Browse Articles

Regression based hybrid machine learning model performance evaluation on air quality index prediction in Kolkata

Abstract Air pollution, especially elevated particulate matter concentrations, presents a substantial risk to public health and environmental sustainability in urban regions. By employing machine learning and hybrid ensemble models, this study develops a robust frame work for predicting the Air Quality Index (AQI). A multi-step imputation method was used to preprocess the dataset containing metrological variables and air contaminants in order to handle missing values. AQI was selected as the target variable. To assess the possibility of target dependency, two feature configurations were taken in to consideration: a full-featured set and a reduced set that excluded PM2.5 and PM10. Multiple models were used, including Linear Regression, Decision Tree, Random Forest, Gradient Boosting, KNN, MLP and LSTM as well as ensemble methods like Voting and Stacking regressor. Baseline models, namely persistence and SMA were incorporated for comparative analysis. To assess the performance RMSE, MAE, MAPE, RMSLE and R 2 with a temporal train test split were used. The Voting regressor achieves the lowest RMSE (10.938) and highest R 2 (0.974), while the Stacking regressor offers the lowest MAE and MAPE demonstrating the superior performance of ensemble models. The LSTM model captures temporal patterns but performs below ensemble models. Models with fewer features perform noticeably worse, underscoring the significance of particulate matter. SHAP analysis shows PM2.5 and PM10 as the most influential features while robustness analysis supports stable performance.

Feasibility of mechanomyography-based fatigue classification for passive lower-limb exoskeleton evaluation: A pilot study

Mechanomyography (MMG) enables non-invasive monitoring of muscle mechanical activity, while its utility in time-resolved fatigue detection during dynamic human–exoskeleton interaction remains underexplored. This pilot study explored the feasibility of combining MMG with machine learning to characterize neuromuscular fatigue and evaluate passive lower-limb exoskeleton assistance during repetitive 10 kg squat-lifting tasks. MMG signals from five lower-limb muscles were extracted for time-domain, frequency-domain and nonlinear features, and fatigue identification was implemented via a spectral-based criterion and multi-muscle voting optimization. A radial basis function-enhanced random forest (RBF-RF) model integrated with data augmentation was validated through leave-one-subject-out cross-validation. The results demonstrated that the 1/5 voting rule achieved optimal performance, with mean accuracy of 0.913 ± 0.057, AUC of 0.792 ± 0.073, and a low fatigue detection error of 1.4 ± 0.8 s. Data augmentation steadily improved model robustness, and predicted fatigue levels were significantly correlated with subjective perceived exertion (ρ = 0.756, p < 0.001). This pilot study demonstrates the feasibility of MMG-based fatigue monitoring for wearable assistive systems. The proposed framework supports objective, high-temporal-resolution fatigue monitoring, and may serve as a viable tool for assessing wearable assistive systems. Further large-cohort studies are required to validate its generalizability for practical applications.

Identification of epithelial, mesenchymal, and platelet-associated circulating tumour cells with translational implications in oral squamous cell carcinoma

Abstract Metastatic dissemination is driven by rare Circulating Tumour Cells (CTCs) that exhibit pronounced phenotypic plasticity and dynamic interactions with different components in the bloodstream. In Oral Squamous Cell Carcinoma (OSCC), limited resolution of epithelial, mesenchymal, and platelet-associated CTC-states has constrained biological understanding of early tumour spread and hindered translational interpretation. In this study, we identify, count and characterize distinct epithelial, mesenchymal, and platelet-associated CTC-states in a cohort of 33 patients using a strategic workflow involving hematopoietic cell depletion with multiparametric flow-cytometric analysis. The FACS (Fluorescence-assisted cell sorting)-strategy incorporated epithelial tumour-associated markers (EpCAM, EGFR, and Cytokeratin), mesenchymal markers (VIM and N-Cadherin), and platelet/leukocyte markers (CD41 and CD45) to resolve biologically distinct CTC-subpopulations. Analytical robustness was established through spike-in experiments using OSCC cell line i.e., Cal27, demonstrating linear detection across clinically relevant ranges(1-100cells/mL of blood, Spearman’s r  = 0.8738, p  < 0.0001) and sensitive recovery of rare tumour cells with a Limit of Detection of 1 cell/mL, Limit of Quantification of 10 cells/mL, and Limit of Blank of 1.779 cells/mL. Molecular validation of sorted populations using whole transcriptome amplification-quantitative PCR confirmed tumour-associated marker expression and absence of hematopoietic contamination. Application of this approach in OSCC patients revealed detectable CTCs in 70% of the cases (ranging from 14.20 to 340.5 CTCs-related events/mL). Importantly, CTCs were identified across discrete phenotypic states, including platelet-associated CTC-clusters that were not captured by epithelial marker-restricted strategies. Quantitative comparison of CTC subtype proportions revealed majority (nearly 83%) of CTCs present as platelet clusters, followed by Epithelial-Single CTCs (21.21%). In comparison, CTCs with only mesenchymal phenotype constitute only 3.22% of the total CTC-population. Receiver operating characteristic analysis supported the discriminatory capacity of CTC enumeration and enabled the definition of a biologically relevant threshold of > 19.40 events mL for CTC positivity. Taken together, our findings outline a practical workflow for identifying and quantifying different CTC-states in OSCC, with platelet-associated CTCs emerging as the predominant population detected. These findings support the importance of incorporating phenotypic heterogeneity and platelet-associated tumour cell interactions into future liquid biopsy-based translational pathology research and clinical biomarker development in OSCC.

