Probability and kinetics of rupture and electrofusion in giant unilamellar vesicles under various frequencies of direct current pulses.

Irreversible electroporation induces permanent permeabilization of lipid membranes of vesicles, resulting in vesicle rupture upon the application of a pulsed electric field. Electrofusion is a phenomenon wherein neighboring vesicles can be induced to fuse by exposing them to a pulsed electric field. We focus how the frequency of direct current (DC) pulses of electric field impacts rupture and electrofusion in cell-sized giant unilamellar vesicles (GUVs) prepared in a physiological buffer. The average time, probability, and kinetics of rupture and electrofusion in GUVs have been explored at frequency 500, 800, 1050, and 1250 Hz. The average time of rupture of many 'single GUVs' decreases with the increase in frequency, whereas electrofusion shows the opposite trend. At 500 Hz, the rupture probability stands at 0.45 ± 0.02, while the electrofusion probability is 0.71 ± 0.01. However, at 1250 Hz, the rupture probability increases to 0.69 ± 0.03, whereas the electrofusion probability decreases to 0.46 ± 0.03. Furthermore, when considering kinetics, at 500 Hz, the rate constant of rupture is (0.8 ± 0.1)×10-2 s-1, and the rate constant of fusion is (2.4 ± 0.1)×10-2 s-1. In contrast, at 1250 Hz, the rate constant of rupture is (2.3 ± 0.8)×10-2 s-1, and the rate constant of electrofusion is (1.0 ± 0.1)×10-2 s-1. These results are discussed by considering the electrical model of the lipid bilayer and the energy barrier of a prepore.

Malignancy pattern analysis of breast ultrasound images using clinical features and a graph convolutional network.

Objective: Early diagnosis of breast cancer can lead to effective treatment, possibly increase long-term survival rates, and improve quality of life. The objective of this study is to present an automated analysis and classification system for breast cancer using clinical markers such as tumor shape, orientation, margin, and surrounding tissue. The novelty and uniqueness of the study lie in the approach of considering medical features based on the diagnosis of radiologists. Methods: Using clinical markers, a graph is generated where each feature is represented by a node, and the connection between them is represented by an edge which is derived through Pearson's correlation method. A graph convolutional network (GCN) model is proposed to classify breast tumors into benign and malignant, using the graph data. Several statistical tests are performed to assess the importance of the proposed features. The performance of the proposed GCN model is improved by experimenting with different layer configurations and hyper-parameter settings. Results: Results show that the proposed model has a 98.73% test accuracy. The performance of the model is compared with a graph attention network, a one-dimensional convolutional neural network, and five transfer learning models, ten machine learning models, and three ensemble learning models. The performance of the model was further assessed with three supplementary breast cancer ultrasound image datasets, where the accuracies are 91.03%, 94.37%, and 89.62% for Dataset A, Dataset B, and Dataset C (combining Dataset A and Dataset B) respectively. Overfitting issues are assessed through k-fold cross-validation. Conclusion: Several variants are utilized to present a more rigorous and fair evaluation of our work, especially the importance of extracting clinically relevant features. Moreover, a GCN model using graph data can be a promising solution for an automated feature-based breast image classification system.

Deletion of Sigmar1 leads to increased arterial stiffness and altered mitochondrial respiration resulting in vascular dysfunction.

