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India is one of the largest contributors to anthropogenic emissions during the recent decade associated with its rapid economic growth in India. Trace gases are important components in the climate change process and due to that climate change, there will be a change in their atmospheric concentrations as the climate is sensitive to Earth's; therefore, proper assessment of trace gases is necessary for ongoing sudden changes in climate. In this study, we used remote-sensing datasets from the Atmospheric Infrared Sounder (AIRS) and Ozone Monitoring Instrument (OMI) to analyze the spatio-temporal variations of four trace gases, like methane (CH 4 ), ozone (O 3 ), carbon monoxide (CO), and nitrogen dioxide (NO 2 ) over India region during 2006-2015 and taken four seasons (i.e., winter, spring, summer, and winter) to interpret the seasonal variation. The project focuses on the temporal pattern of pollutant trace gases i.e., monthly, seasonal, and annual mean variations of trace gases, trend analysis of trace gases, and a comparison of the seasonal behavior of the trace gases by trend analysis was assessed. Higher concentrations of CO show east-to-west, CH 4 show north-to-south, and O 3 south-to-north gradient, indicating the variations in trace gases due to the impact of emissions and local meteorology. On the other hand, due to immense population density, huge traffic emissions, tremendous, polluted air, and overgrown industrial activities, total NO 2 concentrations shoot up over Delhi, Lucknow, and Kolkata. Now as a result of seasonal variation in the long-range transport of air parcels and biomass burning activities, all trace gases shown significant seasonal variations in the spring season and substantially reduced in the summer season. However, in the winter season, O 3 concentration evaluates minimum due to less amount of heat on cold days which leads to the reduction of O 3 formation. Due to trace gases, all are significant to get regional climate variability. In this study by taking 2006 as a base year and investigate the behaviors of gases for 2007-2015 years to exhibit the increment and decrements in four seasons of all trace gases by taking the most populated 11 different cities of India.

Germline BRCA2 mutation carriers frequently develop luminal-like breast cancers, but it remains unclear how BRCA2 mutations affect mammary epithelial subpopulations. Here, we report that monoallelic Brca2 mut/WT mammary organoids subjected to replication stress activate a transcriptional response that selectively expands Brca2 mut/WT luminal cells lacking hormone receptor expression (HR-). While CyTOF analyses reveal comparable epithelial compositions among wildtype and Brca2 mut/WT mammary glands, Brca2 mut/WT HR- luminal cells exhibit greater organoid formation and preferentially survive and expand under replication stress. ScRNA-seq analysis corroborates the expansion of HR- luminal cells which express elevated transcript levels of Tetraspanin-8 ( Tspan8 ) and Thrsp , plus pathways implicated in replication stress survival including Type I interferon responses. Notably, CRISPR/Cas9-mediated deletion of Tspan8 or Thrsp prevents Brca2 mut/WT HR- luminal cell expansion. Our findings indicate that Brca2 mut/WT cells activate a transcriptional response after replication stress that preferentially favours outgrowth of HR- luminal cells through the expression of interferon-responsive and mammary alveolar genes. Here the authors study how BRCA2 mutations affect mammary epithelial subpopulations. They report that Brca2 mut/WT mammary organoids subjected to replication stress activate a transcriptional response that selectively expands Brca2 mut/WT HR- luminal cells.

This paper presents a master–slave (MS) flip-flop design that employs a single-phase clock and a mixed latch topology, utilizing only 19 transistors (13 NMOS and 6 PMOS) to achieve ultra-low power consumption and high-speed operation. The proposed flip-flop is designed to minimize clock-to-Q (TCQ) delay, average power dissipation, and leakage current, making it suitable for energy-efficient VLSI systems. It was implemented in a 45 nm technology node and evaluated under process-voltage-temperature (PVT) variations, temperature fluctuations, and Monte Carlo simulations to verify robustness and reliability. Post-layout analysis confirmed the design’s correctness through successful Design Rule Check (DRC) and Layout Versus Schematic (LVS) verification, with a compact area of 19.106 μm². Furthermore, for fair comparison, both the proposed and baseline flip-flop designs were implemented using the same 90 nm CMOS technology in the Cadence Virtuoso environment. Compared to the Adaptive Data Track Flip-Flop (ADTFF), the proposed design achieves a 13.24% reduction in TCQ delay and a 37.19% reduction in average power, demonstrating its effectiveness for low-power, high-performance digital applications.

