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Single-cell RNA sequencing (scRNA-seq) has transformed our understanding of cellular responses to perturbations such as therapeutic interventions and vaccines. Gene relevance to such perturbations is often assessed through differential expression analysis (DEA), which offers a one-dimensional view of the transcriptomic landscape. This method potentially overlooks genes with modest expression changes but profound downstream effects and is susceptible to false positives. We present GENIX (gene expression network importance examination), a computational framework that transcends DEA by constructing gene association networks and employing a network-based comparative model to identify topological signature genes. We benchmark GENIX using both synthetic and experimental datasets, including analysis of influenza vaccine-induced immune responses in peripheral blood mononuclear cells (PBMCs) from recovered COVID-19 patients. GENIX successfully emulates key characteristics of biological networks and reveals signature genes that are missed by classical DEA, thereby broadening the scope of target gene discovery in precision medicine.

Mycobacterium aviumis an emerging opportunistic pathogen, globally. Infections caused by M. aviumare laborious to treat and could result in drug resistance. This review discusses the importance of many factors including the cell wall in M. aviumpathogenesis, since this unique structure modulates the pathogen’s ability to thrive in various hosts and environmental niches including conferring resistance to killing by antimicrobials. More research efforts in future are solicited to develop novel therapeutics targeting M. avium. The complete eradication of M. aviuminfection in immunocompromised individuals would need a deeper understanding of the source of infection, unique underlying mechanisms and its uncharacterized pathways. This could, perhaps in future, hold the key to target and treat M. aviummore effectively.

The objective of the study was to evaluate the feasibility and acceptability of mobile health (mHealth) phosphorus management programs in hemodialysis (HD) patients.

Despite utilization of hepatitis C viremic organs for hepatitis C naïve recipients (HCV D+/R-) in other solid organ transplants, HCV viremic pancreata remain an unexplored source of donor organs. This study reports the first series of HCV D+/R- pancreas transplants. HCV D+/R- had shorter waitlist times compared to HCV D-/R-, waiting a mean of 16 days from listing for HCV-positive organs. HCV D+/R- had a lower match allocation sequence than HCV D-/R-, and this correlated with receipt of organs with a lower Pancreas Donor Risk Index (PDRI) score. All HCV D+/R- had excellent graft function with a mean follow-up of 438 days and had undetectable HCV RNA levels by a mean of 23 days after initiation of HCV-directed therapy. The rates of infectious complications, reoperation, readmission, rejection, and length of stay were not impacted by donor HCV status. A national review of potential ideal pancreas donors found that 37% of ideal HCV-negative pancreas allografts were transplanted, compared to only 5% of ideal HCV-positive pancreas allografts. The results of the current study demonstrate the safety of accepting HCV-positive pancreata for HCV-naïve recipients and advocates for increased utilization of ideal HCV-positive pancreas allografts.

ABSTRACTTreatments with cytotoxic agents or viruses may cause Immunogenic Cell Death (ICD) that immunize tumor-bearing hosts but do not cause complete regression of tumor. We postulate that combining two ICD inducers may cause durable regression in immunocompetent mice. ICD was optimized in vitro by maximizing calreticulin externalization in human colorectal carcinoma (CRC) cells by exposure to mixtures of Oxaliplatin (OX) and human adenovirus (AdV). Six mm diameter CT26 or 4T1 carcinomas in flanks of BALB/c mice were injected once intratumorally (IT) with OX, AdV or their mixture. Tumor growth, Tumor-Infiltrating Lymphocytes (TIL), nodal cytotoxicity, and rejection of a viable cell challenge were measured. Tumors injected IT once with an optimum mixture of 80 µM OX – AdV 25 Multiplicity of Infection (MOI) in PBS buffer were 17–29% the volume of control tumors. When buffer was changed from PBS to 5% dextrose in water (D5W), volumes of tumors injected IT with 80 µM OX-AdV 25 MOI were 10% while IT OX or AdV alone were 32% and 40% the volume of IT buffer-treated tumors. OX-AdV IT increased CD3+ TIL by 4-fold, decreased CD8+ PD-1+ TIL from 79% to 19% and induced cytotoxicity to CT26 cells in draining node lymphocytes while lymphocytes from CT26-bearing untreated mice were not cytotoxic. OX-AdV IT in D5W caused complete regression in 40% of mice. Long-term survivors rejected a contralateral challenge of CT26. The buffer for Oxaliplatin is critical. The two ICD inducer mixture is promising as an agnostic sensitizer for carcinomas like colorectal carcinoma.

Here, we identified a single tyrosine residue, Y499, in Aplysiacortactin that can be phosphorylated by Src2 and is important for filopodia formation in neuronal growth cones. Phosphorylated cortactin is enriched along the leading edge and filopodia and regulates both filopodia formation and elongation.

