approaches eliminate some of these limitations and provide a more accurate indication of toxicity. This study describes the performance of a flow-through and floating design microbial fuel cell (MFC) biosensors for real-time detection of copper (Cu) and other heavy metal-related toxicity in aquatic environments. Several biomonitoring tests were carried out using Cu and mining effluents as toxicants. The biosensors were able to detect, in real-time, Cu-related toxicity at concentrations as low as 35 - 40 μg L^-1, as confirmed by a Daphnia assay. A comparison of the floating biosensor's outputs with Daphnia magna survival rates showed a linear correlation with a coefficient of determination (R²) higher than 0.9. In addition, the flow-through biosensor was shown to be able to detect  differences in the quality of two mining effluents with different compositions of heavy metals. Finally, the biosensor's real-time field performance was investigated in two aquatic environments in the Sudbury, Ontario region of Canada.

Relative Expression Analysis of Target Genes by Using Reverse Transcription-Quantitative PCR

Real-time PCR is a powerful technique used for quantification of defined nucleic acid sequences. Numerous applications of this method have been described including: gene expression studies, diagnosis of pathogens, and detection of genetically modified organisms or mutations. Here, we describe a simple and efficient protocol to determine gene expression in cereals, based on real-time PCR using SYBR^® Green dye. This technique provide an inexpensive alternative, since no probes are required, allowing for the quantification of a high number of genes with reduced cost.

Evaluation of a real-time magnetic resonance imaging-guided electrophysiology system for structural and electrophysiological ventricular tachycardia substrate assessment

Aims

Potential advantages of real-time magnetic resonance imaging (MRI)-guided electrophysiology (MR-EP) include contemporaneous three-dimensional substrate assessment at the time of intervention, improved procedural guidance, and ablation lesion assessment. We evaluated a novel real-time MR-EP system to perform endocardial voltage mapping and assessment of delayed conduction in a porcine ischaemia–reperfusion model.

Methods and results

Sites of low voltage and slow conduction identified using the system were registered and compared to regions of late gadolinium enhancement (LGE) on MRI. The Sorensen–Dice similarity coefficient (DSC) between LGE scar maps and voltage maps was computed on a nodal basis. A total of 445 electrograms were recorded in sinus rhythm (range: 30–186) using the MR-EP system including 138 electrograms from LGE regions. Pacing captured at 103 sites; 47 (45.6%) sites had a stimulus-to-QRS (S-QRS) delay of ≥40 ms. Using conventional (0.5–1.5 mV) bipolar voltage thresholds, the sensitivity and specificity of voltage mapping using the MR-EP system to identify MR-derived LGE was 57% and 96%, respectively. Voltage mapping had a better predictive ability in detecting LGE compared to S-QRS measurements using this system (area under curve: 0.907 vs. 0.840). Using an electrical threshold of 1.5 mV to define abnormal myocardium, the total DSC, scar DSC, and normal myocardium DSC between voltage maps and LGE scar maps was 79.0 ± 6.0%, 35.0 ± 10.1%, and 90.4 ± 8.6%, respectively.

Conclusion

Low-voltage zones and regions of delayed conduction determined using a real-time MR-EP system are moderately associated with LGE areas identified on MRI.

An ecological momentary assessment of self-management in prostate cancer survivors

PURPOSE

To assess the 'real-time' self-management strategies employed by prostate cancer survivors to inform personalised supportive care interventions in the future.

METHOD

A purposive sampling framework was used to recruit men with different stages of cancer and treatment to an ecological momentary assessment (capturing experiences in real time) study. Each participant was prompted by an audio alert to complete self-report questionnaires three times per day (93 data entries in total) for a total duration of 31 days. The personal digital assistant (PDA) and pocket interview software were used.

RESULTS

Prostate cancer survivors experienced a wide range of after-effects of therapy for which they used various self-management strategies. Many of the men experienced sexual dysfunction but did not perform any self-management.

CONCLUSION

Our findings reinforce the importance of having access to tailored, timely and person-centred supported self-management care plans. Real-time monitoring data can provide helpful information to facilitate tailored recommendations for self-management.

IMPLICATIONS FOR CANCER SURVIVORS

Prostate cancer survivors can experience unmet supportive care needs which may increase men's demands to perform self-management of their condition. Future clinical intervention studies aimed at utilising the remote exchange of real-time data serves to optimise tailored supported self-management.

