Standard Threshold Research Articles

Integrating spatial-temporal features into prediction tasks: A novel method for identifying the potential water pollution area in large river basins

Forecasting potential water pollution areas (PWPA) is essential for effective watershed management. However, there remains a limited understanding of the spatial-temporal features that influence water quality (WQ), and advanced technical methods for WQ forecasting. This study developed an integrated framework utilizing spatial-temporal graph convolution networks (STGCN) to enhance comprehension of the spatial-temporal features influencing WQ and to develop a practical module for integrating features into the WQ prediction. The Pearson correlation method and seasonal decomposition analysis described the WQ features. Subsequently, the spatial-temporal distribution of PWPA was assessed using both the comprehensive pollution index method and Cressman space interpolation technique. Data from 403 monitoring stations was collected from the Yangtze River basin (YZR), encompassing pollutants such as COD, TP and NH₄⁺-N. The finding revealed that maximum concentrations of COD (36.4 mg/L), TP (4.078 mg/L) and NH₄⁺-N (13.58 mg/L) exceeded the standard thresholds necessitating early warnings. A significant correlation among pollutants was observed with coefficients ranging from 0.356 to 0.475 (P < 0.001), indicating their potential utility in predicting PWPA. Seasonality components exhibited strong correlations with the original WQ (correlation coefficients ranging from 0.62 to 0.89), followed by residuals (from 0.37 to 0.61) and trend components (from 0.25 to 0.53). The geographic layout of WQ monitoring stations along river lines resembled a graph network structure, suggesting that watershed WQ prediction can be classified as a spatial-temporal prediction task. The STGCN model achieved R2 values ranging from 0.607 to 0.844 for each pollutant on the test datasets, surpassing traditional models such as RNN, LSTM, and GRU in predictive accuracy. PWPA occurrences were predominantly identified in the southwestern regions as well as within the middle and lower reaches of the YZR. These results validated that the developed framework is capable of forecasting PWPA in large-scale watersheds while supporting effective watershed management.

Leveraging local wildlife surveys for robust occupancy trend estimation

Natural resource agencies are frequently tasked with monitoring populations of at-risk species to ensure management activities do not negatively affect the viability of wildlife populations. Typically, these monitoring efforts evaluate trends in a population’s abundance, occupancy, or geographic distribution. Often, surveys provide local information, but results are generally not incorporated into broad-scale monitoring efforts that focus on range-wide population changes due to their variable nature in both spatial extent and effort. We investigated whether aggregating these local (hereafter “variable”) surveys can generate enough statistical power to estimate broad-scale population trends using simulations of declining populations of fishers (Pekaniapennati) over a 10-year time horizon. Our simulations included three population sizes which we refer to as abundant, common, and rare (N0 = 700, 350, and 100 individuals, respectively) with each declining at a rapid and moderate pace (λ = 0.933, and 0.977, respectively). For each population, we simulated variable surveys using an occupancy framework to subsample the population with parameters that mimic combining multiple independent monitoring efforts which vary annually in location, and effort. Regardless of spatial consistency of annual sampling, there was minimal variation in statistical power under both high and low detection probability simulations. However, when sampling effort varied each year, statistical power was lower for most populations and sampling scenarios when compared to consistent sampling effort unless some baseline level of sampling effort was reliably achieved in all years. In many cases, adding low-level consistent baseline sampling to variable surveys resulted in statistical power close to that of consistent sampling efforts. Our results suggest statistical power is driven by annual consistency in the proportion of landscape sampled rather than spatial consistency in sampling locations. This result indicates that current variable surveys could be leveraged and combined to detect population declines for at-risk species at broad-scales if a baseline proportion of landscape is robustly sampled. The level of baseline sampling is highly dependent on population size and magnitudes of population change. In simulations with a common or abundant population experiencing a rapid decline, a baseline survey effort of at least 5% of the landscape in combination with variable surveys resulted in statistical power consistently above the standard threshold of 0.80 for occupancy monitoring. Leveraging existing local efforts to achieve high detection probability and baseline sampling would reduce financial and logistical burdens of broad-scale wildlife monitoring efforts.