Since aerosols are important to our climate system, we seek to observe the variability of aerosol properties within cloud systems. When applied to the satellite‐borne Moderate‐resolution Imaging Spectroradiometer (MODIS), the Dark Target retrieval algorithm provides global aerosol optical depth (AOD; at 0.55 μm) in cloud‐free scenes. Since MODIS' resolution (500‐m pixels, 3‐ or 10‐km product) is too coarse for studying near‐cloud aerosol, we ported the Dark Target algorithm to the high‐resolution (~50‐m pixels) enhanced‐MODIS Airborne Simulator (eMAS), which flew on the high‐altitude ER‐2 during the Studies of Emissions, Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys Airborne Science Campaign over the United States in 2013. We find that even with aggressive cloud screening, the ~0.5‐km eMAS retrievals show enhanced AOD, especially within 6 km of a detected cloud. To determine the cause of the enhanced AOD, we analyze additional eMAS products (cloud retrievals and degraded‐resolution AOD), coregistered Cloud Physics Lidar profiles, MODIS aerosol retrievals, and ground‐based Aerosol Robotic Network observations. We also define spatial metrics to indicate local cloud distributions near each retrieval and then separate into near‐cloud and far‐from‐cloud environments. The comparisons show that low cloud masking is robust, and unscreened thin cirrus would have only a small impact on retrieved AOD. Some of the enhancement is consistent with clear‐cloud transition zone microphysics such as aerosol swelling. However, 3‐D radiation interaction between clouds and the surrounding clear air appears to be the primary cause of the high AOD near clouds. Since aerosols are important components of our climate system, we seek to use observations to quantify aerosol properties and their interactions with clouds. To study aerosols close to clouds, we adapt a well‐known aerosol retrieval algorithm used for satellite remote sensing (lower spatial resolution) and port to airborne remote sensing (higher spatial resolution). We apply the retrieval to observations collected over the southeastern United States during late summer 2013. The resulting product suggests that total aerosol optical depth (AOD) can be greatly enhanced near clouds. To validate, we compare this retrieved AOD to other data sets and find that the enhanced AOD near clouds is only partially observed by other sensors. This suggests that the enhanced AOD is primarily a cloud adjacency or 3‐dimensional radiative effect. High‐resolution, passive remote sensing measurements can characterize aerosol/cloud environments, thus helping to interpret global AOD data sets from more comprehensive but coarser‐resolution satellite retrievals. An aerosol retrieval algorithm is ported from a satellite sensor to a higher spatial resolution aircraft sensorThe retrieval is applied and compared with other data sets from a 2013 airborne field campaign over the southeastern United StatesComparative data suggest that retrievals of enhanced aerosol optical depth (AOD) near clouds are primarily an adjacency effect

Starting from point sources, wildfire smoke is important in the global aerosol system. The ability to characterize smoke near‐source is key to modeling smoke dispersion and predicting air quality. With hemispheric views and 10‐min refresh, imagers in Geostationary (GEO) orbit have advantages monitoring smoke over once‐per‐day sensors in low‐earth orbit (LEO). However, both can be inadequate in capturing the characteristics of smoke plumes close to their sources due to too‐coarse spatial resolution (both detector and product resolution), too‐sparse temporal resolution (from LEO sensors), and too‐conservative masking. In addition to satellite observations, the Fire Influence on Regional to Global Environments and Air Quality experiment offered sub‐orbital enhanced‐MODIS Airborne Simulator (eMAS) imagery at 50 m pixel resolution—including multiple eMAS flight tracks over individual fires in short time periods. It provided opportunity to explore smoke plume characterization at various spatial and temporal scales and quantify the limitations of space sensors for describing smoke magnitude near source as well as its temporal evolution. Here we applied modified aerosol algorithm to different imagers, relaxing its masking to estimate smoke's aerosol optical depth (AOD) as close as possible to its source. We found that GEO sensors with nominal 1 km spatial resolution can match the much finer resolution eMAS retrieved mean plume AOD, as long as the retrieval spatial resolution is finer than the width of the plumes. However, the plume's maximum AOD may be drastically underestimated by satellite products. Starting from point sources, wildfire smoke is important in the global aerosol system. The ability to characterize smoke near‐source is key to modeling smoke dispersion and predicting air quality. Satellite‐based sensors provide important information about smoke plumes, however, by themselves can be inadequate in capturing the characteristics of smoke plumes close to their sources. In addition to geostationary orbit (GEO) satellite observations with 1–2 km spatial resolution observations at 10‐min intervals and low‐earth orbit (LEO) at 0.5–1 km resolution observations daily, the Fire Influence on Regional to Global Environments and Air Quality (FIREX‐AQ) experiment offered sub‐orbital (airborne) enhanced‐MODIS Airborne Simulator (eMAS) imagery at 50 m pixel resolution. With multiple eMAS flight tracks over individual fires in short time periods, FIREX‐AQ provided opportunity to explore smoke plume characterization at various spatial and temporal scales and quantify the limitations of space sensors for describing smoke magnitude near source as well as its temporal evolution. Here we applied a modified aerosol algorithm to all the different imagers, relaxing its masking to estimate smoke's aerosol optical depth (AOD) as close as possible to its source. We found that GEO sensors with nominal 1 km spatial resolution can match the much finer resolution eMAS retrieved mean plume AOD, as long as the retrieval spatial resolution is finer than the width of the plumes. However, the plume's maximum AOD may be drastically underestimated by satellite products. Remote‐sensed imagery of smoke plumes at different spatial and temporal resolutions are used to observe smoke magnitude and dispersion near fire sourcesHigh‐resolution, sub‐orbital imagery helps quantify limitations of lower‐resolution orbiting sensors for observing smoke's magnitude and evolutionSatellite products with spatial resolution less than the width of the plume can capture the mean but not the maximum smoke loading Remote‐sensed imagery of smoke plumes at different spatial and temporal resolutions are used to observe smoke magnitude and dispersion near fire sources High‐resolution, sub‐orbital imagery helps quantify limitations of lower‐resolution orbiting sensors for observing smoke's magnitude and evolution Satellite products with spatial resolution less than the width of the plume can capture the mean but not the maximum smoke loading