High-Resolution Full-Length HLA Typing Method Using Third Generation (Pac-Bio SMRT) Sequencing Technology

The human HLA genes are among the most polymorphic genes in the human genome. Therefore, it is very difficult to find two unrelated individuals with identical HLA molecules. As a result, HLA Class I and Class II genes are routinely sequenced or serotyped for organ transplantation, autoimmune disease-association studies, drug hypersensitivity research, and other applications. However, these methods were able to give two or four digit data, which was not sufficient enough to understand the completeness of haplotypes of HLA genes. To overcome these limitations, we here described end-to-end workflow for sequencing of HLA class I and class II genes using third generation sequencing, SMRT technology. This method produces fully-phased, unambiguous, allele-level information on the PacBio System.

Forgetting from lapses of sustained attention

When performing any task for an extended period of time, attention fluctuates between good and bad states. These fluctuations affect performance in the moment, but may also have lasting consequences for what gets encoded into memory. Experiment 1 establishes this relationship between attentional states and memory, by showing that subsequent memory for an item was predicted by a response time index of sustained attention (average response time during the three trials prior to stimulus onset). Experiment 2 strengthens the causal interpretation of this predictive relationship by treating the sustained attention index as an independent variable to trigger the appearance of an encoding trial. Subsequent memory was better when items were triggered from good versus bad attentional states. Together, these findings suggest that sustained attention can have downstream consequences for what we remember, and they highlight the inferential utility of adaptive experimental designs. By continuously monitoring attention, we can influence what will later be remembered.

An ensemble forecast model of dengue in Guangzhou, China using climate and social media surveillance data

BACKGROUND

China experienced an unprecedented outbreak of dengue in 2014, and the number of dengue cases reached the highest level over the past 25 years. There is a significant delay in the release of official case count data, and our ability to timely track the timing and magnitude of local outbreaks of dengue remains limited.

MATERIAL AND METHODS

We developed an ensemble penalized regression algorithm (EPRA) for initializing near-real time forecasts of the dengue epidemic trajectory by integrating different penalties (LASSO, Ridge, Elastic Net, SCAD and MCP) with the techniques of iteratively sampling and model averaging. Multiple streams of near-real time data including dengue-related Baidu searches, Sina Weibo posts, and climatic conditions with historical dengue incidence were used. We compared the predictive power of the EPRA with the alternates, penalized regression models using single penalties, to retrospectively forecast weekly dengue incidence and detect outbreak occurrence defined using different cutoffs, during the periods of 2011-2016 in Guangzhou, south China.

RESULTS

The EPRA showed the best or at least comparable performance for 1-, 2-week ahead out-of-sample and leave-one-out cross validation forecasts. The findings indicate that skillful near-real time forecasts of dengue and confidence in those predictions can be made. For detecting dengue outbreaks, the EPRA predicted periods of high incidence of dengue more accurately than the alternates.

CONCLUSION

This study developed a statistically rigorous approach for near-real time forecast of dengue in China. The EPRA provides skillful forecasts and can be used as timely and complementary ways to assess dengue dynamics, which will help to design interventions to mitigate dengue transmission.

Identification of genes involved in fruit development/ripening in Capsicum and development of functional markers

The molecular mechanism of the underlying genes involved in the process of fruit ripening in Capsicum (family Solanaceae) is not clearly known. In the present study, we identified orthologs of 32 fruit development/ripening genes of tomato in Capsicum, and validated their expression in fruit development stages in C. annuum, C. frutescens, and C. chinense. In silico expression analysis using transcriptome data identified a total of 12 out of 32 genes showing differential expression during different stages of fruit development in Capsicum. Real time expression identified gene LOC107847473 (ortholog of MADS-RIN) had substantially higher expression (>500 folds) in breaker and mature fruits, which suggested the non-climacteric ripening behaviour of Capsicum. However, differential expression of Ehtylene receptor 2-like (LOC107873245) gene during fruit maturity supported the climacteric behaviour of only C. frutescens (hot pepper). Furthermore, development of 49 gene based simple sequence repeat (SSR) markers would help in selection of identified genes in Capsicum breeding.

