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Utilizing glauconite extracts to enhance soil health and sugar beet (Beta Vulgaris L.) performance in salt-affected soil

Soil salinity remains a critical constraint to sustainable agricultural production and long-term soil resource management. A field investigation was conducted over two consecutive growing seasons (2022/2023 and 2023/2024) to evaluate the potential of glauconite-derived potassium amendments for improving soil health and enhancing sugar beet ( Beta vulgaris L.) performance under saline soil conditions. Treatments included conventional potassium sulfate (K₂SO₄), raw glauconite powder (G), and foliar applications of glauconite extracts prepared with EDTA (GE), nitric acid (GN), and fulvic acid (GF), each applied at two concentrations (20 and 40 mL L ⁻ ¹). Among the tested treatments, GE2 and GF2 produced the most substantial improvements in soil quality, with GF2 reducing soil electrical conductivity by 35.11% and exchangeable sodium percentage by 23.33%, while increasing organic matter content and available nutrients. Soil biological indicators also responded positively, with GF2 enhancing dehydrogenase, urease, and phosphatase activities by 7.21%, 16.43%, and 48.60%, respectively. Correspondingly, GF2 achieved the highest increases in root yield (67.79%), shoot biomass (107.34%), and sugar yield (92.11%). Multivariate analyses (PCA and RDA) confirmed strong linkages between sugar yield and key soil variables, particularly available potassium, enzymatic activities, and microbial biomass. These results demonstrate that tailored glauconite-based foliar formulations—especially fulvic and EDTA extracts at higher concentrations—can serve as environmentally sound and agronomically effective measures for improving soil quality, restoring saline-affected lands, and enhancing sustainable crop productivity within the broader framework of soil and water conservation.

HIV self-testing awareness among African refugee male sex workers in Italy: A mixed-methods study

HIV disproportionately affects African refugee male sex workers (ARMSWs) in Italy, who face individual, structural and systemic barriers to HIV prevention and care services. HIV self-testing (HIVST) offers a promising strategy to improve testing access, yet awareness remains understudied in this population. This study examines HIVST awareness and associated factors among ARMSWs to inform targeted interventions. A mixed-methods sequential exploratory design was employed, combining quantitative surveys (n = 150) with qualitative interviews (20 in-depth interviews, 2 focus group discussions) among ARMSWs in Italy. Participants were recruited through venue-based and snowball sampling in partnership with a community organization. Quantitative data on HIVST awareness and correlates, including sociodemographic, healthcare access, and sex work characteristics, were analyzed using chi-square tests and logistic regression. Qualitative data from audio-recorded interviews underwent summative content analysis to explore awareness pathways and perceptions. Key findings revealed only 45% of participants were aware of HIVST, with just 47.8% of these having ever used a self-test. Higher education (aOR=1.92, p = 0.022) and prior STI testing (aOR=2.32, p = 0.015) significantly predicted awareness of HIVST. Qualitative data showed two awareness pathways: first-time exposure through the study and prior encounters via clients or community programs. Participants highlighted HIVST’s privacy and convenience as key benefits. Community-based, peer-led approaches, combined with healthcare provider engagement, are essential for increasing HIVST awareness and uptake among ARMSWs. These findings have broader implications for improving HIV testing strategies among hard-to-reach migrant populations across Europe.

The impact of China’s clean energy market on the market connectivity of rare earth industrial chain

The accelerating global transition to clean energy underscores the critical role of rare earth elements in renewable technologies. As the world’s largest producer of clean energy and rare earth minerals, China’s market dynamics are pivotal to the stability and connectivity of the rare earth industrial chain. This study investigates the interplay between China’s clean energy market and the connectivity of its rare earth industry chain using a Time-Varying Parameter Vector Autoregression model, as well as Autoregressive Distributed Lag and Nonlinear Autoregressive Distributed Lag models. The results reveal significant short-term spillover effects from clean energy market shocks, which enhance connectivity within the rare earth industry chain, while long-term impacts weaken these interactions as markets stabilize. Asymmetric effects are pronounced, with the photovoltaic sector exerting a particularly significant influence on rare earth market connectivity. These findings highlight the dynamic and nonlinear linkages between clean energy and rare earth markets, providing valuable insights for policymakers and investors to ensure industrial chain resilience and support sustainable development.