Endoscopic thyroidectomy (ET) and its various approaches are widely used for benign and malignant thyroid nodules. Objective of our review is to compare endoscopic thyroidectomy (ET) and its various approaches with open thyroidectomy (OT) regarding safety and benefits. Electronic search was performed on MEDLINE (via PubMed) and the Cochrane Central Register of Controlled Trials (CENTRAL). Randomized controlled trials (RCTs), well-designed cohorts, or case-controlled studies were included. Participants of any age and gender with a diagnosis of a thyroid nodule/goiter were included. We assessed the included trials using the Newcastle–Ottawa Scale to determine the methodological quality. Nineteen studies were included in this review. The risk of postoperative transient vocal cord palsy in ET was found to be higher than in OT (OR 4.47, 95% CI 2.92 to 6.86). Swallowing discomfort in ET was found to be much lower than OT (OR 0.06, 95% CI 0.01 to 0.31). No statistically significant difference was found in the risk of transient hypocalcemia, permanent hypocalcemia, permanent vocal cord palsy, hematoma/postoperative bleeding, seroma formation, and total complications. The operative time for ET was higher than for OT. The drain output after ET was higher than OT. Less number of lymph nodes were removed during ET compared to OT. No statistically significant difference was found in the length of hospital stay. ET can be used as a comparable replacement to OT in selected patients. ET is a safe technique with comparable long-term complications to OT.

Leclercia adecarboxylata was isolated in pure culture from a peritonsillar and lateral pharyngeal abscess in an immunocompetent host. To our knowledge, this is the first case of infection caused by this microorganism being found in an odontogenic area of the head and neck.

Detecting texts that contain semantic-level new information is not straightforward. The problem becomes more challenging for research articles. Over the years, many datasets and techniques have been developed to attempt automatic novelty detection. However, the majority of the existing textual novelty detection investigations are targeted toward general domains like newswire. A comprehensive dataset for scientific novelty detection is not available in the literature. In this paper, we present a new triplet-based corpus (SciND) for scientific novelty detection from research articles via knowledge graphs. The proposed dataset consists of three types of triples (i) triplet for the knowledge graph, (ii) novel triplets, and (iii) non-novel triplets. We build a scientific knowledge graph for research articles using triplets across several natural language processing (NLP) domains and extract novel triplets from the paper published in the year 2021. For the non-novel articles, we use blog post summaries of the research articles. Our knowledge graph is domain-specific. We build the knowledge graph for seven NLP domains. We further use a feature-based novelty detection scheme from the research articles as a baseline. Moreover, we show the applicability of our proposed dataset using our baseline novelty detection algorithm. Our algorithm yields a baseline F1 score of 72%. We show analysis and discuss the future scope using our proposed dataset. To the best of our knowledge, this is the very first dataset for scientific novelty detection via a knowledge graph. We make our codes and dataset publicly available at https://github.com/92Komal/Scientific_Novelty_Detection.

Research in Natural Language Processing (NLP) is increasing rapidly; as a result, a large number of research papers are being published. It is challenging to find the contributions of the research paper in any specific domain from the huge amount of unstructured data. There is a need for structuring the relevant contributions in Knowledge Graph (KG). In this paper, we describe our work to accomplish four tasks toward building the Scientific Knowledge Graph (SKG). We propose a pipelined system that performs contribution sentence identification, phrase extraction from contribution sentences, Information Units (IUs) classification, and organize phrases into triplets (subject, predicate, object) from the NLP scholarly publications. We develop a multitasking system (ContriSci) for contribution sentence identification with two supporting tasks, viz.Section Identification and Citance Classification. We use the Bidirectional Encoder Representations from Transformers (BERT)—Conditional Random Field (CRF) model for the phrase extraction and train with two additional datasets: SciERC and SciClaim. To classify the contribution sentences into IUs, we use a BERT-based model. For the triplet extraction, we categorize the triplets into five categories and classify the triplets with the BERT-based classifier. Our proposed approach yields the F1 score values of 64.21%, 77.47%, 84.52%, and 62.71% for the contribution sentence identification, phrase extraction, IUs classification, and triplet extraction, respectively, for non-end-to-end setting. The relative improvement for contribution sentence identification, IUs classification, and triplet extraction is 8.08, 2.46, and 2.31 in terms of F1 score for the NLPContributionGraph (NCG) dataset. Our system achieves the best performance (57.54% F1 score) in the end-to-end pipeline with all four sub-tasks combined. We make our codes available at: https://github.com/92Komal/pipeline_triplet_extraction.

