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Causes of community deaths by verbal autopsy among persons with HIV in 33 districts in Zambia, 2020–2023

Zambia has achieved improvements in life expectancy among persons living with HIV (PLHIV) because of high antiretroviral therapy (ART) coverage, which should improve survival due to reductions in AIDS-defining conditions. However, recent estimates of the most common causes of death are not widely available. We utilized mortality surveillance data to report on common causes of death among persons with HIV who died in community settings in Zambia. The Zambian Ministry of Health conducted sentinel mortality surveillance of community deaths in 45 hospitals in 33 of 116 districts from January 2020 through December 2023. Verbal autopsies (VA) were conducted through interviews with relatives or close associates of deceased persons using the 2016 World Health Organization tool. HIV status was reported. A probable cause of death was assigned by a validated computer algorithm (InterVA5). We describe the top assigned causes of death stratified by HIV status. Verbal autopsies were conducted for 67,079 community deaths, of which 11,475 (17.1%) were persons with HIV. The mean age at death was 45 years among persons with HIV and 48 years for persons without HIV (T-test p < 0.001). The most common probable causes of death identified by VA among persons with HIV were HIV/AIDS-related causes (50.4%), cardiac disease (13.1%), pulmonary tuberculosis (7.5%), and digestive neoplasms (3.9%) . Leading probable causes in decedents without HIV were cardiac disease (24.9%), stroke (8.5%), and acute respiratory infection including pneumonia (7.6%). Overall, the percentage of deaths attributed to HIV/AIDS-related causes decreased from 11.2% to 7.5% (trend test p < 0.001) and the percentage of cardiac deaths increased from 18.7% to 25.4% (p < 0.001) from 2020 to 2023. These findings support interventions to strengthen the integrated management of noncommunicable diseases in community settings across Zambia. Among persons with HIV, a high percentage of deaths attributed to HIV/AIDS highlights the need to maintain high ART coverage and retention. Strategies, such as increased use of minimally invasive tissue sampling, may improve characterization of the high proportion of deaths attributed to non-specific HIV/AIDS-related causes through VA surveillance.

Conformationally Adaptive Molecular Cages Enabled by Metal Cluster-Mediated Assembly

Patterns of symptom deterioration can support multimorbidity management in COPD: Perspectives of patients and healthcare professionals

Introduction Comorbidities significantly complicate COPD management. Remote monitoring could aid real-time disease and symptom management, assisting both patients with multimorbidity and healthcare professionals (HCPs). This study aimed to explore how insight in patterns of symptom deterioration, derived from remote monitoring, could enhance multimorbid COPD management as perceived by patients and HCPs. Methods Using daily symptom data collected via a mobile diary in the prospective RE-SAMPLE cohort study, patterns of symptom deterioration of COPD, chronic heart failure, anxiety, and depression were visualized per patient (follow-up duration of ≥4 months). Semi-structured individual interviews were conducted with Dutch patients with COPD and ≥1 comorbidity, and with HCPs from pulmonology, cardiology, and medical psychology who were involved in care for patients with multimorbidity. Interviews addressed current multimorbid COPD management, its challenges, and the way pattern visualizations of symptoms deterioration could support disease management. Transcripts were thematically analyzed using an inductive approach. Results 7 patients (69–80 years, 4 men) and 7 HCPs were interviewed in the hospital (patients and HCPs), at home (patients) or online (HCPs). Three overarching themes were identified, representing the elements of multimorbid COPD management that could be supported by the pattern visualizations: 1) relationship between diseases, 2) decision-making, and 3) self-management. According to patients and HCPs, pattern visualizations can be an informative source to explain the relation between COPD and comorbidities, function as a conversation starter facilitating communication between patients and HCPs as well as between medical disciplines, and educate patients in adequately recognizing their care needs. Conclusion Three elements of personalized multimorbid COPD management were identified through qualitative analysis, which can all be supported by visualizing patterns of symptom deterioration via remote monitoring. The visualizations could enhance patients’ understanding of their diseases, improve shared decision-making, improve in-hospital multidisciplinary collaboration, and support multimorbid COPD (self-)management.

