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Resident microglia of the central nervous system are being increasingly recognized as key players in diseases such as neuropathic pain. Biochemical and behavioral studies in neuropathic pain rodent models have documented compelling evidence of the critical role of ATP mediated-P2X4R-brain-derived neurotrophic factor (BDNF) signaling pathway in the initiation and maintenance of pain hypersensitivity, a feature driving neuropathic pain-related behavior. The goal of this study was to develop and characterize an in vitro cell line model of activated microglia that can be subsequently utilized for screening neuropathic pain therapeutics. In the present study, we characterized the SIM-A9 microglia cell line for key molecules in the P2X4R-BDNF signaling axis using a combination of biochemical techniques and developed an ATP-activated SIM-A9 microglia model. We present three novel findings: first, SIM-A9 cells expressed P2X4R and BDNF proteins, second, ATP, but not LPS, was cytocompatible with SIM-A9 cells and third, exposure of cells to optimized ATP concentrations for defined periods increased intracellular expression of Iba1 and BDNF proteins. Increased Iba1 levels confirmed microglia activation and increased BDNF expression confirmed ATP-mediated stimulation of the P2X4R signaling pathway. We propose that this ATP-activated SIM-A9 cell line model system can be utilized for screening both small- as well as macro-molecular neuropathic pain therapeutics targeting BDNF and/or P2X4R knockdown.

PurposeWe tested polyplexes of a diblock polymer containing a pH-responsive, endosomolytic core (dimethylaminoethyl methacrylate and butyl methacrylate; DB) and a zwitterionic Poly (methacryloyloxyethyl phosphorylcholine) (PMPC) corona for the delivery of plasmid DNA (pDNA) to glioblastoma cells.MethodsWe studied the physicochemical characteristics of the DNA polyplexes such as particle hydrodynamic diameter and surface potential. Cytocompatibility of free PMPC-DB polymer and pDNA polyplexes with U-87MG and U-138MG glioma cell lines were evaluated using the ATP assay. The transfection activity of luciferase pDNA polyplexes was measured using a standard luciferase assay. Anti-proliferative, apoptotic, and cell migration inhibitory activities of PMPC-DB/Interferon-beta (IFN-β1) pDNA polyplexes were examined using ATP assay, flow cytometry, and wound closure assay, respectively.ResultsPMPC-DB copolymer condensed pDNA into nanosized polyplexes. DNA polyplexes showed particle diameters ranging from ca. 100–150 nm with narrow polydispersity indices and near electroneutral zeta potential values. PMPC-DB/Luciferase pDNA polyplexes were safe and showed an 18-fold increase in luciferase expression compared to the gold standard PEI polyplexes in U-87MG cells. PMPC-DB/IFN-β1 polyplexes induced apoptosis, demonstrated anti-proliferative effects, and retarded cell migration in glioblastoma cells.ConclusionThe results described herein should guide the future optimization of PMPC-DB/DNA delivery systems for in vivo studies.

Discovery-based proteomics workflows that identify novel interactors rely on immunoprecipitations or pull-downs with genetically tagged bait proteins immobilized on appropriate matrices. But strategies to analyse protein interactions on a diffusible-membrane surface combined with the practical ease of pull-downs remain unavailable. Such strategies are important to analyse protein complexes that mature in composition and stability because of diffusion-based encounter between participant proteins. Here, we describe a generic pull-down strategy to analyse such complexes using chelating lipid-containing supported bilayers formed on silica beads. These templates can display desired His-tagged bait proteins on a diffusible-membrane surface. Using clathrin-mediated endocytosis as a paradigm, we find that the clathrin-binding adaptor protein epsin1 displayed as bait on these templates pulls down significantly higher amounts of clathrin from brain lysates than when immobilized on conventional matrices. Together, our results establish the potential of such templates as superior matrices for analysing protein–protein interactions and resultant complexes formed on membrane surfaces.Graphic Abstract

Water pollution caused by the textile industry poses significant health and environmental challenges because of the discharge of untreated dye-laden effluents into natural water bodies. Conventional dye removal methods are often cost-prohibitive and energy-intensive. Membrane filtration has advantages such as scalability; however, it exhibits fouling. This study focuses on preparing cost-effective and eco-friendly membranes and evaluating the performance of PES-incorporated inorganic (TiO2), carbon-based (AC), and green-synthesized, eco-friendly Moringa seed extract biosorbents. Previous research has conducted studies on these nanoparticles separately; however, in this study, they were compared altogether, and the nanocomposite membranes were compared with commercial nanofiltration membranes (CM NF 90). The physical properties of the membranes were evaluated based on water uptake, porosity, and mean pore radius. Membrane characterizations were determined using field emission scanning electron microscopy (FESEM) and energy dispersive X-ray spectroscopy (EDS), confirming the successful integration of nanomaterials and improvements in membrane morphology. A dead-end filtration system was used to evaluate the performance of the membranes in removing Evans blue dye. The color removal efficiency (CRE) of PES/ TiO2, PES/AC, and Moringa-based membranes was 97.9%, 92%, and 98.2%, respectively. The activated carbon (AC) and titanium dioxide (TiO2) PES membranes exhibited steady flux. The Moringa-based membrane exhibited a remarkable dye rejection rate and high flux; however, the flux decreased gradually because of fouling. These results confirm that nanocomposite membranes enhance dye removal efficiency and stability. Therefore, the nanocomposite PES membrane has the potential for better dye removal and has broad applications in dye removal from wastewater in the textile industry.