Sigmar1 is a ubiquitously expressed, multifunctional protein known for its cardioprotective roles in cardiovascular diseases. While accumulating evidence indicate a critical role of Sigmar1 in cardiac biology, its physiological function in the vasculature remains unknown. In this study, we characterized the expression of Sigmar1 in the vascular wall and assessed its physiological function in the vascular system using global Sigmar1 knockout (Sigmar1-/-) mice. We determined the expression of Sigmar1 in the vascular tissue using immunostaining and biochemical experiments in both human and mouse blood vessels. Deletion of Sigmar1 globally in mice (Sigmar1-/-) led to blood vessel wall reorganizations characterized by nuclei disarray of vascular smooth muscle cells, altered organizations of elastic lamina, and higher collagen fibers deposition in and around the arteries compared to wildtype littermate controls (Wt). Vascular function was assessed in mice using non-invasive time-transit method of aortic stiffness measurement and flow-mediated dilation (FMD) of the left femoral artery. Sigmar1-/- mice showed a notable increase in arterial stiffness in the abdominal aorta and failed to increase the vessel diameter in response to reactive-hyperemia compared to Wt. This was consistent with reduced plasma and tissue nitric-oxide bioavailability (NOx) and decreased phosphorylation of endothelial nitric oxide synthase (eNOS) in the aorta of Sigmar1-/- mice. Ultrastructural analysis by transmission electron microscopy (TEM) of aorta sections showed accumulation of elongated shaped mitochondria in both vascular smooth muscle and endothelial cells of Sigmar1-/- mice. In accordance, decreased mitochondrial respirometry parameters were found in ex-vivo aortic rings from Sigmar1 deficient mice compared to Wt controls. These data indicate a potential role of Sigmar1 in maintaining vascular homeostasis.

Application of batter coating for modulating oil, texture and structure of fried foods: A review.

Food surface modulation by batter coating is a promising approach to reduce the presence of oil in fried products. This review critically discussed the functionalities, mechanism of actions, rheology, ingredients of formulation, mathematical modeling of the process, cooking method, safety and regulatory aspects, physicochemical, thermal-microstructural characterization of batter coatings, and future research directions. Enormous list of ingredients could be used in preparation of oil-reducing viscoelastic batter coating that includes mostly flours, hydrocolloids, and starches. Bioactive compounds, enzymes, minerals, herbal extracts, baking agents, sugar alcohols, etc. could be incorporated in batter formulation to affect the taste and texture of coated products. Overall mass-transfer process of batter-coated fried foods could be characterized by several mathematical models (Fick, Newton, Page, Henderson & Pabis, modified Page, Arrhenius). Surface and internal microstructural characterization techniques, thermal probing, physicochemical characterization techniques and artificial intelligence can characterize different functionalities of batter coatings including oil reduction and textural evolution.

Evaluation of In Vitro Antimicrobial, Cytotoxic, Thrombolytic, and Antiarthritic Property of Different Parts of Bari Orchid.

Many different herbal extracts have historically been utilized to treat microbe-induced infections, injuries, cancer, thrombosis, and arthritis. The purpose of this study was to determine the antibacterial, cytotoxic, in vitro thrombolytic, and in vitro antiarthritic properties of ethanolic extracts of stem and seed of Bari orchid 1 (BO) plant. This orchid plant was developed by the Bangladesh Agriculture Research Institute (BARI) in Gazipur. Fourteen microbes were employed in the antimicrobial investigation, and samples of orchids were compared to ciprofloxacin as a reference. The BO/seed extract was found to possess more antibacterial activity. The lethality test of brine shrimps was used to assess the LC50 values. The BO/stem extract exhibited a higher cytotoxicity potential, in comparison to the BO/seed extract. Two concentrations (1000 and 100 ppm) and two incubation times (24 hours and 1.5 hours) were used to assess the thrombolytic activity of the extracts. Regarding the thrombolytic effect, the BO/stem extract has demonstrated greater promise. Furthermore, the herbal extract's antiarthritic activity was investigated at four different concentrations, and the results were evaluated in comparison with those of diclofenac sodium. When comparing BO/stem extract to other extracts, the greatest values for protein denaturation were obtained.

Design, synthesis, and bioevaluation of novel unsaturated cyanoacetamide derivatives: In vitro and in silico exploration.