Reversible Dimensional Programming of Covalent Organic Frameworks

Abstract While the dimensionality of covalent organic frameworks (COFs) is a fundamental determinant of their physicochemical properties, their precise control remains a mystery and poses considerable challenges. Herein, we present a novel reversible coordination‐directed clip‐off chemistry strategy for reversible dimensional programming of COFs. Utilizing COFs containing coordinative Ag–N bonds as templates, structural transformation from a higher dimension to the lower one can be achieved by selectively cleaving these linkages. Noticeably, a 3D COF is converted into an unprecedented 1.5‐dimensional (1.5D) COF, which is constructed with three‐dimensional (3D) bonds but exhibits one‐dimensional (1D) linear chains. This dimensional tailoring is fully reversible; reintroduction of Ag(I) repairs the cleaved bonds, restoring the original dimensions. Significantly, the derived lower‐dimensional COFs exhibit markedly improved efficiency in extracting uranium from seawater and mining wastewater.

Comparing intentional and unintentional poisoning among patients presenting to the emergency department at a tertiary care center in Lebanon: A retrospective descriptive analysis

Introduction Poisoning is a significant global public health issue, contributing substantially to emergency department (ED) visits. In 2021, the WHO reported nearly 2 million deaths and 53 million disability-adjusted life-years (DALYs) lost due to chemical exposures. Although regional data exist, Lebanon lacks national statistics on intentional and unintentional poisonings. This study compares these exposures in terms of patient characteristics, exposure agents, ED management, outcomes, and disposition. Methods A retrospective chart review was performed using a toxicology database at a tertiary care center in Beirut from March 1, 2015, to August 1, 2023. All patients presenting with poisoning were included. Variables collected included demographics, psychiatric history, exposure route and type, ED course, and clinical outcomes. Results Of 886 cases, 56.2% were intentional and 43.8% unintentional. Females predominated in intentional cases (68.3% vs. 47.9%, p < 0.001). Children under 6 years accounted for most unintentional exposures (0% vs. 48.5%, p < 0.001), while adults aged 20–59 were more often involved in intentional poisonings (69.9% vs. 31.2%, p < 0.001). Intentional exposures commonly involved sedatives, hypnotics, and antipsychotics (32.1%), while unintentional ones included analgesics (8%) and cleaning agents (7.5%). Mood disorders were reported in 45.6% of intentional cases. More patients were discharged from the ED in the unintentional group (50% vs. 38.4%, p < 0.001). Minor effects predominated in intentional exposures; unintentional cases more often showed no clinical effects. Moderate and severe outcomes occurred at similar rates. Discussion This study reveals a higher prevalence of intentional poisoning in Lebanon, particularly among females and individuals with psychiatric disorders. Unintentional poisonings predominantly affected children under six, often due to poor storage and lack of child-resistant packaging. The findings underscore the need for regulatory policies, public education, and psychiatric support. Conclusion Key differences between intentional and unintentional poisonings in Lebanon highlight the need for targeted preventive strategies and risk mitigation in high-risk populations.

A deep learning-based evaluation system for child-friendly urban streets integrating abstract and concrete features—A case of Shanghai Urban Street

To address the challenges of high subjectivity, difficult data acquisition, and low efficiency in current evaluation methods for child-friendly urban streets, this study proposes a deep learning-based evaluation system that integrates both concrete and abstract features. The study utilizes 1,322 street samples in Shanghai, integrating 50 quantifiable concrete features with abstract features extracted from 6,724 street view images. Perceptual survey data from children aged 7–12 were incorporated as the target output for model training. Methodologically, abstract features were first extracted from streetscapes using a ResNet18 convolutional neural network. These features were then fused with the concrete features, and a multi-layer artificial neural network was constructed to predict child-friendliness. The results demonstrate that the model achieved an average accuracy of 96.91% on the validation set and an overall accuracy of 97.35% on the test set, indicating its effectiveness in identifying street samples with low levels of child-friendliness. Further case validation demonstrates the model’s capability to rapidly identify child-unfriendly spatial characteristics at an urban scale, including poor traffic safety, inadequate pedestrian environments, and a lack of engaging elements. This study offers a novel technical pathway for the quantitative evaluation and targeted management of child-friendly streets.

