Life

Abstract Background: Acute Lymphoblastic Leukemia (ALL) is a highly heterogeneous pediatric malignancy. Despite high survival rates, relapse and the involvement of central nervous system (CNS) remains a significant clinical challenge. Traditional clinical parameters often lack the precision required for early detection and risk stratification. This study utilizes high-throughput proteomics and machine learning to identify molecular signatures in cerebrospinal fluid (CSF) that characterize disease effect and treatment response. Methods: 82 CSF samples from 41 pediatric ALL patients at diagnosis (VD) and remission (VR) were analyzed. Proteomic profiling of 276 proteins was performed using Olink Proximity Extension Assay. Differentially abundant proteins were identified (q-value< 0.05, |Log_2FC| > 0.5) using the Wilcoxon rank-sum test. Three machine-learning algorithms - Random Forest, LASSO, and SVM-RFE - were integrated to select the differentially abundant proteins in VR and VD and between CNS involvement levels. To validate the data Pan-Cancer Atlas analysis was done using two different platforms. Results: In the remission phase, we observed significant alterations in the expression of key proteins compared to diagnosis, with ADGRG1 and KYNU showing a marked increase, while CCL17, CD5, CD27, CXCL9, CXCL11, FASLG, GZMA, and TNFRSF9 were significantly downregulated. Furthermore, our analysis identified distinct protein signatures associated with CNS involvement: CCL4, CTSC, CXCL10, CXCL9, and MMP7 were differentially abundant at the VD stage, whereas CAIX, CASP-8, HAGH, CXCL9, MMP7, MCP-2, and VWC2 at the VR stage. Conclusion: Integrating Olink proteomics with machine learning identified molecular signatures in ALL that have the potential to be further developed to a biomarker panel for monitoring treatment response and guiding personalized therapeutic strategies shifting the focus toward the Precision One Health approaches.

BackgroundThe physical properties of leukocytes, such as cell size and stiffness, are critical for their circulation in microcapillary networks where rapid shape changes are required to squeeze through vascular constrictions. Alterations in the cells physical phenotype can promote venous thromboembolism (VTE), a common cause of death in cancer patients receiving chemotherapy. While biochemical VTE predictors are well studied, physical properties of blood cells receive less attention. MethodsUsing real-time deformability cytometry (RT-DC), we monitored for the first time the physical phenotype of leukocytes in a longitudinal study of a breast cancer patient treated with epirubicin/cyclophosphamide (EC) and paclitaxel (Pax). ResultsThe leukocyte counts extracted from RT-DC were in good agreement with standard clinical leukograms and EC had no immediate effect on leukocyte properties. However, Pax caused a significant softening of granulo/monocytes and a stiffening of lymphocytes immediately after administration. Leukocyte size was constant throughout the therapy, but we observed an overall increase in leukocyte stiffness, which was restored to normal values 45 weeks post treatment. ConclusionTaken together, our data reveal chemotherapy-induced specific alterations of leukocyte stiffness potentially critical for microcirculation. Thus, RT-DC measurements can add important, yet currently not available information to VTE prediction in cancer patients.

Introduction Recent respiratory illness, especially influenza, may trigger acute cardiac events via elevated inflammatory mediators. During the 2018 influenza season in Bangladesh, this study examined whether recent acute clinical respiratory illness (CRI) or laboratory-confirmed influenza was associated with elevated hs-CRP and IL-6, linked to acute cardiac events. Methods A total of 139 participants aged [&ge;]40 were recruited from a Dhaka cardiac hospital: 70 with acute myocardial infarction (AMI), 30 with other acute cardiac events, and 39 healthy individuals. CRI was defined as fever with cough and/or respiratory symptoms within seven days. Respiratory swabs were tested for influenza, and blood was analyzed for hs-CRP and IL-6. Results Median hs-CRP and IL-6 were higher in participants with CRI or influenza but not significantly. Cardiac patients had elevated hs-CRP (9.98 mg/L in other cardiac; 4.86 mg/L in AMI vs. 1.73 mg/L in healthy) and IL-6 (0.1 pg/mL in other cardiac; 0.145 pg/mL in AMI vs. 0.08 pg/mL in healthy) (p<0.001). CRI was not significantly associated with elevated hs-CRP or IL-6, though influenza in healthy participants was linked to higher IL-6. Cardiac patients had a higher risk of hs-CRP [&ge;]3 mg/L and elevated IL-6. Conclusion Cardiac patients showed significantly increased inflammatory markers, but CRI was not clearly linked to inflammation. Further research should assess biomarker utility for early cardiac risk.

