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Caste Inequality in Occupational Exposure to Heat Waves in India
No full textIndia is a leading global hot spot for extreme heat waves induced by climate change. The social demography of India is centered on its caste hierarchy rooted in endogamous occupational groups. We investigate the association between caste and climate inequality by studying occupational exposure during the 2019 and 2022 heat waves. We combine high spatiotemporal resolution heat stress information from satellite imagery with a large nationally and regionally representative labor force survey with rich socioeconomic and demographic information (n > 100,000 individuals). The slope of the heat stress dose–workhours curve corresponding to the marginalized caste groups is between 25% and 150% steeper than that for dominant caste groups for UTCI (Universal Thermal Climate Index) thresholds between 26°C and 35°C. Our models control for other economic-demographic confounders, including age, gender, education, and economic status, besides political-geographic controls and fixed effects. Our robust evidence for the association between caste identity and exposure to heat stress shows why adaptation and mitigation plans in India must account for the hierarchical social order characterized by the “division of laborers” along caste lines rather than the mere division of labor. Methodologically, our analysis demonstrates the utility of pairing satellite imagery and detailed demographic data
Novel Deep Learning Transformer Model for Short to Sub‐Seasonal Streamflow Forecast
No full textAccurate short-to-subseasonal streamflow forecasts are becoming crucial for effective water management in an increasingly variable climate. However, streamflow forecast remains challenging over extended lead times, uncertainty in meteorological inputs, and increased frequency and variability in extreme weather and climate events. We implemented a Future Time Series Transformer (FutureTST) model for streamflow forecasting that separately integrates past meteorological and streamflow data while incorporating future weather conditions. FutureTST achieves a mean Nash-Sutcliffe Efficiency (NSE) of 0.82 to 0.67 for 1- to 30-day streamflow forecasts. Incorporating upstream streamflow information improved forecast accuracy by up to 10%. During real-time forecast, FutureTST maintains higher forecast skills of 9.03 for 1-day and 5.74 for 14-day forecasts. In contrast, calibrated process-based hydrological model forecasts become unreliable beyond a 4-day lead time. Our findings demonstrate the potential of FutureTST as a reliable streamflow forecasting tool that offers a valuable addition to operational flood monitoring systems and climate-resilient decision-making
IBCL-295: Prognostic value of neutrophil-to-lymphocyte ratio in follicular lymphoma: A tertiary care analysis
No full textBackground:
Follicular lymphoma (FL) is the second most common type of indolent non-Hodgkin lymphoma. Despite its generally favorable prognosis, a subset of patients experience early progression or transformation, underscoring the need for accessible prognostic markers. The neutrophil-to-lymphocyte ratio (NLR), a surrogate marker of systemic inflammation, has been investigated in various malignancies; however, its prognostic utility in FL remains unclear, particularly in real-world settings.
Objectives:
Assess the prognostic value of baseline NLR for overall survival (OS) and progression-free survival (PFS) in patients with FL treated at a tertiary care center.
Methods:
We conducted a retrospective analysis of 107 patients diagnosed with FL between 2012 and 2023 at a tertiary care center. Baseline NLR was calculated from complete blood counts performed prior to initiation of therapy. Receiver operating characteristic curve analysis was used to evaluate the ability of NLR to predict OS and PFS. The area under the curve (AUC) and optimal NLR cutoff values were determined using Youden’s index. Results:
For OS, the NLR had an AUC of 0.538 (95% CI: 0.321–0.754), indicating limited predictive value. The optimal NLR cutoff for OS prediction was 1.605, yielding a sensitivity of 54.5% and a specificity of 70.8%. For PFS, the NLR had an AUC of 0.506 (95% CI: 0.391–0.621), again reflecting poor discrimination. The optimal cutoff was 1.973, with a sensitivity of 63.8% and a specificity of 53.5%. No statistically significant association was observed between NLR and survival outcomes in either univariable or multivariable models.
Conclusions:
In this real-world cohort of FL patients, baseline NLR showed limited utility in predicting OS or PFS. Larger, prospective studies are needed to further elucidate its value in risk stratification
A comprehensive targeted panel of 295 genes: Unveiling key disease initiating and transformative biomarkers in multiple myeloma
No full textBackground:
Multiple myeloma (MM) is a hematological malignancy that progresses from a benign precursor stage known as Monoclonal Gammopathy of Undetermined Significance (MGUS). Distinguishing MM from MGUS at the molecular level by identifying key biomarkers, genomic alterations, and gene interactions is critical for early detection and deeper insight into MM pathogenesis.
