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STAT-C, an innovative training workshop supporting management of sick leave related to common mental health disorders: A case study for spontaneous scaling in primary care
Background Scaling primary care innovations to benefit broader populations is a key priority for decision-makers. While the science of effective scaling evolves, little is known about innovations that scale spontaneously , i.e., without deliberate guidance. Objectives To assess the spontaneous scaling process of STAT-C, a training workshop supporting management of sick leave related to common mental health disorders, and its perceived effects on primary care services and beneficiaries. Methods We conducted a mixed-methods descriptive single-case study using an Integrated Knowledge Translation (iKT) approach involving patient users. The case was defined as the spontaneous scaling of STAT-C, presented at the Quebec College of Family Physicians’ Innovation Symposium and assessed using a selection criteria checklist. Over one year, we observed the scaling process through monthly meetings with the innovation team and collected documents to retrace key steps. We conducted interviews with decision-makers, healthcare professionals, and end-users, along with a focus group with the innovation team. Data were analyzed thematically using documents, interviews, and meetings. The scaling process was examined using the Scaling Impact principles: justification, optimal scale, coordination, and dynamic evaluation. Results STAT-C met 71% of selection criteria. Fourteen participants were interviewed: innovation team (n = 2), healthcare professionals (n = 5), decision-makers (n = 4), and end-users (n = 3). Technical justifications included the need to standardize information across professionals (n = 10), while moral ones emphasized alignment with patient values (n = 8). Interviews revealed limited awareness of dynamic evaluation and a lack of indicators supporting further scaling. Ethical rationales reflected goal-oriented and duty-based reasoning. Preliminary data suggested improvements in healthcare professionals’ self-reported competence in managing CMHD-related sick leave, offering early indications of the innovation’s relevance. Conclusion This study highlights strategies, challenges, and outcomes of spontaneous scaling under real-world conditions, showing how pathways emerge, strategies evolve, and ethical dimensions shape decision-making.
The Attack on Equity in Medicine
Comparative analysis of empirical evapotranspiration models across Northern Ethiopia’s Climatic Zones
Outcomes of damage control laparotomy after trauma in low andmiddle-income countries: A systematic review and meta-analysis
Background Damage control laparotomy (DCL) is an established life-saving strategy for critically injured patients presenting with the lethal triad of hypothermia, acidosis, and coagulopathy. While outcomes in high-income countries (HICs) are well documented, evidence from low- and middle-income countries (LMICs), as classified by the World Bank, remains fragmented. This systematic review synthesises available evidence on DCL outcomes in LMICs. Methods A systematic search of PubMed, Scopus, Google Scholar, the Cochrane Library, and African Journals Online was conducted from January 2004 to February 2026. Studies reporting mortality outcomes after DCL for civilian trauma in World Bank–classified LMICs were included. Proportional meta-analysis using a DerSimonian-Laird random-effects model with logit-transformed proportions was performed. The protocol was prospectively registered on PROSPERO (CRD42025639498). The detailed search strategy is provided in S1 Table. Results Ten retrospective studies comprising 914 patients from five countries (South Africa, Pakistan, India, Oman, and Brazil) met the inclusion criteria. Six of the ten studies (n = 704, 77.0%) were from South Africa. The pooled mortality rate was 37.77% (95% CI: 31.38%–44.62%; 95% prediction interval: 20.1%–59.1%), with substantial heterogeneity (I² = 74.46%), based on 327 deaths among 914 patients. Subgroup analysis showed a pooled mortality of 31.61% (95% CI: 28.27%–35.15%, I² = 0.00%) in South African studies and 53.62% (95% CI: 44.47%–62.54%, I² = 31.65%) in non–South African LMIC studies (Cochran Q-test for subgroup differences: Q = 14.23, df = 1, p < 0.001). Conclusions DCL mortality in LMICs appears higher than mortality rates reported in HIC series, though direct comparison is limited by differences in study populations, injury profiles, case-mix, and the predominance of South African data in the available literature. The pooled estimate should be interpreted cautiously given the small number of studies, high heterogeneity, and retrospective study designs. Pre-hospital care, emergency theatre access, blood banking infrastructure, ICU capacity, and infection prevention represent potential areas for targeted improvement. Further prospective, multi-centre studies with standardised outcome definitions are needed to better characterise DCL outcomes across diverse LMIC settings.
