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RETRACTED ARTICLE: An enzymatic BioBattery based on multicopper oxidases with reduced substrate diffusion constraints for sustainable energy harvesting

Screening for hypertension in a public dental clinic: A single-centre cross-sectional study in Australia

Background Hypertension affects over 1.3 million people globally and markers of poor oral health have been associated with hypertension. Objective This study aimed to determine hypertension awareness, treatment and control, among adults attending a public dental clinic, and explore age-related differences between younger (< 65 years) and older adults (≥ 65 years) including associations between markers of oral health and hypertension. Method This cross-sectional study recruited adults ≥18 years from an Australian public dental clinic between November 2022 and May 2023. Two blood pressure readings were obtained using an automated device and the average used for analyses. Demographic, oral health and medical history details were obtained via survey. Hypertension was defined as a systolic blood pressure (SBP) ≥140 mmHg and/or diastolic blood pressure (DBP) ≥90 mmHg, or being aware (self-reported diagnosis), and treated with anti-hypertensive medication. Results Participants (n = 302) were middle aged (mean 59.9 ± 17.5 years, 51.5% ≥ 65 years, 60.7% female), one third had significant tooth loss (<20 teeth), half required treatment for periodontitis and 52.0% had hypertension (95% CI: 46.2%, 57.7%). Of those with hypertension (n = 157), 82.7% were aware, 76.9% were treated for hypertension, and 56.6% of those treated had controlled blood pressure. Although older adults were more likely than younger adults to have hypertension (74.2% vs 28.1%), younger adults were less likely to be aware and treated (70.7% vs 86.8%, 56.1% vs 86.8%, respectively). Markers of poor oral health were not independently associated with hypertension. Conclusions In this population with a high burden of oral disease, hypertension was common highlighting the importance of opportunistic blood pressure assessment. Dental settings may offer an additional point of contact for identifying individuals with undiagnosed or uncontrolled hypertension, particularly among younger adults with lower awareness.

HIV-1 protease cleavage sites detection with a quantum convolutional neural network algorithm

Gendered dimensions of sustainable land management: Evidences from farm size and training effects on willingness to pay in Ghana’s Volta Region

Land degradation is a critical threat to agricultural productivity in Ghana, reducing soil fertility and deepening rural poverty. Efforts to promote Sustainable Land Management (SLM) have increased, but adoption remains uneven, with persistent gender disparities in access to land, training, and decision-making. This study draws on survey data from 1,036 farming households across five municipalities in Ghana’s Volta Region to examine how SLM training and farm size affect farmers’ willingness to pay (WTP) for SLM practices, with a focus on gender differences. A Tobit regression model is used to estimate both main and interaction effects. The results support the study hypotheses. SLM training (β = 0.164, p < 0.01 ) significantly increases WTP, with stronger effects among male farmers, confirming H1. Farm size (β = 0.058, p < 0.01 ) is positively associated with WTP, as larger landholdings increase farmers’ investment capacity, supporting H2. Gender differences are evident: male farmers show higher baseline WTP, while female farmers show large increases in WTP as access to land and SLM training improves, partially supporting H3 and suggesting that disparities are driven mainly by structural constraints. The three-way interaction between SLM training, gender, and farm size is positive and significant (β = 0.375, p < 0.05 ), confirming H4 and indicating that the effect of SLM training on WTP depends jointly on gender and resource endowment. Overall, the findings suggest that gender is central to understanding investment decisions in SLM and highlight the need for gender-responsive policies that address inequalities in access to land, training, and productive resources.

Gene therapies to fix failing hearts gain steam after years in the doldrums

A feature-enhanced transformer for point-like micro-defect detection on semiconductor wafer surfaces

Formulation of 5-fluorouracil loaded chitosan-based nanoparticles and evaluation of its cytotoxic effects against MCF-7 human breast cancer cells

Breast cancer remains a major global health issue with a high mortality rate. In breast cancer treatment, chemotherapeutic drugs have a toxic effect on both cancerous and healthy cells which can lead to severe adverse effects and chemoresistance. Chitosan-based nanoparticles (NPs) have been reported to improve cellular drug delivery, thereby remediating the chemoresistance of anticancer drugs. The purpose of this research was to formulate 5-fluorouracil (5-FU) loaded chitosan nanoparticles. 5-FU nanoparticles were synthesized using ionic gelation technique which is based on the ionic interaction of positively charged chitosan and negatively charged tripolyphosphate that serves as a cross linker. The formulated nanoparticles were evaluated using UV spectrophotometer, Fourier-transform infrared spectroscopy, X-ray diffraction, Scanning Electron Microscopy. The cytotoxicity study was done using MTT assays. FTIR analysis revealed complete drug encapsulation of the nanoparticles via intermolecular interactions. The result of the XRD analysis showed that the drug was crystalline in the nanoparticle distribution. The SEM analysis confirmed the spherical morphology and structure. The synthesized nanoparticles had a mean particle size of 218.62 nm, zeta potential values of ≤+32.18 mV, Pdi values ranging from 0.14–0.29 and encapsulation efficiency results of ≤37.54%. The drug release mechanism was via Fickian diffusion. MTT analysis showed a time-dependent cytotoxic effect of 5-FU nanoparticles on breast cancer (MCF-7) cell lines after 72 h. This study confirmed that formulation of 5-FU into nanoparticles is a promising approach for sustained release and site-specific anticancer drug delivery which can potentially minimize the systemic side effects and improve treatment outcomes in cancer patients.