Objective: To construct and evaluate, in an exploratory manner, a pathophysiologic rationale link- ing biological pathways derived from the peripheral transcriptome in ischemic stroke (IS) to nursing diagnoses in the NANDA-I 2024-2026 taxonomy, while emphasizing that this association is not di- rect, deterministic, or automatically inferable from textual similarity with large language models (LLMs). Methods: A computational study was conducted using public secondary data from the Gene Ex- pression Omnibus series GSE16561, which includes 63 peripheral blood samples: 39 from indi- viduals with IS and 24 from healthy controls. The pipeline integrated transcriptomic analysis and functional enrichment, semantic mapping through ClinicalBERT embeddings, and mechanistic and clinical-conceptual judgment using Claude Sonnet 4.6 as a judge. The judgment stage was treated as the central interpretive layer, designed to mediate the transcriptome, pathophysiology, functional manifestation, and NANDA-I diagnosis. Results: The analysis identified a bimodal transcriptomic pattern, with activation of pathways re- lated to innate immunity and suppression of pathways related to adaptive immunity. Semantic map- ping generated 158 pathway-diagnosis pairs. The Spearman correlation between cosine similarity and the mechanistic score was negative and statistically significant (rho = -0.243; p = 2.09e-03), but weak in magnitude. This effect size indicates that semantic similarity explained less than 6% of the variance in mechanistic plausibility, reinforcing the insufficiency of embeddings as a stand- alone criterion. Of the 158 pairs, 14 were classified as high concordance, 8 as moderate, and 136 as divergent. Conclusion: The main value of this study lies in demonstrating that translating biological pathways into nursing diagnoses requires pathophysiologic, functional, and clinical-conceptual mediation. The prioritized pairs represent mechanistically plausible hypotheses for future research, without implying causality, direct clinical confirmation, or immediate care recommendations.

O_LIThe effect of some bioactive compounds on living organisms is dependent on their concentration and gradients, as is the case of hormones and signalling peptides, determining cell identity, activity and organism development. C_LIO_LIThere are a handful of methods that allow to produce spatially confined peaks of concentration local application of biochemicals on plants, such as agar blocks and microinjection, but they lack in precision, throughput and/or simplicity. C_LIO_LIWe developed the MicroTron, a microfluidics-based method specifically for filamentous organisms or life cycle stages, like the moss plant Physcomitrium patens protonemata, that serves as a platform for the application of chemicals on single cells and study the cell response. C_LIO_LIWe show how chemical applications could be performed on cells, either on the side or apically with dyes and hormones, targeting the cell wall, cell membrane, cytosol and nucleus. C_LIO_LITreatments could be applied on single filaments and with a precision of up to single cells in optimal conditions. C_LIO_LIThis method could be used to study live responses to chemicals with high spatiotemporal resolution. C_LI

Cancer is a major global health issue with rising incidence and mortality. Early detection, tumor characterization, and disease surveillance are crucial for timely and effective treatment, ultimately reducing mortality rates. Liquid biopsy (LB) has emerged as a valuable detection tool offering a non-invasive method to determine tumor-derived biomarkers in body fluids with demonstrated translational potential. To increase biomarker sensitivity, high-throughput sequencing platforms deliver massive volumes of data. Artificial Intelligence (AI) is pivotal in enabling huge and complex data integration. This contribution aims to assess the current state of integrative AI-based research in the LB field and provide methodological guidance. First, we conducted a PubMed search and found that the literature is sparse in studies integrating LB features, particularly by applying AI. When adopting the latter approach, defining the study objectives is crucial to guide the subsequent methodological aspects, including study design, patient selection criteria, sample size, nature of the LB features, and metadata to collect. Specifically, we propose strategies and tools for data preprocessing, including normalization and batch correction, as well as handling outliers and missing data. Furthermore, we recommend various Machine/Deep Learning approaches for feature selection techniques to ensure model robustness, and we highlight the importance of undergoing rigorous internal and external validations of the selected models. Assessing clinical utility and interpretability is often overlooked but fundamental for real-world implementation. In conclusion, we provide the LB scientific community with an AI-based methodological guidance to bridge the two fields and enhance the integrative analysis of LB features. Graphical abstractWorkchart for multiomics integrative studies in the liquid biopsy field. Note: CTCs, circulating tumor cells; ctDNA, circulating tumor-DNA; TEPs, tumor-educated platelets; miRNA, microRNA; cfRNAs, cell-free RNAs. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC="FIGDIR/small/724535v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@1f250b2org.highwire.dtl.DTLVardef@18fe36corg.highwire.dtl.DTLVardef@19c02b9org.highwire.dtl.DTLVardef@176f6e0_HPS_FORMAT_FIGEXP M_FIG C_FIG