ViViEchoformer: Deep Video Regressor Predicting Ejection Fraction

AbstractHeart disease is the leading cause of death worldwide, and cardiac function as measured by ejection fraction (EF) is an important determinant of outcomes, making accurate measurement a critical parameter in PT evaluation. Echocardiograms are commonly used for measuring EF, but human interpretation has limitations in terms of intra- and inter-observer (or reader) variance. Deep learning (DL) has driven a resurgence in machine learning, leading to advancements in medical applications. We introduce the ViViEchoformer DL approach, which uses a video vision transformer to directly regress the left ventricular function (LVEF) from echocardiogram videos. The study used a dataset of 10,030 apical-4-chamber echocardiography videos from patients at Stanford University Hospital. The model accurately captures spatial information and preserves inter-frame relationships by extracting spatiotemporal tokens from video input, allowing for accurate, fully automatic EF predictions that aid human assessment and analysis. The ViViEchoformer’s prediction of ejection fraction has a mean absolute error of 6.14%, a root mean squared error of 8.4%, a mean squared log error of 0.04, and an $${R}^{2}$$ R 2 of 0.55. ViViEchoformer predicted heart failure with reduced ejection fraction (HFrEF) with an area under the curve of 0.83 and a classification accuracy of 87 using a standard threshold of less than 50% ejection fraction. Our video-based method provides precise left ventricular function quantification, offering a reliable alternative to human evaluation and establishing a fundamental basis for echocardiogram interpretation.

Exploring Bioinformatics-Driven Approaches for Enhanced Diagnosis of Chlamydia trachomatis Infections: Analysis of Target Proteins

Chlamydia trachomatis, a major cause of sexually transmitted infection, poses a range of symptoms including genital discharge, pain during urination, and abdominal pains in women, and can lead to serious health complications such as pelvic inflammatory diseases, infertility, and ectopic pregnancy if left untreated. The need for rapid and accurate detection is imperative so prompt treatment and control of the disease can be achieved. This study conducted an immunoinformatic analysis of proteins of Chlamydia trachomatis (incA, hctA, ompA, omcB, rpoB, and HSP60) for the development of a lateral flow assay-based diagnostic test. Detailed in silico evaluation of selected proteins from publicly available genomic databases was conducted to evaluate their suitability as targets for lateral flow assay-based detection. The series of tests included antigenicity, toxicity, solubility, physicochemical characteristics and molecular docking of the derived constructs, and protein sequence. Chimeric construct was derived from the prediction of linear B cell epitopes, helper T cell major histocompatibility complex II binding epitopes, and IL4 and IL10 inducers using bioinformatic tools at standard thresholds. With a Ramachandra’s score of 95.4% and Z-score of -5.1, results indicate that the construct efficacy is high in potential to provide extreme specificity and sensitivity for the detection of Chlamydia trachomatis in clinical samples as compared to traditional culture-based methods using nucleic acid amplification, hereby providing a quicker and more accurate diagnostic tool for Chlamydia trachomatis infection. Findings offer valuable data for the development of a rapid and reliable diagnostic point-of-care test kit for Chlamydia trachomatis that allows for drastic reduction in clinical wait time and treatment.

Exploring Bioinformatics-Driven Approaches for Enhanced Diagnosis of Chlamydia trachomatis Infections: Analysis of Target Proteins

Chlamydia trachomatis, a major cause of sexually transmitted infection, poses a range of symptoms including genital discharge, pain during urination, and abdominal pains in women, and can lead to serious health complications such as pelvic inflammatory diseases, infertility, and ectopic pregnancy if left untreated. The need for rapid and accurate detection is imperative so prompt treatment and control of the disease can be achieved. This study conducted an immunoinformatic analysis of proteins of Chlamydia trachomatis (incA, hctA, ompA, omcB, rpoB, and HSP60) for the development of a lateral flow assay-based diagnostic test. Detailed in silico evaluation of selected proteins from publicly available genomic databases was conducted to evaluate their suitability as targets for lateral flow assay-based detection. The series of tests included antigenicity, toxicity, solubility, physicochemical characteristics and molecular docking of the derived constructs, and protein sequence. Chimeric construct was derived from the prediction of linear B cell epitopes, helper T cell major histocompatibility complex II binding epitopes, and IL4 and IL10 inducers using bioinformatic tools at standard thresholds. With a Ramachandra’s score of 95.4% and Z-score of -5.1, results indicate that the construct efficacy is high in potential to provide extreme specificity and sensitivity for the detection of Chlamydia trachomatis in clinical samples as compared to traditional culture-based methods using nucleic acid amplification, hereby providing a quicker and more accurate diagnostic tool for Chlamydia trachomatis infection. Findings offer valuable data for the development of a rapid and reliable diagnostic point-of-care test kit for Chlamydia trachomatis that allows for drastic reduction in clinical wait time and treatment.

Combined [18F]-FDG PET-MR Imaging: A promising tool for diagnostics of small bowel Crohn's disease.