In this study, we synthesized novel α,ß-unsaturated 2-cyanoacetamide derivatives (1-5) using microwave-assisted Knoevenagel condensation. Characterization of these compounds was carried out using FTIR and 1H NMR spectroscopy. We then evaluated their in vitro antibacterial activity against both gram-positive and gram-negative pathogenic bacteria. Additionally, we employed in silico methods, including ADMET prediction and density functional theory (DFT) calculations of molecular orbital properties, to investigate these cyanoacetamide derivatives (1-5). Molecular docking was used to assess the binding interactions of these derivatives (1-5) with seven target proteins (5MM8, 4NZZ, 7FEQ, 5NIJ, ITM2, 6SE1, and 5GVZ) and compared them to the reference standard tyrphostin AG99. Notably, derivative 5 exhibited the most favorable binding affinity, with a binding energy of -7.7 kcal mol-1 when interacting with the staphylococcus aureus (PDB:5MM8), while also meeting all drug-likeness criteria. Additionally, molecular dynamics simulations were carried out to evaluate the stability of the interaction between the protein and ligand, utilizing parameters such as Root-Mean-Square Deviation (RMSD), Root-Mean-Square Fluctuation (RMSF), Radius of Gyration (Rg), and Principal Component Analysis (PCA). A 50 nanosecond molecular dynamics (MD) simulation was performed to investigate stability further, incorporating RMSD and RMSF analyses on compound 5 within the active binding site of the modeled protein across different temperatures (300, 305, 310, and 320 K). Among these temperatures, compound 5 exhibited an RMSD value ranging from approximately 0.2 to 0.3 nm at 310 K (body temperature) with the 5MM8 target, which differed from the other temperature conditions. The in silico results suggest that compound 5 maintained significant conformational stability throughout the 50 ns simulation period. It is consistent with its low docking energy and in vitro findings concerning α,ß-unsaturated cyanoacetamides. Key insights from this study include:•The creation of innovative α,ß-unsaturated 2-cyanoacetamide derivatives (1-5) employing cost-effective, licensed, versatile, and efficient software for both in silico and in vitro assessment of antibacterial activity.•Utilization of FTIR and NMR techniques for characterizing compounds 1-5.

Joint transformer architecture in brain 3D MRI classification: its application in Alzheimer's disease classification.

Alzheimer's disease (AD), a neurodegenerative disease that mostly affects the elderly, slowly impairs memory, cognition, and daily tasks. AD has long been one of the most debilitating chronic neurological disorders, affecting mostly people over 65. In this study, we investigated the use of Vision Transformer (ViT) for Magnetic Resonance Image processing in the context of AD diagnosis. ViT was utilized to extract features from MRIs, map them to a feature sequence, perform sequence modeling to maintain interdependencies, and classify features using a time series transformer. The proposed model was evaluated using ADNI T1-weighted MRIs for binary and multiclass classification. Two data collections, Complete 1Yr 1.5T and Complete 3Yr 3T, from the ADNI database were used for training and testing. A random split approach was used, allocating 60% for training and 20% for testing and validation, resulting in sample sizes of (211, 70, 70) and (1378, 458, 458), respectively. The performance of our proposed model was compared to various deep learning models, including CNN with BiL-STM and ViT with Bi-LSTM. The suggested technique diagnoses AD with high accuracy (99.048% for binary and 99.014% for multiclass classification), precision, recall, and F-score. Our proposed method offers researchers an approach to more efficient early clinical diagnosis and interventions.

Phage predation, disease severity, and pathogen genetic diversity in cholera patients.

Despite an increasingly detailed picture of the molecular mechanisms of bacteriophage (phage)-bacterial interactions, we lack an understanding of how these interactions evolve and impact disease within patients. In this work, we report a year-long, nationwide study of diarrheal disease patients in Bangladesh. Among cholera patients, we quantified Vibrio cholerae (prey) and its virulent phages (predators) using metagenomics and quantitative polymerase chain reaction while accounting for antibiotic exposure using quantitative mass spectrometry. Virulent phage (ICP1) and antibiotics suppressed V. cholerae to varying degrees and were inversely associated with severe dehydration depending on resistance mechanisms. In the absence of antiphage defenses, predation was "effective," with a high predator:prey ratio that correlated with increased genetic diversity among the prey. In the presence of antiphage defenses, predation was "ineffective," with a lower predator:prey ratio that correlated with increased genetic diversity among the predators. Phage-bacteria coevolution within patients should therefore be considered in the deployment of phage-based therapies and diagnostics.