Understanding the gut microbiome through a fitness intervention of aerobic and resistance training for individuals with type 2 diabetes mellitus (GUTFIT: A Study Protocol)

Introduction Exercise is a cornerstone of type 2 diabetes (T2DM) management, yet individuals exhibit vast inter-individual variability in glycemic response to interventions. Gut microbial diversity and exercise intensity may be factors influencing this response variability. However, the interplay between exercise intensity, microbial adaptations, and glycemic outcomes in individuals living with T2DM remains unclear. Objectives The purpose of this protocol is to describe the GUTFIT study, which aims to test whether performing vigorous-intensity combined aerobic and resistance training produces greater changes in glycemia and gut microbial diversity than moderate-intensity training in individuals living with T2DM. A secondary objective is to explore whether decreases in glycemia after exercise are associated with alterations in gut microbial community architecture and diversity. Methods The GUTFIT Study (NCT06268743) is a parallel-group, single-blinded, randomized trial involving 40 adult participants (n = 20 female) living with T2DM. Participants will be randomized to 16 weeks of: 1) vigorous-intensity exercise (aerobic training at 70–80% heart rate reserve and resistance training at 8–10 repetitions of 75–80% maximal strength) or 2) moderate-intensity exercise (aerobic training at 45–55% heart rate reserve and resistance training at 12–15 repetitions of 65–70% maximal strength). Glycemia will be measured via glycated hemoglobin (HbA1c), and gut microbial composition will be determined in participant fecal samples using next-generation sequencing (Illumina MiSeq) of 16S ribosomal DNA genes. All outcome measures will be tested pre- and post-intervention. Discussion Results of this study will provide further insight into the role of exercise intensity in changes in glycemia and the gut microbiome, and whether there is an intensity-dependent association between exercise-induced changes in glycemia and gut microbial diversity in individuals living with T2DM.

Expression of Concern: Shikonin Kills Glioma Cells through Necroptosis Mediated by RIP-1

Global, regional, and national burdens of attention deficit hyperactivity disorder in adolescents and young adults aged 10–24 years from 1990 to 2021: A trend analysis