Clusters of Concern — Spatial Link between Childhood Undervaccination and Measles Outbreaks in South Carolina
Event-triggered adaptive formation control for multi-agent systems using ratio-of-distance rigidity
The perspectives of individuals with incomplete spinal cord injury on measuring the intensity of balance challenge during reactive balance training: A qualitative study
Importance Balance rehabilitation is an important component of recovery for individuals with incomplete spinal cord injury (iSCI), who are at heightened risk of falls due to impaired postural control. Intensity of balance challenge refers to the postural control demand of a task relative to an individual’s maximum capacity. Achieving adequate intensity of balance challenge is essential for appropriate prescription of balance exercises. Balance intensity is often assessed through self-report on an ordinal scale. However, there is limited understanding of how individuals with iSCI interpret the concept of balance intensity and use self-reported scales. Design A qualitative descriptive study was conducted. Twelve individuals with iSCI (nine male, three female; mean age 67.2 ± 12.9 years) participated while undergoing Reactive Balance Training. Over six weeks, participants rated the balance challenge intensity of each exercise using an 11-point ordinal scale. Once per session, participants explained their ratings to a researcher who recorded the comments as field notes. After completing ≥10 training sessions, participants completed a semi-structured interview exploring their definitions of balance challenge, factors influencing their difficulty ratings, and their views on the Balance Intensity Scale, an alternative measure used with older adults. Interviews were audio recorded, transcribed verbatim, and analyzed alongside field notes using a conventional content analysis. Results Five themes were identified: 1) Influence of task familiarity on perceived balance challenge, 2) Influence of fear of falling on perceived balance challenge, 3) Misuse of ordinal scale, 4) Ambiguity of ordinal scale, and 5) Concern of the time demand of scales. Participants are concerned about lost training time and value clinician expertise over their self-reported rating for efficient assessment. Conclusions Participants’ perspectives on measuring balance intensity highlight the complexity of this concept. Future work could employ quantitative evaluations of the validity of self-reported balance intensity and consider the tools/skills used by clinicians.
Local scour around spur dikes under ice-jammed flow conditions
Deciphering intercellular communication in the cerebellar external granule layer: Insights into non-classical connections in neural development
Intercellular communication is essential for brain development. While classical modes—paracrine, juxtacrine, and synaptic signaling—are well characterized, emerging evidence suggests that membranous bridges, such as tunneling nanotubes (TNTs), forming de novo between cells and mainly described in vitro , may also contribute. Yet their presence and function in vivo remain unclear, partly due to the difficulty of distinguishing them from other intercellular connections (ICs). Building on connectomic observations in fixed tissue reporting ICs in the external granule layer (EGL) of the developing cerebellum, we examined their nature in postnatal day 7 (P7) mice. Using immunofluorescence, sparse genetic labelling, and live imaging, we distinguished division-independent ICs from cytokinetic bridges (CBs) and intercellular bridges (IBs). CBs were detected in the EGL, whereas IBs were not observed in this region. In addition to CBs, we identified membranous protrusions which appeared to link clonally and non-clonally related cells. The presence of these ICs reinforces previous connectomic evidence in fixed tissue and raises the possibility that they may participate in intercellular communication during cerebellar development. These findings warrant further investigation into a potentially underexplored mode of communication in the developing brain.