Key personality and training factors influencing athletes’ mental health - based on machine learning

Athletes face a higher risk of mental health disorders compared to the general population, and prior theoretical and empirical work suggests that personality traits and training-related factors may play important roles in shaping athletes’ mental health. This study aimed to identify the key personality traits and training-related factors associated with mental health outcomes among athletes. A total of 328 athletes (53% male, 17.84 ± 3.155 years) were assessed using standardized measures of demographics, training history, Cattell’s 16 Personality Factors, and mental health status, with psychological symptoms evaluated via the Symptom Checklist-90 (SCL-90). To determine the most influential factors related to mental disorders, both random forest and logistic regression models were applied. The results showed that 44.6% of athletes presented at least one symptom of a mental disorder. According to the random forest model, the most significant personality and training factors included injury impact, athletic level, training years, boldness, sensitivity, apprehension, and tension. Logistic regression analysis further indicated that high boldness, higher athletic level, and longer training years acted as protective factors, while greater injury impact, apprehension, tension, and sensitivity were associated with an increased risk of mental disorders. These results identify key risk and protective factors for mental health disorders among athletes, highlighting the need for individualized approaches in athlete mental health management, and emphasizing the importance of early identification and targeted interventions.

Snapshots of Cooperative Trimetallic Alkene Hydrogenation

Investigating organizational resilience in a medicine and health sciences university in United Arab Emirates

Introduction COVID-19 pandemic emerged in late 2019, leading to global disruption and forcing people to adapt to a new reality. The intensity of the pandemic affected many organisations’ preparedness, response, and recovery efforts, causing numerous businesses to struggle. Although no single theory fully explains why some businesses thrived during this time, the concept of organisational resilience stands out. Organisations with a resilient culture seemed better equipped to address risks, adapt effectively, and seize opportunities for innovation. Therefore, the purpose of the current study is to critically examine the response to COVID-19 of a medicine and health sciences university in Dubai, United Arab Emirates. Methods The study relied on a convergent mixed methods approach to research. A tailor-made questionnaire was used to collect quantitative data using two 5-point Likert-type scales: ‘Opinions about Organizational Response’ and ‘Conducive Organizational Response Behaviours’ (where 110 current employees who were tenured during COVID-19 were selected, using purposive, non-probability sampling, and in turn invited to participate). Semi-structured interviews were conducted to collect qualitative data [where seven respondents who had completed the questionnaire and agreed to participate in follow-up interviews were selected (i.e., convenience, nonprobability sampling) and in turn invited to participate]. The quantitative data were descriptively and inferentially analysed. Qualitative data was analysed using an inductive six-step thematic approach. The quantitative findings were mapped onto the output of qualitative analysis using the iterative joint display analysis process. Results A total of 70 employees completed the questionnaire (63.64%), and six out of seven invitees participated in the semi-structured interviews. The percentage of the total extent of agreement of ‘Opinions about Organizational Response’ score was 90.94%. As for the percentage of the total frequency of observation of ‘Conducive Organizational Response Behaviours’ score, it was 95.08%. The qualitative analysis generated a conceptual model, namely: ‘Enablers of Organizational Resilience’, with five interlinked themes namely: Preparedness and planning for uncertainty, Adaptation and agility, Team cohesion, Social responsibility, and Learning organisation. Four meta-inferences emerged from integrating the data findings: Response characteristics, Behaviour specificities, Consistency of opinions, and the Fundamental role of organizational culture. Conclusion The findings reveal that organizations, in the intersect between higher education and public health, should continue on innovatively investing in agile leadership, strategic partnerships, and a robust continuous learning and development culture to better navigate future disruptions.

O ₂ -Mediated Reactivity of Confined Carbenium Ions in Zeolites

Research on the double-edged effect of intelligent algorithm recommendation on shaping college students’ values and the path of collaborative governance

This study proposes a stochastic game model of value perception using a multi-agent reinforcement learning framework to address the double-edged influence of algorithmic recommendation systems on college students’ values. With 73% of students trapped in algorithmic information cocoons and a 23% exposure rate to historical nihilism content on campus platforms, traditional governance methods such as keyword filtering and manual review are insufficient. To address this, we construct a 128-dimensional state space that integrates user personas, policy strength, and value similarity, and define a constrained action space to regulate recommendation weights. A dual-path evolution mechanism is introduced: one path driven by social practice diffuses red values through replication dynamics, while the other uses institutional deterrence to suppress harmful content. The model rigorously proves convergence to a Nash equilibrium with value similarity ≥0.8 when the deterrence factor equals 0.4. Empirical validation on 15,600 users and 12,340 content items, with cross-validation on 5,200 users, shows a 107% increase in value similarity and a 91% reduction in harmful content exposure. Consensus convergence time is reduced by 3.3 times. The results demonstrate the effectiveness and generalizability of this approach, offering a dynamic governance paradigm aligned with national algorithm regulation strategies.