Dynamic effects of China’s national volume-based procurement on generic drug consistency evaluation: An interrupted time series analysis

Objectives China’s national volume-based procurement (NVBP) policy uniquely requires the generic drug consistency evaluation (GCE) for generic drugs on the purchase list. It employs large-scale centralized procurement to lower the prices of qualified generic drugs and encourages manufacturers to get GCE certification for their generic drugs. Although it is a fundamental part of the NVBP system, research on the impact of NVBP on manufacturers has only recently emerged and is still not comprehensive enough. This study is the first to systematically evaluate the dynamic effects of the NVBP policy on the quantity of GCE-certified generic drugs and uncover their relationship in terms of both time and quantity. Study design Interrupted time series analysis(ITSA). Methods The NVBP lists were published by the National Healthcare Security Administration (NHSA). The information of GCE-certified generic drugs was obtained from the databases of the National Medical Products Administration (NMPA) and the Center for Drug Evaluation (CDE). Generic drugs were divided into four categories: all GCE-certified generics; GCE-certified generics of NVBP-listed drugs (NVBP-GCE generics); GCE-certified generics of non-NVBP drugs (non-NVBP GCE generics); and GCE-certified generics from each individual NVBP list. Results Overall, the 2018 NVBP intervention resulted in a monthly increase of 2.876 in generics certified by GCE (95% CI: 1.311–4.317). In contrast, the 2016 policy showed no statistical significance. Both NVBP-GCE and non-NVBP GCE generics experienced significant increases, with NVBP-GCE showing a more rapid initial rise. In the analysis of 8 NVBP batches, the 2016 intervention had no significant statistical impact on either the immediate or long – term effects. Conversely, the 2018 intervention significantly increased the quantity of GCE – certified generics in the short term and widened the gap between NVBP – GCE generics and non – NVBP GCE generics. Nevertheless, this effect gradually diminished over time. The quantity of NVBP – GCE generics reached its peak before or at the release of each NVBP list, while non – NVBP GCE generics continued to grow. Conclusion The NVBP policy has resulted in a substantial increase in the quantity of GCE – certified generic drugs. From a comprehensive perspective, the growth rates of NVBP-GCE generics and non-NVBP GCE generics were comparable. The maximum number of GCE – certified generic drugs was witnessed either prior to or simultaneously with the release of each round of NVBP procurement documents. After the publication of each NVBP announcement, the number of GCE – certified generics on that particular procurement list started to decrease, whereas the number of non – NVBP GCE generics continued to increase steadily until April 2024.

Prospective memory and executive functions in adults across the wider autistic spectrum

Abstract Prospective memory (PM) refers to the cognitive ability of remembering to execute an intended action in the future. Empirical evidence indicates reduced PM performance in autistic individuals. This study aimed to explore PM performance across the wider autistic spectrum, including individuals with diverse cognitive profiles, and to investigate the impact of executive functions on PM. Thirty autistic and 30 non-autistic adults (18–65 years), matched for age, gender and non-verbal abilities, took part in the study. Participants completed an event-based PM task, and three executive function tasks measuring planning, inhibition and generativity abilities. Overall, non-autistic adults performed better in the event-based PM task in comparison to autistic participants. Better executive functioning was associated with better event-based PM performance in both groups; the completion time of the planning task significantly predicted PM performance. Results confirm earlier findings of lower PM performance in autistic individuals and close links of executive functions and PM. Considering the significant impact of PM on day-to-day life, future studies should develop practical interventions to support PM (e.g., targeted training in planning abilities, the use of agendas, to-do lists or assistive technologies), especially for autistic individuals who are dependent on external aid.