Opportunistic sampling of yellow canary (Crithagra flaviventris) has revealed a high genetic diversity of detected parvoviral sequences.

Parvoviruses are known to be significant viral pathogens that infect a wide range of species globally. However, little is known about the parvoviruses circulating in Australian birds, including yellow canaries. Here, we present four parvoviral sequences including three novel parvoviruses detected from 10 yellow canaries (Crithagra flaviventris), named canary chaphamaparvovirus 1 and -2 (CaChPV1 and CaChPV2), canary dependoparvovirus 1 and -2 (CaDePV1 and CaDePV2). The whole genome sequences of CaChPV1, CaChPV2, CaDePV1, and CaDePV2 showed the highest identity with other parvoviruses at 76.4%, 75.9%, 84.0%, and 59.1%, respectively. Phylogenetic analysis demonstrated that CaChPV1 and CaChPV2 were clustered within the genus Chaphamaparvovirus. Meanwhile, CaDePV1 and CaDePV2 fall within the genus Dependoparvovirus and have the closest evolutionary relationship to the bird-associated dependoparvoviruses. Overall, this study enriched our understanding of the genetic diversity among avian parvoviruses within the Parvoviridae family.

Data Management in Multicountry Consortium Studies: The Enterics For Global Health (EFGH) Shigella Surveillance Study Example.

Background: Rigorous data management systems and planning are essential to successful research projects, especially for large, multicountry consortium studies involving partnerships across multiple institutions. Here we describe the development and implementation of data management systems and procedures for the Enterics For Global Health (EFGH) Shigella surveillance study-a 7-country diarrhea surveillance study that will conduct facility-based surveillance concurrent with population-based enumeration and a health care utilization survey to estimate the incidence of Shigella--associated diarrhea in children 6 to 35 months old. Methods: The goals of EFGH data management are to utilize the knowledge and experience of consortium members to collect high-quality data and ensure equity in access and decision-making. During the planning phase before study initiation, a working group of representatives from each EFGH country site, the coordination team, and other partners met regularly to develop the data management systems for the study. Results: This resulted in the Data Management Plan, which included selecting REDCap and SurveyCTO as the primary database systems. Consequently, we laid out procedures for data processing and storage, study monitoring and reporting, data quality control and assurance activities, and data access. The data management system and associated real-time visualizations allow for rapid data cleaning activities and progress monitoring and will enable quicker time to analysis. Conclusions: Experiences from this study will contribute toward enriching the sparse landscape of data management methods publications and serve as a case study for future studies seeking to collect and manage data consistently and rigorously while maintaining equitable access to and control of data.

Exploring Natural Immune Responses to Shigella Exposure Using Multiplex Bead Assays on Dried Blood Spots in High-Burden Countries: Protocol From a Multisite Diarrhea Surveillance Study.

Background: Molecular diagnostics on human fecal samples have identified a larger burden of shigellosis than previously appreciated by culture. Evidence of fold changes in immunoglobulin G (IgG) to conserved and type-specific Shigella antigens could be used to validate the molecular assignment of type-specific Shigella as the etiology of acute diarrhea and support polymerase chain reaction (PCR)-based microbiologic end points for vaccine trials. Methods: We will test dried blood spots collected at enrollment and 4 weeks later using bead-based immunoassays for IgG to invasion plasmid antigen B and type-specific lipopolysaccharide O-antigen for Shigella flexneri 1b, 2a, 3a, and 6 and Shigella sonnei in Shigella-positive cases and age-, site-, and season-matched test-negative controls from all sites in the Enterics for Global Health (EFGH) Shigella surveillance study. Fold antibody responses will be compared between culture-positive, culture-negative but PCR-attributable, and PCR-positive but not attributable cases and test-negative controls. Age- and site-specific seroprevalence distributions will be identified, and the association between baseline antibodies and Shigella attribution will be estimated. Conclusions: The integration of these assays into the EFGH study will help support PCR-based attribution of acute diarrhea to type-specific Shigella, describe the baseline seroprevalence of conserved and type-specific Shigella antibodies, and support correlates of protection for immunity to Shigella diarrhea. These insights can help support the development and evaluation of Shigella vaccine candidates.