Background Attention Deficit Hyperactivity Disorder (ADHD) is a major neurodevelopmental disorder among adolescents and young adults (AYAs) worldwide. However, there is still insufficient understanding of the burden and trends of this condition. This study aims to assess the trends in the global, regional, and national burden of ADHD among AYAs aged 10–24 years from 1990 to 2021. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021, our study reports estimates of the incidence, prevalence, and disability-adjusted life-years (DALYs) of ADHD among AYAs at the global, regional, and national levels, including the corresponding rates and 95% uncertainty intervals (UIs). We also analyzes the trends in the burden of ADHD from 1990 to 2021 from both global and local perspectives, specifically by Estimated Annual Percentage Change (EAPC) and Average Annual Percentage Changes (AAPCs). Additionally, these global trends are further examined according to age, sex, and Socio-Demographic Index (SDI). Results Globally, the incidence of ADHD among AYAs decreased slightly from 12.61 per 100,000 population in 1990 to 11.89 per 100,000 population in 2021, with an EAPC of −0.61% (95% CI −0.79 to −0.43) and AAPCs of −0.17% (95% CI −0.28 to −0.05). The prevalence rate decreased slightly from 2,381.82 per 100,000 population in 1990–2,173.48 per 100,000 population in 2021, with an EAPC of −0.58% (95% CI −0.63 to −0.53) and AAPCs of −0.44% (95% CI −0.47 to −0.42). The rate of DALYs decreased from a 1990 rate of 30.31 per 100,000 population to 26.56 per 100,000 population in 2021, with an EAPC of −0.58% (95% CI −0.63 to −0.52) and AAPCs of −0.44% (95% CI −0.47 to −0.42). In terms of gender, incidence, prevalence and rates of DALYs were higher in males than in females during the same period. In terms of age, the incidence rate originated only from the 10–14 years age group, and only prevalence and DALYs rates were present in the 15–19 years age group and 20–24 years age group and the trend analysis results were correlated with the age group. According to SDI quintiles, incidence, prevalence, and rates of DALYs for ADHD had the highest increases from 1990 to 2021 in areas with a High-middle SDI or High SDI. However, the relationship between incidence, prevalence, and DALYs rates and SDI was nonlinear, and regionally, Australasia had the highest incidence, prevalence, and DALYs rates in 2021, with Western Europe and East Asia having the largest increases in incidence, prevalence, and DALYs rates. In terms of countries, Australia has the highest incidence, prevalence and DALYs rates in 2021, while the UK, Spain and China have the highest rate increases. Conclusions Over the past 30 years, there has been a general downward trend in the incidence and prevalence of ADHD and in the rate of DALYs worldwide. However, phased studies have shown less homogeneous trends in recent years, which may be related to changes in the level of socioeconomic development, diagnostic criteria, and therapeutic approaches. Therefore, it is necessary to continue to promote research on the accuracy and universality of ADHD diagnosis and treatment in the future, with a view to further reducing the global health burden of ADHD.

Numerical simulation and experimental verification of venturi tube hydraulic cavitation

This study conducted a numerical simulation of hydraulic cavitation characteristics in a Venturi tube using FLUENT software. The Realizable k-ε turbulence model, Mixture multiphase flow model, and Singhal cavitation model were employed to investigate the effects of inlet pressure, outlet cone angle, and throat parameters (diameter and length) on cavitation performance. A critical inlet pressure threshold (~1.5 MPa) exists, beyond which the cavitation growth rate significantly decreases. Increasing the outlet cone angle weakens cavitation intensity due to reduced pressure recovery efficiency. Larger throat diameters enhance cavitation generation, whereas extended throat lengths suppress it by prolonging pressure recovery. Experimental validation demonstrated consistent trends between temperature variations, conductivity measurements, and simulation results, confirming the validity of the numerical methodology. These findings provide theoretical guidance for optimizing Venturi tube structures in industrial applications such as wastewater treatment and chemical reactors. The systematic analysis of parameter interactions offers practical insights for cavitation control and device performance enhancement.

Strategic selection of MDM2 inhibitors enhances the efficacy of FAK inhibition in mesothelioma based on TP53 genotype

Mesothelioma has characteristic genetic changes including inactivation of neurofibromatosis type 2 ( NF2 ) and deletion of the INK4A/ARF region. Cells deficient of NF2 protein (MERLIN) depend on focal adhesion kinase (FAK) for cell adhesion and FAK inhibitors suppress the cell growth. The INK4A/ARF deletion activates MDM2 functions which ubiquitinate and degrade p53, and consequently the cellular p53 levels decrease. The deletion therefore induces loss of p53 functions although a majority of mesothelioma has wild-type TP53 genotype. An MDM2 inhibitor which blocked the ubiquitination increased p53 levels, restored p53 functions and facilitated cell growth arrest. Moreover, FAK and p53 expressions were reciprocally regulated. We examined growth suppressive effects of a FAK inhibitor, defactinib, and MDM2 inhibitors, nutlin-3a and reactivation of p53 and induction of tumor cell apoptosis (RITA), with representative wild-type and mutated TP53 mesothelioma and investigated molecular changes induced by the agents. We analyzed possible combinatory effects of the inhibitors and molecular changes caused by the combination. Our study showed that defactinib inhibited cell growth and induced FAK dephosphorylation irrespective of the TP53 genotype, and that the inhibited FAK phosphorylation was not associated with MERLIN levels or with p53 up-regulation, but linked with AKT dephosphorylation. Nutlin-3a preferentially suppressed growth of wild-type TP53 cells and augment p53 expression without DNA damage, whereas RITA-mediated p53 up-regulation was linked with the damage. A combination of defactinib and the MDM2 inhibitors showed that nutlin-3a showed synergistic/additive effects in wild-type and antagonistic effects in mutated TP53 cells, whereas RITA retained synergistic activity in mutated TP53 cells. These results suggest that the therapeutic success of combined FAK and MDM2 inhibition in mesothelioma depends on the precise matching of MDM2 inhibitors with the TP53 genotypes, and highlight the need for genotype-based selection of MDM2 inhibitors.