Plasma vitamin C levels are associated with brain structural networks on MRI: A large cohort study

Background Neurodegenerative diseases significantly impact brain health in older adults, and although dietary vitamin C intake has been associated with a reduced risk of cognitive impairment, it remains unclear whether plasma vitamin C levels independently affect brain structure and neural connectivity. This study aimed to investigate whether plasma vitamin C levels were independently associated with brain volume and default mode network (DMN) connectivity in older adults. Methods All participants underwent 3T magnetic resonance imaging (MRI). Total intracranial volume (ICV), gray matter volume (GMV), and white matter volume (WMV) were calculated using CAT 12 in SPM 12. DMN connectivity was assessed using independent component analysis, based on shared GMV variance across voxels, and quantified by the loading coefficients. Multiple regression analysis was used to investigate the associations among brain volume, DMN connectivity measurements, and plasma vitamin C levels. These analyses were adjusted for potential confounders (age, sex, Mini-Mental State Examination score, diabetes, hypertension, hyperlipidemia, and education levels), and lifestyle factors (smoking history, drinking history, and physical activity). GMV/ICV ratio and WMV/ICV ratio were calculated to adjust for individual differences in head size. Results This cross-sectional study included 2,044 participants (median age, 69 years; females, 61.1%). Low plasma vitamin C levels were significantly and independently associated with the GMV/ICV ratio (p < 0.001) and DMN connectivity (p < 0.001). Conclusions In conclusion, our findings demonstrate that plasma vitamin C levels are positively associated with the structural integrity of the gray matter and DMN connectivity, generating the hypothesis that vitamin C may play a role in brain health.

Differentiating malignancy from liver parenchyma in Ex-Vivo OCT images using anomaly detection

Abstract Primary liver cancer and colorectal liver metastases (CRLM) pose significant challenges, because of limited early diagnosis and the reliance on time-consuming frozen section analysis during surgery to confirm complete tumor resection (R0). This study investigates the potential of optical coherence tomography (OCT) combined with anomaly detection for differentiating hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (iCCA) and CRLM from normal liver parenchyma, ex-vivo. Our dataset comprises 173 OCT images sourced from 69 patients undergoing liver surgery. We leveraged pre-trained neural networks with frozen weights and statistical outlier modeling to train an anomaly detection model using only non-cancer parenchyma scans. Given the small-scale nature of the dataset and the presence of label uncertainty, a stratified cross-validation procedure was employed to robustly assess the model’s performance in accurately matching OCT scans with their corresponding histological diagnoses. This resulted in promising classification performance using a pre-trained Vision Transformer: sensitivity 80%, specificity 78%, accuracy 79%, and area under the receiving-operating-characteristic-curve (ROC-AUC) of 81%. While limited by a relatively small and noisy dataset, this study highlights the promising potential of OCT combined with anomaly detection for intraoperative liver cancer detection. This semi-supervised learning approach offers several advantages, including reduced training time and data requirements, as well as interpretable anomaly scores.

Correction: The association between platelet-to-albumin ratio and diabetic peripheral neuropathy: A cross-sectional study in the Chinese population

Barriers and opportunities in pediatric ophthalmology: a cross-sectional survey among Brazilian ophthalmologists

A pilot randomized clinical trial of the Skills to Enhance Positivity (STEP) group intervention for young adults with depression: Examining feasibility and acceptability

Addressing the pressing concern of rising rates of depression and suicide in young adults, the present study explores the feasibility of adapting the Skills to Enhance Positivity (STEP) intervention as a group-based program in a community mental health setting in the United States. STEP is an adjunctive intervention designed to enhance positive emotions to reduce suicide risk and alleviate depressive symptoms. Fifty-two participants aged 18–26 ( M  = 21.40, SD  = 2.00) were randomized to receive group-based STEP or enhanced treatment as usual (ETAU). The group-based STEP format was well-received, with high attendance and positive feedback, demonstrating feasibility and acceptability. While underpowered to detect between-group differences, at post-intervention and follow-up, those in STEP exhibited increases in positive emotions and significant reductions in depression and suicidal ideation. These changes were larger compared to the effect sizes from those in ETAU. These findings underscore the potential of the adapted STEP model to help young adults, warranting further exploration in larger trials. Study is registered on clinicaltrails.gov under ID Number: NCT06621992.