Introduction Diagnostics of small bowel Crohn's disease (CD) can be difficult. Combined positron emission tomography-magnetic resonance enterography (PET-MRE) can be used to evaluate intestinal metabolism, but clinical use has been limited due to accessibility, costs, absence of standardized methods and diagnostic thresholds. Our aim was to show that combined PET-MRE can be used to diagnose active small bowel CD. Methods We performed a fusion PET-MRE-scan with [18F]-FDG-tracer to 30 patients with suspected small bowel CD in colonoscopy. Standardized uptake values (SUV) were measured from small bowel. The diagnosis was confirmed with small bowel capsule endoscopy. Clinicians chose appropriate medication to each patient blinded from SUV-results. Endoscopic, laboratory and MRE-findings were investigated in relation to SUV. Results Fusion PET-MRE outperformed MRE in diagnostic accuracy. Patients diagnosed with CD (N=24) had higher SUV than patients not diagnosed with CD (N=6) (3.34 vs. 1.84, p=0.022). A diagnostic cut-off at SUV at 2.5. could be used (AUROC=0.81). A higher SUV predicts need for immunosuppressive medication (p=0.0026) and biologics (p=0.0005). SUV correlates positively with SES-CD-score (Simple Endoscopic Score for Crohn's Disease), fecal calprotectin and CRP and negatively with Hb and serum albumin. Conclusion In future, [18F]-FDG PET-MRE can be used in diagnostics of small bowel CD as a safe alternative for capsule endoscopy. High SUV can predict a more progressive disease course and need for more advanced therapies.

Automated pericardium segmentation and epicardial adipose tissue quantification from computed tomography images

Background and ObjectiveEpicardial Adipose Tissue (EAT) is regarded as an independent risk factor for cardiovascular disease, and an increase in its volume is closely associated with disorders such as coronary artery atherosclerosis. Traditional manual and semi-automatic methods for EAT segmentation rely on subjective judgment, resulting in uncertainty and unreliability, which limits their application in clinical practice. Therefore, this study aims to develop a fully automatic segmentation and quantification method to improve the accuracy of EAT assessment. MethodsA Boundary-Enhanced Multi-scale U-Net network with a Convolutional Transformer (BMT-UNet) is developed to segment the pericardium. The BMT-UNet comprises Boundary-Enhanced (BE) modules, Multi-Scale (MS) modules, and a Convolutional Transformer (ConvT) module. The MS and BE modules in the encoding part are designed to capture detailed boundary features and accurately delineate the pericardium boundary by combining multi-scale features with morphological operations, leveraging their complementarity. The ConvT module integrates global contextual information, thereby enhancing overall segmentation accuracy and addressing the issue of internal holes in the segmented pericardial images. The volume of EAT is automatically quantified using standard fat thresholds with a range of −190 to −30 HU. ResultsFor a Coronary Computed Tomography Angiography (CCTA) dataset which contained 50 patients, the Dice coefficient and Hausdorff distance for the proposed method of pericardial and EAT segmentation are 98.3% ± 0.2%, 5.7±0.8 mm, and 93.9% ± 1.7%, 2.1 ± 0.3 mm, respectively. The linear regression coefficient between the EAT volume segmented and the actual volume is 0.982, and the Pearson correlation coefficient is 0.99. Bland-Altman analysis further confirmed the high consistency between the automated and manual methods. These results demonstrate a significant improvement over existing methods, particularly in terms of segmentation precision and reliability, which are critical for clinical application. ConclusionsThis work develops an automated method for quantifying EAT in Computed Tomography (CT) images, and the results agreed closely with expert evaluations. Code is available at: https://github.com/wy-9903/BMT-UNet.

Enhancing Hemoglobin Levels and Macro-Micronutrient Intake Through the Well-Being Workshop of First 8000 Days of Life

Introduction: Chronic malnutrition is a major source of concern in the malnutrition community. Addressing nutritional needs that are inappropriate for pre-conception adolescents in the first 8000 days of life is a trigger for anemia and stunting in children later in life. The authors developed The Well-Being Workshop of First 8000 Days of Life. This study compared the hemoglobin levels and macro-micro nutrient intake of female adolescents before and after the well-being workshop of first 8000 days of life and their assistance. Methods: An experimental design, within group method, with an equivalent time series design, and 3 times interventions were carried out. A hundred female adolescents aged 14-19 years Yogyakarta city were assigned to this study. All respondents underwent a pretest and posttest before and after being given interventions of well-being workshop. On completion of the three times workshop, blood sampling of haemoglobin level and food record were collected analyzed. In total, the data was collected 3 times after each workshop was held. The data generated was processed using a paired t test. Results: The average hemoglobin level in female adolescents has increased from the first to the fourth examination, with a standard limit value (&gt; 12.0 gr/dL), but the average of macro and micronutrients intake, as assessed using the Nutrisurvey, is below the standard threshold value. A paired T-test revealed a significant difference within the increase in Hb levels on all examinations. The analysis of macronutrients showed that only fiber had a significant difference before and after a series of well-being workshops of first 8000 days of life interventions, i.e. the first and second examinations. Meanwhile the micronutrient analysis, only iron and zinc there were significant differences before and after being given a series of workshops. Conclusions: "The well-being workshops of first 8000 days of life" can be considered in changing the eating behavior of female adolescents to increase hemoglobin levels.