Early prognostication for ICU patients with combined respiratory and circulatory failure: an interpretable machine learning approach
Abstract Accurate prognostication in the intensive care unit (ICU) is essential for delivering personalized and ethically sound care, yet it remains a challenge for high-risk patients. This study aimed to develop and validate an exploratory machine learning model for predicting ICU mortality in critically ill patients requiring both mechanical ventilation and vasoactive support. We conducted a retrospective analysis of 4816 patient records from the AmsterdamUMCdb database. The XGBoost model was developed using 66 clinical and laboratory features collected within the first 24 h of ICU admission. The model demonstrated robust discriminatory performance in predicting in-ICU mortality at 24h from admission, achieving in internal validation an area under the receiver operating characteristic curve (AUROC) of 0.831 (95% CI [0.799–0.860]), a macro F1 score of 0.735, and a Brier score of 0.130, indicating reliable calibration. Explainable AI methods identified the minimum Glasgow Coma Scale score, patient age, and minimum platelet count as the most significant predictors. In this exploratory study, a machine learning model using single-center early ICU data showed promising performance for mortality prediction in a high-risk population. Given the lack of external or prospective validation, the model should be considered investigational and requires further validation before clinical application.
Ecotypes of triple-negative breast cancer in response to chemotherapy
Abstract Triple-negative breast cancer (TNBC) is an aggressive subtype that is frequently treated with chemotherapy, but only half of the patients respond well and have good clinical outcome 1,2 . Here we leveraged pretreatment tissue samples from treatment-naive patients with TNBC who received neoadjuvant chemotherapy and performed single-cell transcriptomic analysis of 427,857 cells from 101 patients and spatial transcriptomic analysis of 44 patients. We classified TNBC tumours into 4 patient-level subtypes (archetypes) using the cancer-cell gene expression and identified 13 metaprograms that reflect intra-tumoural heterogeneity at the single-cell level. The TNBC tumour microenvironment consisted of 49 immune and stromal cell states, many of which were reprogrammed relative to normal breast tissues. Furthermore, we identified eight distinct cellular communities (ecotypes) on the basis of the co-occurrences of cancer cells and tumour microenvironment cell types, and their spatial organization in tissues. In contrast to previous studies on T cells, our data show the importance of macrophage subtypes and cancer-cell metaprograms for interferon signalling, human leukocyte antigen expression and cell cycle activity that are associated with a good response to neoadjuvant chemotherapy. Collectively, this study provides new insights into the biology of untreated TNBC tumours and their association with chemotherapy response.
How gender is associated with physical bullying and victimization across adolescent stages
Background Physical bullying remains a significant form of peer aggression during adolescence, a developmental period marked by rapid bodily, psychological, and social change. Although gender differences in bullying have been widely documented, less is known about whether the association between gender and physical bullying perpetration and physical victimization varies across adolescent stages in contemporary non-WEIRD settings. Methods This study conducted a secondary data analysis of openly available survey data from 169 school-going adolescents in India. Participants were grouped into three developmental stages: early adolescence (10–12 years, 35.5%), middle adolescence (13–15 years, 49.1%), and late adolescence (16–18 years, 14.8%). Two Bayesian regression models aided by Markov Chain Monte Carlo estimation were used to examine the association between gender and physical bullying perpetration and victimization, and to assess whether age moderated these associations. Findings Male adolescents showed higher levels of both physical bullying perpetration and physical victimization than female adolescents. The association between male gender and physical bullying perpetration became more pronounced across later adolescent stages. By contrast, age did not clearly moderate the association between gender and physical victimization. Implications The findings suggest that bullying prevention in school settings should pay closer attention to gendered peer dynamics, developmental stage, and school climate. In particular, school-wide and developmentally sensitive approaches may be more useful than isolated incident-based responses for addressing physical bullying in adolescent populations.