Real-Time Water Distribution System Hydraulic Modeling Using Prior Demand Information by Formal Bayesian Approach

Real-time water distribution system (WDS) hydraulic models are used in water utilities to facilitate the planning and operation of the water distribution system. As a critical model input, spatiotemporally varying nodal water demands significantly affect the performance and applicability of such WDS models. Thus, real-time nodal demands must be calibrated for reliability before their use. The main difficulty for real-time calibration is the lack of observed data sufficient to determine thousands of nodal demands accurately in a network. To address the difficulty, this study proposes a formal Bayesian approach to determine nodal demands in WDS hydraulic modeling by explicitly taking prior water demand information into account and coupling more information to constrain the nodal water demand modeling. Application of the approach on a simple hypothetical network and a field network in a city of eastern Zhejiang Province, China demonstrates that by adding prior information, the nodal demand can be uniquely determined in real time. The approach limits uncertainty propagation and improves the robustness of the real-time model calibration and analysis.

Live imaging of cortical granule exocytosis reveals that in vitro matured mouse oocytes are not fully competent to secrete their content

Oocyte in vitro maturation does not entirely support all the nuclear and cytoplasmic changes that occur physiologically, and it is poorly understood whether in vitro maturation affects the competence of cortical granules to secrete their content during cortical reaction. Here, we characterize cortical granule exocytosis (CGE) in live mouse oocytes activated by strontium chloride using the fluorescent lectin FITC-LCA. We compared the kinetic of CGE between ovulated (in vivo matured, IVO) and in vitro matured (IVM) mouse oocytes. Results show that: (1) IVM oocytes have a severely reduced response to strontium chloride; (2) the low response was confirmed by quantification of remnant cortical granules in permeabilized cells and by a novel method to quantify the exudate in non-permeabilized cells; (3) the kinetic of CGE in IVO oocytes was rapid and synchronous; (4) the kinetic of CGE in IVM oocytes was delayed and asynchronous; (5) cortical granules in IVM oocytes show an irregular limit in regards to the cortical granule free domain. We propose the analysis of CGE in live oocytes as a biological test to evaluate the competence of IVM mouse oocytes.This article has an associated First Person interview with the first author of the paper.

A framework for constraining image SNR loss due to MR raw data compression

INTRODUCTION

Computationally intensive image reconstruction algorithms can be used online during MRI exams by streaming data to remote high-performance computers. However, data acquisition rates often exceed the bandwidth of the available network resources creating a bottleneck. Data compression is, therefore, desired to ensure fast data transmission.

METHODS

The added noise variance due to compression was determined through statistical analysis for two compression libraries (one custom and one generic) that were implemented in this framework. Limiting the compression error variance relative to the measured thermal noise allowed for image signal-to-noise ratio loss to be explicitly constrained.

RESULTS

Achievable compression ratios are dependent on image SNR, user-defined SNR loss tolerance, and acquisition type. However, a 1% reduction in SNR yields approximately four to ninefold compression ratios across MRI acquisition strategies. For free-breathing cine data reconstructed in the cloud, the streaming bandwidth was reduced from 37 to 6.1 MB/s, alleviating the network transmission bottleneck.

CONCLUSION

Our framework enabled data compression for online reconstructions and allowed SNR loss to be constrained based on a user-defined SNR tolerance. This practical tool will enable real-time data streaming and greater than fourfold faster cloud upload times.

Real time detection of glutathionse in chemotherapy squamous-cell carcinoma cells of a fluorescent probe

Glutathione (GSH) plays a key role in protecting damage induced by radiation and chemotherapy drugs. Current methods, which quantify GSH level changes by using cellular extraction or being based on redox homeostasis results, are unable to directly measure real time GSH level in live cells. In this article, we utilized a newly designed reversible fluorescent probe to measure GSH in living cells. The image of probe 1 can reveal intracellular GSH location and GSH level changes caused by different chemotherapy drugs in squamous-cell carcinoma cells. The results show that it is the first report with probe 1 that to quantify real-time GSH level changes in the cultured chemotherapy cancer cells and different changes in GSH level that may confer chemotherapy resistance.