Shigella Detection and Molecular Serotyping With a Customized TaqMan Array Card in the Enterics for Global Health (EFGH): Shigella Surveillance Study.

Background: Quantitative polymerase chain reaction (qPCR) targeting ipaH has been proven to be highly efficient in detecting Shigella in clinical samples compared to culture-based methods, which underestimate Shigella burden by 2- to 3-fold. qPCR assays have also been developed for Shigella speciation and serotyping, which is critical for both vaccine development and evaluation. Methods: The Enterics for Global Health (EFGH) Shigella surveillance study will utilize a customized real-time PCR-based TaqMan Array Card (TAC) interrogating 82 targets, for the detection and differentiation of Shigella spp, Shigella sonnei, Shigella flexneri serotypes, other diarrhea-associated enteropathogens, and antimicrobial resistance (AMR) genes. Total nucleic acid will be extracted from rectal swabs or stool samples, and assayed on TAC. Quantitative analysis will be performed to determine the likely attribution of Shigella and other particular etiologies of diarrhea using the quantification cycle cutoffs derived from previous studies. The qPCR results will be compared to conventional culture, serotyping, and phenotypic susceptibility approaches in EFGH. Conclusions: TAC enables simultaneous detection of diarrheal etiologies, the principal pathogen subtypes, and AMR genes. The high sensitivity of the assay enables more accurate estimation of Shigella-attributed disease burden, which is critical to informing policy and in the design of future clinical trials.

Interactions between integrin α9ß1 and VCAM-1 promote neutrophil hyperactivation and mediate poststroke DVT.

ABSTRACT: Venous thromboembolic events are significant contributors to morbidity and mortality in patients with stroke. Neutrophils are among the first cells in the blood to respond to stroke and are known to promote deep vein thrombosis (DVT). Integrin α9 is a transmembrane glycoprotein highly expressed on neutrophils and stabilizes neutrophil adhesion to activated endothelium via vascular cell adhesion molecule 1 (VCAM-1). Nevertheless, the causative role of neutrophil integrin α9 in poststroke DVT remains unknown. Here, we found higher neutrophil integrin α9 and plasma VCAM-1 levels in humans and mice with stroke. Using mice with embolic stroke, we observed enhanced DVT severity in a novel model of poststroke DVT. Neutrophil-specific integrin α9-deficient mice (α9fl/flMrp8Cre+/-) exhibited a significant reduction in poststroke DVT severity along with decreased neutrophils and citrullinated histone H3 in thrombi. Unbiased transcriptomics indicated that α9/VCAM-1 interactions induced pathways related to neutrophil inflammation, exocytosis, NF-κB signaling, and chemotaxis. Mechanistic studies revealed that integrin α9/VCAM-1 interactions mediate neutrophil adhesion at the venous shear rate, promote neutrophil hyperactivation, increase phosphorylation of extracellular signal-regulated kinase, and induce endothelial cell apoptosis. Using pharmacogenomic profiling, virtual screening, and in vitro assays, we identified macitentan as a potent inhibitor of integrin α9/VCAM-1 interactions and neutrophil adhesion to activated endothelial cells. Macitentan reduced DVT severity in control mice with and without stroke, but not in α9fl/flMrp8Cre+/- mice, suggesting that macitentan improves DVT outcomes by inhibiting neutrophil integrin α9. Collectively, we uncovered a previously unrecognized and critical pathway involving the α9/VCAM-1 axis in neutrophil hyperactivation and DVT.

Thermomechanical transitions of meat-analog based fried foods batter coating.