Comparative analysis of clinical characteristics and self-management among patients with chronic wounds across different altitudes
Abstract To compare the clinical characteristics and self-management status of patients with chronic wounds across different altitudes and to identify factors associated with self-management. A cross-sectional design was used. Using convenience sampling, 113 patients with chronic wounds were recruited from the Hospital of the Tibet Autonomous Region Chengdu Office and categorized by long-term residential altitude into a high-altitude group (≥ 3000 m, n = 76) and a low-altitude group (< 3000 m, n = 37). Data were collected using a general information questionnaire and the Chronic Wound Self-Management Scale. Between-group comparisons were performed using the independent-samples t test, χ² test, or the Mann–Whitney U test according to data distribution. Multiple linear regression was conducted to explore factors associated with each dimension of self-management. The mean residential altitude was 3644.6 ± 118.2 m in the high-altitude group and 432.98 ± 172.3 m in the low-altitude group. Compared with the low-altitude group, the high-altitude group had higher proportions of Tibetan ethnicity, lower educational attainment, chronic refractory wounds, lower-limb wounds, yellow or black necrotic tissue, moderate-to-severe malodor, larger wound surface area, and polymicrobial infection, and lower proportions of complete independence in mobility and red granulation tissue (all P < 0.05). Regression analysis showed that sex, health insurance status, annual household income, wound duration, wound odor, mobility, and self-dressing behavior were associated with scores for living-arrangement management ( P < 0.05), while sex, annual household income, and occupation were associated with nutrition-management scores ( P < 0.05). Marked differences exist in clinical characteristics and self-management among chronic wound patients living at different altitudes, and self-management is jointly influenced by multiple factors. Tailored, precision health education and interventions should be implemented with consideration of lower educational levels and more complex wounds among patients living at high altitude to enhance self-management and improve outcomes.
Early potential safety signals for gliptins and gliflozins using real-world pharmacy data compared to spontaneous reporting
Background Dipeptidyl peptidase 4 inhibitors (DPP4i, gliptins) and sodium-glucose co-transporter 2 inhibitors (SGLT2i, gliflozins) are two oral antidiabetic drug classes that have been widely used in recent decades. Their pharmacological actions have led to the identification of new adverse drug reactions and contraindications. In this context, ambulatory real-world data (RWD) analysis has the potential to detect early signals of suspected adverse drug reactions (ADR) that complement or anticipate risk events. Methods We conducted an exploratory pharmacovigilance study based on a multicentre observational cross-sectional survey with retrospective 6-month recall in community pharmacies among patients treated with DPP4i or SGLT2i, using metformin as a control. Candidate drug–event signals identified in the pharmacy dataset collected in 2021 were compared with spontaneous reporting data from the Spanish Agency of Medicines and Medical Devices repository in 2022 and 2024. A validated adaptation of the Bayesian Confidence Propagation Neural Network (BCPNN) methodology was applied in all analyses. Results Exploratory signals identified in the community pharmacy dataset included sitagliptin–dry mouth (FDR 0.059), empagliflozin–asthenia (0.067), linagliptin–bone fracture (0.077), linagliptin–renal impairment (0.082), dapagliflozin–hyperglycemia (0.088), canagliflozin–pruritus (0.092), dapagliflozin–urinary tract infection (0.096), and alogliptin–exanthematic eruptions (0.100). Some of these findings were already described in the Summaries of Product Characteristics (SmPC), whereas others were not and later showed greater convergence with spontaneous reporting patterns in 2024. These findings should be interpreted as exploratory statistical signals for follow-up, particularly when based on small numbers of reports. Conclusions Community pharmacy real-world data may contribute to the early identification of potential safety signals that complement spontaneous reporting systems. Signals detected near the exploratory threshold should be interpreted cautiously and considered candidates for monitoring and further investigation rather than confirmed adverse drug reactions.
A comprehensive numerical investigation of memory effects and treatment impact in HIV-HPV co-infection dynamics
Embedding a primary care provider in sickle cell teams improves sickle cell care
Adults with sickle cell disease (SCD) experience fragmented access to primary and preventive care, which leads to poor adherence to general and SCD‑specific clinical practice guidelines. To address this gap, we implemented an embedded primary care model where a board‑certified internist/pediatric primary care provider (PCP) was embedded as a full member of the adult SCD care team, attending operational and educational meetings and practicing alongside hematologists in a comprehensive SCD clinic. Our primary aim was to test the hypothesis that an embedded primary care model was associated with improved guideline‑based preventive care and changes in acute healthcare utilization (e.g., emergency room visits and hospitalizations). We conducted a retrospective cohort study of adults with SCD seen at a single tertiary care center between July 2020 and June 2025. Of the 388 adults with SCD seen at the center, 174 received care from the embedded PCP. Patients in the embedded PCP model demonstrated significantly higher adherence to general preventive care including cervical cancer screening ((Odds Ratio) OR: 4.49; 95% (Confidence Interval) CI: 2.46, 8.23), depression screening (OR: 7.97; 95% CI: 1.78, 35.69), and diphtheria-tetanus-pertussis (Tdap) immunization (OR: 2.88; 95% CI:1.72, 4.84), and SCD‑specific guidelines, including annual eye examinations (OR: 2.59; 95% CI: 1.66, 4.04), pneumococcal immunization (OR: 3.58; 95% CI: 2.16, 5.92), urine protein screening (OR: 3.36; 95% CI: 1.89, 6.00), and ACE inhibitor/ARB use for microalbuminuria (OR: 9.37; 95% CI: 3.11, 28.23). Among patients who saw the embedded PCP, patients had significantly more annual outpatient visits (post-PCP: 4.2 vs pre-PCP: 2.7, p < 0.0001) and, while insignificant, fewer annual inpatient admissions (post-PCP: 1.4 vs pre-PCP: 1.9, p = 0.4869). Embedding a PCP within the adult SCD care team was associated with improved guideline‑based preventive care and more annual outpatient visits, which was consistent with more coordinated, outpatient‑focused management.
