Chemistry – A European Journal

Flavonoids have been widely investigated for their antiviral and anti-inflammatory properties, but their mechanisms of action often remain insufficiently defined. In the present study, high-purity flavonoids were evaluated using an integrated workflow combining molecular docking, LigPlot interaction mapping, surface plasmon resonance (SPR), fluorescence-based TMPRSS2 inhibition assays, and cell-based viability studies. Docking with AutoDock Vina identified Hesperidin as the strongest overall candidate among the compounds evaluated. Hesperidin showed strong active-site engagement with TMPRSS2, including interactions with catalytic residues His296, Asp345, and Ser441, and stable binding within the SARS-CoV-2 main protease (Mpro) pocket. Comparative docking showed weaker or more peripheral interaction patterns for Rutin and moderate Spike binding for Hesperidin and Rutin. Experimental validation demonstrated dose-dependent inhibition of TMPRSS2 activity with an IC50 of 79.1 uM for Hesperidin and 43.5 uM for Hesperetin, while Rutin showed partial inhibition without a defined IC50 in the tested range. In Calu-3 cells, pre-treatment with Hesperidin or Rutin reduced SARS-CoV-2 Spike-induced cytotoxicity by approximately 30 percent without detectable intrinsic toxicity at the concentrations tested. Docking analysis of Hesperidin and Rutin with the SARS-CoV-2 Spike protein revealed moderate interaction patterns involving residues such as Asn343, Ser371, and Val367. Hydrogen bond distances were generally in the range of approximately 2.9-3.3 A, indicating moderate stabilization compared with the stronger active-site interactions observed for Hesperidin in TMPRSS2. The resulting binding poses suggest that these flavonoids can associate with structurally relevant regions of the Spike receptor-binding domain; however, they do not strongly overlap with the key residues required for ACE2 interaction. Rutin, in particular, exhibited a more peripheral and distributed binding mode within the Spike-ACE2 complex, indicating limited potential for direct disruption of the binding interface. In addition to SARS-CoV-2 targets, docking analysis extended to influenza viral proteins revealed moderate interaction of Hesperidin with hemagglutinin (HA) and strong catalytic-pocket binding of Rutin to neuraminidase (NA), involving key residues associated with enzymatic activity. These findings broaden the scope of the study to include influenza viral entry and release mechanisms, supporting a multi-virus, multi-target framework.

The emergence of antimicrobial resistance has been rapid, necessitating the development of alternative therapeutic approaches beyond traditional antibiotics. In this proof-of-concept study, we examined the antibacterial activity of citrate-stabilized, colloidally aggregated silver nanoparticles (AgNPs) against Escherichia coli by combining physicochemical characterization with experimental antibacterial testing The synthesis of silver nanoparticles was done through a modified thermal citrate reduction protocol, and UV-visible spectroscopy, dynamic light scattering (DLS), and zeta potential were used to characterize the nanoparticles. Spectroscopy analysis showed a clear surface plasmon resonance peak at 310-320 nm, indicating the formation of nanoparticles. DLS measurements showed that the dominant hydrodynamic diameter was around 250-270 nm, which is indicative of controlled colloidal aggregation, and near-neutral values of zeta potential indicated steric stabilization of the nanoparticle clusters. Agar tests demonstrated a clear zone of inhibition, and broth cultures showed a lower turbidity and slower bacterial growth with AgNPs. The above findings suggest that nanoparticles that are colloidally aggregated maintain a significant antimicrobial activity even though the surface area is lower than that of monodispersed systems. Mechanistically, the observed antibacterial effect can be explained by a multi-modal effect through direct membrane disruption, localized release of silver ions, and the induction of oxidative stress pathways in bacterial cells. The aggregated form could also help to increase the nanoparticle cell interactions through the provision of multivalent contact points of nanoparticles, and thus the antibacterial efficacy. Controlled colloidal aggregation of AgNPs is a promising approach to the development of effective and possibly more stable antimicrobial agents. These results indicate the possibilities of aggregated nanoparticle systems in fighting drug-resistant pathogens and a basis on future studies of its clinical use.