Premna odorata extract exhibits anti-inflammatory activity via suppression of NLRP3 inflammasome

Abstract Premna odorata (family Verbenaceae), known as “Alagaw” in the Philippines, has traditionally been used to treat inflammatory respiratory conditions; however, molecular evidence supporting its pharmacological effects remains limited. Given that NOD-like receptor pyrin domain-containing protein 3 (NLRP3) inflammasome-driven IL-1β secretion plays a central role in inflammatory respiratory conditions, we investigated whether P. odorata extract (POE) modulates NLRP3 inflammasome activation. In LPS-primed J774A.1 and THP-1 macrophages, POE reduced IL-1β secretion induced by ATP or nigericin without affecting NLRC4 or AIM2 inflammasome activation, indicating NLRP3 selectivity. POE treatment inhibited adaptor apoptosis-associated speck-like protein containing CARD (ASC) oligomerization and speck formation without affecting cell viability or intracellular ROS levels, indicating suppression of inflammasome assembly. In vivo, POE attenuated inflammatory cell infiltration in an LPS-induced zebrafish model. Together, these findings indicate that POE suppresses NLRP3 inflammasome–mediated inflammatory responses, providing a molecular basis for its traditional use in managing inflammatory conditions and offering a promising natural scaffold for the development of NLRP3-targeted therapeutics.

Diverse coping strategies for food insecurity: A qualitative study of economically precarious households in India in the context of COVID-19

Objective The study examines how households in two Indian states managed food insecurity in the context of COVID-19, focusing on differences between migrant and non-migrant households in rural and urban areas. Methods We integrate Davies’ framework of coping strategies with the Sustainable Livelihoods and Resilience frameworks to analyze how coping capacity is shaped by structural inequalities, existing resources, social networks, and access to entitlements. Between December 2022 and March 2023, we conducted 343 semi-structured interviews in 86 households in Uttar Pradesh and Goa, purposively sampled by migration status, location, caste, and household type. Thematic analysis was complemented with narrative analysis of 60 interviews from 15 households that had experienced severe COVID-related shocks, including job loss, reverse migration, and illness. Findings Strategies ranged from routine adjustments—dietary substitutions, portion control, and pooling resources—to erosive responses such as maternal buffering, selling assets, accumulating debt, withdrawing children from school, and delaying healthcare. Rural non-migrants drew on kinship ties and PDS support, while migrants, especially circular migrant workers/recent arrivals were excluded from both entitlements and social support networks. Reverse migration reconnected households with rural networks but also strained agrarian systems. Conclusion Migration status and rural–urban location critically shaped resilience. Coping responses to COVID-19 depended less on income loss than on structural access to entitlements and social support networks, highlighting the need for inclusive, context-specific, and targeted social protection.

Seasonal utilization distributions, site fidelity, and habitat use of the black-tailed gull (Larus crassirostris) in the Yellow Sea

Shared decision making in Eosinophilic esophagitis: Integrating physician and patient perspectives

Background and objectives Shared decision making (SDM) is a patient-centered approach for conditions where multiple, preference-sensitive treatment options exist and there is no single best choice. Eosinophilic esophagitis (EoE), an increasingly prevalent chronic immune-mediated disease, offers an example of how patients and physicians use SDM to navigate the challenging tradeoffs of weighing pharmacologic and dietary therapies. We aimed to identify communication challenges for SDM in EoE care from physician and patient perspectives and to explore how patient treatment preference archetypes influence SDM. Research Design and methods We conducted a qualitative study with one-on-one, semi-structured interviews with adult patients with EoE and physicians. Patients (n = 35) were recruited from a single academic center (mean age 41 years [(SD 15.2]; 51% male; predominantly White 83%). Physicians included gastroenterologists (n = 9) and allergists (n = 7) from varied practices across Michigan. Interview guides were informed by the Theoretical Domains Framework and iteratively refined. Interview transcripts were coded using both deductive and inductive strategies and analyzed thematically via descriptive content analysis. Results Three central themes emerged: 1) Patients often lack knowledge or have misconceptions about EoE and its treatments, but differed in how and from where they want to gain disease-focused information, 2) Physicians generally supported SDM, but patients varied in how they want to be involved in decisions about their care, and 3) Both patients and physicians wanted accurate and user-friendly informational resources about EoE to support effective communication and SDM. Conclusions Our analysis revealed that patients with EoE have diverse preferences for disease-related learning, decision making, and communication. There is a clear need for accurate, accessible, and personalized information to improve patient-physician understanding and communication, without which SDM and patient-centered care in EoE cannot be achieved. What we learned can be applied to other health conditions where there is clinical equipoise between various effective management options.

