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Exploring β-catenin and TCF4 interaction in complex environments by means of novel biosensing platform focal molography

Analyzing biomolecular interactions is essential for drug discovery, aiding the design of new candidates by revealing their action with targets. Various biophysical methods are routinely applied to characterize binding properties between molecules. Recently, focal molography, a novel sensor-based technology, has been developed to study interactions in complex environments. It measures changes in the intensity of diffracted light at a focal point due to analyte binding to a patterned array of binding sites, known as a mologram. Focal molography filters a specific binding signal from nonspecific background binding, allowing holistic analysis in biologically relevant environments. We present binding data and method’s validation in both, buffer and complex media, using focal molography and compare results to the gold standard method, surface plasmon resonance. Our model system focuses on the interaction between β-Catenin and a T-cell factor 4. β-Catenin, crucial in gene regulation for cell proliferation and differentiation, is a key target in cancer therapeutics. Confirming focal molography’s ability to accurately measure binding affinities creates a reliable methodology that fills gaps in current drug discovery techniques.

Preferential apical infection and spread of human metapneumovirus highlights the importance of inhaled delivery of neutralizing monoclonal antibody to treat established infections

Human metapneumovirus (hMPV) is a frequent cause of acute respiratory infections in infants, the elderly, and the immunocompromised. No vaccines or treatments are currently available beyond supportive care. Building on our previous work with parainfluenza viruses and respiratory syncytial virus, we investigate the pattern of hMPV infection and spread in polarized and well-differentiated cultures of human airway epithelium (WD-HAE). We found productive infection of WD-HAE requires apical inoculation of hMPV, with infectious spread dependent on progeny viruses shedding into mucus secretions overlaying the apical surface of WD-HAE. A potent neutralizing monoclonal antibodies (mAb) against hMPV fusion protein—mAb364 (also termed MPV364)—prevented initial infection by hMPV and halted spread of established hMPV infection when dosed directly to the apical surface of WD-HAE. Conversely, mAb364 delivered to the basal compartment was unable to curb established infections, even at 100-fold greater concentrations. Intranasal delivery of mAb364 to hamsters with established hMPV infections reduced viral titers by ~four logs within 2 d and alleviated key pathological outcomes of hMPV infection. These results are consistent with hMPV infection and continued spread occurring via the apical surface of the respiratory epithelium, and underscore delivery of neutralizing mAbs to the respiratory tract as an effective intervention against established hMPV infections.

Deep transfer learning based feature fusion model with Bonobo optimization algorithm for enhanced brain tumor segmentation and classification through biomedical imaging

Insecticide resistance and species diversity in Anopheles gambiae s.l. in Côte d’Ivoire

Background Insecticide resistance in malaria vectors poses a significant threat to effective control of malaria vectors across sub-Saharan Africa. In Côte d’Ivoire, Anopheles gambiae s.l. exhibits considerable variability in species distribution and insecticide resistance levels across distinct ecological areas. This study reports on insecticide resistance profiles within An. gambiae complex as well as species composition dynamics in various ecological settings in Côte d’Ivoire. Methods From July to October 2020, larval and adult mosquitoes were collected across three ecological settings (savannah, pre-forest and forest) in Côte d’Ivoire. Larvae were reared to adult stage for susceptibility bioassays. Diagnostic concentrations (DCs) applied against An. gambiae s.l. were deltamethrin 0.05%, permethrin 0.75% and pirimiphos methyl 0.25% using WHO susceptibility test kits. When increased survival to diagnostic concentrations (DCs) was observed, intensity bioassays were conducted using 5x and 10x DCs. In addition, synergist assays were performed at the DC level with pre-exposure to 4% piperonyl butoxide (PBO). Together with adults directly collected from the field, female samples from the bioassays outcome were speciated and resistance target site mechanisms (Kdr L1014F and Ace-1R G119S) were determined using PCR. Species distribution and insecticide resistance were analyzed across ecological areas. Results Significant variations in insecticide resistance phenotypes and mechanisms in An. gambiae s.l. were found across the three ecological areas in Côte d’Ivoire. Mortality rates, following pyrethroid exposure, were significantly higher in An. gambiae s.l. collected in the savannah zone compared to those collected from the forest zone (p < 0.05). An. gambiae was more predominant in the savannah area (98.8%, 95% confidence of interval (CI) [93.5–100.0]), whereas An. coluzzii dominated in the pre-forest (92.9%, 95% CI [88.9–95.8]) and forest zones (61.3%, 95% CI [53.4–68.9]). Such predominance of An. coluzzii was associated with high intensity of pyrethroid resistance in these areas. Overall, the allelic frequencies of the resistance mutations in An. gambiae were higher than those in An. coluzzii regardless of the area. Kdr L1014F frequency in the forest zone was 78.1% (95% CI [68.0–88.2]) in An. gambiae larvae, 51.8% (95% CI [33.3–70.4]) in adults, and 63.1% (95% CI [52.4–73.8]) in An. coluzzii larvae. Conclusion Variations in species distribution and insecticide resistance in ecological areas in Côte d’Ivoire should be carefully considered when developing and implementing vector control strategies.