Emerin (EMD), an inner nuclear membrane protein essential for nuclear architecture integrity, gene expression, cellular signaling, and chromatin stability, interacts with the LINC complex and participates in cytoskeleton-nucleoskeleton communication by binding to nuclear actin filaments. EMD is implicated in migration, invasion, and metastasis in some tumors, but its role in glioblastoma (GBM) remains unclear. This study evaluated the effects of EMD knockdown and overexpression in GBM cell lines following genotoxic treatment with cisplatin. In both wild-type p53 (U87-MG) and mutant p53 (U138-MG) GBM cells, EMD expression is high, and cisplatin treatment did not affect these protein levels. EMD knockdown in U87-MG cells significantly increased cisplatin IC50, viability, and proliferation. Conversely, stable overexpression of EMD in U87-MG cells led to reduced cisplatin IC50, viability, proliferation, and migration. EMD knockdown or overexpression did not affect any U138-MG phenotypes, with or without cisplatin treatment. Modulation of EMD levels causes morphological changes in stress fiber cytoskeleton, whereas overexpression of EMD in U87-MG cells promotes an increase and a decrease in nuclear and cytoplasmic actin levels, respectively. These biological responses of U87-MG cells overexpressing EMD were coincidentally associated with alterations in the levels of pH2AX(Ser139), p-p53(Ser15), p53, and p21Kip1 proteins after cisplatin exposure. In sum, modulation of EMD levels affects the viability, migration, and proliferation of wild-type p53 GBM cells treated with cisplatin, suggesting unknown roles in the DNA damage response and repair. This work highlights EMD as a potential regulator of GBM chemoresistance and a target for therapeutic intervention.

Rationale. Racial disparities in outcomes among patients with acute respiratory failure are well-described, but the contributions of clinicians to these disparities have not been evaluated. Objectives. Among mechanically ventilated patients, we evaluated racial disparities in severity of illness trajectories and adapted value-added modeling to quantify nurse and physician relationships with these disparities. Methods. In a retrospective cohort of mechanically ventilated patients across five hospitals between 2018 and 2022, we used generalized estimating equations to model the change in Laboratory-based Acute Physiology Score version 2 (LAPS) from the start to end of intensive care unit admission ({Delta}LAPS). Consistent with value-added modeling, we randomly allocated the cohort into development and testing partitions, and fit separate multiple linear regression models of {Delta}LAPS using concurrent nurse and physician assignments (determined at 4-hour intervals), patient race, and clinician-race interaction terms as fixed effects. Clinician-specific and clinician-race interaction coefficients were extracted to determine race-specific value-add for each clinician. We defined the race-contextual value-add difference (RCVAD) as a clinician-level measurement of the difference in that clinician's value-add between Black and White patients in their care; a positive RCVAD indicates a more favorable severity of illness trajectory for Black relative to White patients and vice versa. Measurement and Main Results. Among 6,555 distinct patients, 7,247 clinical encounters, 405 nurses, and 70 physicians, Black patients accounted for 2,926 (40%) encounters. Overall, Black patients had significantly less improvement in {Delta}LAPS than White patients (difference in LAPS decline = 2.26 [0.23, 4.29], p=0.029). In the development partition, median nurse RCVAD was -0.10 (interquartile range [IQR]: -1.17, 1.14) with 191 (47%) nurses having a positive RCVAD; median physician RCVAD was -0.18 (IQR: -1.34, 0.56) with 29 (41%) having a positive RCVAD. Conclusions. Black mechanically ventilated patients experience less improvement in severity of illness during intensive care unit admission than White patients. While the majority of physicians and nurses were associated with disparities-exacerbating illness trajectories, many other clinicians were associated with disparities-mitigating trajectories. Future work to understand practices associated with disparities-exacerbating and disparities-mitigating care profiles could inform interventions to reduce disparities overall.

Chronic kidney disease is a progressive condition characterized by the accumulation of nitrogenous waste products, including urea, creatinine, and uric acid, leading to significant morbidity in advanced stages. Current management strategies, such as dialysis, are effective but associated with substantial clinical and socioeconomic burdens, highlighting the need for alternative approaches to reduce circulating toxins. In this study, we evaluated a novel formulation of psyllium-based granules functionalized with specific antibody combinations targeting urea, creatinine, and uric acid. The aim was to assess the biochemical effects, as well as the binding and sequestration efficiency, of these formulations under controlled experimental conditions. A randomized, double blind controlled in vitro study was conducted using serum samples obtained from twenty patients with uremia undergoing dialysis. Three formulations, labeled S1, S2, and S3, were evaluated. All tested formulations resulted in statistically significant reductions in urea, creatinine, and uric acid concentrations compared with baseline values. Among them, the S1 formulation demonstrated the highest binding efficiency, reducing urea by 70% {+/-} 7%, creatinine by 80% about 4%, and uric acid by 52% about 11%. Linear regression analysis confirmed a statistically significant association between the S1 formulation and reductions in these biochemical parameters. These findings suggest that antibody functionalized granules can effectively bind and sequester nitrogenous waste products under in vitro conditions. This approach may represent a potential strategy for reducing uremic toxin burden, either as a complementary method or as a future alternative to existing renal replacement therapies. Further studies, including in vivo validation, dose optimization, and controlled clinical trials, are required to establish safety, efficacy, and translational applicability.