Treating knowledge as a conservation asset to resolve present–future biodiversity trade-offs
Abstract Conservation planning must allocate limited resources under substantial uncertainty about species interactions. A central dilemma is whether prioritization should be guided by phylogenetic diversity (PD), which preserves long-term evolutionary potential, or functional diversity (FD), which supports current ecosystem functioning. Because PD and FD are often weakly correlated, fixed prioritization schemes can misallocate effort when ecological information is incomplete. We develop a dynamic allocation framework in which the conservation objective is fixed, but the biodiversity proxy guiding decisions adapts to the level of interaction knowledge. When interaction information is limited, PD-based rankings are more robust to uncertainty; as interaction knowledge accumulates, rankings based on FD become increasingly reliable. We evaluate this framework using a 148-year Northeast Atlantic fish stomach time series and simulations on synthetic food webs. Across both empirical and simulated ecosystems, the adaptive strategy consistently produces higher post- disturbance diversity than fixed-weight PD–FD strategies and no-intervention baselines. This indicates that the PD–FD trade-off should be conditioned on the prevailing level of ecological knowledge, rather than fixed ex ante.
‘Us’ not ‘them’: scientists must use their skills to help stop polarization and division
Design and evaluation of a novel fusion antigen for diagnosing human strongyloidiasis: An immunoinformatics approach
Strongyloidiasis, caused by Strongyloides stercoralis , remains a neglected tropical disease (NTD) with significant clinical implications, particularly in immunocompromised individuals. Current serological assays for diagnosing strongyloidiasis are limited by suboptimal sensitivity and specificity. The development of recombinant fusion proteins for serodiagnostic applications represents a promising strategy to improve diagnostic accuracy. This study aimed to design a novel recombinant fusion antigen for the serodiagnosis of strongyloidiasis, using immunoinformatics approaches. Four immunogenic proteins (SsIR, L3NieAg.01, Ss3a, and Ss1a) were selected for the design of the fusion antigen. The most immunogenic regions of these proteins were identified based on epitope density and minimal cross-reactivity, and they were linked, using EAAAK linkers. The designed fusion antigen was then evaluated for its physicochemical properties, solubility, antigenicity, and potential cross-reactivity. Its three-dimensional (3D) structure was predicted, and the nucleotide sequence was codon-optimized to ensure efficient expression in Escherichia coli ( E. coli ). Finally, the optimized sequence was in silico cloned into the pET23a(+) expression vector. Immunoinformatics analyses demonstrated that the designed fusion antigen exhibits appropriate stability and robust antigenicity while showing no significant cross-reactivity. Codon optimization resulted in a codon adaptation index (CAI) of 0.92, and a GC content adjusted to 47%, confirming its compatibility with the E. coli expression system. Furthermore, no inhibitory cis-regulatory elements or repetitive sequences were identified post-optimization, supporting the feasibility of successful recombinant expression in E. coli . The bioinformatics findings of this study indicate that the designed fusion antigen holds significant potential for incorporation into ELISA-based serodiagnostic assays for strongyloidiasis.