Biomarkers of immune dysregulation and posttreatment inflammation in spinal muscular atrophy

Spinal Muscular Atrophy (SMA) is a neurodegenerative disorder primarily affecting motor neurons, but immune dysfunction may contribute to disease progression and treatment response. While AAV9-delivered SMN1 gene therapy (e.g., Zolgensma) improves survival, long-term motor outcomes remain variable. This study integrates bulk and single-cell RNA sequencing (scRNA-seq) to define immune dysregulation in SMA. We analyzed peripheral blood from infants with SMA (n = 7 for bulk RNA-seq; n = 4 for scRNA-seq, <25 mo of age) along with age-matched healthy controls (n = 4 for bulk RNA-seq; n = 6 for scRNA-seq). We profiled differentially expressed genes, immune pathways, cell–cell interactions, and gene regulatory networks. SMA samples showed distinct transcriptomic signatures and elevated immune activation compared to controls. NECTIN1 was identified as a transcriptomic biomarker of disease progression, while HSPA7 was validated from prior reports. A 6- to 7-mo inflection point marked a transition from metabolic regulation to immune activation in SMA infants. NF-κB–related inflammatory gene expression was significantly elevated post–gene therapy relative to both pretreatment and healthy controls, with IL1B and RNF19B emerging as key transcriptomic mediators. scRNA-seq revealed early dysfunction and G1-phase arrest in CD4+ T-cells, along with a switch to RELB -mediated noncanonical NF-κB signaling. In symptomatic infants, CD8+ T-cells showed higher proliferation and exhaustion, with co-upregulation of TBX21 and EOMES , genes consistent with chronic stimulation and a trajectory toward terminal differentiation. Immune dysregulation is a central feature of SMA and may influence treatment response. These findings support future development of adjunct immunomodulatory strategies to enhance gene therapy efficacy and suggest that immune signatures may correlate with motor function outcomes.

Assessment of heavy metal levels in surface water, sediment and agricultural soils around the abandoned Laga Dambi gold mine, Ethiopia

Digital nursing and midwifery leadership: Protocol for a multi-method exploration of policy implementation and impact on practice in the WHO European Region

Background Digital health is redefining nursing and midwifery practice, fuelled by national and international priorities for health improvement and workforce planning. Developing digitally enabled healthcare systems can help enable universal health coverage and improve safety outcomes while offering solutions to workforce shortages. However, research suggests that nursing/midwifery leaders are often absent from the strategic planning, design, and implementation of digitally enabled healthcare service models and the associated technological systems that directly impact practice. Objectives This paper presents the protocol for a sequential, multi-method exploration of digital health policy implementation and its impact on practice. This investigation from the perspective of national nursing/midwifery leaders, will increase understanding of the impact these professions have on national decision-making, which will be used to inform digital healthcare policy implementation and development across Europe and beyond. Methods A purposive sample of national nursing/midwifery leaders across the WHO European region will be recruited. In Phase 1, individuals will be invited via email to participate in an anonymous online survey, with findings used to inform the topic guide for online focus groups in Phase 2. Descriptive statistical analysis of the survey dataset will be used to understand the range of countries, roles, contexts, participant experiences, and perceptions on which the findings are based. Where possible, analysis will be undertaken, e.g., by country, and participant role to identify any patterns, gaps, and key areas for further exploration during Phase 2. Survey respondents will be offered the opportunity to participate in an online focus group. Free text questions from the survey and data from focus groups will be transcribed verbatim and analysed using a reflexive thematic approach. Discussion The study outlined within this paper will generate empirical data on to what extent and how national nursing/midwifery leaders influence the progress of digital healthcare, based on their experiences implementing key European policy. In gaining a better understanding of this policy implementation, and the role played by nursing and midwifery leaders, the factors that facilitate or hinder this process can be identified and better managed, to maximise the benefits of digital healthcare for population outcomes moving forward. Ethical approval Ethical approval for this study was granted on 10.12.25 by Anglia Ruskin University [ID ETH2425−0725]

Severe water crisis in southern Spain under expanding irrigated agriculture: A multidimensional drought analysis