Background: Large language models (LLMs) struggle with dynamic, longitudinal clinical reasoning. We developed a Multi-Stage Iterative Clinical Reasoning Agent framework to address this gap and systematically decouple the clinical efficacy of static retrieval-augmented generation (RAG) from dynamic self-refinement. Methods: Ten complex longitudinal nephrology cases, rigorously selected via a modified Delphi consensus technique, were blindly evaluated by four board-certified nephrologists and a multi-model AI panel. We compared three architectures across nine cognitive steps: (Model A) a baseline frontier LLM, (Model B) an LLM augmented with static guideline-based RAG, and (Model C) our proposed multi-agent framework featuring RAG integrated with iterative self-critique and refinement. Results: In human evaluations (20-point scale), Model C (mean 17.2, SD 1.2) significantly outperformed both Model A (16.1, 1.3) and Model B (16.2, 1.2) (P < 0.001). Implementing static RAG (Model B) yielded no significant improvement over the baseline. Automated AI evaluations (15-point scale) corroborated these findings: Model C (14.7, 0.6) outscored Model A (14.2, 0.9, P < 0.001) and Model B (14.3, 0.9, P = 0.01). While monolithic models exhibited severe score degradations in planning-heavy tasks such as dynamic differential diagnoses, the multi-agent framework effectively intercepted error cascades, achieving significantly higher diagnostic accuracy (mean 17.6, P = 0.019) and therapeutic management scores (17.3, P = 0.002). Conclusions: Static knowledge retrieval alone fails to enhance frontier LLM performance in longitudinal medical reasoning. Distributing clinical workflows into a multi-agent dynamic refinement pipeline significantly improves reasoning completeness, intercepts error cascades, and safely resolves planning bottlenecks in complex patient care.

Rapid and specific diagnosis of viral and bacterial infections is a significant challenge in medicine and veterinary science, especially in the case of epidemically dangerous pathogens. The African swine fever virus (ASFV), for example, causes annual outbreaks among livestock, resulting in significant economic losses for farmers. DNA aptamers have been identified as a promising tool for point-of-care diagnostics, being highly specific to the target and stable ambient temperatures during storage. In this study, we describe the selection of DNA aptamers targeting the p54 viral protein using a single-round selection process. These aptamers were able to bind both to recombinant protein and inactivated ASFV viral particles. Analysis of the newly generated aptamers revealed a dependence of affinity and thermal stability on Ni2+ content, which was a dopant in the selection process. In some cases, the affinity increased 100 times, and melting temperature increased by 30{degrees}C. We have identify two novel DNA motifs that bound 2-3 Ni2+ or Zn2+ ions.

Abstract Objective: To synthesize the available evidence on the association between SARS-CoV-2-related microvascular thrombosis and acute kidney injury (AKI), with emphasis on renal outcomes, mortality, and renal replacement therapy requirements. Methods: This systematic review followed the PRISMA 2020 statement and was prospectively registered in PROSPERO (CRD420251132701). PubMed/MEDLINE, Scopus, and Embase were searched for systematic reviews, including meta-analyses, and umbrella reviews investigating the association between SARS-CoV-2-related microvascular thrombosis and acute kidney injury. Two reviewers independently performed study selection, data extraction, and methodological quality assessment using AMSTAR-2 and ROBIS. Evidence was synthesized through a structured narrative synthesis supported by quantitative data extracted from the included reviews. Results: Six evidence syntheses evaluating kidney involvement, thrombotic events, and microvascular mechanisms in COVID-19 were included. AKI incidence was 9.2% (95%CI 4.6-13.9) among hospitalized patients and 32.6% (95%CI 8.5-56.6) among critically ill patients. In children with multisystem inflammatory syndrome associated with SARS-CoV-2, AKI incidence was 20% (95%CI 14-28). Microvascular or thrombotic events were associated with adverse renal outcomes (OR 2.14; 95%CI 1.32-3.48). AKI was associated with increased mortality (OR 4.68; 95%CI 1.06-20.70) and greater likelihood of renal replacement therapy requirement (OR 2.87; 95%CI 1.45-5.68). The certainty of evidence ranged from moderate to high for the principal outcomes. Conclusion: Current evidence supports an important association between microvascular thrombotic injury and COVID-19-associated AKI. These findings reinforce the relevance of endothelial dysfunction and thromboinflammatory pathways in kidney involvement during COVID-19 and highlight the need for early renal monitoring, risk stratification, and kidney-protective strategies in high-risk patients. Keywords: COVID-19; Acute Kidney Injury; Microvascular Thrombosis; SARS-CoV-2; Renal Replacement Therapy; Systematic Review