Bridget Ogilvie obituary: parasitologist who championed biomedical labs and scientific evidence

Agricultural pesticide use and Alzheimer’s disease dementia prevalence across US counties in a mixed supervised–unsupervised analysis

Fluid sparing effects of chemokine (C-C motif) receptor 1 and 2 antagonists during resuscitation from hemorrhagic shock in rat models

We described previously that the chemokine (C-C motif) receptor 1 (CCR1) and CCR2 antagonists BX471 and INCB3284 reduce fluid requirements during resuscitation after hemorrhage. Their effects, however, have not been directly compared with each other and consequences of simultaneous blockade of CCR1/2 are unknown. Here we utilized rat (Sprague-Dawley) models of hemorrhagic shock to compare fluid sparing properties when administered individually or in combination and to assess effects on shock tolerance. Series 1: rats were hemorrhaged to a mean arterial blood pressure (MAP) of 30 mmHg for 30 min, followed by blood pressure-directed fluid resuscitation for 6h. At t = 30 min, vehicle (n = 12), BX471 (0.5 µmol/kg, n = 9), INCB3284 (5 µmol/kg, n = 7), or BX471 (0.5 µmol/kg) plus INCB3284 (5 µmol/kg, n = 6) were injected. Series 2: rats were hemorrhaged to a MAP of 30 mmHg for 45 min, injected with vehicle (n = 8), BX471 (0.5 µmol/kg, n = 7) or INCB3284 (5 µmol/kg, n = 5), and observed until t = 225 min. Series 1: cumulative fluid requirements sharply increased between t = 220–300 min and averaged 108±20 mL/kg at t = 390 min with vehicle-treatment. After treatment with BX471, INCB3284 or both, fluid requirements remained constant and averaged 31±8 mL/kg, 51±12 mL/kg and 36.5±8 mL/kg, respectively, at t = 390 min (p < 0.05 vs. vehicle). Mortality was 75% with vehicle treatment and 33%, 57% and 66% with BX471, INCB3284 and BX471 plus INCB3284 treatment, respectively (p > 0.05 vs. vehicle). Measurements of a panel of systemic inflammation markers suggested that BX471 and INCB3284 attenuate release of TNFα and IL6, and enhance release of CCL5 during resuscitation. Series 2: BX471 and INCB3284 treatment did not affect survival times. Our findings confirm fluid sparing effects of BX471 and INCB3284 over 6h of resuscitation, suggest that both drugs exert comparable efficacy to reduce fluid requirements and modulate the systemic inflammatory response to hemorrhage and fluid resuscitation.

Overexpression of Synaptopodin increases the number of spine apparatuses and active synapses of dentate granule cells

Abstract Synaptopodin (SP) is a plasticity-related actin-modulating protein found in a subpopulation of mature cortical spines. Its presence within spines is essential for the formation of the spine apparatus (SA) organelle, a local calcium store. SP has been functionally linked to enhanced synaptic strength and long-term spine stability, i.e., indicators of potentiated synapses involved in memory trace formation. As SP is transcriptionally upregulated under contextual learning conditions in dentate granule cells (GCs), we generated a gain-of-function mouse model (Cyan Fluorescent Protein-SP transgenic mouse; CSPtg) with a ~threefold overexpression of SP to study the cellular effects of an increased availability of SP in GCs. Like the wild-type (WT) protein, transgenic SP was sorted to spines and rescued the SA organelle in GCs of SP-deficient mice. In CSPtg mice, SP was found in twice as many spines compared to WT. At the ultrastructural level, a ~threefold increase in the number of SAs was observed. Other structural properties, including spine density, average spine head size, and average SP puncta size, were not significantly altered. Patch-clamp recordings of GCs in CSPtg mice revealed an ~ 3.5-fold increase in miniature excitatory postsynaptic current frequency, indicating that the increased expression of SP/SA in spines resulted in a larger number of active synapses. Thus, higher levels of SP in GCs may increase the number of synapses available for strengthening and plasticity. This could enhance the ability of GCs to be recruited into new ensembles under contextual learning conditions.