Capturing Dynamic Core Reconstruction and Ligand Desorption of Atomically Precise Ag Nanoclusters with Machine Learning Force Field

Detection of traces of calcium oxalate druses in fossil leaves of angiosperms and gymnosperms from different sites and geological periods

Calcium biomineralization in plants occurs in a variety of patterns such as calcium carbonate cystoliths and calcium oxalate (CaOx) crystals and agglomerates in different forms. CaOx druses and prismatic crystals with sizes between 20–100 µm are found in large amounts in the leaves of many extant plants, in angiosperms particularly in dicotyledons. In gymnosperms, large CaOx druses are often found in Cycadales and Ginkgo along the leaf veins, while most conifers contain microcrystals of <10 µm size in the parenchyma. In plant fossils, patterns of calcium biominerals are rarely reported because they usually disappear during fossilization. Traces of CaOx druses have been reported recently in fossils of dicotyledon plant leaves from Oligocene; here the CaOx was replaced by organic or mineral compounds. But there is still no certain report of CaOx druses traces in Paleozoic or Mesozoic fossils. In the study presented here, granular structures in fossil leaves from different sites across the Devonian to the Neogene were investigated and compared with biomineral patterns in extant leaves of gymnosperm and angiosperm trees. These granular structures resembled patterns of CaOx druses in extant leaves in morphology and distribution and were interpreted as probable casts of CaOx druses. Well-preserved angiosperm fossils from various sites such as seed ferns since Devonian, and Ginkgophytae since Carboniferous all showed such granular traces. The diverse chemical composition of these casts of CaOx druses (e.g., pyrite, iron oxide, organic material, SiO 2 ) depends on fossilization conditions and the chemistry of the surrounding matrix. Good knowledge of the morphology and distribution patterns of biominerals in all relevant plant groups is a basic prerequisite for recognizing their traces in plant fossils. This first extensive study of previously overlooked traces of CaOx druses in plant fossils is a promising step toward a more detailed identification of these fossil microstructures.

Molecular Wedge Reconstructing the Solvation Structure for Low-Temperature Ah-Level Anode-Free Sodium Metal Batteries

Species diversity within morpho-functional groups drives diversity dependence in reef ecosystems

Changes in species diversity can alter reef ecosystem composition by impacting the origination and extinction of species within co-existing groups. A massive literature exists on exploring the impact of species diversity shifts through a taxonomic centered perspective. We here address the consequences of shifts in diversity using a novel morpho-functional (MF) group approach. We categorized species into MF groups based on growth forms. Our analysis demonstrates that species diversity has not been uniform across morpho-functional (MF) groups over time. Examination of coral origination and extinction rates revealed multiple pulses of rate shifts, indicating non-uniform rate changes in both processes. When addressing the potential drivers for these patterns, we found no significant correlation between species diversity increases and extinction within MF groups, thus identifying the absence of redundancy-related effects within individual groups. However, our study highlights a strong correlation between species diversity within a MF group and the rates of origination and extinction of some co-existing groups, thus, identifying morphology mediated species diversity as a potential driver for diversity dependence. We demonstrate this relationship is selective and that species capable of building biogenic habitat structures can influence the diversity and morphology of species that coexist, thus constantly modifying the reef architecture and functional potential through time. Species diversity dependence mediated through morphology shapes the reef functional composition through time.

Dioxazolones as Masked Isocyanate Electrophiles for Global Profiling of Lysine Reactivity and Ligandability