Assessing mercury intoxication in isolated/remote populations: Increased S100B mRNA in blood in exposed riverine inhabitants of the Amazon

Mercury is a heavy metal responsible for human intoxication worldwide and especially in the Amazon, where both natural and anthropogenic sources are responsible for exposure in riverine populations. Methylmercury is the most toxic specie of mercury with recognized neurotoxicity due to its affinity for the central nervous system. S100B protein is a well-established biomarker of brain damage and it was recently associated with mercury-related neurotoxicity. Accurate measurement is especially challenging in isolated/remote populations due to the difficulty of adequate sample conservation, therefore here we use S100B mRNA levels in blood as a way to assay mercury neurotoxicity. We hypothesized that individuals from chronically exposed populations showing mercury levels above the limit of 10 μg/g in hair would present increased levels of S100B mRNA, likely due to early brain damage. A total of 224 riverine individuals were evaluated for anthropometric data (age, body mass index), self-reported symptoms of mercury intoxication, c-reactive protein in blood, and mercury speciation in hair. Approximately 20% of participants showed mercury levels above the limit, and prevalence for most symptoms was not different between individuals exposed to high or low mercury levels. Rigorous exclusion criteria were applied to avoid confounding factors and S100B mRNA in blood was tested by RT-qPCR. Participants with ≥10 μg/g of mercury had S100B mRNA levels over two times higher than that of individuals with lower exposure. A significant correlation was also detected between mercury content in hair and S100B mRNA levels in blood, supporting the use of the latter as a possible candidate to predict mercury-induced neurotoxicity. This is the first report of an association between S100B mRNA and mercury exposure in humans. The combination of both exposure and intoxication biomarkers could provide additional support for the screening and early identification of high-risk individuals in isolated populations and subsequent referral to specialized centers.

Real-time Microwave Exposure Induces Calcium Efflux in Primary Hippocampal Neurons and Primary Cardiomyocytes

OBJECTIVE

To detect the effects of microwave on calcium levels in primary hippocampal neurons and primary cardiomyocytes by the real-time microwave exposure combined with laser scanning confocal microscopy.

METHODS

The primary hippocampal neurons and primary cardiomyocytes were cultured and labeled with probes, including Fluo-4 AM, Mag-Fluo-AM, and Rhod-2, to reflect the levels of whole calcium [Ca2+], endoplasmic reticulum calcium [Ca2+]ER, and mitochondrial calcium [Ca2+]MIT, respectively. Then, the cells were exposed to a pulsed microwave of 2.856 GHz with specific absorption rate (SAR) values of 0, 4, and 40 W/kg for 6 min to observe the changes in calcium levels.

RESULTS

The results showed that the 4 and 40 W/kg microwave radiation caused a significant decrease in the levels of [Ca2+], [Ca2+]ER, and [Ca2+]MIT in primary hippocampal neurons. In the primary cardiomyocytes, only the 40 W/kg microwave radiation caused the decrease in the levels of [Ca2+], [Ca2+]ER, and [Ca2+]MIT. Primary hippocampal neurons were more sensitive to microwave exposure than primary cardiomyocytes. The mitochondria were more sensitive to microwave exposure than the endoplasmic reticulum.

CONCLUSION

The calcium efflux was occurred during microwave exposure in primary hippocampal neurons and primary cardiomyocytes. Additionally, neurons and mitochondria were sensitive cells and organelle respectively.

Real time relationship between individual finger force and grip exertion on distal phalanges in linear force following tasks

Individual finger force (FF) in a grip task is a vital concern in rehabilitation engineering and precise control of manipulators because disorders in any of the fingers will affect the stability or accuracy of the grip force (GF). To understand the functions of each finger in a dynamic grip exertion task, a GF following experiment with four individual fingers without thumb was designed. This study obtained four individual FFs from the distal phalanges with a cylindrical handle in dynamic GF following tasks. Ten healthy male subjects with similar hand sizes participated in the four-finger linear GF following tasks at different submaximal voluntary contraction (SMVC) levels. The total GF, individual FF, finger force contribution, and following error were subsequently calculated and analyzed. The statistics indicated the following: 1) the accuracy and stability of GF at low %MVC were significantly higher than those at high SMVC; 2) at low SMVC, the ability of the fingers to increase the GF was better than the ability to reduce it, but it was contrary at high SMVC; 3) when the target wave (TW) was changing, all four fingers strongly participated in the force exertion, but the participation of the little finger decreased significantly when TW remained stable; 4) the index finger and ring finger had a complementary relationship and played a vital role in the adjustment and control of GF. The middle finger and little finger had a minor influence on the force control and adjustment. In conclusion, each of the fingers had different functions in a GF following task. These findings can be used in the assessment of finger injury rehabilitation and for algorithms of precise control.