Prostate-specific photodynamic therapy (PDT) is limited by poor light penetration in deep-seated tumors. To address this, we report a prostate-specific membrane antigen (PSMA)-targeted nanotheranostic platform (UCNPs@mSiO2/HPPH@TCS) that enables near-infrared (NIR)-activated PDT and ultrasound-mediated sonodynamic therapy (SDT). The platform integrates NaYF4:Yb3+, Er3+ up-conversion nanoparticles (UCNPs) coated with mesoporous silica to convert 980 nm NIR light for deep tissue penetration. The clinically approved agent HPPH (Photochlor) serves as both photosensitizer and sonosensitizer, while a PSMA-targeted chitosan shell ensures selective tumor uptake and high loading efficiency (>90%). Physicochemical characterization confirmed a uniform core-shell structure ([~]63 nm). Tissue-mimicking depth studies demonstrate that SDT and 980 nm PDT significantly outperformed conventional 665 nm PDT, with SDT generating superior total reactive oxygen species (ROS). In vitro results showed PSMA-dependent uptake, lysosomal localization, and enhanced therapeutic responses in PSMA+ LNCaP cells. Three-dimensional spheroid models further validate the therapeutic ability of our nanoformulation (NF), demonstrating rapid structural collapse (even in large spheroids [~]2.6 mm) through apoptosis. Notably, SDT demonstrated earlier apoptosis and more uniform penetration compared to PDT, consistent with superior ROS generation. Collectively, these findings identify SDT as a promising deep-tissue activation strategy and highlight PSMA-targeted UCNPs NF as candidates for penetration-enhanced precision therapy in prostate cancer.

Protein synthesis represents an attractive target space for the development of anti-malarials with novel modes of action. Natural-product inhibitors of the eukaryotic 80S ribosome can have potent anti-malarial activity but are often poorly selective due to mammalian cytotoxicity. Blasticidin S (BlaS) is a microbially-produced natural product that broadly inhibits prokaryotic and eukaryotic protein synthesis by binding to the ribosomal peptidyl transferase center. In this study, we explored the potential for improving the anti-malarial potency and selectivity of the blasticidin S scaffold with semi-synthetic analogs that are modified at the C6 and C4 sites. The two best analogs were two orders of magnitude more potent than BlaS against Plasmodium falciparum drug-sensitive and -resistant lines while displaying low cytotoxicity towards mammalian cells. These analogs exhibited improved kinetics of inhibition of protein synthesis in cultured parasites and blocked the development of asexual stages expressing the plasmodial surface anion channel, a transporter required for nutrient acquisition and BlaS uptake. They also exhibited a dramatically improved speed of killing over BlaS. Molecular docking analysis revealed that these analogs are able to form more interactions with the P. falciparum ribosomal peptidyl transferase center than is BlaS, which is consistent with their increased potency. Together, these studies demonstrate the feasibility of generating BlaS analogs with potent anti-malarial activity and provide a roadmap for further development.

Chronic obstructive pulmonary disease (COPD), a chronic lung disease, involves complex metabolic disturbances that remain poorly characterized using non-invasive matrices. The metabolic alterations associated with cigarette smoke (CS), one of the major drivers of disease progression in COPD patients, have not been explored in detail. This study primarily aimed to investigate the metabolic signatures in COPD patients categorized into smoker (n=15), ex-smoker (n=11), and non-smoker (n=3) subgroups. Utilizing saliva as a noninvasive sample, we identified 26 metabolites with differential expression in smokers and 31 in ex-smokers. However, no such significant alteration was observed in the non-smokers subgroup. The multivariate analysis distinctly separated the COPD subgroups from healthy controls. Additionally, pathway enrichment analysis revealed perturbations in key metabolic pathways, including unsaturated fatty acid biosynthesis, arginine biosynthesis, the tricarboxylic acid (TCA) cycle, and pyruvate metabolism. Moreover, univariate Random forest analysis identified four metabolites (cyclopentanone, tetradecane 4-methyl, acetophenone, and scyllo-inositol) as potential biomarkers distinguishing COPD subgroups from healthy controls. This study offers novel molecular insights into the association of smoking with disease progression and provides a mechanistic understanding of COPD in different subgroups for better management of the disease. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=163 SRC="FIGDIR/small/717654v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@11db4org.highwire.dtl.DTLVardef@1451fb5org.highwire.dtl.DTLVardef@124b62aorg.highwire.dtl.DTLVardef@133872a_HPS_FORMAT_FIGEXP M_FIG C_FIG