Background This study explored the relationship between personality attributes and substance use disorder (SUD). Research has identified specific personality dimensions, such as neuroticism, psychoticism, antisocial personality traits, paranoia, and anxiety, as contributing factors on the way to the initiation, continuation, and relapse of SUD.Purpose To explore this connection, we examined the personality profiles of subjects with alcohol use disorder (AUD) and opioid use disorder (OUD).Methods A total of 928 subjects, 320 with AUD, 490 with OUD and 118 healthy controls (HC), in the age range of 16–65 years were recruited in the study. The Clinical Profile Sheet and the Multiphasic Personality Questionnaire (MPQ) were administered to HC and patients who fulfil the diagnostic criteria for substance dependence as defined by ICD-10 (WHO-1992).Results We found significant differences in personality profiles between individuals with OUD and AUD. Patients with AUD scored higher than OUD on the MPQ subscales for depression, mania, paranoia, and antisocial personality traits. All subscales of the MPQ showed elevated scores in subjects with SUD compared to HC.Conclusion Elevated scores on the MPQ subscales suggest that personality factors may contribute to the pattern of substance use and misuse in this cohort.

Background Shilajit a natural phytomineral has a proven record of treating many human body ailments.Purpose This study aimed to explore the influence of Shilajit on cell proliferation and apoptosis induction in oral cancer cells (OCC) and to comprehend the molecular mechanism associated with OCC migration.Materials and Methods Human gingival fibroblast (hGF) and OCC (KB-1 (KERATIN-forming tumor cell line HeLa)) were exposed to Shilajit solution dilutions. Cell growth and apoptosis were measured by MTT and Annexin-V tests (control/test group). Cellular morphology using an inverted microscope, cellular apoptosis using acridine orange/ethidium bromide dual staining, reactive oxygen species production analysis using 2′,7′-dichlorodihydrofluorescein diacetate (DCFH-DA) staining, and gene protein expression using real-time polymerase chain reaction test were used to measure study outcomes. The data enumerated were the average of three trial experiments. Categorical and numerical data were expressed as frequency distribution and means, respectively. Differences in groups (control/test; zero/24 h/48 h) were determined using Student’s t-test and one way analysis of variance, with probability ‘p’ value considered significant at ≤0.05.Results The viability of OCC exhibited a concentration and time-dependent response to Shilajit. Notably, Shilajit demonstrated selectivity against cancer cells. Through an examination of the Annexin-V apoptosis assay, it was observed that Shilajit induces apoptosis by upregulating the proapoptotic gene expression (p≤ 0.05) and downregulating antiapoptotic proteins (p≤ 0.05). Furthermore, the impact of Shilajit on cell migration decreased significantly when compared to control cells through modulating the urokinase-type plasminogen activator (uPA) and its receptor (uPAR) and chemokines gene expression.Conclusion Shilajit exhibited greater cytotoxicity, decreased OCC proliferation and migration, and initiated OCC apoptosis as equivalent to normal cells. These promising outcomes indicate that Shilajit holds potential as a robust, promising option for oral cancer treatment, underscoring the need for further research in this domain.

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ABSTRACTBackgroundIndia 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.ObjectivesTo determine the number of ACF cycles implemented in 2021 at national, state (n = 36) and district (n = 768) level and quality indicators for the first ACF cycle.MethodsIn 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).ResultsOf 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.ConclusionIn 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.

This study was designed to compare and detect possible differences between the metacarpal length (MCL) and all metacarpal length ratios in left - and right hands of female and male individuals of Haryanvi and J&K populations.