This study aimed to characterize the thermomechanical transitions of meat-analog (MA) based coated fried foods. Wheat and rice flour-based batters were used to coat the MA and fried at 180 °C in canola oil for 2, 4 and 6 min. Glass-transition-temperature (Tg) of the coatings were assessed by differential scanning calorimetry, directly after frying or after post-fry holding. Mechanical texture analyzer and X-ray microtomography were employed to assess textural attributes and internal microstructure, respectively. Batter-formulation substantially impacted the Tg of fried foods coating i.e., crust. Tg of fried foods crust were ranged between -20 °C to -24 °C. Tg was positively correlated with frying time and internal microporosity (%), whereas negatively correlated with moisture content. Internal microstructure greatly influenced the textural attributes (hardness, brittleness, crispiness). Post-fry textural stability considerably impacted by Tg. Negative Tg value explains post-fry textural changes (hard-to-soft, brittle-to-ductile, crispy-to-soggy) of MA-based coated products at room-temperature (25 °C) and under IR-heating (65 °C).

Microbiological Methods Used in the Enterics for Global Health Shigella Surveillance Study.

Background: Shigella is a major cause of diarrhea in young children worldwide. Multiple vaccines targeting Shigella are in development, and phase 3 clinical trials are imminent to determine efficacy against shigellosis. Methods: The Enterics for Global Health (EFGH) Shigella surveillance study is designed to determine the incidence of medically attended shigellosis in 6- to 35-month-old children in 7 resource-limited settings. Here, we describe the microbiological methods used to isolate and identify Shigella. We developed a standardized laboratory protocol for isolation and identification of Shigella by culture. This protocol was implemented across all 7 sites, ensuring consistency and comparability of results. Secondary objectives of the study are to determine the antibiotic resistance profiles of Shigella, compare isolation of Shigella from rectal swabs versus whole stool, and compare isolation of Shigella following transport of rectal swabs in Cary-Blair versus a modified buffered glycerol saline transport medium. Conclusions: Data generated from EFGH using culture methods described herein can potentially be used for microbiological endpoints in future phase 3 clinical trials to evaluate vaccines against shigellosis and for other clinical and public health studies focused on these organisms.

Evaluation of Fecal Inflammatory Biomarkers to Identify Bacterial Diarrhea Episodes: Systematic Review and Protocol for the Enterics for Global Health Shigella Surveillance Study.

Background: The measurement of fecal inflammatory biomarkers among individuals presenting to care with diarrhea could improve the identification of bacterial diarrheal episodes that would benefit from antibiotic therapy. We reviewed prior literature in this area and describe our proposed methods to evaluate 4 biomarkers in the Enterics for Global Health (EFGH) Shigella surveillance study. Methods: We systematically reviewed studies since 1970 from PubMed and Embase that assessed the diagnostic characteristics of inflammatory biomarkers to identify bacterial diarrhea episodes. We extracted sensitivity and specificity and summarized the evidence by biomarker and diarrhea etiology. In EFGH, we propose using commercial enzyme-linked immunosorbent assays to test for myeloperoxidase, calprotectin, lipocalin-2, and hemoglobin in stored whole stool samples collected within 24 hours of enrollment from participants in the Bangladesh, Kenya, Malawi, Pakistan, Peru, and The Gambia sites. We will develop clinical prediction scores that incorporate the inflammatory biomarkers and evaluate their ability to identify Shigella and other bacterial etiologies of diarrhea as determined by quantitative polymerase chain reaction (qPCR). Results: Forty-nine studies that assessed fecal leukocytes (n = 39), red blood cells (n = 26), lactoferrin (n = 13), calprotectin (n = 8), and myeloperoxidase (n = 1) were included in the systematic review. Sensitivities were high for identifying Shigella, moderate for identifying any bacteria, and comparable across biomarkers. Specificities varied depending on the outcomes assessed. Prior studies were generally small, identified red and white blood cells by microscopy, and used insensitive gold standard diagnostics, such as conventional bacteriological culture for pathogen detection. Conclusions: Our evaluation of inflammatory biomarkers to distinguish diarrhea etiologies as determined by qPCR will provide an important addition to the prior literature, which was likely biased by the limited sensitivity of the gold standard diagnostics used. We will determine whether point-of-care biomarker tests could be a viable strategy to inform treatment decision making and increase appropriate targeting of antibiotic treatment to bacterial diarrhea episodes.