Air-conduction and bone-conduction reference threshold levels-A multicenter studya).

Air-conduction (AC) and bone-conduction (BC) thresholds were measured to evaluate standard reference thresholds and recommend revisions to audiometer standards. AC and BC thresholds were measured from listeners with normal hearing (NH) and sensorineural hearing loss (SNHL) at three sites. NH participants (n = 53) were selected based on age (18-25 years old), normal AC thresholds, tympanometry, otoscopy, and absence of otologic disease. SNHL participants (n = 49) were selected based on AC thresholds, tympanometry, otoscopy, and absence of otologic disease. AC thresholds obtained from NH listeners averaged 3.7 dB hearing level (HL). Air-bone gaps (ABGs) occurred in NH and SNHL listeners above 2000 Hz and in SNHL listeners at 250 Hz. Corrections to standard reference equivalent threshold sound pressure levels are recommended. ABGs in listeners without conductive pathology result from incorrect reference threshold levels for frequencies above 2000 Hz. False ABGs increase with hearing-loss magnitude, probably the result of the effects of ambient and internal noise for low-level BC stimuli. False ABGs place patients at risk for unnecessary medical and surgical intervention. Reference threshold levels should achieve two objectives: (1) AC thresholds from young NH listeners should average 0 dB HL; and (2) ABGs from listeners with normal middle-ear function should average 0 dB.

Mycosis fungoides - differentiation from inflammation and detection of circulating tumor cells with the EuroClonality-NGS assay.

Mycosis fungoides (MF) is a rare malignancy characterized by the presence of circulating tumor cells (CTCs) in a subgroup of patients. Reliably distinguishing MF from inflammatory skin conditions (IF) is a challenging task. This study aimed to evaluate the potential benefits of next-generation sequencing (NGS)-based T-cell receptor (TR) rearrangement repertoire analysis for detecting clonal rearrangements in MF and IF. Skin biopsies and blood samples from 33 MF patients (diagnosed according to WHO-EORTC criteria) and 10 IF patients were analyzed using TRB- and TRG-NGS. 27/33 MF patients were early-stage IA (n=19), IB (n=8), and six had advanced stages (IIB, n=5; IIIA, n=1). Analysis applying the standard abundance thresholds identified at least one clonal rearrangement in the skin DNA of 32/33 MF (97%) and 9/10 IF cases (90%). To enhance specificity, an abundance- and distribution-based approach was applied, considering only rearrangements that significantly stood out from the physiological background as clonal (MF 29/33, IF 1/10), allowing for a highly sensitive (88%) and specific (90%) discrimination between MF and IF. CTCs were detected in 11/24 (46%) early-stage and 3/5 (60%) late-stage MF patients. NGS-based TR repertoire analysis is a highly sensitive and specific method for the differential diagnosis of early-stage MF compared to IF, and for the sensitive molecular detection of CTCs.

Diagnosis of acute myocardial infarction in patients with renal failure using high-sensitivity cardiac troponin T