Methods:
We have developed an advanced genomics domain-rooted AI-workflow that combines the traditional statistical mutation profiling methods with the proposed BIO-DGI (Bio-Inspired Graph Network Learning-based Gene-Gene Interaction) attention-based deep learning architecture exploiting gene-gene interaction. Our proposed framework utilizes multiple variant profiles including SNVs and CNVs extracted from WES data and SVs extracted from WGS data. Rigorous post-hoc validation including ShAP analysis, community analysis, survival analysis, Geo2R validation, and pathway enrichment analysis are utilized to eventually design the panel.
Results:
BIO-DGI outperformed traditional machine learning and deep learning methods on quantitative metrics and identified the highest number of MM-relevant genes in post-hoc analysis. ShAP analysis of gene SNV profiles, community analysis of the disease-specific gene-gene graph, survival analysis of SNVs, CNVs, and SVs led to the design of 295 gene-panel for multiple myeloma. The pathway enrichment analysis confirmed strong association of our gene-panel with the MM-related biological pathways.
Conclusion:
This study presents a comprehensive framework combining bio-inspired graph learning, multi-variant genomic profiling, post-hoc interpretability, and survival-driven clinical validation to advance biomarker discovery in multiple myeloma. By integrating exomic variants with network-based gene-gene interactions through the novel BIO-DGI model, we developed a clinically curated 295-gene panel for MM
Wastewater surveillance for Salmonella Typhi and its association with seroincidence of enteric fever in Vellore, India
No full textBackground
Blood culture-based surveillance for typhoid fever has limited sensitivity, and operational challenges are encountered in resource-limited settings. Environmental surveillance targeting Salmonella Typhi (S. Typhi) shed in wastewater (WW), coupled with cross-sectional serosurveys of S. Typhi-specific antibodies estimating exposure to infection, emerges as a promising alternative.
Methods
We assessed the feasibility and effectiveness of wastewater (WW) and sero-surveillance for S. Typhi in Vellore, India, from May 2022 to April 2023. Monthly samples were collected from 40 sites in open drainage channels and processed using standardized protocols. DNA was extracted and analyzed via quantitative PCR for S. Typhi genes (ttr, tviB, staG) and the fecal biomarker HF183. Clinical cases of enteric fever were recorded from four major hospitals, and a cross-sectional serosurvey measured hemolysin E (HlyE) IgG levels in children under 15 years of age to estimate seroincidence.
Results
7.50% (39/520) of grab and 15.28% (79/517) Moore swabs were positive for all 3 S. Typhi genes. Moore swab positivity was significantly associated with HF183 (adjusted odds ratio (aOR): 3.08, 95% CI: 1.59–5.95) and upstream catchment population (aOR: 4.67, 1.97–11.04), and there was increased detection during monsoon season - membrane filtration (aOR: 2.99, 1.06–8.49), and Moore swab samples (aOR: 1.29, 0.60–2.79).
Only 11 blood culture-confirmed typhoid cases were documented over the study period. Estimated seroincidence was 10.4/100 person-years (py) (95% CI: 9.61 - 11.5/100 py). The number of S. Typhi positive samples at a site was associated with the estimated sero-incidence in the site catchment population (incidence rate ratios: 1.14 (1.07–1.23) and 1.10 (1.02–1.20) for grab and Moore swabs respectively.
Conclusions
These findings underscore the utility and effectiveness of alternate surveillance approaches to estimating the incidence of S. Typhi infection in resource-limited settings, offering valuable insights for public health interventions and disease monitoring strategies where conventional methods are challenging to implement
W-Doped Cs<sub>2</sub>SnCl<sub>6</sub> for Near-Infrared Emission
No full text0D perovskite derivatives such as Cs2WCl6 and Cs2WOxCl6-x have been recently shown to emit near-infrared (NIR) radiation. The d–d electronic transition of W4+/W5+ yields an NIR emission. However, the close proximity of those ions can quench the photoluminescence via concentration quenching. To address this issue, here we dilute the emission centers by doping a small amount of W into the Cs2SnCl6 0D perovskite. The results suggest that the dopant centers are [WOCl5]2- replacing [SnCl6]2- octahedra in the host lattice. The optimal 3.3% W-doped Cs2SnCl6 exhibits NIR (965 nm) emission with over 52 times higher intensity compared to that of Cs2WOxCl6-x. The suppression of concentration quenching in W-doped Cs2SnCl6 also significantly alters its temperature-dependent (7–300 K) photoluminescence compared to that of Cs2WOxCl6-x. Finally, we demonstrated NIR phosphor-converted light-emitting diodes of W-doped Cs2SnCl6 showing an output power of 10.3 mW at 400 mA. This is the first report of W doping in 0D perovskites showing its potential as an NIR phosphor
Transfer hydrogenation catalyzed by a bifunctional cobalt‐based supramolecular complex offering hydrogen bonding cavities
