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Revisiting bioluminescence and sucrose utilization in aquatic pathogens Vibrio harveyi and V. campbellii using genome-wide in silico mapping and phenotyping
Metformin suppresses PPARδ-driven CD47 transcription to enhance macrophage phagocytosis in lung cancer
Four year mortality and quality of life after ICU treatment for COVID 19 related acute respiratory distress syndrome
Abstract Severe COVID-19 leading to ARDS and ICU admission is associated with high early mortality, yet data on long-term outcomes and societal burden remain limited, particularly in Central and Eastern Europe. To describe 4-year mortality, patient-reported functional status and health-related quality of life (HRQoL) among ICU-treated COVID-19 ARDS patients, and to explore early factors associated with short- and long-term mortality as well as long-term recovery. Single-center retrospective–prospective cohort study with structured 4-year telephone follow-up. 283 adults treated in the Temporary ICU Hospital in Zielona Góra, Poland (December 2020–July 2021). Follow-up interviews were completed in 81 of 157 confirmed 4-year survivors. Associations with 30-day mortality and late mortality (among 30-day survivors) were explored using multivariable logistic regression. Survivors completed a structured interview assessing HRQoL (EQ-5D-5 L/EQ-VAS), dyspnoea severity assessed with the mMRC scale, functional status assessed with PCFS, fatigue, brief cognitive screening items, return to work, rehabilitation use, and financial burden. A cumulative post-ICU impairment score (0–6 domains) was constructed. Cost estimates were exploratory and based on public ICU reimbursement rates and patient-reported rehabilitation burden. Thirty-day mortality was 29.0%, and cumulative 4-year mortality was 45%. In adjusted analyses, older age and higher white blood cell count at ICU admission were associated with mortality endpoints (model discrimination up to AUC 0.86, depending on endpoint). Among 4-year survivors, 27.5% reported clinically relevant fatigue, 46.8% insomnia, and a substantial proportion reported persistent limitations across functional and EQ-5D domains. Rehabilitation was reported by 39% and was associated with lower QALY, likely reflecting greater baseline impairment. Median 4-year QALY was 3.7, varying significantly by fatigue, dyspnoea, return-to-work status, and subjective cognitive complaints. Among ICU-treated COVID-19 ARDS patients, long-term mortality remained high and many survivors reported persistent multidomain impairment years after discharge. These findings support structured post-ICU follow-up pathways and targeted rehabilitation and occupational support for long-COVID survivors.
Dissecting a two-domain alginate lyase of family PL6 reveals a mechanistic basis for substrate specificity and enzyme activity
Associations between political orientation and allyship: Evidence from potential allies and their LGBTQ+ close others
Abstract To support the LGBTQ+ community , many straight , cisgender individuals position themselves as allies to their cause. It is possible that those identifying as liberal may champion LGBTQ+ causes more passionately than those identifying as conservative , though it is also possible that liberals’ self-perceptions do not align with how LGBTQ+ individuals perceive them. In this study , we systematically investigated the relationship between political orientation and allyship to the LGBTQ+ community. We recruited 378 dyads composed of a cisgender , straight individual and an LGBTQ+ close other. Findings suggested that self-perceptions of allyship (from cisgender , straight individuals) were largely consistent with evaluations from LGBTQ+ close others. In line with our expectations , on average , liberals (compared to conservatives) both viewed themselves and were perceived as better allies. However , there was a small but significant tendency for liberals to overestimate their allyship relative to conservatives. In addition , exploratory analyses revealed other-perceived allyship was positively associated with higher interpersonal trust , underscoring allyship’s importance in close relationships. These findings contribute to a growing understanding of the ideological and interpersonal antecedents of allyship and inform strategies for fostering stronger , more authentic relationships with the LGBTQ+ community. The stage 1 protocol for this Registered Report was accepted in principle on 11/15/2024. The protocol, as accepted by the journal, can be found at: https://doi.org/10.17605/OSF.IO/2Q7W6 .