Background: Deceased-donor kidney transplantation is a component of the Brazilian transplant system and takes place within a deceased-donation environment that in-cludes donor identification, notification, family approach and authorization, organ allocation, and logistics. This study described temporal, macroregional, and federative unit-level variation in deceased-donor kidney transplantation in Brazil from 2014 to 2024, together with hospitalization-based indicators and contextual indicators of the deceased-donation environment. Methods: This nationwide descriptive time-series study used publicly available secondary data from the Hospital Information System of the Unified Health System (SIH/SUS), the Brazilian Transplant Registry (RBT/ABTO), and the Brazilian National Transplant System (SNT). Indicators includ-ed the number of transplants, transplant rates per million population, kidney transplant waiting list stock, mean length of hospital stay, in-hospital mortality, potential donor notifications, and family interview and refusal proportions. The three databases were analyzed separately and in parallel, without linkage. Results: The annual number of deceased-donor kidney transplants increased over the study period. The kidney trans-plant waiting list stock also increased. Mean length of hospital stay decreased, and in-hospital mortality decreased over time. Marked macroregional and federative unit-level heterogeneity was observed in transplant activity, hospitalization-based indica-tors, and contextual indicators of the deceased-donation environment. Conclusions: Deceased-donor kidney transplantation increased in Brazil between 2014 and 2024, although regional disparities persisted. These findings support monitoring strategies that incorporate contextual indicators alongside measures of transplant activity. Be-cause this was a descriptive study based on secondary data from distinct sources, the findings should not be interpreted as evidence of causal relationships.

In the next years, several space missions will search for evidence of life on exoplanets, focusing on robust biosignatures associated with oxygenic photosynthesis, including atmospheric oxygen accumulation and the Vegetation Red-Edge in surface reflectance spectra. Many potentially habitable rocky exoplanets orbit M-dwarf stars, whose spectral energy distribution may challenge oxygenic photosynthesis. Differently from the Sun, M-dwarf stars emit predominantly far-red (700- 750 nm) and infrared (750-1000 nm) light, and relatively little visible (400-700 nm) radiation, which constitutes photosynthetically active radiation. Some organisms have been found to photosynthesize under such spectrum but less efficiently than under solar light, as their photosynthetic apparatus evolved to harvest visible light emitted by the Sun. Around M-dwarfs, such different irradiation might have selected adaptations optimized for harvesting far-red / infra-red light. On Earth, similar selection can be found in Acaryochloris marina strains, constitutively presenting high chlorophyll d content in photosystem II & I, with in vivo absorption peaks beyond 700 nm. Here we tested the Moss Beach strain under a simulated M-dwarf spectrum and a simulated primeval atmosphere - anoxic and enriched in carbon dioxide. Results underline how this permanently red-shifted photosynthetic apparatus does not require acclimation to the stellar spectrum and enables for a strong growth and oxygen production, higher than under simulated solar light. Moreover, cells reflectance spectrum highlights a shift of the canonical red-edge toward longer wavelengths, resulting in a Chl d-near-infrared edge, suggesting a similar metabolism on exoplanets orbiting M-dwarfs could successfully produce both a gaseous biosignature and a characteristic surface biosignature. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=144 SRC="FIGDIR/small/719884v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@7f91bdorg.highwire.dtl.DTLVardef@1391bdborg.highwire.dtl.DTLVardef@53f7b4org.highwire.dtl.DTLVardef@ab59fa_HPS_FORMAT_FIGEXP M_FIG C_FIG Created in BioRender. Liistro, E. (2026) https://BioRender.com/j2de4ay