A Bit-Encoding Based New Data Structure for Time and Memory Efficient Handling of Spike Times in an Electrophysiological Setup

Recent neuroscientific and technical developments of brain machine interfaces have put increasing demands on neuroinformatic databases and data handling software, especially when managing data in real time from large numbers of neurons. Extrapolating these developments we here set out to construct a scalable software architecture that would enable near-future massive parallel recording, organization and analysis of neurophysiological data on a standard computer. To this end we combined, for the first time in the present context, bit-encoding of spike data with a specific communication format for real time transfer and storage of neuronal data, synchronized by a common time base across all unit sources. We demonstrate that our architecture can simultaneously handle data from more than one million neurons and provide, in real time (< 25 ms), feedback based on analysis of previously recorded data. In addition to managing recordings from very large numbers of neurons in real time, it also has the capacity to handle the extensive periods of recording time necessary in certain scientific and clinical applications. Furthermore, the bit-encoding proposed has the additional advantage of allowing an extremely fast analysis of spatiotemporal spike patterns in a large number of neurons. Thus, we conclude that this architecture is well suited to support current and near-future Brain Machine Interface requirements.

Fast and robust Block-Sparse Bayesian learning for EEG source imaging

We propose a new Sparse Bayesian Learning (SBL) algorithm that can deliver fast, block-sparse, and robust solutions to the EEG source imaging (ESI) problem in the presence of noisy measurements. Current implementations of the SBL framework are computationally expensive and typically handle fluctuations in the measurement noise using different heuristics that are unsuitable for real-time imaging applications. We address these shortcomings by decoupling the estimation of the sensor noise covariance and the sparsity profile of the sources, thereby yielding an efficient two-stage algorithm. In the first stage, we optimize a simplified non-sparse generative model to get an estimate of the sensor noise covariance and a good initialization of the group-sparsity profile of the sources. Sources obtained at this stage are equivalent to those estimated with the popular inverse method LORETA. In the second stage, we apply a fast SBL algorithm with the noise covariance fixed to the value obtained in the first stage to efficiently shrink to zero groups of sources that are irrelevant for explaining the EEG measurements. In addition, we derive an initialization to the first stage of the algorithm that is optimal in the least squares sense, which prevents delays due to suboptimal initial conditions. We validate our method on both simulated and real EEG data. Simulations show that the method is robust to measurement noise and performs well in real-time, with faster performance than two state of the art SBL solvers. On real error-related negativity EEG data, we obtain source images in agreement with the experimental literature. The method shows promise for real-time neuroimaging and brain-machine interface applications.

Exploring the role of Inositol 1,3,4-trisphosphate 5/6 kinase-2 (GmITPK2) as a dehydration and salinity stress regulator in Glycine max (L.) Merr. through heterologous expression in E. coli

Phytic acid (PA) is implicative in a spectrum of biochemical and physiological processes involved in plant stress response. Inositol 1,3,4, Tris phosphate 5/6 kinase (ITPK), a polyphosphate kinase that converts Inositol 1,3,4 trisphosphate to Inositol 1,3,4,5/6 tetra phosphate, averting the inositol phosphate pool towards PA biosynthesis, is a key regulator that exists in four different isoforms in soybean. In the present study, in-silico analysis of the promoter region of ITPKs was done and among the four isoforms, promoter region of GmITPK2 showed the presence of two MYB binding elements for drought inducibility and one for ABA response. Expression profiling through qRT-PCR under drought and salinity stress showed higher expression of GmITPK2 isoform compared to the other members of the family. The study revealed GmITPK2 as an early dehydration responsive gene which is also induced by dehydration and exogenous treatment with ABA. To evaluate the osmo-protective role of GmITPK2, attempts were made to assess the bacterial growth on Luria Broth media containing 200 mM NaCl, 16% PEG and 100 μM ABA, individually. The transformed E. coli BL21 (DE3) cells harbouring the GmITPK2 gene depicted better growth on the media compared to the bacterial cells containing the vector alone. Similarly, the growth of the transformed cells in the liquid media containing 200 mM NaCl, 16% PEG and 100 μM ABA showed higher absorbance at 600 nm compared to control, at different time intervals. The GmITPK2 recombinant E. coli cells showing tolerance to drought and salinity thus demonstrated the functional redundancy of the gene across taxa. The purity and specificity of the recombinant protein was assessed and confirmed through PAGE showing a band of ∼35 kDa on western blotting using Anti- Penta His- HRP conjugate antibody. To the best of our knowledge, the present study is the first report exemplifying the role of GmITPK2 isoform in drought and salinity tolerance in soybean.