Factors influencing food waste reduction in University Canteens: Toward sustainable campus waste management

Objective Food waste in university canteens poses a significant challenge to advancing sustainability in higher education. Context-specific, targeted strategies remain limited. This study examines the psychosocial factors influencing food waste reduction behaviors among users of university canteens in Thailand. Materials and methods Drawing on ETPB and the waste hierarchy framework, a cross-sectional survey was conducted with 400 undergraduate students in a large Thai university canteen. Data was collected through structured questionnaires and analyzed using descriptive statistics and multiple linear regression to identify key factors influencing food waste reduction behaviors. Results While responses showed consistently high levels across all dependent variables, participants engaged moderately in food waste reduction. Multiple regression analysis of the survey’s results only accounted for 17.1% of the variance in food waste reduction behaviors. Perceived behavioral control (β = 0.338, p < 0.001) and motivation (β = 0.162, p = 0.001) emerged as the strongest predictors. The study also found that structural barriers, including poor food quality (65.0%), limited portion size flexibility (36.3%), and time constraints during peak hours (58.8%), hindered upstream food waste prevention. Conclusion The findings of this study demonstrate that food waste reduction behavior amongst students is primarily driven by perceived control and motivation rather than knowledge alone. Moreover, although canteens support segregation, upstream prevention is hindered by structural barriers. These findings highlight the need for dual strategies aimed at strengthening psychosocial drivers and improving service environments, in alignment with institutional food waste policies and the global SDG 12.3 targets.

Differential analysis of mean blood glucose levels from venous and fingertip in predicting 30-day mortality among ICU patients with severe trauma: A retrospective study utilizing the MIMIC-IV database

Background To investigate the correlation between mean blood glucose of venous (VMBG) and mean blood glucose of fingertip (FMBG) within 30 days and 30-day mortality in trauma patients in intensive care unit (ICU), and to systematically evaluate the prognostic value of early-stage and long-term monitoring intervals. Materials and methods Utilizing data from the MIMIC-IV database, we employed receiver operating characteristic (ROC) curves, restricted cubic splines (RCS), and Cox proportional hazards models to assess glucose-outcome relationships. Sensitivity analyses using complete datasets, propensity score matching (PSM), and subgroup analyses were conducted to verify result robustness. Furthermore, to minimize the bias of immortal time, the Landmark analysis was employed to investigate the correlation between the early-stage VMBG, FMBG and 30-day mortality rate. Secondary outcomes included 90-, 180-, and 360-day all-cause mortality. Results A total of 2,699 patients were enrolled in the study. The AUC values (95% CI) for VMBG and FMBG were 0.705 (0.675-0.735) and 0.640 (0.608-0.672), respectively. VMBG demonstrated superior predictive ability for 30-day mortality compared to FMBG (Z=5.833, P<0.001). Multivariate-adjusted Cox regression revealed independent associations between VMBG, FMBG, and 30-day mortality, with HRs of 1.019 (1.016-1.023) and 1.009 (1.006-1.013), respectively. RCS analysis further indicated a nonlinear “J-shaped” relationship between VMBG, FMBG, and outcomes (P for nonlinearity<0.001), with two thresholds at 88.1 mg/dL and 125.4 mg/dL for VMBG, and 95.4 mg/dL and 134.0 mg/dL for FMBG. The threshold values for FMBG were observed to be higher than those of VMBG. According to the thresholds of VMBG and FMBG, patients were stratified into hypoglycemic, normoglycemic, and hyperglycemic groups, respectively. Whether in the pre-PSM or post-PSM cohort, with the normoglycemic group as the reference, both the hypoglycemic and hyperglycemic groups of VMBG and FMBG were associated with an increased 30-day mortality rate. Subgroup analyses revealed that the impact of elevated VMBG and FMBG on prognosis was more pronounced in patients aged <65 years, non-White individuals, and those without diabetes(P for interaction<0.05). VMBG and FMBG during different time intervals were all non - linearly correlated with the 30 - day mortality rate. The Landmark analysis indicated that during the early-stages, there was also a significant statistical correlation among VMBG, FMBG and prognosis. For secondary outcomes, VMBG and FMBG also showed significant associations with 90-day, 180-day, and 360-day all-cause mortality. Conclusion In ICU trauma patients, both VMBG and FMBG across various time intervals exhibited nonlinear associations with 30-day mortality. Although venous blood glucose monitoring typically demonstrated higher prognostic predictive accuracy compared to fingertip measurements, the early - warning value of fingertip blood glucose should not be overlooked. In clinical monitoring, the characteristics of both measurement methods should be comprehensively recognized.