Background: Uremic pruritus affects up to 90% of individuals and substantially impairs quality of life, in the group of patients undergoing chronic dialysis. Despite multiple therapeutic options, an optimal and well tolerated treatment remains elusive. Ketotifen, a mast cell stabilizer with antihistaminic properties prevent itch by inhibition of mast cell derived tryptase, which modulates protease-activated receptor-2 (PAR-2) in the cowhage itch pathway. Materials and Methods: In this prospective observational study, 230 chronic dialysis patients were screened, of whom 48 (20.9%) had clinically significant pruritus identified using a structured questionnaire. Twenty-four patients with moderate-to-severe symptoms who were prescribed ketotifen as part of routine clinical care consented to prospective follow-up. Ketotifen was initiated at 1 mg twice daily, with dose escalation to 2 mg twice daily in patients with persistent symptoms according to routine clinical practice. Pruritus severity was assessed using visual (VAS), verbal (VRS), and numerical (NRS) rating scales before and after treatment. Results: After two weeks of initial 1mg therapy, 19 showed significant clinical improvement. Mean scores reduced 77.5 [-&gt;] 27.1 (VAS), 87.5 [-&gt;] 20.8 (VRS), and 74.2 [-&gt;] 25 (NRS) (around 65% reduction with p < 0.001 across all scales). Clinical relief was achieved in 83.3% overall and mild tolerable drowsiness occurred only at the 2mg dose. Conclusion: Ketotifen is a safe, effective and well tolerated option for moderate to severe uremic pruritus in dialysis patients. Larger multicenter studies are warranted to confirm efficacy and optimize dosing.

Introduction Hospitalised community-acquired pneumonia (CAP) is heterogeneous in aetiology, severity, and outcome. Phenotyping and endotyping approaches offer potential to stratify patients biologically and guide targeted therapy, but require well-characterised cohorts with linked biosamples. We describe the PARIS (Pneumonia: Acute Respiratory Infection +/- Sepsis) study: a prospective observational cohort of hospitalised patients with pneumonia, designed to characterise functional outcomes and to provide a biobank for translational immunological research. Methods Adults admitted with CAP to a single NHS district general hospital were enrolled within 24 hours of admission between December 2020 and March 2022. Clinical, functional, and physiological data were collected at enrolment, hospital discharge, and 6-8 week follow-up. Serial blood samples were collected for flow cytometry, transcriptomics, pathogen DNA detection, and plasma biobanking. Results Forty-seven patients were enrolled (15 without and 32 with sepsis [SOFA >=2] at enrolment); 87% met sepsis criteria by 24 hours post enrolment. Most patients (30/47, 64%) were managed as COVID-19, microbiologically confirmed in 27. Mean age was 57 years (SD 16), 70% were male, and baseline comorbidity burden was low. Severity was moderate (median NEWS2 4 at enrolment, rising to 6 by 24 hours post enrolment; p<0.001). Mortality was 4/47 (8.5%), with 44/47 (94%) alive at hospital discharge. Median length of stay was 8 days (IQR 5.5-11). Translational samples were collected from the majority: fresh flow cytometry (44/47, 94%), transcriptomics from the sepsis subgroup (31/32, 97%), pathogen DNA sampling (35 samples received across study timepoints; see Table 5), and stored plasma (29/47, 62%). The primary outcome of functional decline (Barthel score decrease >=1.85) occurred in only 1/29 patients with paired assessments (3.4%). Persistent CRP elevation (>3 mg/L) at 6-8 week follow-up was present in 16/31 (52%) survivors with available data. Conclusions The PARIS cohort provides a well-characterised clinical platform and linked biobank to support translational studies of pneumonia and sepsis. The low rate of functional decline reflects the younger, lower-comorbidity, COVID-predominant population recruited. Primary protocol endpoints were not achieved owing to pandemic-related disruption. Data and samples underpin a programme of linked translational studies.

Transfusion-ready red blood cells can be cultured ex vivo from hematopoietic progenitors. Despite its promising outlook, a cultured transfusion unit cannot be produced at competitive costs. Large media volumes are required to maintain a maximum erythroblast cell density of 1-2.106 cells/mL during the erythroblast proliferation stage. To identify the origin of the cell density limitation, we investigated the cellular support and metabolomic phenotype using different media formulations and feeding regimens. Media that were exposed to an increasing density of erythroblasts (termed spent media) displayed a proportional decrease in erythroblast proliferation support. A 1:1 combination of spent media with fresh media (not previously exposed to the cells) restored growth for all tested conditions. Filtering both fresh and spent media with a 3 kDa cut-off filter, and subsequent recombination of the two fractions, indicated that exhaustion of the small molecular weight fraction (<3 kDa) was primarily responsible for growth limitation. We performed targeted and untargeted metabolomics analysis, for both the intra- and extracellular compartments, following seeding in fresh medium (12, 24, 36 h). We observed degradation of nucleosides, depletion of amino acids, and a decrease in intermediates of the glutathione-ascorbate, {gamma}-glutamyl and cysteine-methionine cycles. The latter compounds suggested an increase in oxidative stress in high density erythroblast cultures. Elimination of nucleosides from the medium led to a lower accumulation of purine salvage intermediates, and a 30% increase in cell productivity. In conclusion, we demonstrate that high-density erythroid cultures are subject to metabolic stress, defining critical constraints for scalable culture expansion.