Correction: Caring is not always sharing: A scoping review exploring how COVID-19 containment measures have impacted unpaid care work and mental health among women and men in Europe

Ceramic art design generation and aesthetic quality evaluation based on multimodal large language models and diffusion probabilistic framework

Abstract Ceramic art design faces persistent challenges in balancing cultural authenticity with production efficiency, as conventional workflows rely heavily on subjective artisan expertise. This paper presents a unified framework that integrates multimodal large language models with diffusion probabilistic models for surface-decoration generation and computational visual-aesthetic proxy evaluation of vessel-based ceramic objects, with a dataset predominantly drawn from Chinese ceramic traditions. The framework comprises three coupled modules: a multimodal semantic parsing module that extracts structured design attributes from textual briefs or reference images via instruction-tuned vision-language modeling augmented by a ceramic domain knowledge graph; a style-conditioned diffusion generation network employing cross-attention semantic injection and adaptive layer normalization to synthesize ceramic designs under fine-grained stylistic control; and a multi-dimensional aesthetic quality evaluation model that scores generated outputs across compositional rationality, color harmony, texture fineness, and style consistency using attention-weighted adaptive fusion calibrated against expert judgment. Experiments on a purpose-built dataset of over 21,000 annotated ceramic images spanning five major traditions centered on Chinese porcelain and stoneware demonstrate that the proposed method achieves a FID of 28.35 and an IS of 10.46, substantially outperforming existing baselines. The aesthetic evaluation model attains an SRCC of 0.891 and a PLCC of 0.903 against expert ground truth. We explicitly acknowledge that the framework operates on two-dimensional imagery and does not model three-dimensional form, clay-body or glaze material composition, or firing dynamics; the reported aesthetic scores therefore reflect computational proxies of visual properties rather than holistic aesthetic judgment. Ablation studies confirm that the semantic parsing module constitutes the most critical component, and that multi-dimensional decomposition with adaptive weighting significantly surpasses monolithic scoring approaches.

Understanding mechanistic responses underlying diurnal photoprotection and photosynthetic plasticity among cacao genotypes under natural amazonian field conditions

Cacao ( Theobroma cacao ) is a key tree species for chocolate production and a vital income source for millions, especially in Africa and South America. In the Amazon, physiological studies on cocoa have focused on abiotic factors, but the comparison of clones in these environments is still in its infancy.This study examined the physiological responses of cacao clones to the typical diurnal conditions of the Colombian Amazon. We measured environmental, plant health, and chlorophyll fluorescence variables in 18 cacao clones using MultispeQ and Imaging-PAM throughout the day; we estimated F v /F m , ΦII, ETR, and NPQ t , calculated SLA, and quantified photosynthetic pigments. Significant phenotypic differences were identified in photosynthetic efficiency and morphology. High specific leaf area (SLA), linked to efficient energy capture and reduced transpiration, was observed in LUKER-40 and FGH-4. Chlorophyll a fluorescence approach, revealed differences in photochemical efficiency (F v /F m ) and excess energy dissipation. Genotypes like FGH-4, FSV-41, and IMC-67 showed high F v /F m and electron transport rates (ETR) (p < 0.05) under heat stress, indicating strong PSII functionality. Conversely, ICS-95 relied on non-photochemical quenching (NPQ t ) for heat dissipation. LUKER-50, with high carotenoid content, demonstrated resilience to oxidative stress. Variations in chlorophyll content affected light capture efficiency, with ICS-60 excelling in photosynthesis under high temperatures and excess light at noon. Leaf temperature regulation emerged as critical, with genotypes like LUKER-40 maintaining cooler leaves to avoid potential thermal damage. These traits highlight the acclimation of genotypes to high light and heat in the Colombian Amazon, with LUKER-50, ICS-95, FLE-3, and LUKER-40 identified as promising candidates for agroforestry in this region.

Black soldier fly larvae and cricket fortified crackers are a safe, nutritious, and acceptable snack for school children in Madagascar

Experimental investigation and reliability-based optimization of the nut factor in bolted joints considering friction coefficient, surface roughness and material hardness

The nut factor is a critical parameter that defines the relationship between tightening torque and axial preload in bolted joints. Accurate estimation of this coefficient is essential to ensure joint integrity and reliability. This study presents a controlled experimental investigation to evaluate the effects of three key assembly parameters including friction coefficient (μ), surface roughness (Ra), and material hardness (HB) on the nut factor (K). A second-order regression model was developed based on experimental data to describe the nonlinear relationship between these variables. Furthermore, a Reliability-Based Design Optimization (RBDO) approach was employed, integrating Monte Carlo simulation and Genetic Algorithm, to determine the optimal combination of μ, Ra, and HB that minimizes the expected nut factor while ensuring that the probability of remaining within the safe range [0.2, 0.3] exceeds 99.9%. The results demonstrate that the RBDO approach yields a more robust and reliable tightening configuration compared to conventional optimization methods. Sensitivity analysis was also conducted to quantify the relative influence of each input variable on the reliability of the nut factor. The proposed methodology demonstrates the potential applicability of probabilistic optimization approaches for improving torque control and reliability performance of bolted assemblies under uncertainty.