Abstract Background Diagnosing myocardial infarction (MI) in patients with chronic kidney disease (CKD) is difficult as these patients often have elevated baseline high-sensitivity cardiac troponin T (hs-cTnT) concentrations. Methods Observational U.S. cohort study of emergency department (ED) patients undergoing hs-cTnT measurement. Cases with &amp;gt;1 hs-cTnT increase &amp;gt;99th percentile were adjudicated following the Fourth Universal Definition of MI. Diagnostic performance of baseline and serial 2- and 6-hour hs-cTnT thresholds for ruling-in acute MI was compared between those without and with CKD (eGFR &amp;lt;60 ml/min/1.73m2). Results The study cohort included 1992 patients, amongst whom 501 (25%) had CKD. There were 701 (82%) patients with myocardial injury, 64 (7.5%) with type 1, and 91 (11%) with type 2 MI. In CKD patients with baseline hs-cTnT thresholds of &amp;gt;52, &amp;gt;100, &amp;gt;200 or &amp;gt;300 ng/L, PPVs for acute MI were 37% [95% CI 28-46], 53% (95% CI 39-67), 73% (95% CI 50-89) and 80% (95% CI 44-98), and in those without CKD, 64% (95% CI 50-77), 69% (95% CI 49-85), 59% (95% CI 33-82) and 54% (95% CI 25-81). In CKD patients with a 2-hour hs-cTnT delta of &amp;gt;10, &amp;gt;20 or &amp;gt;30 ng/L, the corresponding PPVs were 65% (95% CI 50-78), 86% (95% CI 68-96) and 88% (95% CI 68-97), and in those without CKD, 65% (95% CI 51-78), 73% (95% CI 57-86) and 75% (95% CI 58-88) (Figure). Conclusion Diagnostic performance of standard baseline and serial 2-hour hs-cTnT thresholds to rule-in MI is suboptimal in patients with CKD. It significantly improves when using higher baseline thresholds and delta values.

Evaluating the connection between mean platelet volume (MPV) and peripheral arterial disease risk: a meta-analysis

Background: Numerous studies have been conducted to evaluate the role of Mean Platelet Volume (MPV) in relation to Peripheral Artery Disease (PAD). However, the results of these studies have been inconsistent regarding the significance of MPV as an indicator for PAD. Objective: This meta-analysis aimed to clarify the role of MPV in PAD by collecting and analyzing data from various studies. The goal was to provide a more definitive assessment of whether MPV levels could serve as a reliable indicator for PAD Methods: We conducted a meta-analysis from July to August 2024, utilizing data from three major databases: Scopus, Embase, and PubMed. We gathered data on MPV levels from studies comparing PAD patients with control groups. The meta-analysis included cumulative effect estimates, with analysis performed using the inverse variance method to synthesize data and evaluate the overall effect of MPV on PAD. Results: Nine studies were included in this meta-analysis, comprising 1,214 PAD cases and 6,568 controls. Our analysis demonstrated that MPV was a significant marker in PAD, with PAD patients having higher MPV levels compared to controls (MD: 0.46; 95%CI: 0.25, 0.66; p Egger: 0.0911; p Heterogeneity &lt;0.0001; p &lt;0.0001). Conclusion: Our findings support that MPV is an important indicator in the context of PAD. Further study is needed to explore the clinical applications of MPV in PAD and to establish standardized thresholds for its use in clinical practice. Keyword: diagnosis, mean platelet volume, peripheral disease, predictor

AI-based algorithm for assessing coronary artery calcium score on contrast-enhanced cardiac computed tomography scans

Abstract Introduction In cardiac computed tomography (CT) examinations, non-contrast scans are often performed in addition to contrast-enhanced scans to quantify the coronary artery calcification (CAC) score. These calcium score scans are associated with additional exposure to ionizing radiation. Purpose We sought to develop a fully automated artificial intelligence (AI)-based algorithm capable of determining CAC score based solely on contrast-enhanced CT scans, eliminating the need for additional non-contrast scans. Methods An automated CAC scoring algorithm on contrast-enhanced CT scans was developed and trained using a dataset of 297 cardiac CT studies. Coronary artery calcifications were manually segmented in contrast-enhanced scans using a threshold of 2 standard deviations above the mean attenuation value of the ascending aorta. On non-contrast scans, CAC was manually assessed using a standard threshold of ≥130 Hounsfield Units. A correction factor for calcium score results assessed on contrast-enhanced scans was determined using linear regression. The algorithm was tested on an independent set of 90 contrast-enhanced CT scans (four manufacturers, eight scanner models). We compared automated CAC scores to manual expert reader reference assessments on non-contrast CT scans. CAC scores were categorized into four risk categories following the Society of Cardiovascular Computed Tomography recommendations: 0, 1-100, 101-300, and &amp;gt;300 Agatston Units. Results In the assessment of 90 CT studies (mean age 61.0±11.4 years, 46.7% males), the AI-model detected CAC in 69 contrast-enhanced scans (76.7%), comparable to the human reader's detection rate of CAC in 71 non-contrast scans (78.9%) (p = 0.63). The CAC score was initially calculated using AI-based segmentation of coronary calcification on contrast-enhanced scans and then the result was multiplied by established linear correction factor of 1.97. There was an excellent correlation between AI-model and manual reference total CAC scores (Pearson’s r = 0.96, 95% CI 0.94–0.97, p &amp;lt; 0.001). The model correctly classified 77 patients (85.6%) into the same CAC risk category as the human reader (Figure 1). Among 19 patients (21.1%) with a CAC score of zero, only 1 patient (5.3%) was reclassified with a non-zero CAC score by the AI-model. Cohen’s kappa value for CAC score risk categorization was 0.80 (p &amp;lt; 0.001), indicating very good agreement (Figure 2). Bland–Altman analysis revealed minimal bias of -9.7 Agatston Unit with 95% limits of agreement ranging from -184.8 to 165.5 Agatston Unit. Conclusions CAC score can be accurately quantified on contrast-enhanced cardiac CT scans using an automated AI-based algorithm. This approach has the potential to eliminate the necessity for an additional non-contrast CT scan, thereby reducing the patient's exposure to ionizing radiation.