Background Hypercapnia may indicate a primary ventilatory syndrome, a complication of another illness, or an epiphenomenon of severe disease. The presenting context of hypercapnia is poorly quantified, limiting clinical interpretation and synthesis of epidemiologic studies. Methods We performed a retrospective cross-sectional study of Medical Information Mart for Intensive Care IV (MIMIC-IV) hospital admissions linked to an emergency department (ED) presentation from 2011 through 2019. Admissions were included if the triage chief complaint was not missing and at least one prespecified criterion for hypercapnia was met: an International Classification of Diseases (ICD) code for hypercapnic respiratory failure or obesity hypoventilation syndrome, arterial blood gas (ABG) PCO2 45 mmHg, venous blood gas (VBG) PCO2 50 mmHg, or indeterminate-source blood gas PCO2 50 mmHg. Triage chief-complaint text was classified by natural language processing (NLP) into 17 National Hospital Ambulatory Medical Care Survey reason-for-visit (RFV) categories using a multi-label framework. Primary analyses estimated admission-level RFV category prevalences; secondary analyses compared distributions by overlapping ascertainment indicator, age, and acidemia. Results The total cohort included 11,941 admissions: 1,542 (12.9%) met both blood-gas and ICD-code criteria, 9,958 (83.4%) met blood-gas criteria only, and 441 (3.7%) met ICD-code criteria only. Median age at admission was 68 years (IQR 56-78), and 6,423 admissions (53.8%) were for male patients. Respiratory RFV categories were most prevalent (30.2%), followed by administrative reasons (17.5%), digestive symptoms (14.0%), injuries and adverse effects (14.0%), and nervous-system symptoms (13.8%); categories were not mutually exclusive. Respiratory categories were more common in ICD-positive admissions (50.2%) than in VBG-defined (36.3%) or ABG-defined admissions (27.3%). Injuries and adverse effects were most prevalent among admissions for patients aged 18-39 years (34.4%), whereas respiratory categories increased from 13.7% among admissions for patients aged 18-39 years to 36.5% among admissions for patients aged 80 years. NLP-derived classifications showed mean set-F1 of 0.84 against adjudicated clinician labels in the full annotated benchmark sample. Conclusions Among ED-linked admissions with hypercapnia by diagnosis code, blood gas, or both, respiratory complaints were the most common chief-complaint category but represented fewer than one-third of admissions. Presentation context should be incorporated when defining, comparing, and interpreting hypercapnia cohorts, particularly those ascertained by blood-gas criteria.

BackgroundiPSCs generated from healthy individuals constitute an important control resource for disease modelling applications but existing biobanks are highly skewed towards populations of European ancestry while well characterized control lines from Indian populations remain limited. Given the extensive genetic diversity of the Indian subcontinent, the availability of ethnically relevant healthy control lines is important for developing accurate disease models and reducing population specific confounding effects. MethodologyWe used peripheral blood mononuclear cells (PBMNCs) of a healthy female donor of Eastern Indian origin for the generation a wild type iPSC line using non-integrating episomal reprogramming vectors. Established colonies were expanded and characterized through morphological assessment, expression of pluripotency and trilineage markers, episomal vector clearance analysis, and chromosomal stability evaluation and mycoplasma contamination analysis. ResultsThe line generated exhibited characteristic pluripotent stem cell morphology and also showed strong expression of pluripotency markers, was free from any contamination and free from the reprogramming vectors confirming an integration free system. The cells maintained a normal diploidy number during characterization. Expression of lineage specific markers associated with ectoderm, mesoderm and endoderm confirmed the developed iPSCs functional capacity to undergo trilineage differentiation. ConclusionWe have developed and validated an iPSC line from an underrepresented Indian population. This well characterized, ethnicity specific iPSC line provides a valuable cell line for establishing a high quality, well characterized control baseline, which is a major missing element in South Asian stem cell repositories and thus will provide a solid foundation for future disease specific modelling and screening.