Scene-aware contrastive learning with multi-scale domain-invariant feature alignment for robust visual recognition under complex scenes

Automatic sentence simplification system for Arabic Script Punjabi

In the domain of language simplification, creating aligned monolingual parallel datasets tailored to specific linguistic dialects is a significant endeavor. This pursuit, introduces the pioneering Punjabi Simplification (PUSIM) corpus, which focuses on the Shahmukhi dialect. Shahmukhi, one of the two prominent dialects of Punjabi, serves as the foundation for this corpus development. This study employs a hybrid approach that ensures the comprehensive assessment of simplification outcomes. The detailed process of simplification underwent thorough examination, aiming to transform complex sentences into simpler ones by enhancing writing clarity and vocabulary. To quantify the quality and readability of simplified texts, automated readability assessments were conducted using well-established text readability metrics, a significant SARI score of 45.3, attested to the high quality of simplification approach. The unique aspect of this work lies in its focus on the Shahmukhi dialect, addressing a linguistic facet that had previously received limited attention in natural language processing. It is anticipated that this dataset will pave the way for further exploration and research, offering novel possibilities for leveraging automated simplification techniques in the realm of Shahmukhi Punjabi language processing.

TM-Loop: Transformer multi-omics hierarchical detection of chromatin loop

Abstract Chromatin loops form the hierarchical 3D genome architecture and act as critical regulatory hubs, bringing distant cis-elements together to precisely control target gene transcription. Disruption of these spatial interactions is closely linked to human diseases including cancer. Hi-C provides genome-wide interaction maps, yet robust identification of chromatin loops remains a major bottleneck in 3D genomics, especially for contact matrices with low signal-to-noise ratio and high sparsity. We propose TM-Loop, a framework for accurate chromatin loop detection that integrates multi-omics data, Transformer deep learning, and hierarchical multi-scale clustering. Using 10 kb Hi-C matrices as core data, it combines ATAC-seq and CTCF ChIP-seq signals to build a weighted feature system and reduce sample imbalance. The Transformer’s multi-head attention captures global and local feature dependencies, while dual-threshold filtering and anchor-guided clustering effectively remove false signals and lower false discovery rate. Source code: https://github.com/yimuhuashui/TM-Loop. Experiments show TM-Loop outperforms existing methods in APA, protein enrichment, and 3D structural consistency, providing a new tool for high-precision genome-wide chromatin loop analysis.

From means to meaningful: undertaking cluster analysis to develop health literacy profiles of people in Australian prisons

Prison populations are diverse, experience substantial vulnerabilities and commonly have poor health outcomes. Cluster analysis of Health Literacy Questionnaire (HLQ) data provides an opportunity to account for the prison population’s diversity and generate fit-for-purpose intervention ideas for the prison context. This mixed-methods study aimed to undertake cluster analysis to explore the diverse health literacy profiles of people in the New South Wales (NSW), Australia, prison setting, and to co-design a series of vignettes that represent people in prison. Cluster analysis using Ward’s method was applied to HLQ data (n = 471) to identify health literacy profiles of people in NSW prisons. Semi-structured interviews with people in prison were conducted to collect in-depth personal experiences of prison health services access and use. Interview data were combined with cluster analysis results to co-design vignettes with various stakeholders. A 14-cluster solution was identified as the optimal solution for the sample as a whole, whereas a 9-cluster solution was identified for the sample of people who self-identified as Aboriginal. Qualitative data from 10 semi-structured interviews were combined with the health literacy profiles identified in the cluster analyses. A total of 23 vignettes were co-designed with stakeholders (n = 34) to represent the voices of a typical person with lived experience across each cluster. Cluster analysis has unmasked previously unforeseen variations and enabled us to move from merely reporting means to gaining meaningful insights into the health literacy profiles of people in prisons. Our findings are important because they show that using the mean or proxies alone does not capture population variation, which may inadvertently exclude or disadvantage population subgroups. The co-designed vignettes are expected to stimulate discussions to generate localised, fit-for-purpose health literacy-informed interventions to address health inequities for prison populations in NSW.