The effect of personality traits on consumer behaviour among football fans: The mediating role of fan loyalty

The aim of the current study was to examine the impact of personality traits on consumer behaviour among football fans in a Turkish setting by focusing on the mediating role of sports fans’ loyalty. Drawing on the Social Identity Theory, this research examines how the Big Five Personality characteristics, including openness, agreeableness, conscientiousness, extraversion, and emotional stability, influence sports consumption through loyalty mechanisms. Data were gathered from 929 active university students who were all active football fans by using three validated scales for personality, fan loyalty, and consumption behaviour. The indirect effects of personality traits on consumer behaviour through fan loyalty were significant, whereas the direct effects were not statistically significant. Besides, the results indicate that personality traits are associated with sports fan consumption patterns through fan loyalty. This highlights fan loyalty as a potential mechanism linking individual characteristics with collective behaviour patterns. Furthermore, the findings shed light on our understanding of sports fan engagement by combining perspectives from personality theory and social identity theory. Ultimately, it offers practical implications for both sports marketers and club managers seeking ways to foster long-term relationships with their fans, particularly within collectivist cultures.

Geospatial variation and associated factors of unintended pregnancy among women of reproductive age in Ethiopia: Geographically Weighted Regression Analysis

Background Unintended pregnancies are a serious public health concern that has several effects on the health of mothers and children. However, no studies have been conducted on unintended pregnancy using geographically weighted regression in the 2016 Ethiopian demographic and health survey. Therefore, this study assessed the geospatial and associated factors of unintended pregnancy in Ethiopia using a 2016 demographic and health survey. Methods A cross-sectional study used data from the 2016 demographic and health survey and included 7589 women of the reproductive age. Spatial analysis and mapping were conducted using ArcGIS version 10.8. Spatial clusters were identified using the Bernoulli model in SaTScan 10.1. Geographically weighted regression was used to assess associated factors, with significance at p < 0.05. Results Unintended pregnancy showed a clustered spatial pattern. SaTScan found 171 primary significant clusters (risk ratio = 1.86, p < 0.001) in Addis Ababa, Oromia, and SNNPR. A geographically weighted regression revealed that maternal age (35–49 years), maternal primary education, high socio economic status, and distance to a health facility (a big problem) were significant factors contributing to unintended pregnancy. Conclusions Hotspot analysis identified statistically significant hotspot areas of unintended pregnancy in Amhara, Addis Ababa, Oromia, and SNNPR. Statistically significant coldspot areas of unintended pregnancy were observed in Afar, Dire Dawa, and Somali. Maternal age (35–49 years), maternal primary education, high socio economic status, and distance to health facility (big problem) were statistically significant factors of unintended pregnancy. These results show that the capital city and some key rural and ethnic areas had higher rates of unintended pregnancies, especially among relatively older women with high socioeconomic status and basic education, which indicates that sexual and reproductive health education needs to be strengthened and carried out at all levels, including among high socioeconomic groups.