Axenic cultivation of novel bacterial lineages, referred to as "gold standard in microbiology", remains challenging for fastidious or uncultured taxa due the challenges of replicating adequate growth conditions. We isolated strain PM69, a representative of the previously undescribed Bacillota class SHA-98, from a phenyl acid degrading, oligotrophic batch culture. By employing a broad spectrum of (anaerobic) culture techniques, biochemical, physiological, and genomic analyses, we characterised the strain as Thermoaminiphila catenidiffluenda, gen. nov., sp. nov., a thermophilic, strictly anaerobic, bacterium fermenting monosaccharides to acetate. Its motility, biofilm forming capacity, and ecological niche in biogas fermenters and hydrocarbon-associated habitats suggest adaptive strategies for harsh environments exhibiting e.g., high concentrations of aromatic compounds. This description of a new bacterial class not only expands the taxonomic diversity of phylum Bacillota but also provides insights into the metabolic versatility of yet uncultured microorganisms, with implications for carbon cycling and biotechnological applications. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=142 SRC="FIGDIR/small/718153v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@109cdd5org.highwire.dtl.DTLVardef@a896faorg.highwire.dtl.DTLVardef@502388org.highwire.dtl.DTLVardef@14ce1fd_HPS_FORMAT_FIGEXP M_FIG C_FIG

In this study, we investigate the individuality and information content of infrared molecular profiles derived from blood samples in a large, longitudinal health-profiling cohort and compare them to a standard clinical laboratory panel. Using Fourier-transform infrared spectroscopy, we obtained comprehensive molecular fingerprints from 4,704 self-reported healthy individuals over five visits spanning 1.5 years, alongside routine clinical laboratory measurements. We show that infrared profiles are highly individual-specific and remarkably stable over time, with intra-individual variability significantly lower than inter-individual differences--paralleling the characteristics observed in clinical laboratory data. To quantify and compare the information content of these molecular datasets, we employ individual identification as a proxy for Shannon entropy. In this framework, higher identification accuracy reflects a higher amount of information. Infrared profiles outperform the clinical laboratory panel in identifying individuals at scale, suggesting higher intrinsic information content. Furthermore, combining infrared and clinical laboratory data substantially improves identification performance (the identification of less than 3000 individuals by the clinical laboratory panel is boosted to more than 4000 by incorporating the infrared spectroscopic markers), highlighting the value of integrating complementary data modalities. These findings suggest a practical framework, rooted in information theory, for comparing molecular profiling approaches and emphasize the potential of infrared spectroscopy as a complementary tool in personalized medicine.

Pantothenamides (PanAms) comprise a promising class of antimalarial compounds that kill asexual blood-stage Plasmodium falciparum parasites and block transmission. Intriguingly, the most advanced PanAm in drug development, MMV693183, is approximately 100 times more potent against female gametocytes than males. We hypothesized that this specificity is explained by a difference in PanAm uptake, which we studied using a PanAm-based photoaffinity labelling (PAL) probe. We successfully synthesized a probe that competed with MMV693183 in drug sensitivity assays, while the probe did not display high potency by itself. We observed no significant difference in median fluorophore-labelled probe signal intensity between male and female gametocytes, although there might be a difference in subcellular localization of the probe between the sexes. By combining PAL with affinity purification and mass spectrometry, we were not able to identify novel candidate PanAm transporters. We conclude that PAL provides evidence that differences in PanAm uptake do not underly differences in PanAm sensitivity between the gametocyte sexes.