Background and Objective: In the analysis of dichotomous type response variable, logistic regression is usually used. However, the performance of logistic regression in the presence of sparse data is questionable. In such a situation, a common problem is the presence of high odds ratios (ORs) with very wide 95% confidence interval (CI) (OR: >999.999, 95% CI: <0.001, >999.999). In this paper, we addressed this issue by using penalized logistic regression (PLR) method. Materials and Methods: Data from case-control study on hyponatremia and hiccups conducted in Christian Medical College, Vellore, Tamil Nadu, India was used. The outcome variable was the presence/absence of hiccups and the main exposure variable was the status of hyponatremia. Simulation dataset was created with different sample sizes and with a different number of covariates. Results: A total of 23 cases and 50 controls were used for the analysis of ordinary and PLR methods. The main exposure variable hyponatremia was present in nine (39.13%) of the cases and in four (8.0%) of the controls. Of the 23 hiccup cases, all were males and among the controls, 46 (92.0%) were males. Thus, the complete separation between gender and the disease group led into an infinite OR with 95% CI (OR: >999.999, 95% CI: <0.001, >999.999) whereas there was a finite and consistent regression coefficient for gender (OR: 5.35; 95% CI: 0.42, 816.48) using PLR. After adjusting for all the confounding variables, hyponatremia entailed 7.9 (95% CI: 2.06, 38.86) times higher risk for the development of hiccups as was found using PLR whereas there was an overestimation of risk OR: 10.76 (95% CI: 2.17, 53.41) using the conventional method. Simulation experiment shows that the estimated coverage probability of this method is near the nominal level of 95% even for small sample sizes and for a large number of covariates. Conclusions: PLR is almost equal to the ordinary logistic regression when the sample size is large and is superior in small cell values.

In civil engineering and construction, soil stabilization is an important aspect. There are diverse conventional techniques to improve soilproperties and for soil stabilization. This study explores the viability of twotypes of biopolymers, Guar gum and Gellan gum, as sustainable and ecofriendly additives for clayey soil stabilization. Compaction, unconfined compression test, permeability, consistency limit, consolidation tests were performed in the study. The sample for the test has been prepared that biopolymer has been mixed with soil in different proportions. These biopolymers forms hydrogels when they get activated, and it enhances the bonding between soil particles thereby increasing the strength. Treating soilwith biopolymer increases dry unit weight and decreases optimum moisturecontent (OMC).Addition of gum solution reduces friction between soil particles, leading to marginal increase in dry unit weight. Higher the biopolymer content lower is the OMC content and soil become more stiff. The compressive strength and load bearing capacity isfound increasing soilbiopolymerspecimen upon different days of curing. For every tested percentage of treatment the percentage reduction factor rises withbiopolymer concentration due to drop in void ratio that results in a drop in the soil's permeability. Guar Gum and Gellan Gum are used as stabilizers in soil treatment, increasing liquid and plastic limits, shrinkage limit, and viscosity. They activate hydrogels, strengthen bonding activity, and increaseshrinkage limit. The addition of Guar Gum and Gellan Gum improves soil biopolymer mix viscosity and adhesion. The findings of this study positivelyimply that adding this material to weak soil would improve the soil’s characteristics.

India has been implementing active case-finding (ACF) for TB among marginalised and vulnerable (high-risk) populations since 2017. The effectiveness of ACF cycle(s) is dependent on the use of appropriate screening and diagnostic tools and meeting quality indicators. To determine the number of ACF cycles implemented in 2021 at national, state (  = 36) and district (  = 768) level and quality indicators for the first ACF cycle. In this descriptive study, aggregate TB program data for each ACF activity that was extracted was further aggregated against each ACF cycle at the district level in 2021. One ACF cycle was the period identified to cover all the high-risk populations in the district. Three TB ACF quality indicators were calculated: percentage population screened (≥10%), percentage tested among screened (≥4.8%) and percentage diagnosed among tested (≥5%). We also calculated the number needed to screen (NNS) for diagnosing one person with TB (≤1538). Of 768 TB districts, ACF data for 111 were not available. Of the remaining 657 districts, 642 (98%) implemented one, and 15 implemented two to three ACF cycles. None of the districts or states met all three TB ACF quality indicators' cut-offs. At the national level, for the first ACF cycle, 9.3% of the population were screened, 1% of the screened were tested and 3.7% of the tested were diagnosed. The NNS was 2824: acceptable (≤1538) in institutional facilities and poor for population-based groups. Data were not consistently available to calculate the percentage of i) high-risk population covered, ii) presumptive TB among screened and iii) tested among presumptive. In 2021, India implemented one ACF cycle with sub-optimal ACF quality indicators. Reducing the losses between screening and testing, improving data quality and sensitising stakeholders regarding the importance of meeting all ACF quality indicators are recommended.