The Axarquía region in southern Spain, a hotspot of avocado and mango production in Europe, underwent an extreme water crisis in 2019–2024. Reservoir levels dropped below the 8% outlet threshold and groundwater in the main aquifer dropped to sea level in several locations, risking seawater intrusion. Socioeconomic impacts ranged from substantial crop losses to a potential long-term decline in regional economic viability. We examine the main drivers of this crisis using a coupled human and natural systems approach, combining an examination of water and land governance with analysis of time series (dam inflows and outflows, meteorological variables, reservoir, and groundwater levels) and spatial data (irrigated land use, groundwater bodies, water entitlement location, and volume). Our results show two severe meteorological droughts in close succession immediately preceding rapid declines in reservoir and groundwater reserves. Emergency measures delayed dam depletion but likely exacerbated groundwater extraction. Reservoir data disaggregating inflows, outflows, and uses (irrigation and urban) show an increasing trend in dam water use for irrigation in 2000–2022 associated with increasing irrigated area. Water management planning since 1998 reveals important inconsistencies within and between plans pointing to large uncertainties in freshwater availability and extraction and aquifer overdraft even during nondrought periods. The Axarquía case exhibits many symptoms of water crises faced by agriculturally significant regions globally. It highlights the necessity for integrated basin-scale land–water management, caps on irrigated area, flexible extraction quotas, real-time metering at all extraction points, and effective enforcement mechanisms, substantiating management lessons derived from major drought-affected regions worldwide.

Stochastic fractional order model for the computational analysis of computer virus

Correction: Pot-pollen DNA barcoding as a tool to determine the diversity of plant species visited by Ecuadorian stingless bees

Targeting endothelial ERG to mitigate vascular regression in retinopathies

Retinopathy of prematurity (ROP) and diabetic retinopathy (DR) are ocular disorders in which an initial loss of retinal capillaries leads to damaging tissue ischemia followed by a compensatory neovascularization response that generates pathological capillaries in the eye. Using a mouse model of ROP and samples from DR patients, we found that the highly homologous and homeostatic erythroblast transformation-specific (ETS) family transcription factors ETS-related gene (ERG) and Friend leukemia integration 1 (FLI1) are downregulated in endothelial cells (ECs) of retinal capillaries prior to their regression in early stages of these diseases. We developed a mouse model of inducible EC-specific overexpression of Erg and found it mitigates capillary regression, retinal neuron death, neovascularization, and visual defects in the ROP model. Erg overexpression also reduces capillary regression in early stages of a murine DR model. We next found that simultaneous deletion of endothelial Erg and Fli1 is sufficient to promote regression of the pathological retinal capillaries that arise in late stages of the ROP model. Altogether, our data demonstrate that deletion of homeostatic endothelial ETS factors promotes capillary regression, while maintenance of even one of these factors prevents regression. These findings offer insights into approaches for preventing and treating retinopathies at different stages of these diseases.

Development and evaluation of a battery powered harvester for sustainable leafy vegetable cultivation

DiabetesXpertNet: An innovative attention-based CNN for accurate type 2 diabetes prediction

Type 2 diabetes mellitus remains a critical global health challenge, with rising incidence rates placing immense pressure on healthcare systems worldwide. This chronic metabolic disorder affects diverse populations, including the elderly and children, leading to severe complications. Early and accurate prediction is essential to mitigate these consequences, yet traditional models often struggle with challenges such as imbalanced datasets, high-dimensional data, missing values, and outliers, resulting in limited predictive performance and interpretability. This study introduces DiabetesXpertNet, an innovative deep learning framework designed to enhance the prediction of Type 2 diabetes mellitus. Unlike existing convolutional neural network models optimized for image data, which focus on generalized attention mechanisms, DiabetesXpertNet is specifically tailored for tabular medical data. It incorporates a convolutional neural network architecture with dynamic channel attention modules to prioritize clinically significant features, such as glucose and insulin levels, and a context-aware feature enhancer to capture complex sequential relationships within structured datasets. The model employs advanced preprocessing techniques, including mean imputation for missing values, median replacement for outliers, and feature selection through mutual information and LASSO regression, to improve dataset quality and computational efficiency. Additionally, a logistic regression-based class weighting strategy addresses class imbalance, enhancing model fairness. Evaluated on the PID dataset and Frankfurt Hospital, Germany Diabetes datasets, DiabetesXpertNet achieves an accuracy of 89.98%, AUC of 91.95%, precision of 89.08%, recall of 88.11%, and F1-score of 88.01%, outperforming existing machine learning and deep learning models. Compared to traditional machine learning approaches, it demonstrates significant improvements in precision (+5.1%), recall (+4.8%), F1-score (+5.1%), accuracy (+6.0%), and AUC (+4.5%). Against other convolutional neural network models, it shows meaningful gains in precision (+2.2%), recall (+1.1%), F1-score (+1.2%), accuracy (+1.9%), and AUC (+0.6%). These results underscore the robustness and interpretability of DiabetesXpertNet, making it a promising tool for early Type 2 diabetes diagnosis in clinical settings.