Rademikibart (CBP-201) is a human monoclonal antibody with higher binding affinity to IL-4R compared to dupilumab. Dupilumab is a first-generation interleukin-4 receptor alpha (IL-4R) inhibitor for treating IL-4R-dependent inflammatory disorders, including several dermatologic and respiratory conditions. Rademikibart, however, demonstrated better inhibition of STAT6 intracellular signaling in vitro and similar potency in inhibiting both IL-4 induced TARC release and IL-4 induced B cell activation. To further characterize the molecular function of rademikibart and its differentiation from dupilumab, we determined the crystal structure of the rademikibart fragment antigen binding (Fab) bound to IL-4R at 2.71 [A] resolution and compared this to the 2.82 [A] resolution structure of dupilumab Fab bound to IL-4R. The rotation angle between dupilumab and rademikibart bound to IL-4R is 54.88{degrees}. This rotation enables the binding epitopes of rademikibart, but not dupilumab, on IL-4R to overlap more closely with the conserved binding interface naturally utilized by IL-4 and IL-13 cytokines. Molecular dynamics (MD) studies on rademikibart and dupilumab bound to IL-4R examined the stability of the complexes and effects of amino acid mutations on receptor complex formation. MD simulations demonstrated that the third interface loop (residues 145 to 153 in domain 2) of IL-4R interacts directly with rademikibart, which is absent in the dupilumab/IL-4R complex. This finding is confirmed by increased hydrogen bond interactions at the interface between rademikibart and IL-4R, demonstrating superior binding energy for rademikibart. Through analysis of the x-ray crystallography structures, MD-equilibrated structures, and computational point-mutation analysis of rademikibart, we identified residue Y50 and R55 of the light chain and R97, R99, and Y101 of the heavy chain of rademikibart as key residues interacting with IL-4Rs third interface loop. Our data provides a molecular and structural rationale for the enhanced IL-4R inhibition by rademikibart over dupilumab, confirming rademikibart as an optimized second-generation IL-4R inhibitor.

The interdomain flexibility of GT-B fold glycosyltransferases regulates substrate binding and catalysis, yet the role of local structural variations in donor substrate specificity remains unclear. GumK, a GT70 enzyme from Xanthomonas campestris, exhibits local plasticity within its donor-binding pocket. We classify this plasticity into two conformational states, defined by the presence (closed state) or absence (open state) of a conserved hydrophobic interaction stabilizing the pocket. Using the AI-enhanced docking approach GNINA, we investigated the relationship between these states and substrate specificity by comparing UDP-glucuronate with various acidic and neutral substrate analogs. While docking scores showed limited discrimination among substrates, distance-based analysis between the sugar C6 atom and Lys307 revealed conformation-dependent trends. In the open state, negatively charged sugars preferentially interact with Lys307 via their carboxylate groups. Conversely, the closed state favors interactions with the pyrophosphate moiety. These results are consistent with physics-based simulations and suggest that donor specificity arises from the interplay between substrate chemistry and binding-site plasticity rather than from a single rigid binding mode. This study demonstrates how AI-driven docking, combined with an explicit representation of conformational states, can provide mechanistic insights into flexible enzymes and provide a rapid strategy for screening potential mutants.

Tissue-clearing techniques have transformed optical imaging of fixed specimens, yet their application to living systems remains limited by toxicity and removal of key tissue components. We recently demonstrated that absorbing molecules such as tartrazine can reversibly render live mouse skin transparent. Subsequently, it was reported that isotonic protein solutions can achieve ex vivo and in vivo cellular clearing. However, discrepancies remain regarding the optimal refractive index (RI) for live-cell clearing and the impact of elevated osmolality on cell viability. Here, using cultured mammalian cells, we systematically examine the dependence of optical contrast on medium RI and the effects of hyperosmolality. We find that, contrary to the recent report of an optimal RI of 1.36[~]1.37 for suspended cells, densely-packed adherent cells exhibit a monotonic decrease in phase contrast up to an RI of 1.41 with tartrazine. Moreover, even under highly hyperosmotic conditions ([~]1200 mOsm/kg), cultured cells exhibit minimal deformation and negligible loss of viability for up to 30 min in the clearing solution. These results demonstrate that tartrazine enables effective live-cell clearing at RI up to 1.41 while preserving viability under elevated osmolality, and motivate future studies to define optimal conditions for in vivo optical clearing. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=44 SRC="FIGDIR/small/717314v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@1c45280org.highwire.dtl.DTLVardef@483a5org.highwire.dtl.DTLVardef@5ed60forg.highwire.dtl.DTLVardef@377714_HPS_FORMAT_FIGEXP M_FIG C_FIG