The psychological, emotional and social well-being of an individual determines their ability to contribute and function as a social member. Several studies over the years have proven that an alarming number of people live with mental illnesses, of which only a fraction is documented. Studies conducted by Open Sourcing Mental Illness (OSMI) organization have indicated that these figures are much higher in the tech industry. We present an analysis of patterns and infer contributory factors for mental illness in the tech industry, to aid in the early detection and assess employees’ risk of diagnosis. Towards this end, the study comprises a detailed analysis, models for prediction of diagnosis, risk-based clustering and investigation into existing literature on factors contributing to mental illness. In addition to this, we have attempted to understand the impact of Covid-19 through analyzing trends of the factors influencing mental health, pre- and post-pandemic. We conclude with an insight to the impact of the COVID-19 pandemic on global mental health and the actions taken in the workplace to mitigate this.

Coronavirus disease 2019 (COVID-19) and its association with diabetes might lead to mucormycosis, and studies have reported an association between them. This study aims to find the correlation between COVID-19 and diabetic status in patients with mucormycosis and its role in disease progression and prognosis. The objectives of the study are to analyze the clinical range of mucormycosis in those with diabetes and COVID-19 and to correlate the clinical and radiographic findings. A retrospective cohort analysis was carried out at Saveetha Dental College and Hospitals in Chennai (approval number: IHEC/SDC/OMED-2204/23/218). The data collection was done from the institution's electronic database from April 2019 to April 2023 which included the patients' age and gender and COVID-19 and diabetic status and clinical and radiographic features of mucormycosis. From the data analyzed, 25 patients had a history of mucormycosis with diabetes and COVID-19 infections. The patients' average age was 47.76, out of which 22 were males and three were females. The chi-squared test showed no significant association between age (0.178), diabetes (0.465), and COVID-19 (0.583). Spearman's correlation was done showing an association between mucormycosis, diabetes, and COVID-19. Radiographically, 100% of the patients had involvement of the maxillary sinus, followed by the palate (32%), orbit (28%), nasal floor (24%), ethmoidal sinus (16%), sphenoidal sinus (12%), and frontal sinus (8%). The findings of this study point out the importance of considering the presence of systemic comorbidities like diabetes in COVID-19 patients. Early identification, surgical debridement, and antifungal medications are part of the treatment for increased survival.

Introduction With technology advancing across all fields, the utility of digital screens is increasing among all age groups for various purposes. Research indicates that while digital technology presents clear advantages, prolonged exposure can have detrimental effects on various aspects of health, behavior, emotions, and cognitive functions like attention and working memory. A crucial cognitive process for learning and information processing which is working memory, can be affected by factors including screen time. Studies have found that the impact of screen time on working memory can be negative, positive, or show no discernible relationship. However, earlier investigations are limited to smartphone use as screen time exposure and further to only active screen time. As there is a dearth of studies in the Indian context and young adults are more exposed to screen time, it is important to investigate along these lines. Hence, the present study aimed to investigate the impact of active and passive screen time exposure on modality-specific working memory in young adults. Methods Seventy-seven neurotypical individuals aged between 18 and 22 years were recruited. The study utilized auditory and visual reverse digit span tasks and the Corsi-backward task to measure working memory span. Screen time data of the participants were collected through a self-administered 18-item questionnaire covering active and background screen time domains. Results and discussion The present study concluded that only active screen time has a significant effect on visual reverse digit span and supports the notion of the visual superiority effect against an auditory superior effect as suggested by earlier findings. The preliminary findings of correlation observed exclusively within the visual domain in this study could be attributed to the potential impact of screen time exposure (active screen time and textual content). Screen usage demands effective switching between various visual stimuli and ongoing updates of information in memory. Nonetheless, interpreting this explanation and generalization requires caution, given the low ecological validity of the task employed in the study. Future investigations should aim to collect screen time exposure data more objectively, perhaps through online tracking techniques. Furthermore, it would be prudent to expand the correlation analysis to include other cognitive processes and populations.