Characterization and molecular modeling of Inositol 1,3,4 tris phosphate 5/6 kinase-2 from Glycine max (L) Merr.: comprehending its evolutionary conservancy at functional level

Soybean genome encodes a family of four inositol 1,3,4 trisphosphate 5/6 kinases which belong to the ATP-GRASP group of proteins. Inositol 1,3,4 trisphosphate kinase-2 (GmItpk2), catalyzing the ATP-dependent phosphorylation of Inositol 1,3,4 trisphosphate (IP3) to Inositol 1,3,4,5 tetra phosphate or Inositol 1,3,4,6 tetra phosphate, is a key enzyme diverting the flux of inositol phosphate pool towards phytate biosynthesis. Although considerable research on characterizing genes involved in phytate biosynthesis is accomplished at genomic and transcript level, characterization of the proteins is yet to be explored. In the present study, we report the isolation and expression of single copy Itpk2 (948 bp) from Glycine max cv Pusa-16 predicted to encode 315 amino acid protein with an isoelectric point of 5.9. Sequence analysis revealed that GmITPK2 shared highest similarity (80%) with Phaseolus vulgaris. The predicted 3D model confirmed 12 α helices and 14 β barrel sheets with ATP-binding site close to β sheet present towards the C-terminus of the protein molecule. Spatio-temporal transcript profiling signified GmItpk2 to be seed specific, with higher transcript levels in the early stage of seed development. The present study using various molecular and bio-computational tools could, therefore, help in improving our understanding of this key enzyme and prove to be a potential target towards generating low phytate trait in nutritionally rich crop like soybean.

Evaluation of two real time PCR assays for the detection of bacterial DNA in amniotic fluid

PURPOSE

The aim of this study was to evaluate two non-commercial Real-Time PCR assays for the detection of microorganisms in amniotic fluid followed by identification by pyrosequencing.

METHODS

We collected 126 amniotic fluids from 2010 to 2015 for the evaluation of two Real-Time PCR assays for detection of bacterial DNA in amniotic fluid (16S Universal PCR and Ureaplasma spp. specific PCR). The method was developed in the Department of Microbiology of the University Hospital La Paz.

RESULTS

Thirty-seven samples (29.3%) were positive by PCR/pyrosequencing and/or culture, 4 of them were mixed cultures with Ureaplasma urealyticum. The Universal 16S Real-Time PCR was compared with the standard culture (81.8% sensitivity, 97.4% specificity, 75% positive predictive value, 98% negative predictive value). The Ureaplasma spp. specific Real-Time PCR was compared with the Ureaplasma/Mycoplasma specific culture (92.3% sensitivity, 89.4% specificity, 50% positive predictive value, 99% negative predictive value) with statistically significant difference (p=0.005).

CONCLUSIONS

Ureaplasma spp. PCR shows a rapid response time (5h from DNA extraction until pyrosequencing) when comparing with culture (48h). So, the response time of bacteriological diagnosis in suspected chorioamnionitis is reduced.

The Changing Role of the Clinical Microbiology Laboratory in Defining Resistance in Gram-negatives

The evolution of resistance in Gram-negatives has challenged the clinical microbiology laboratory to implement new methods for their detection. Multidrug-resistant strains present major challenges to conventional and new detection methods. More rapid pathogen identification and antimicrobial susceptibility testing have been developed for use directly on specimens, including fluorescence in situ hybridization tests, automated polymerase chain reaction systems, microarrays, mass spectroscopy, next-generation sequencing, and microfluidics. Review of these methods shows the advances that have been made in rapid detection of resistance in cultures, but limited progress in direct detection from specimens.

Time-resolved monitoring of polycyclic aromatic hydrocarbons adsorbed on atmospheric particles

Real-time monitoring of individual particles from atmospheric aerosols was performed by means of a specifically developed single-particle fluorescence spectrometer (SPFS). The observed fluorescence was assigned to particles bearing polycyclic aromatic hydrocarbons (PAH). This assignment was supported by an intercomparison with classical speciation on filters followed by gas chromatography-mass spectrometry (GC-MS) analysis. As compared with daily averaged data, our time-resolved approach provided information about the physicochemical dynamics of the particles. In particular, distinctions were made between background emissions related to heating, and traffic peaks during rush hours. Also, the evolution of the peak fluorescence wavelength provided an indication of the aging of the particles during the day.