Population Enumeration and Household Utilization Survey Methods in the Enterics for Global Health (EFGH): Shigella Surveillance Study.

Background: Accurate estimation of diarrhea incidence from facility-based surveillance requires estimating the population at risk and accounting for case patients who do not seek care. The Enterics for Global Health (EFGH) Shigella surveillance study will characterize population denominators and healthcare-seeking behavior proportions to calculate incidence rates of Shigella diarrhea in children aged 6-35 months across 7 sites in Africa, Asia, and Latin America. Methods: The Enterics for Global Health (EFGH) Shigella surveillance study will use a hybrid surveillance design, supplementing facility-based surveillance with population-based surveys to estimate population size and the proportion of children with diarrhea brought for care at EFGH health facilities. Continuous data collection over a 24 month period captures seasonality and ensures representative sampling of the population at risk during the period of facility-based enrollments. Study catchment areas are broken into randomized clusters, each sized to be feasibly enumerated by individual field teams. Conclusions: The methods presented herein aim to minimize the challenges associated with hybrid surveillance, such as poor parity between survey area coverage and facility coverage, population fluctuations, seasonal variability, and adjustments to care-seeking behavior.

The Enterics for Global Health (EFGH) Shigella Surveillance Study in Bangladesh.

Background: Shigella is an important cause of diarrhea in Bangladeshi children <5 years of age, with an incidence rate of 4.6 per 100 person-years. However, the report was more than a decade old, and data on Shigella consequences are similarly outdated and heterogeneously collected. Methods: Facility-based disease surveillance is planned to be carried out under the Enterics for Global Health (EFGH) Shigella Surveillance Study consortium for 2 years with aims to optimize and standardize laboratory techniques and healthcare utilization and coverage survey, clinical and anthropometric data collection, safety monitoring and responsiveness, and other related activities. The EFGH is a cohesive network of multidisciplinary experts, capable of operating in concert to conduct the study to generate data that will pave the way for potential Shigella vaccine trials in settings with high disease burden. The study will be conducted within 7 country sites in Asia, Africa, and Latin America. Conclusions: We outline the features of the Bangladesh site as part of this multisite surveillance network to determine an updated incidence rate and document the consequences of Shigella diarrhea in children aged 6-35 months, which will help inform policymakers and to implement the future vaccine trials.

Correction to: Osmotic and convective hot air drying of sweet gourd.

[This corrects the article DOI: 10.1007/s10068-022-01193-x.].

Improving the Automated Diagnosis of Breast Cancer with Mesh Reconstruction of Ultrasound Images Incorporating 3D Mesh Features and a Graph Attention Network.

This study proposes a novel approach for breast tumor classification from ultrasound images into benign and malignant by converting the region of interest (ROI) of a 2D ultrasound image into a 3D representation using the point-e system, allowing for in-depth analysis of underlying characteristics. Instead of relying solely on 2D imaging features, this method extracts 3D mesh features that describe tumor patterns more precisely. Ten informative and medically relevant mesh features are extracted and assessed with two feature selection techniques. Additionally, a feature pattern analysis has been conducted to determine the feature's significance. A feature table with dimensions of 445 × 12 is generated and a graph is constructed, considering the rows as nodes and the relationships among the nodes as edges. The Spearman correlation coefficient method is employed to identify edges between the strongly connected nodes (with a correlation score greater than or equal to 0.7), resulting in a graph containing 56,054 edges and 445 nodes. A graph attention network (GAT) is proposed for the classification task and the model is optimized with an ablation study, resulting in the highest accuracy of 99.34%. The performance of the proposed model is compared with ten machine learning (ML) models and one-dimensional convolutional neural network where the test accuracy of these models ranges from 73 to 91%. Our novel 3D mesh-based approach, coupled with the GAT, yields promising performance for breast tumor classification, outperforming traditional models, and has the potential to reduce time and effort of radiologists providing a reliable diagnostic system.