BackgroundDrug-tolerant persister (DTP) cell states have been implicated in relapse across multiple cancers, including acute myeloid leukaemia (AML) [1,2]. Methods that score such states from transcriptomic data, generalise to held-out samples, expose calibrated probability outputs, and link predictions to candidate biology are useful for prioritising follow-up experimental work. Existing transcriptomic methods for scoring drug-tolerant or persister-like states largely rely on fixed gene signatures or general-purpose cell-type classifiers adapted post hoc (scPred, scANVI, scClassify); deep-learning approaches developed specifically for AML drug-tolerant persister scoring with calibrated probability outputs, prespecified thresholds, and transparent external validation against ex-vivo drug-response data are, to our knowledge, lacking. Our approach addresses this gap by combining a Transformer teacher with a knowledge-distilled 1,000-gene student, prespecified threshold {tau} = 0.31, and direct evaluation against BeatAML drug-AUC. Our in silico approach aims to fill this gap of non-existent analytical methods to identify and mark the DTP cells. MethodsWe trained a Transformer classifier on a pooled scRNA-seq corpus of nine samples (six from GSE123902-lung adenocarcinoma metastasis, normal, and primary tumour [4]-plus three primary AML samples; 32,342 cells, 13,369 common genes), with stratified 5-fold cross-validation at the cell level, a 20% held-out test split, and a prespecified probability threshold selected on out-of-fold predictions. A 1,000-gene student model was trained by knowledge distillation [5]. For every input cell, the student outputs a probability between 0 and 1 (hereafter "the score") representing predicted membership in the positive training class. The trained model was applied without re-tuning to five external or independent application cohorts: 39 primary AML donors[in-house]; GSE74246[6]; BeatAML (n = 452 with linked ex-vivo drug-AUC; n = 405 with overall-survival metadata)[7]; TCGA-LAML (n = 149)[8]; and an in-house n = 10 scRNA-seq cohort with linked survival. Survival and drug-response data were not used during training, threshold selection, or tuning. The score was anchored mechanistically against CRISPR/DepMap essentiality[9], pathway enrichment, and a normal-tissue-filtered surface-protein candidate list (HPA[11], GTEx[12]). To assess concordance between transcriptomic prioritisation and protein-level evidence, each ranked candidate was additionally annotated with two HPA-derived flags: HPA_surface_protein (Yes/No, derived from HPA Protein class and Subcellular location fields, identifying genes annotated as plasma-membrane, GPCR, ion-channel, transporter, receptor, or CD-marker) and HPA_antibody_reliability (Enhanced, Supported, Approved, Uncertain, or Not available, per HPA antibody validation tier). Annotations were merged on HGNC symbol; 248 of 250 candidates (99.2%) matched. Two candidates using the older CORF nomenclature did not auto-match HPAs lowercase convention and were resolved manually. HPAs per-gene RNA-protein numeric correlation is published only on per-gene web pages and not in the bulk download; we therefore used the detection-level and antibody-reliability tiers as the operational concordance filter. ResultsCross-validation area under the receiver operating characteristic curve (AUROC) was 0.936 +/- 0.014 (held-out test 0.941, Matthews correlation coefficient (MCC) 0.696, F1-score 0.895). The 1,000-gene student showed Spearman {rho} {approx} 0.96 with the teacher and >85% class agreement at the prespecified threshold. The principal external result was in BeatAML: the score correlated with ex-vivo drug-response AUC across seven AML-relevant drugs, with consistent per-drug Spearman correlations (r = 0.41-0.53, all p < 0.05). The aggregate correlation across 3,164 patient-drug pairs from 452 patients was r = +0.482 and is reported as a summary, recognising that pairs from the same patient are not fully independent. The score did not stratify overall survival in TCGA-LAML or in the in-house n = 10 cohort, in part because predicted high-score fractions saturated. At the prespecified threshold the score did not separate cell types in GSE74246, indicating that absolute calibration is cohort-dependent. Compared against logistic regression, random forest, the LSC17 stemness signature, and a mean-expression baseline on the same gene panel, the Transformer was the most stable model under aliquot-grouped cross-validation and the only one to transfer with strong, positive correlation to BeatAML drug-AUC. The mechanistic candidate-target pipeline produced a 250-candidate ranked surface-protein list (full breakdown in Results); FLT3 and CD33 were recovered from the unbiased ranking as positive controls. ConclusionWe present a Transformer-derived transcriptomic score that addresses the lack of validated computational methods for identifying drug-tolerant persister-like states in AML. The score shows external rank-order association with ex-vivo drug response, providing a research-use tool for prioritising candidate persister-associated transcriptional programs for follow-up. Together, these results support the score as a research-use transcriptomic ranking tool for AML drug-response-associated states. The strongest external support comes from the consistent association with BeatAML ex-vivo drug-response AUC. The fixed probability threshold did not transfer reliably across all cohorts, so threshold-based classification should require cohort-specific recalibration. The score is not validated for clinical decision-making and is not proposed as a survival predictor. The candidate-target list is a starting point for functional follow-up.