Comparison of histopathology, acid fast bacillus smear and real-time polymerase chain reaction for detection of Mycobacterium tuberculosis in anal fistula in 161 patients: A prospective controlled trial

OBJECTIVE/BACKGROUND

Mycobacterium tuberculosis (MTB) is a known cause of refractory and recurrent fistula-in-ano. Histopathology of fistula tract and acid fast bacillus (AFB) smear of the pus are the standard procedures employed to diagnose MTB. However, they have some drawbacks. Nontubercular mycobacteria (NTM) has also been detected to cause fistula-in-ano and these methods cannot differentiate between MTB and NTM. Secondly, as these methods have low sensitivity, they could possibly be missing out MTB patients. Real-time polymerase chain reaction (RT-PCR) has high sensitivity in detecting mycobacteria. The aim of the study was to compare the sensitivity of RT-PCR, histopathology, and AFB smear in detecting MTB in fistula-in-ano.

METHODS

The histopathology and RT-PCR of tissue (fistula tract) was done along with AFB smear and RT-PCR of the pus was done in all the cases as per the availability of the specimen. The histopathology, AFB smear and RT-PCR was done by same pathologists in all the cases and all the patients were operated by a single surgeon.

RESULTS

A total of 286 samples were tested in 161 patients of fistula-in-ano who were operated over a period of 1year. The mean age was 38.6±10.5 and male/female ratio was 153/8. Histopathology and RT-PCR of tissue (fistula tract) was done in 131 patients and 141 patients respectively. AFB smear and RT-PCR of pus (fistula) was done in 14 patients. Overall, MTB was detected in total of 17/161 (10.63%) patients. Out of these, MTB was detected in tissue (fistula tract) in 1/131 (0.76%) by histopathology and 14/141 (10%) by RT-PCR tissue. In pus samples, AFB smear was negative in all cases (0/14), whereas RT-PCR detected MTB in four of 14 (28.6%) patients. In 17 patients detected to have MTB, four-drug antitubercular therapy (ATT) was recommended. ATT was started in 15 patients. Nine of 17 patients completed 6months ATT and were cured. Six of 17 patients are currently taking ATT. Two patients did not take ATT; both of these have persistent symptoms of pus formation. Out of nine cured patients, two patients did not start ATT for 2months after detection. Only after the symptoms (persistent pus discharge) continued, did they start ATT and were subsequently cured.

CONCLUSION

RT-PCR is significantly more sensitive than histopathology and AFB smear in detecting MTB in fistula-in-ano. The routine practice of doing only histopathology and AFB smear in fistula patients might be missing a significant number of MTB cases and could be responsible for many recurrences in fistula patients. RT-PCR should preferably be done in all fistula cases and at least in refractory and recurrent fistulas.

A real time metabolomic profiling approach to detecting fish fraud using rapid evaporative ionisation mass spectrometry

INTRODUCTION

Fish fraud detection is mainly carried out using a genomic profiling approach requiring long and complex sample preparations and assay running times. Rapid evaporative ionisation mass spectrometry (REIMS) can circumvent these issues without sacrificing a loss in the quality of results.

OBJECTIVES

To demonstrate that REIMS can be used as a fast profiling technique capable of achieving accurate species identification without the need for any sample preparation. Additionally, we wanted to demonstrate that other aspects of fish fraud other than speciation are detectable using REIMS.

METHODS

478 samples of five different white fish species were subjected to REIMS analysis using an electrosurgical knife. Each sample was cut 8-12 times with each one lasting 3-5 s and chemometric models were generated based on the mass range m/z 600-950 of each sample.

RESULTS

The identification of 99 validation samples provided a 98.99% correct classification in which species identification was obtained near-instantaneously (≈ 2 s) unlike any other form of food fraud analysis. Significant time comparisons between REIMS and polymerase chain reaction (PCR) were observed when analysing 6 mislabelled samples demonstrating how REIMS can be used as a complimentary technique to detect fish fraud. Additionally, we have demonstrated that the catch method of fish products is capable of detection using REIMS, a concept never previously reported.

CONCLUSIONS

REIMS has been proven to be an innovative technique to help aid the detection of fish fraud and has the potential to be utilised by fisheries to conduct their own quality control (QC) checks for fast accurate results.