Phyllodes tumour is a rare breast tumour which is locally invasive, and full thickness chest wall involvement by phyllodes is rarely reported. A woman presented with recurrent phyllodes tumour and multilobulated exophytic mass of size 18.5×5.3 cm in anterior chest wall which was abutting the right 2nd−7th rib, left 3rd−5th rib and costal cartilages. She underwent wide excision of the left chest wall tumour with excision of left 3rd−5th rib, with polypropylene mesh and pedicled lattismus dorsi myocutaneous flap reconstruction. After recovery, 3 weeks later, she underwent wide excision of the phyllodes tumour on the right chest wall with excision of 2nd–7th rib, lateral border of sternum, right crus of the diaphragm and the lower lobe of the right lung. Anterior chest wall was reconstructed using scaffold made from Steinmann pins and polypropylene mesh with greater omentum pedicled flap and split thickness skin graft.

BackgroundNon-small cell lung cancer (NSCLC) accounts for the majority of lung cancer cases, with EGFR-mutant NSCLC among never-smokers particularly prevalent in Asian populations. A major clinical challenge in treating advanced NSCLC is the development of resistance to tyrosine kinase inhibitors (TKIs), highlighting the need to comprehensively profile the cellular mechanisms underlying drug resistance. We propose to address this by investigating the adaptive features of residual and resistant cancer cells, as well as the role of the tumour microenvironment in sustaining tumour growth, resistance, and disease progression.MethodsIn this study, we utilise single-nucleus and spatial transcriptomic profiling, integrated with matched genomic sequencing, to characterise the response of EGFR-mutant tumours in 41 samples from 34 NSCLC patients before, during, and after TKI treatment, including cases with acquired resistance. We present an analytical framework that maps consensus gene expression programs in residual cancer and immune cells that persist through treatment and at resistance. Furthermore, we investigate how interactions between cancer and immune cells, including T lymphocytes and mononuclear phagocytes, shape tumour cell states.ResultsWe present the most comprehensive single-cell atlas to date of EGFR-mutant NSCLC. Our findings reveal that cancer cells engage coordinated gene expression programs that define distinct cell states following TKI treatment. Moreover, our data suggest that immune-mediated cues, particularly metabolic and paracrine signals from myeloid populations, may contribute to the persistence of treatment-tolerant cancer cell subsets.ConclusionsAs part of our ongoing efforts, we are integrating data from clinical trials and preclinical models to further dissect immune dynamics between treatment-persistent and fully resistant tumours, with the ultimate goal of guiding therapeutic strategies that target early adaptive and persister cancer cell populations.

Cell culture in shake flask and air-lift bioreactor was carried out to exploit the potential of Arnebia sp. for napthoquinone metabolite production. Cell suspension cultures of Arnebia were established from friable callus in liquid MS medium supplemented with 6-benzylaminopurine (BAP) (10 μM) and indole-3-butyric acid (IBA) (5 μM). Growth kinetic studies were done by using settled cell volume and fresh/dry cell weight method. Suspension cultures were maintained by sub-culturing at 10 days interval. A two-stage culture system is employed using growth medium (GM) and modified M9 medium (production medium) for cell biomass and naphthoquinone pigment production, respectively. Results showed that cultivation of cells under dark conditions at room temperature (25 ± 2 °C) enhanced the cell biomass from 100 to 625 g l −1 . The pigment production was also found to be increased in dark conditions at room temperature. Alkaline pH found to have positive effect on pigment yield. In case of M9 medium constituents, absence of Na 2 SO 4 does not affect the pigment yield. The current approaches have the cumulative effect to meet an increased level of (25.5 μg/ml) metabolite production in air-lift bioreactor.