Large extracellular vesicles regulate endothelial angiogenic potential via paracrine and autocrine signaling
Integrating 3D structural modelling and seismic interpretation to optimize hydrocarbon development in the Early Miocene Nukhul Formation, October Oil Field, Gulf of Suez, Egypt
Abstract This study presents an integrated 3D structural modelling workflow as a quantitative framework for applying advanced geological understanding to the spatial distribution of discrete and continuous reservoir properties of the underexplored, structurally complex Nukhul Formation in the October Oil Field. The updated 3D structural model was constructed by integrating high-resolution seismic interpretation with multidisciplinary subsurface datasets, including electric logs, detailed stratigraphic correlations, petrophysical evaluation, and production performance data from drilled wells. The current study specifically evaluates the structural controls on reservoir distribution and trapping styles within the field by combining 3D seismic interpretation with well-log and core-derived information. The refined model reveals a fault architecture dominated by a NNW–SSE (Clysmic) trend, with major faults dipping south-southwest (SSW) and horizons oriented northeast (NE), as determined from dipmeter data and seismic interpretation. The Nukhul reservoir is defined by a three-way dip closure, bounded by fault-dependent seals, where sealing capacity is governed by fault throw that juxtaposes permeable sand layers against impermeable lithologies. This configuration effectively inhibits cross-fault hydrocarbon migration, preserving attic accumulations. By integrating geological, geophysical, and petrophysical datasets, the new model significantly improves the delineation of attic targets, fault-bounded compartments, and reservoir–seal juxtapositions. Consequently, it provides refined well-placement recommendations, including high-potential attic infill drilling locations. Furthermore, the model establishes a technically robust basis for reservoir management and depletion planning, aiming to maximize recovery while minimizing water-handling risks. These outcomes demonstrate the value of incorporating new seismic and well datasets into legacy models and highlight their potential for reducing uncertainty in structurally complex syn-rift settings. Beyond the October Field, the updated structural modelling approach has broader implications for syn-rift petroleum systems in the Gulf of Suez and analogous rift basins, offering a predictive tool for fault-seal analysis, volumetric assessment, reservoir performance evaluation, and optimized drilling strategies.
Writers and readers of sialylation in immunoregulation in cancer
Shaking and withering intensity from oolong tea processing alters the chemical and sensory quality of tobacco
Deregulated translation of the transcription factor Myt3 predisposes islet β cells to dysfunction under obesity-induced metabolic stress
Analysis of the resistance of small peptides from Periplaneta americana to H2O2-induced apoptosis in KGN Cells based on miRNA-seq
HSP-1-specific nanobodies alter chaperone function in vitro and in vivo
A multimodal data framework for motorcyclist injury severity on rural undivided roads
Unraveling the regioselectivity of Ophiostoma piceae sterol esterase as a case study for lipases with wide acyl-binding tunnel entrances
Adaptive lateral constraint-driven POCS interpolation method
Abstract The Projection onto Convex Sets (POCS) interpolation algorithm is widely adopted in seismic data processing, benefiting from its low computational complexity and strong data adaptability. However, the conventional POCS method fails to fully explore the inter-trace correlation information of seismic data, which leads to interpolation results with poor lateral continuity and high interpolation noise. To address this issue, this paper takes the traditional alternating projection framework for biconvex sets as the foundation, introduces a laterally constrained convex set, and thus effectively improves the interpolation quality of seismic data in terms of lateral continuity, signal-to-noise ratio (SNR) and interpolation accuracy. The specific research work is outlined as follows: First, the triple convex sets are defined in detail, the projection formula of the lateral constrained set is derived, and the triple convex set interpolation workflow is established. Second, the convergence of the new algorithm is theoretically proven, and its computational efficiency is compared and analyzed, which provides a reliable theoretical foundation for the stability of the algorithm. Finally, to verify the effectiveness of the proposed method, experiments are conducted on both synthetic seismic data and field seismic data, with a quantitative comparison of the interpolation accuracy between the two algorithms. The results demonstrate that the proposed algorithm significantly enhances interpolation accuracy while ensuring reconstruction efficiency, and therefore possesses excellent practical value.
A conformation-dependent hydrophobic degron determines Rab9a-mediated vesicular trafficking
PoseShot: hybrid CNN–BiLSTM transformer model for free throw action recognition via pose analysis
Abstract The evaluation of basketball free throw techniques has traditionally relied on subjective assessments, which introduces inherent biases and inconsistencies in performance analysis. This study presents PoseShot, a novel dual channel hybrid CNN-BiLSTM-Transformer Model that facilitates the comprehensive analysis of free throw mechanics with data-driven insights. Unlike conventional human activity recognition that focuses on coarse activity labels, PoseShot is designed to analyze fine-grained, phase-dependent mechanics within a single basketball free throw motion. The proposed framework integrates training footage with precise body posture angle calculations via a dual-channel deep learning architecture to enable the capture of subtle technical variations. Our innovative approach synthesizes convolutional neural networks (CNN) for spatial feature extraction, bidirectional long short-term memory (BiLSTM) for temporal sequence processing, and a transformer encoder for enhanced contextual understanding of motion dynamics. The model demonstrates exceptional performance, achieving an F 1 -score of 95.76%, precision of 95.72%, and recall of 95.80%. These metrics surpass the performance of established architectures, including DenseNet, Swin Transformer, and Vision Transformer, particularly for the analysis of complex throwing motions. By incorporating both spatial features and postural dynamics, PoseShot provides accuracy in motion analysis. Empirical evaluation reveals PoseShot’s capacity to identify crucial biomechanical determinants of successful free throws, thus offering quantifiable insights for performance enhancement. Since the model’s analysis elucidates the intricate relationship between posture optimization and action consistency, it can provide actionable guidance for athletes and coaches. This research bridges the gap between subjective evaluation methods and advanced motion analytics, establishing PoseShot as a transformative tool in sports performance analysis. The findings demonstrate the potential for data-driven approaches to revolutionize basketball training methodologies through precise, objective assessment criteria.