Antagonistic SnRK2 and PID kinases' action on auxin transport–mediated root gravitropism

Plants have evolved sophisticated mechanisms to adapt to environmental changes, with root gravitropism playing a pivotal role in nutrient and water acquisition. Our study reveals that SnRK2 kinases (SnRK2.2 and SnRK2.3) are critical regulators of root gravitropism through their direct phosphorylation of the auxin transporter PIN2 at S259. We demonstrate that SnRK2s-mediated phosphorylation modulates both the polar localization and transport activity of PIN2. Importantly, SnRK2s function antagonistically to the AGCVIII kinase PID, which phosphorylates PIN2 at a distinct site (S258), establishing a regulatory balance essential for adaptive root growth. Structural modeling and phosphorylation assays further suggest that SnRK2s-mediated phosphorylation at S259 sterically hinders access of PID to S258, providing a mechanistic basis for their antagonistic relationship. These findings uncover a novel regulatory mechanism, by which plants fine-tune root developmental programs to adapt to environmental stimuli, highlighting the evolutionary significance of multilayered kinase-mediated regulation in plant adaptation.

Enhancing CYP2D6 genotyping with nanopore sequencing to address allele diversity P. vivax malaria elimination

Abstract The precise profiling of CYP2D6 alleles is critical for identifying patients who are likely to benefit from primaquine therapy, a standard treatment for preventing P. vivax relapse and, as a result, obstacle for malaria elimination. Conventional assays often fall short, as they do not capture the wide range of allele diversity found at the CYP2D6 locus, particularly in populations from malaria-endemic regions. In response, we developed a methodology integrating cost-effective DNA library preparation with nanopore sequencing, reducing reliance on extensive third-party enzymes and reagents and shortening processing times to enhance accessibility. Using well-characterized DNA standards, we evaluated various bioinformatics tools for their ability to accurately call CYP2D6 star alleles. Nanopore sequencing proved particularly valuable for identifying complex structural variants, which led us to propose a novel approach to manage hybrid structural variations using long-read amplicon data. We conducted an in-depth genotypic analysis of DNA samples from 90 individuals in Thailand’s Greater Mekong Subregion, achieving a high level of resolution in CYP2D6 genotyping. This analysis not only identified structural variants but also a previously unidentified allele. The findings suggest potential paths forward for testing that is sensitive to local genetic variability and supports informed policy decision-making in real time, thereby potentially enhancing the effectiveness of P. vivax elimination.

Influence of gestational weight gain and maternal depression on offspring BMI trajectory from birth to 3 years: A longitudinal mother-infant study

Objective Gestational weight gain (GWG) is associated with offspring growth trajectories and early childhood obesity, but existing studies rarely account for maternal psychological status, which may confound or modify this association. This study aimed to evaluate the impact of GWG patterns on offspring body mass index-for-age Z score (BMI-Z) trajectories from birth to 3 years, adjusting for maternal depression and examining effect modification by depressive symptoms. Methods This mother-infant paired longitudinal cohort study was conducted between September 2019 and September 2024 at the Liuzhou Maternity and Child Healthcare Hospital. Data on maternal sociodemographic characteristics, health status, lifestyle factors, clinical and anthropometric measurements were collected. Linear mixed-effects models were used to assess the association between GWG patterns and offspring BMI trajectories, adjusting for maternal pre-pregnancy BMI, sociodemographic factors, and maternal depression status. Stratified analyses by depression status were conducted to explore effect modification. Results A total of 1,133 mother-infant pairs were included in this study. Offspring of mothers with excessive GWG showed higher BMI-Z scores after 24 months. Children born to underweight mothers had lower BMI-Z scores throughout follow-up. Mixed-effects modeling indicated that both pre-pregnancy BMI and GWG pattern were independently associated with BMI-Z trajectories (P < 0.05). After adjusting for depression scores, the association between overweight/obesity (β = 0.48, 95% CI: 0.23–0.76, P < 0.001) as well as excessive GWG (β = 0.17, 95% CI: 0.04–0.29, P < 0.05) and child BMI trajectory persisted. Maternal underweight was still negatively associated with child BMI z -scores (β = −0.35, 95% CI: −0.52 – −0.15, P < 0.001). Stratified analyses showed that the effect was more pronounced in mothers with depressive symptoms (P < 0.05). Conclusion Excessive GWG significantly influences early childhood growth patterns. Maternal depressive symptoms may partially confound or modify this association. These findings highlight the need to integrate psychological assessments into prenatal care to optimize offspring growth trajectories and reduce the risk of early-life overweight.