Relationship between hearing loss and Glasgow prognostic score in patients with cancer

ObjectiveOxidative stress damages cochlear hair cells in vitro. However, the effect of systemic inflammation on hearing loss remains unclear. Growing evidence suggests that malnutrition influences the development of hearing loss. In this study, we aimed to investigate the influence of the Glasgow prognostic score (GPS), which is calculated based on systemic inflammatory responses and malnutrition, on auditory threshold increases in patients with cancer. MethodsThis single-center retrospective cohort study included patients with cancer who underwent standard pure-tone audiometry (PTA) between November 2014 and May 2023. Patients with complete data in their electronic medical records within 90 days before undergoing standard PTA were included. Multivariate analysis was performed using auditory threshold as the response variable. Covariates, including GPS, were obtained from blood data and physical data before standard PTA. The GPS was classified into three levels based on serum albumin and C-reactive protein levels. ResultsStandard PTA was performed 14,868 times in 5,462 patients. Of these, 742 had cancer and 384 met the inclusion criteria. Multivariate analysis revealed that older age, creatinine clearance <60 mL/min, and high GPS significantly increased the auditory threshold at frequencies of 500–8,000 Hz. A history of platinum drug use and male sex increased the auditory threshold at frequencies >4,000 and >2,000 Hz, respectively. ConclusionThe GPS was independently associated with elevated standard PTA thresholds in patients with cancer. These results suggest an association between malnutrition/chronic inflammation and hearing loss and provide new information for planning clinical research on hearing loss prevention.

Interpreting the Epidemiological Characteristics of HIV-1 in Heterosexually Transmitted Population Based on Molecular Transmission Network in Kunming, Yunnan: A Retrospective Cohort Study.

Heterosexuals have become the most prevalent group of HIV-1 in Kunming, Yunnan Province. Utilizing the principle of genetic similarity between their gene sequences, we built a molecular transmission network by gathering data from earlier molecular epidemiological studies. This allowed us to analyze the epidemiological features of this group and offer fresh concepts and approaches for the prevention and management of HIV-1 epidemics. Cytoscope was used to visualize and characterize the network following the processing of the sample gene sequences by BioEdit and HyPhy. The number of possible links and the size of the clusters were investigated as influencing factors using a zero-inflated Poisson model and a logistic regression model, respectively. A scikit-learn-based prediction model was developed to account for the dynamic changes in the HIV-1 molecular network. Six noteworthy modular clusters with network scores ranging from 4 to 9 were found from 150 clusters using Molecular Complex Detection analysis at a standard genetic distance threshold of 0.01. The size of the number of possible links and the network's clustering rate were significantly impacted by sampling time, marital status, and CD4+ T lymphocytes (all p < 0.05). The gradient boosting machine (GBM) model had the highest area under the curve value, 0.884 ± 0.051, according to scikit-learn. Though not all cluster subtypes grew equally, the network clusters were relatively specific and aggregated. The largest local transmission-risk group for HIV-1CRF08_BC is now the heterosexual transmission population. The most suitable model for constructing the HIV-1 molecular network dynamics prediction model was found to be the GBM model.

Environmental health risk assessment and acute effects of sulfur dioxide (SO2) inhalation exposure on traditional sulfur miners at Ijen Crater Volcano, Indonesia