Using machine learning to predict and analyze complex trait diseases: Lessons from a simple abstract model

The ability to predict individual genetic susceptibility to a complex trait disease is a major challenge in modern medicine. One approach to addressing this challenge utilizes an additive combination of contributions from a large number of single nucleotide polymorphisms (SNPs), with weights derived from Genome Wide Association Studies (GWAS). While this approach is somewhat successful in predicting whether an individual is likely to develop a specific disease, it does not explain why a person is likely to become sick. Here, we designed and utilized abstract disease models to investigate the relationship between disease structure, susceptibility, and predictability. The model consists of a set of interacting pathways, each including several nodes representing loci at which genetic variants can alter the function of the corresponding proteins. Due to the introduction of thresholds for pathway functionality, and the interplay between the pathways, this model is inherently non-additive. We use this “toy model” together with simulated variant data to examine the effect of changing various properties, some of which cannot be easily controlled in a “real-world” scenario. As expected, larger sample sizes improved the performance; the omission of some contributing variants from the dataset was associated with a significant decrease in performance, whereas adding irrelevant variants had little effect. Surprisingly, diseases with a more complex underlying structure were better predicted than those with a simpler structure. In addition, risk prediction was more accurate for diseases with lower prevalence. The algorithm was robust to a reasonable percentage of false negative disease assignments. The largest decrease in performance occurred when two diseases with different genetic etiologies were classified as a single pathology, as often occurs in clinical situations, and apparently confuses the neural network algorithm. Finally, we show that a post-analysis of a neural network using t-SNE can provide biological insights into the underlying disease structure.

Assessing the multifunctionality of service crops in mediterranean vineyards using a functional trait approach

Vineyard soils face various agronomic issues such as poor organic carbon levels, erosion, fertility losses, and numerous studies have highlighted the ability of service crops to address these issues. Because biodiversity enhances the multifunctionality of managed ecosystems, service crop mixtures that increase functional diversity represent a promising option to improve vineyard sustainability. Plant functional traits play a crucial role in understanding ecosystem functions, serving as drivers for ecosystem processes and influencing ecosystem services, but the relationship between plant functional traits and ecosystem services is also complex. This study aimed to identify the links between the functional structure of the service crops associated with grapevines, the function they deliver and ecosystem function multifunctionality (EFM), in a Mediterranean vineyard. Thirteen different monocultures of service crop species were sown in the inter-rows of plots of 30 m length that covered one row and the two adjacent inter-rows, at random locations. We then studied 38 plant communities each composed of one of the sown service crop and the spontaneous vegetation that developed with it. At vine budburst, we simultaneously measured five indicators of ecosystem functions (runoff reduction, soil stabilization, soil mineral nitrogen supply for the vine, soil water supply for the vine, and community biomass production), along with 12 above- and below-ground functional markers of the community associated with these functions, in each plant community. Relationships between ecosystem functions and functional markers were analyzed by combining PCA, correlations and multiple linear regressions. We showed that traits upscaled at the community level (CWM) explained part of the targeted functions: significant correlations between traits and functions ranged from 0.33 to 0.6; the R 2 values of the linear regression models between functional indicators and the PCA axes derived from the traits ranged from 0.16 to 0.56. Additionally, we identified tradeoffs between functions, and observed that the biomass production was a major driver of soil-based ecosystem functions. In conclusion, functionally different communities provided different levels of functions and EFM. Designing service crops communities with complementary plant traits may be particularly relevant for increasing multifunctionality and agrosystem sustainability.