Recombinant peptide production was pioneered in the 1970s for the generation of therapeutic peptides, with notable examples including insulin and somatostatin. These early methods required the use of cyanogen bromide (BrCN) for cleavage of the native peptide sequence from a fusion protein. Since that time, while numerous BrCN-dependent peptide methods continue to be reported, the accessibility and cost of site-specific proteases have improved dramatically. These developments have enabled alternative approaches to recombinant peptide generation that obviate the need for BrCN, an environmentally destructive toxin. We recently created an immobilized SUMO protease that can replace BrCN usage in recombinant peptide production workflows by releasing native peptides expressed as part of a SUMO-peptide fusion protein. We have used this approach to generate P113 peptide, the minimal active fragment of the antifungal peptide Histatin 5. In this report, we describe the creation and characterization of this immobilized SUMO protease and its application in the production of experimentally viable quantities of active P113 peptide.

DNA double-crossover (DX) molecules, comprising two Holliday junctions connected by two duplex arms, are fundamental building blocks of DNA nanostructures, but their mechanical properties remain poorly understood. Here we investigate the elasticity of isolated antiparallel DX motifs with 18 to 22 base pairs between the crossovers. Using mechanical models parameterized by extensive all-atom molecular dynamics simulations, we demonstrate that the bending rigidity of the duplexes within a DX motif is highly anisotropic, and that this anisotropy results from long-range elastic couplings involving all the duplex base pairs between the crossovers. The duplex stretch modulus decreases due to localized defects, while the twist stiffness is close to that of an isolated duplex. The DX core as a whole follows an analytical beam theory in bending but not in torsion. Our results extend beyond local elastic models of DNA nanostructures and pave the way for probing peculiar mechanical properties of other key motifs for DNA and RNA nanotechnology.

BackgroundPatent ductus arteriosus (PDA) is a common and potentially serious cardiovascular condition in preterm infants, particularly those with low gestational age and birth weight. Its management remains controversial due to variability in screening, diagnostic criteria, and treatment strategies. This study aimed to evaluate risk factors, outcomes, and management strategies for PDA in preterm infants, and to identify predictors of clinical and echocardiographic response to therapy. MethodsWe conducted a retrospective cohort study over a 4-year period (2016-2019) in the neonatal intensive care unit (NICU) of a tertiary care center. All consecutive preterm infants admitted during the study period were eligible. Infants with echocardiographically confirmed PDA who received pharmacological treatment with intravenous paracetamol or ibuprofen were included in the analysis. Missing data were minimal and handled using available-case analysis. Statistical analyses included descriptive statistics, Pearsons chi-square test, and multivariable logistic regression. ResultsAmong 2154 preterm infants admitted to the NICU, 60 were diagnosed with PDA (incidence : 2.8%). The mean gestational age was 29 {+/-} 2.6 weeks, and the median birth weight was 1200 g. Respiratory distress occurred in 95% of cases, mainly due to hyaline membrane disease (86.7%). PDA was symptomatic in 80% of infants. First-line treatment resulted in clinical improvement in 77% and ductal closure in 83.3% of cases, most within 3 days. Predictors of successful closure included gestational age [&ge;] 28 weeks (OR = 5.9; 95% CI : 1.7-20.2) and antenatal corticosteroid exposure (OR = 1.2; 95% CI : 1.0-1.6). Overall mortality was 35% and was significantly higher in infants < 28 weeks (OR = 5.0; 95% CI : 2.4-10.3). Clinical improvement (OR = 3.7) and echocardiographic closure (OR = 4.5) after first-line treatment were associated with reduced mortality. ConclusionsPDA in preterm infants is associated with substantial morbidity and mortality, particularly in those born before 28 weeks of gestation. Early diagnosis, antenatal corticosteroid exposure, and timely pharmacological treatment may improve outcomes. Systematic echocardiographic screening in high-risk neonates should be considered.