The Ijen Crater volcano is one of the geological wonders recognized by UNESCO. Inside it is a blue lake with a high acidity level, and a blue fire phenomenon has formed due to the very high concentration of sulfur. This crater is also one of Indonesia's largest sources of sulfur and is used by locals as a traditional sulfur mine. This study aims to measure SO2 concentrations and assess the health risks of SO2 exposure in traditional sulfur mine workers. The SO2 measurements were taken using impingers at six sample points along the mine workers' path. In addition, anthropometric data, work activity patterns, and health complaints during work were collected through direct interviews with 30 respondents selected based on inclusion criteria. Short-Term Health Impact Method was carried out based on a comparison of threshold level values and acute effects obtained from interviews regarding health complaints. The Hazard Question Index (HQ Index) of SO2 exposure was calculated using the health risk assessment method. The SO2 concentrations between 3.14 and 18.24 mg/m3. All sample points were above the quality standard threshold set by the EPA of 1.97 mg/m3. The most common health complaints workers experienced were eye irritation and coughing while working, followed by headache, shortness of breath, and skin irritation. The HQ index of SO2 exposure in workers was 1.02 for real-time exposure and 2.15 for long-term exposure. An HQ index ≥ 1 indicates a potential health risk for workers. Therefore, it is important to control workers' SO2 exposure.

An orthogonal analytical platform for determining critical material attributes for in situ formation of thermosensitive hyaluronic acid-poly(N-isopropylacrylamide) copolymers

The developability assessment of the in situ formation of thermosensitive injectables requires the unequivocal determination of their lower critical solution temperatures (LCSTs). Herein, we established a standardized threshold for LCST detection by harmonizing and cross-validating the orthogonal methods using techniques such as nuclear magnetic resonance spectroscopy, light scattering, turbidimetry, backgrounded membrane imaging, and rheology. The selected techniques were in agreement and promptly disclosed unique features and instrumental biases of otherwise difficult interpretations in the characterization of thermosensitive polymers. Thus, various hyaluronic acid–poly (N-isopropylacrylamide) copolymers were synthesized via strain-promoted azide–alkyne cycloaddition to understand their critical material attributes. Structure–function relationships and behaviors of the copolymers were tested under in vitro-simulated in vivo conditions.

Clinical Evaluation of Blood Culture Identification Gram-Positive Panel on Methicillin Resistant Gene Testing in a Large Metropolitan Teaching Hospital

Abstract Introduction The ePlex blood culture identification (BCID) gram-positive panel is a PCR-based approach used for the detection of common pathogens associated with bloodstream infections and corresponding antibiotic-resistance genes. One of the genes, mecA, is associated with methicillin, penicillin, and other penicillin-like-antibiotic-resistant gram-positive bacteria (GPB). It is unclear whether the BCID panel has predictive utility and accuracy in treating hospital infections due to GPB. This retrospective study attempts to determine the consistency and accuracy of BCID gene testing compared to more traditional susceptibility methods at a large public hospital. Method A search query was performed for all BCID results at one teaching hospital in a large metropolitan area for one year (2022). The query included demographic information, BCID results, culture results, and combined susceptibility data. The results were filtered to include only cases in which the mecA gene was detected. The filtered results were then analyzed to determine if the susceptibility results from the susceptibility platform (VITEK) were consistent with the expected susceptibility of the target gene, specifically for oxacillin and vancomycin. The susceptibility cutoff was set as &amp;gt;0.5 mcg/mL and &amp;lt;1 mcg/mL respectively, the standard threshold used at the institution. Results A total of 1211 culture results were obtained, of which the mecA gene was identified by BCID in 321 cases, along with the following GPB: Staphylococcus aureus, Staphylococcus epidermidis, and Staphylococcus sp. (not aureus). The corresponding cultures grew the following isolates: S. aureus, S. epidermidis, S. hominis, and S. haemolyticus. Of the 321 BCID results, 75 were identified as S. aureus. The isolates grew methicillin-resistant Staph aureus (MRSA) (69/75) 92%, while the typical S. aureus grew (6/75) in 8% of the isolates. In these cases, we compared susceptibility testing for both isolates as either sensitive or resistant, with a MIC of &amp;gt;0.5 mcg/mL for oxacillin to be designated as resistant, and &amp;lt;1 mcg/mL to be designated as sensitive to vancomycin. Of the 75 specimens, the concordance rate was 97% (73/75) for oxacillin and 100% (75/75) for vancomycin. The average receipt to verification turnaround time (TAT) was 36 hours for BCID results and 121 hours (about 5 days) for culture sensitivity results. Conclusion The results show that oxacillin resistance can be predicted by detecting S. aureus and the mecA gene using the BCID panel. However, the mecA gene can be identified in other GPB such as S. epidermidis, in which it should not be used to infer oxacillin or vancomycin susceptibilities. In the case of mecA and S. aureus detection by BCID, treating the patient as a MRSA infection may be appropriate before the susceptibilities have been performed. This approach can reduce the turnaround time for antimicrobial resistance reporting and improve antimicrobial stewardship efforts.