Spatiotemporal evolution and driving factors of water conservation capacity in Lanzhou City

Laplace Transform–Based Nonparametric Test of Exponentiality against DMRL class with preservation under the Homogeneous Poisson Shock Model and applications in survival analysis and reliability

This paper introduces a novel, computationally efficient nonparametric test for assessing the null hypothesis of exponentiality against alternatives belonging to the Decreasing Mean Residual Life (DMRL) class. The test statistic is developed using Laplace transform techniques in conjunction with the theory of U-statistics, ensuring asymptotic normality and scale invariance. In addition, we establish the preservation of the proposed methodology under the Homogeneous Poisson Shock Model, further extending its theoretical robustness in reliability contexts. Critical values are obtained through extensive Monte Carlo simulations under both complete and right-censored data, enhancing the method’s practical applicability. A comprehensive simulation study demonstrates that the proposed test consistently outperforms classical procedures in terms of power across a wide range of alternative distributions commonly encountered in reliability and survival analysis. The usefulness of the method is further illustrated with real datasets, including COVID-19 mortality and clinical survival data, where the test successfully detects departures from exponentiality with DMRL characteristics. By combining advanced probabilistic transforms with nonparametric inference, this work provides a rigorous and scalable framework for lifetime data analysis, adaptable to the complex censoring mechanisms prevalent in medical and engineering applications.

StyleGAN-based synthetic image augmentation for multi-class otoscopy image classification

Four methods for estimating hepatitis C incidence using extant testing data

Background Accurate estimation of hepatitis C (HCV) incidence is crucial for measuring progress towards HCV elimination targets set by the World Health Organization (WHO). Extant HCV antibody (Ab) and RNA test results are widely used to estimate HCV incidence, but the impact of cohort specification and case definition on validity and generalizability is poorly understood. Methods Using databases linked at ICES – a repository of administrative health data for Ontario residents – we constructed a cohort of 15.8 million Ontarians aged 18–80 between 1999 and 2018 to estimate annual HCV incidence using four methods. The population-based method calculated HCV incidence as the number of new HCV diagnoses each year divided by annual population size estimates, while Poisson regression was used in the other three incidence estimation methods: the test-negative method defined eligibility at first negative test; the RNA-based method prioritized specificity by requiring RNA+ tests; and the antibody-inclusive method prioritized sensitivity by including all Ab+ tests. Results Distinct patterns of HCV incidence were found across the estimation methods: the RNA-based estimates were lowest and fluctuated around 30 cases per 100,000 person-years, while population-based and antibody-inclusive estimates were 1.5-fold higher, and test-negative estimates were 7.9-fold higher. Population-based estimates were sensitive to changes in the HCV case definition used in Ontario from 1999–2018. The test-negative cohort had a high prevalence of human immunodeficiency virus (HIV) and substance use disorder, limiting generalizability of HCV incidence estimates. RNA-based estimates likely underestimated HCV incidence because 22% of Ab+ tests were unconfirmed by RNA testing, while antibody-inclusive estimates likely overestimated HCV incidence by assuming all unconfirmed Ab+ tests were true cases. Conclusion These new findings illustrate the influence of cohort definition and HCV case definition when estimating HCV incidence using extant testing data, which will support accurate measurement of progress towards WHO HCV elimination goals.

Designing potent and immunogenic epitope based peptide vaccine against all serotypes of DENV via structural, physico-chemical and immunoinformatics-based approaches

Modification of pre-operative order set to reduce PACU stay times for outpatient benign gynecological surgery

A quality improvement project was implemented at a single medical center’s outpatient benign gynecological surgery division to address prolonged post anesthesia care unit (PACU) stays (defined as greater than 120 minutes). Initial barrier analysis within the department identified gabapentin use in the perioperative setting as a possible contributor. The intervention removed the default pre-op order set of 600 mg gabapentin. One-year post-intervention (baseline n = 281, intervention n = 573) it was observed that the average PACU stay time for benign gynecological surgeries was reduced from an average of ~183 to ~159 minutes marking a 12.6% reduction in PACU stay time (p < 0.0001). Gabapentin use decreased from 92.17% to 1.25% with no change in pain scores. After the intervention, there was no longer a statistically significant difference in PACU stay times by age. This intervention successfully decreased PACU stay times, highlighting pathways to advance individualized, age-conscious care through quality improvement interventions.