No full textA cobalt-containing supramolecular complex, Co-L, is presented, offering dual functionalities. Co-L contains both Lewis acidic–basic sites provided by the cobalt ions and hydroxyl groups, and Brønsted acid sites from the free carboxylic acid groups. This complex forms a 3D layered structure via assorted intra-layer and inter-layer hydrogen bonds. Functioning as a heterogeneous catalyst, Co-L efficiently promotes the base-free transfer hydrogenation of carbonyl and imine compounds, while using environmentally benign isopropanol as a hydrogen donor. The Co-L illustrates remarkable catalytic activity across diverse substrates, including aldehydes, ketones, and imines, achieving high conversions and exclusive selectivity. The biomass-derived substrates, such as furfural, levulinic acid, and 5-methylfurfural, along with pharmaceutically significant ones, such as cinnamaldehyde and estrone, were effectively transformed to their target products. The mechanistic studies revealed a synergy between the Lewis acid–base pairs (Co2+/OH−) and Brønsted acid sites (-COOH) during the catalysis. A combination of spectral and molecular docking studies asserts the role of dual functionalities in Co-L. An ester analogue of Co-L, EtCo-L, showed lower catalytic activity, asserting the role of Brønsted acidic groups
Indian solar and heliospheric physics vision: Fundamental science to a space weather resilient society
No full textThe Sun is the only star that harbours a planet known to host life. Our home, the Earth, and other solar system planets reside within the heliosphere – the sphere of influence of the Sun. Within this domain, the Sun’s radiation, energetic particles, plasma wind, magnetic fluxes, and dynamic events, such as flares and coronal mass ejections influence planetary environments. While the Sun provides the basis for life, it also produces severe space weather that is hazardous to humanity’s space-based technologies. Long-term solar variations also influence planetary evolution and habitability. Dynamic solar variability originates in magnetohydrodynamic processes in its interior and atmosphere that provide a window to the plasma universe. Therefore, exploring the origin, impact, and overarching astrophysical implications of the Sun’s activity is of fundamental importance to humanity. In this vision for solar and heliospheric physics – contributing to the vision document of the Astronomical Society of India – we provide a brief synopsis of the current status of the field, focus on outstanding challenges that are expected to drive the field over the next decade or so, and based on an assessment of the expertise available within India, we provide specific recommendations that the Indian community is well poised to address
Study of rotational temperatures with a multi-wavelength photometer from the Indian equatorial station Tirunelveli
No full textA multi-wavelength photometer (MWP) was operated at the equatorial station Tirunelveli (8.7°N, 77.8°E geographic), India, to study different nightglow emissions. In the present work, the intensities of the P1(2) and P1(4) lines of the OH(6,2) Meinel band were used to derive rotational temperatures in the mesosphere-lower thermosphere (MLT) region during February–April 2015. The methodology adopted to derive rotational temperatures using the MWP data is discussed in detail. A comparison with temperatures measured by the Sounding of the Atmosphere by Broadband Emission Radiometry (SABER) instrument onboard NASA's TIMED satellite was performed to validate the MWP-derived rotational temperatures. An excellent correlation was observed between the MWP-derived and SABER temperatures, with a mean temperature difference of ∼15 K. The plausible reasons for this temperature bias are discussed in this work. In addition, the P1 line intensities of the OH(6,2) band and temperatures obtained with the MWP were compared with the OH broadband intensity acquired by a co-located all-sky airglow imager (ASAI). Furthermore, the local time variation of the MWP-derived temperatures was studied, and the results were compared with the NRLMSISE-00 model simulation. This study demonstrates the effectiveness of the MWP in measuring MLT temperatures and highlights the importance of multi-instrument comparisons for validating the temperatures and airglow intensity
Topologically reconfigurable nematic emulsions
No full textIn emulsions of multicomponent fluids, the dispersed phase forms tiny droplets in the continuous phase. In situ control and manipulation to achieve diversity in emulsion droplets for emerging applications is challenging. In a liquid crystal-based emulsion, the surface anchoring of the molecules at the isotropic fluid-liquid crystal interface introduces elastic distortions that result in anisotropic interparticle interactions, similar to electrostatic interactions between multipoles, which also lends a naming analogy as elastic dipoles, quadrupoles, and higher. However, controlling the anchoring condition at the interface at will is rarely achieved. Here, we present an emulsion system in which silicone oil droplets in a nematic liquid crystal spontaneously induce conic surface anchoring, forming elastic hexadecapoles without any surfactant. The conic degenerate surface anchoring shows continuous reversible anchoring transition to tangential and homeotropic below and above the ambient temperature, respectively. We introduce a physical design principle and in situ control to achieve three-phase compound droplets with diverse morphologies and topologies by fusing elastic hexadecapoles of oil droplets with elastic dipoles of glycerol droplets. The surrounding director field and the resulting defect structure of the compound droplets are analyzed by numerical simulations. Our approach to forming compound droplets will allow the on-demand design of building blocks for engineered emulsions for reconfigurable composite materials