ImportanceGuideline-concordant care for young children with attention-deficit/hyperactivity disorder (ADHD) includes recommending parent training in behavior management (PTBM) as first-line treatment. However, assessing guideline adherence through manual chart review is time-consuming and costly, limiting scalable and timely quality-of-care measurement. ObjectiveTo evaluate the accuracy and explainability of large language models (LLMs) in identifying PTBM recommendations in pediatric electronic health record (EHR) notes as a scalable alternative to manual chart review. Design, Setting, and ParticipantsThis retrospective cohort study was conducted in a community-based pediatric healthcare network in California consisting of 27 primary care clinics. The study cohort included children aged 4-6 years with [&ge;] 2 primary care visits between 2020-2024 and ICD-10 diagnoses of ADHD or ADHD symptoms (n=542 patients). Clinical notes from the first ADHD-related visit were included. A stratified subset of 122 notes, including all cases with model disagreement, was manually annotated to assess model performance in identifying PTBM recommendations and rank model explanations. ExposuresAssessment and plan sections of clinical notes were analyzed using three generative large language models (Claude-3.5, GPT-4o, and LLaMA-3.3-70B) to identify the presence of PTBM recommendations and generate explanatory rationales and documentation evidence. Main Outcomes and MeasuresModel performance in identifying PTBM recommendations (measured by sensitivity, positive predictive value (PPV), and F1-score) and qualitative explainability ratings of model-generated rationales (based on the QUEST framework). ResultsAll three models demonstrated high performance compared to expert chart review. Claude-3.5 showed balanced performance (sensitivity=0.89, PPV=0.95, and F1-score=0.92) and ranked highest in explainability. LLaMA3.3-70B achieved sensitivity=0.91, PPV=0.89, and F1-score=0.90, ranking second for explainability. GPT-4o had the highest PPV [0.97] but lowest sensitivity [0.82], with an F1-score of 0.89 and the lowest explainability ranking. Based on classifications from the best-performing model, Claude-3.5, 26.4% (143/542) of patients had documented PTBM recommendations at their first ADHD-related visit. Conclusions and RelevanceLLMs can accurately extract guideline-concordant clinician recommendations for non-pharmacological ADHD treatment from unstructured clinical notes while providing clear explanations and supporting evidence. Evaluating model explainability as part of LLM implementation for medical chart review tasks can promote transparent and scalable solutions for quality-of-care measurement.

Objective Cerebral palsy (CP) affects approximately 1 million Americans and 18 million individuals worldwide, yet contemporary US epidemiologic data remains limited. We aimed to use Cerebral Palsy Research Network (CPRN) clinical registry to describe demographics and clinical characteristics of individuals with CP across the US and determine associations with gross motor function and genetic etiology. Methods Registry subjects were included if they had clinician-confirmed CP and prospectively entered data for Gross Motor Function Classification System (GMFCS) Level, gestational age, genetic etiology, CP distribution, and tone/movement types. Logistic regression was used to determine which of these variables plus race, sex, ethnicity, and age were associated with GMFCS level and genetic etiology. Results A total of 9,756 children and adults with CP from 22 CPRN sites met inclusion criteria. Participants were predominantly White (73.0%), male (57.3%), non-Hispanic (87.8%), and younger than 18 years (73.7%). Most were classified as GMFCS levels I-III (55.6%), born preterm (52.8%), had spasticity (83.8%), and had quadriplegia (41.9%); 12.2% were identified as having a genetic etiology. Tone/movement types, CP distribution, and gestational age were significantly associated with both GMFCS level and genetic etiology (p<0.001). Compared to White individuals, Black individuals were more likely to have greater gross motor impairment (p<0.001). Conclusion In this large US cohort, clinical and demographic factors, including race, were associated with gross motor function and genetic etiology in CP. These findings highlight persistent disparities and demonstrate the value of a national clinical registry for informing prognostication, quality improvement efforts, and targeted genetic testing strategies.