Why depolarization is hard: Evaluating attempts to decrease partisan animosity in America

Affective polarization is a corrosive force in American politics. While numerous studies have developed interventions to reduce it, their capacity for creating lasting, large-scale change is unclear. This study comprehensively evaluates existing interventions through a meta-analysis of 77 treatments from 25 published studies and two large-scale experiments. Our meta-analysis reveals that the average effect of treatments on animosity is modest (a 5.4-point shift on a 101-point scale), and decays within two weeks. We experimentally test whether stacking multiple treatments in one sitting or repeating them over time as “booster shots” enhances their impact. We find no evidence that multiple or repeated exposures produce substantially larger or more durable reductions in partisan animosity. This reveals the uneven utility of these interventions. They serve as valuable tools for testing the psychological mechanisms of polarization, but our findings indicate they are not, on their own, a scalable solution for reducing societal-level conflict. We conclude that achieving lasting depolarization will likely require a shift in focus, moving beyond individual-level treatments to address the elite behaviors and structural incentives that fuel partisan conflict.

Magnetic field assisted uniaxial deformation and forming behaviour of an advanced high strength steel sheet

The mental health impact of physical inactivity: A study on UAE adolescents

Mental and physical health are essential for well-being, particularly during adolescence. The study aimed to assess the prevalence, factors, and relationship between physical inactivity and depression, and to determine the predictors of depression among adolescents in the UAE. A cross-sectional study was conducted among students in grades 9–12 from selected schools in the UAE. The study included adolescents of all genders and all nationalities. Two standardized questionnaires were employed: the “Physical Activity Questionnaire for Adolescents (PAQ-A)” to evaluate physical activity levels and the “Centre for Epidemiologic Studies Depression Scale (CES-D)” to assess symptoms of depression among the participants. Correlation test, independent t-test, chi-square test, bivariate and multivariate logistic regression analyses were used, with significance set at p < 0.05. The study included 365 participants, with the majority being over 14 years old (68.7%), female (60%), and in grade 10 (32.2%). The prevalence of depression and physical inactivity was 51.2% and 68.8%, respectively, and a significant negative correlation was found between depression and physical activity scores. Significant positive correlations are found between depression and grade level, and chronic health problems, and a negative correlation with crowding index. Significant negative correlations are found between physical activity, age, grade level, and chronic health problems. Predictors of depression are physical inactivity, female gender, overweight and obesity, and having a chronic disease. The study reveals a high prevalence of depression and physical inactivity among adolescents in the UAE. Consequently, physical activity may serve as a key protector against depression, and it potentially influences mental health through many physiological, neurological, and behavioural pathways. This underlines the critical need for interventions aimed at promoting physical activity.

A TGF-βR/IL-2R immunomodulatory fusion protein transforms immunosuppression into T cell activation to enhance adoptive T cell therapy

Adoptive T cell therapies have shown limited efficacy against solid tumors due in part to immunosuppressive cues such as from TGF-β and insufficient survival/proliferative signals within the tumor microenvironment (TME). We engineered chimeric immunomodulatory fusion proteins (IFPs) that convert immunosuppressive TGF-β signals into proliferative/survival Interleukin 2 (IL-2) signals in T cells. Chimeric TGF-βR/IL-2R IFPs were constructed by fusing extracellular domains of the TGF-β receptor chains with intracellular domains of IL-2Rβ and IL-2Rγ to enable TGF-β binding to trigger STAT5 phosphorylation and activate the downstream IL-2 pathway. In human primary CD8 + T cells, select IFP designs robustly induced p-STAT5 upon exposure to TGF-β1, and simultaneously reduced canonical SMAD2/3 signaling. IFP-expressing T cells proliferated and displayed enhanced viability in response to TGF-β1, effectively leveraging TGF-β-rich conditions to outcompete nontransduced cells. Transcriptomic analyses revealed that IFP signaling promoted T cell activation and allowed maintenance of stemness during culture with TGF-β. Functionally, coexpressing IFPs with a mesothelin-specific T cell receptor improved tumor killing and promoted T cell expansion in the presence of TGF-β1, highlighting both neutralization of TGF-β–mediated suppression and enhanced proliferation. TGF-βR/IL-2R IFPs appear promising for reprogramming the signals T cells receive in the TME and improving efficacy of adoptive T cell therapy in solid tumors.