Effect of Ab interno XEN gel stent implantation on corneal astigmatism

Purpose To assess surgically induced astigmatism (SIA) after XEN gel stent implantation over 5 visits during a 3-month follow-up. Changes in intraocular pressure (IOP), IOP-lowering medications, and best-corrected visual acuity (BCVA) were also assessed. Methods This prospective cohort study recruited 24 eyes from 24 glaucoma patients at KKU Eye Center, Khon Kaen University, Thailand. All eyes underwent XEN implantation, using our specific surgical technique. We evaluated both the magnitude and the axis of SIA at 1, 2 weeks, 1, 2 and 3 months after the procedure. Preoperative and postoperative intraocular pressure (IOP), IOP-lowering medications, and best-corrected visual acuity (BCVA) were also analyzed. Results We observed a statistically significant centroid SIA of 0.14 D. at an axis of 105° and median SIA of 0.36 D. at 1 week following XEN (p < 0.01). However, no further significant statistical change in SIA was found at 2 weeks, and 1, 2, and 3 months postoperatively. Additionally, there was no significant change in BCVA after XEN. Moreover, reductions in IOP and IOP-lowering medications were statistically significant. Conclusions Ab Interno XEN gel stent implantation induces a small SIA immediately after the surgery, but no further significant change during 3-month follow-up period. Although SIA has no significant effect on visual acuity, this should be addressed with patients preoperatively. Further studies are needed to investigate how different surgical techniques may affect refractive changes after XEN.

Designing Fluorine-Free Electrolytes for Lithium Metal Batteries

Retraction: Cardiovascular and mortality outcomes of DPP-4 inhibitors vs. sulfonylureas as metformin add-on therapy in patients with type 2 diabetes: A systematic review and meta-analysis

Aza Analogs of Arene Oxygenase Metabolization via Iron Catalysis

Metabolic profiles of captive Asian elephants (Elephas maximus) in Lao PDR and Thailand

This study compared metabolic health biomarkers, lipid profiles, body condition scores (BCS), and adrenocortical function of 78 captive Asian elephants ( Elephas maximus ) managed under contrasting systems in Laos and Thailand. In Laos, elephants are primarily managed in naturalistic forest environments with limited tourist interaction, while many Thai elephants participate in tourism activities like riding and are fed calorie-dense supplemental foods, with restricted access to natural forage. Serum and fecal samples were collected for 1 year to assess serum glucose, insulin, cholesterol, triglycerides, lipoproteins, fecal glucocorticoid metabolites (fGCM), and BCS across seasons, sexes, and management regimens. Thai elephants exhibited significantly higher glucose, insulin, lipid levels, and BCS, reflecting the effects of high-calorie diets and reduced exercise, while Lao elephants displayed healthier metabolic profiles and BCS, attributed to natural foraging and physical activity. In Thai elephants, BCS was positively correlated with insulin, and negatively correlated with the glucose-to-insulin ratio, total cholesterol, HDL, and LDL, suggesting overweight elephants in Thailand are at risk of metabolic derangements. None of those parameters were significantly correlated with BCS in the Laotian population. A surprising finding was higher fGCM in Lao elephants, which could have been related to new social opportunities and pandemic-driven management disruptions at the Elephant Conservation Center. These findings underscore how management practices, particularly diet composition, exercise opportunities, and degree of naturalistic living, can influence the health and welfare of captive elephants and support the adoption of more naturalistic management strategies to improve elephant welfare in captivity.

Air-Stable Cobalt−Semiquinone Radical Complexes on Carbon Nanotubes: A Redox Switch for Anion Response

STAC-Net: A hierarchical framework for modeling and predicting urban traffic flow with uncertainty quantification

With the rapid urbanization and growing traffic complexity, predicting urban traffic flow with high accuracy has become an essential challenge. Traditional methods struggle to model the uncertainty in traffic flow due to intricate spatiotemporal dependencies and external influencing factors such as weather and events. In this paper, we propose a novel approach based on STAC-Net for urban traffic flow uncertainty modeling and prediction. The proposed method introduces a framework that combines spatiotemporal graph convolution, Convolutional Gated Recurrent Units (ConvGRU), and hierarchical self-attention mechanisms to effectively capture the spatiotemporal dependencies and dynamic uncertainty in traffic data. The spatiotemporal graph convolution module models the spatiotemporal features of traffic flow, ConvGRU enhances the ability to learn long-term temporal dependencies, and the hierarchical self-attention mechanism optimizes multi-scale feature extraction, improving prediction accuracy and robustness. To address uncertainty quantification, we incorporate the Neural Processes (NP) module, which generates multiple prediction outcomes to quantify uncertainty and provide more reliable decision support. This multi-output approach allows the model to provide precise and reliable traffic flow predictions for traffic management departments. Experimental results show that, on the METR-LA, PeMS04, and PeMS08 datasets, our model outperforms baseline methods across all time horizons, achieving a 10.5% reduction in Mean Absolute Error (MAE) and a 12.3% improvement in Root Mean Squared Error (RMSE). In conclusion, our method provides a reliable and efficient framework for urban traffic flow prediction, addressing uncertainty in real-world traffic scenarios.