Implementing intravenous iron for maternal anemia in Nigeria: A qualitative study of healthcare provider experiences using the normalization process theory

Background Maternal anemia remains a significant public health challenge in Nigeria, affecting approximately 25–46% of pregnant women and contributing to adverse maternal and neonatal outcomes. Intravenous (IV) iron provides a promising alternative to conventional oral iron supplementation for managing moderate to severe maternal anemia; however, its implementation in resource-limited settings faces numerous challenges. This study aimed to understand how the implementation of IV iron became embedded in everyday practice, including factors influencing skilled healthcare providers’ (SHPs) engagement, workflow integration processes, and sustainability. Methods This was a qualitative study embedded within the Implementation Research for Intravenous Iron Use in Pregnant and Postpartum Women in Nigeria (IVON-IS) project across six healthcare facilities in Lagos, Nigeria. Eighteen key informant interviews were conducted with purposively sampled SHPs across the six IVON-IS facilities. The data were analyzed deductively based on the Normalization Process Theory (NPT) constructs (coherence, cognitive participation, collective action, and reflexive monitoring), and inductively to identify themes related to each of these constructs. Results Our study revealed strong coherence among SHPs regarding the purpose and benefits of IV iron compared to traditional treatments. Cognitive participation varied across facilities, with leadership support and patient-centred motivation emerging as critical facilitators. Collective action was faced with challenges, including workflow disruptions, staffing constraints, and space limitations, despite adequate resource provision. Reflexive monitoring processes were robust, with providers continuously evaluating effectiveness through clinical outcomes and patient feedback while expressing concerns about long-term sustainability. Conclusion The implementation of IV iron for maternal anemia in Nigeria demonstrated variability across NPT constructs, with strong coherence and reflexive monitoring but challenges in cognitive participation and collective action. Critical success factors included strong leadership support, adequate resource provision, continuous quality improvement processes, and proactive sustainability planning. The findings from this study provide valuable guidance for scaling up IV iron use as part of comprehensive maternal health services in Nigeria and similar resource-constrained settings.

Water‐Resistant Defective iMOFs via Halogen Coordination for CO ₂ Capture and Size‐Selective Cycloaddition

Abstract A bottom‐up ligand engineering strategy enables the construction of ionic metal‐organic frameworks (iMOFs) with hierarchical porosity and abundant unsaturated Cu+ active sites via halogen anion coordination. These iMOFs exhibit exceptional water stability due to a unique Cu ─ Br stabilization mechanism. The defect‐engineered frameworks demonstrate enhanced CO 2 adsorption, efficient humid CO 2 capture, and superior catalytic performance in CO 2 ‐epoxides coupling reaction, exhibiting size‐selectivity correlated with their pore dimensions.

Development of an automatic segmentation system for anterolateral thigh flap perforators in maxillofacial reconstruction

The anterior thigh (ALT) flap is commonly used in reconstructive surgery, especially in maxillary reconstruction. Accurately identifying the perforator that supplies blood to the flap is critical for surgical success but is time-consuming and prone to variability since it is traditionally performed manually. Advances in artificial intelligence have shown convolutional neural networks (CNN) the potential to automate medical image segmentation. However, ALT flap perforator segmentation poses a unique challenge due to the small size of the perforator and its high anatomical variability. To address this challenge, we developed and validated a CNN-based automatic segmentation model for detecting ALT flap perforators on computed tomography angiography (CTA). Manual annotations of bilateral lateral femoral circumflex artery perforators were obtained from 80 patients using an image tracing program for comparison. The training for the development of an automatic segmentation system was then conducted based on these manual segmentation. The automatic segmentation system employed a two-stage cascaded approach: 2D detection with DeepLabv2 and 3D segmentation with ResNet152. Data augmentation techniques were applied to improve model generalization. Performance metrics included the dice similarity coefficient (DSC) and jaccard similarity coefficient (JSC). The automatic segmentation system achieved DSC and JSC values of 69.67 ± 1.48 and 67.81 ± 1.70, respectively. The distance differences between manual and automatic detection were 38.28 ± 15.52 mm on the left side and 31.96 ± 18.11 mm on the right side. The automatic segmentation system for ALT flap perforators demonstrates promising accuracy, highlighting its potential for clinical application. By reliably identifying perforator locations in CTA, the system can enhance the efficiency and precision of surgical planning, particularly for maxillofacial reconstruction.