Genetics, age, and diet influence gut bacterial communities and performance of black soldier fly larvae (Hermetia illucens)

BackgroundThe gut microbiota of black soldier fly larvae (BSFL, Hermetia illucens) play a crucial role in recycling various organic waste streams. This capability is linked to the presence of a potential common core microbiota in BSFL. However, subjective thresholds for defining core taxa and the difficulty of separating genetic and environmental influences have prevented a clear consensus in the literature. We analysed the gut bacterial communities of two genetically distinct BSF lines (wild type (WT) and lab-adapted line (LD)) raised on ten different diets based on common agricultural by-products and food waste in Southeast Asia.ResultsHigh-throughput 16S rRNA gene sequencing revealed that gut bacterial communities were significantly influenced by genetics (p = 0.001), diet (plant/meat-dominated; p = 0.001), larval age (p = 0.001), and the interactions between all three (p = 0.002). This led us to investigate both common core taxa and lineage-specific core taxa. At a strict > 97% prevalence threshold, four core taxa were identified: Providencia_A_732258, an unclassified genus within the family Enterococcaceae, Morganella, and Enterococcus_H_360604. A relaxed threshold (> 80% prevalence) extended the core to include other potential common core taxa such as Klebsiella, Proteus, and Scrofimicrobium. Our data suggest that Proteus, Scrofimicrobium, Corynebacterium, Vagococcus_B, Lysinibacillus_304693 (all LD), and Paenibacillus_J_366884 (WT) are lineage-specific rather than members of a common core (> 90% prevalence in either LD or WT, with prevalence significantly different between lines (p ≤ 0.05)). Positive correlations were observed between several core genera and larval performance in LD, typical of a highly optimized lab-adapted line. Interestingly, only members of the genus Providencia appeared to play a crucial role in most aspects of larval performance in both genetic lineages.ConclusionOur study demonstrates that the gut microbiota of BSFL is influenced by genetic factors, diet composition, larval age, and their interactions. We identified a distinct lineage-specific core microbiota, emphasizing genetic background’s role. Future studies should apply a standardized high prevalence threshold of at least > 90% unless there is a valid reason for relaxation or sample exclusion. The consistent association of Providencia spp. with larval performance across both genetic lines highlights their crucial role in the BSFL gut ecosystem.

Impact of Skin Pigmentation on Pulse Oximetry Blood Oxygenation and Wearable Pulse Rate Accuracy: Systematic Review and Meta-Analysis.

Photoplethysmography (PPG) is a technology routinely used in clinical practice to assess blood oxygenation (SpO2) and pulse rate (PR). Skin pigmentation may influence accuracy, leading to health outcomes disparities. This systematic review and meta-analysis primarily aimed to evaluate the accuracy of PPG-derived SpO2 and PR by skin pigmentation. Secondarily, we aimed to evaluate statistical biases and the clinical relevance of PPG-derived SpO2 and PR according to skin pigmentation. We identified 23 pulse oximetry studies (n=59,684; 197,353 paired SpO2-arterial blood observations) and 4 wearable PR studies (n=176; 140,771 paired PPG-electrocardiography observations). We evaluated accuracy according to skin pigmentation group by comparing SpO2 accuracy root-mean-square values to the regulatory threshold of 3% and PR 95% limits of agreement values to +5 or -5 beats per minute (bpm), according to the standards of the American National Standards Institute, Association for the Advancement of Medical Instrumentation, and the International Electrotechnical Commission. We evaluated biases and clinical relevance using mean bias and 95% CI. For SpO2, accuracy root-mean-square values were 3.96%, 4.71%, and 4.15%, and pooled mean biases were 0.70% (95% CI 0.17%-1.22%), 0.27% (95% CI -0.64% to 1.19%), and 1.27% (95% CI 0.58%-1.95%) for light, medium, and dark pigmentation, respectively. For PR, 95% limits of agreement values were from -16.02 to 13.54, from -18.62 to 16.84, and from -33.69 to 32.54, and pooled mean biases were -1.24 (95% CI -5.31 to 2.83) bpm, -0.89 (95% CI -3.70 to 1.93) bpm, and -0.57 (95% CI -9.44 to 8.29) bpm for light, medium, and dark pigmentation, respectively. SpO2 and PR measurements may be inaccurate across all skin pigmentation groups, breaching U.S. Food and Drug Administration guidance and industry standard thresholds. Pulse oximeters significantly overestimate SpO2 for both light and dark skin pigmentation, but this overestimation may not be clinically relevant. PRs obtained from wearables exhibit no statistically or clinically significant bias based on skin pigmentation.