Objectives: Acute gastroenteritis is a leading cause of pediatric emergency department (ED) visits. While ondansetron reduces vomiting, intravenous rehydration, and hospital admissions, its efficacy when initiated at triage remains unclear. We aimed to evaluate whether triage nurse-initiated administration of ondansetron in children with suspected gastroenteritis reduces the proportion of patients requiring observation following initial physician assessment. Methods: We conducted a randomized, double-blind, placebo-controlled trial in a tertiary pediatric ED in Canada. Children aged 6 months to 17 years presenting with morae than 3 episodes of vomiting in the preceding 24 hours (including 1 within 2 hours of arrival), were eligible. At triage, we randomized participants to receive liquid ondansetron or a color- and taste-matched placebo. The primary outcome was the proportion of patients requiring observation after the first physician evaluation. Secondary outcomes included post-intervention vomiting, ED length of stay, patient comfort, and 48-hour return visits. The trial was registered at ClinicalTrials.gov (NCT03052361). Results: Recruitment was stopped prematurely due to the COVID-19 pandemic. Ninety-one participants were randomized to ondansetron (n= 44) or placebo (n= 47). Overall, 40 patients (45%) were discharged immediately after the initial physician assessment, with no difference between the ondansetron and placebo groups (44% vs. 45%; absolute difference -1%, 95% CI: -20% to 19%). No significant differences were observed in all secondary outcomes. Conclusion: In this trial, triage nurse-initiated ondansetron administration did not reduce the need for ED observation in children with presumed gastroenteritis. While being underpowered, this study could inform researchers planning larger clinical trials.

Background: Preterm births contribute to approximately 35% of neonatal deaths globally, with an estimated 13.4 million infants born prematurely each year. Despite this substantial burden, limited evidence exists on time to discharge and its determinants among preterm neonates admitted to Neonatal Intensive Care Units (NICUs), particularly in rural Ugandan settings. This study aimed to investigate time to discharge and associated factors among preterm neonates admitted to Kiwoko Hospital in Nakaseke District, Uganda. Methods: A retrospective cohort study was conducted using secondary data from Kiwoko Hospital on preterm neonates admitted to the Neonatal Intensive Care Unit (NICU) between 2020 and 2021 (n = 847). The cumulative incidence function was used to estimate the probability of discharge within 28 days of admission, accounting for competing events. A Fine and Gray sub-distribution hazard regression model was fitted to identify factors associated with time to discharge. Results: Of the 847 preterm admissions, 70.1% were discharged alive within 28 days. The median time to discharge was 14 days. The cumulative incidence of discharge by 28 days was 68%, accounting for competing events. During follow-up, 165 neonates did not complete the 28-day period, including 88 deaths. Factors significantly associated with time to discharge included place of delivery (SHR: 0.62; 95% CI: 0.53-0.73; p<0.001), maternal residence in other districts (SHR: 0.69; 95% CI: 0.48-0.99; p=0.044), extreme preterm (SHR: 0.05; 95% CI: 0.03-0.09; p<0.001), very preterm (SHR: 0.18; 95% CI: 0.14-0.25; p<0.001), moderate preterm (SHR: 0.59; 95% CI: 0.46-0.76; p<0.001), triplet births (SHR: 0.40; 95% CI: 0.23-0.68; p=0.001), 2-4 ANC visits (SHR: 0.70; 95% CI: 0.56-0.87; p=0.002), <=1 ANC visit (SHR: 0.64; 95% CI: 0.49-0.85; p=0.002), respiratory distress syndrome (SHR: 0.64; 95% CI: 0.48-0.74; p<0.001), and birth trauma (SHR: 2.62; 95% CI: 1.60-4.29; p<0.001). Conclusions: Respiratory distress syndrome, fewer antenatal care visits, out-of-district residence, and higher degrees of prematurity were associated with prolonged time to discharge among preterm neonates. Strengthening antenatal care utilization and improving access to quality neonatal care in underserved areas may enhance discharge outcomes.

Large language models are increasingly used for clinical guidance while their parent companies introduce advertising. We tested whether pharmaceutical ads embedded in the prompts of 12 models from OpenAI, Anthropic, and Google shift drug recommendations across 258,660 API calls and four experiments probing distinct epistemic conditions. When two drugs were both guideline appropriate, advertising shifted selection of the advertised drug by +12.7 percentage points (P < 0.001), with some model scenario pairs shifting from 0% to 100%. Google models were the most susceptible (+29.8 pp), followed by OpenAI (+10.9 pp), while Anthropic models showed minimal change (+2.0 pp). When the advertised product lacked evidence or was clinically suboptimal, models resisted. This reveals a structured vulnerability: advertising does not override medical knowledge but fills the space where clinical evidence is underdetermined. An open response sub analysis (2,340 calls across three representative models) confirmed that advertising restructures free-text clinical reasoning: models echoed ad claims at 2.7 times the baseline rate while maintaining high stated confidence and rarely disclosing the ad. Susceptibility was provider dependent (Google: +29.8 pp; OpenAI: +10.9 pp; Anthropic: +2.0 pp). Because this bias operates within clinically correct answers, it is invisible to accuracy based evaluation, identifying a class of AI safety vulnerability that standard testing cannot detect.

BackgroundMajor depressive disorder (MDD), a leading cause of disability worldwide, exhibits substantial heterogeneity in treatment outcomes. Patients who do not respond to standard antidepressant therapy account for the majority of MDDs disease burden. Risk factors have been implicated in treatment response, including genes impacting on how antidepressants are metabolised. Yet, despite its clinical importance, risk factors for treatment-resistant depression (TRD) remain unexplored in low- and middle-income countries (LMIC). We used data from the DIVERGE study on MDD to investigate the risk factors of TRD in Pakistan. MethodsDIVERGE is a genetic epidemiological study that recruited adult MDD patients ([&ge;]18 years) between Sep 27,2021 to Jun 30, 2025, from psychiatric care facilities across Pakistan. Detailed phenotypic information was collected by trained interviewers and blood samples taken. Infinium Global Diversity Array with Enhanced PGx-8 from Illumina was used for genotyping followed by DRAGEN calling to infer metaboliser phenotypes for Cytochrome P450 (CYP) enzyme genes. We defined TRD as minimal to no improvement after [&ge;]12 weeks of adherent antidepressant therapy. We conducted multi-level logistic regression to test the association of demographic, clinical and pharmacogenetic variables with TRD. FindingsAmong 3,677 eligible patients, polypharmacy was rampant; 86% were prescribed another psychotropic drug along with an antidepressant. Psychological therapies were uncommon (6%) while 49% of patients had previously visited to a religious leader/faith healer in relation to their mental health problems. TRD was experienced by 34% (95%CI: 32-36%) patients. The TRD group was characterised by more psychotic symptoms and suicidal behaviour (OR=1.39, 95%CI=1.04-1.84, p=0.02; OR=1.03, 95%CI=1.01-1.05, p=0.005). Social support (OR=0.55, 95%CI=0.44-0.69, p=1.4x10-7) and parents being first cousins (OR=0.81, 95%CI=0.69-0.96, p=0.01) were associated with lower odds of TRD. In 1,085 patients with CYP enzyme data, poor (OR=1.85, 95%CI=1.11-3.07, p=0.01) and ultra-rapid (OR=3.11, 95%CI=1.59-6.12, p=0.0009) metabolizers for CYP2C19 had increased risk of TRD compared with normal metabolisers. InterpretationThere was an excessive use of polypharmacy in the treatment of depression while psychological therapies were uncommon highlighting the need for more evidence-based practice. This first large study of MDD from Pakistan uncovered the importance of culture-specific forms of social support in preventing TRD, highlighting opportunities for interventions in low-income settings. Pharmacogenetic markers can be leveraged to predict TRD.