Browse Articles

Cultural adaptation and psychometric validation of the Health Literacy Instrument for Adults with Tuberculosis (HELIA-TB) in India

Background Tuberculosis (TB) remains a critical public health challenge in India, where sustained patient engagement is essential for its effective management. Despite the pivotal role of health literacy, the ability to access, understand, appraise, and apply health-related information in treatment adherence and outcomes, few tools are TB specific, culturally attuned to India, and psychometrically validated. The Health Literacy Instrument for Adults (HELIA), developed in Iran, is a multidimensional, World Health Organization (WHO)-aligned measure with proven reliability and open access, making it an ideal candidate for adaptation. This study aimed to culturally adapt and validate the HELIA for use among adults receiving TB treatment in India (HELIA-TB). Methods An exploratory sequential mixed-methods design was employed for the cultural adaptation and psychometric validation of the HELIA-TB in Junagadh district, Gujarat, India, between March 2024 and March 2025. The qualitative phase included expert review, forward translation, cognitive interviews with adults with TB and  frontline healthcare workers, back translation, and pilot testing, following international cross-cultural validation guidelines. Findings from the qualitative phase directly informed item modification, simplification of terminology, and contextual adaptation of the HELIA-TB prior to quantitative psychometric validation. The finalized instrument was subsequently administered to 393 adults with TB to assess internal consistency, test-retest reliability, content validity, and construct validity. Results HELIA-TB retained the original five domains, access, reading, understanding, appraisal, decision-making with TB specific modifications. Internal consistency and test-retest reliability were high (α = 0.82–0.89 across domains; 0.86 overall; ICC = 0.88), and so was content validity (S-CVI/Ave = 0.92). Health literacy scores were significantly associated with treatment adherence (Cohen's d = 0.89, p < 0.001) and self-rated health (Cohen's d = 0.76, p < 0.001). No significant differences were observed by TB type or drug resistance status. Conclusions The adapted HELIA-TB demonstrated satisfactory psychometric properties and may support assessment of health literacy and development of targeted TB care interventions in the Indian context.

Numerical modeling of the hydrodynamic behavior of MgO–water nanofluid in plate-fin heat exchangers under varying operating conditions

Abstract This research examined the ability of an artificial neural network to predict flow behavior, defined by Reynolds number and pressure drop as functions of volume fraction and temperature, at fixed flow rates of 5, 8, and 11 LPM. The proposed framework was developed to address the nonlinear, interrelated thermo-compositional effects that influence flow inertia and pressure losses, without relying on predefined empirical relationships. The model’s reliability and predictive performance were evaluated through 5-fold cross-validation, monitoring of learning errors, regression diagnostics, error quantification, and sensitivity analysis. Results from cross-validation indicated stable Reynolds number predictions at low and moderate flow rates, with mean RMSE values of 6.39 at 5 LPM and 6.16 at 8 LPM. At 11 LPM, the mean RMSE rises to 13.87, highlighting the greater sensitivity and complexity of inertia-dominated flow regimes. Conversely, predictions of pressure drop remained consistently accurate across all operating conditions, achieving mean RMSE values of 2.68 mbar, 0.56 mbar, and 0.94 mbar at 5, 8, and 11 LPM, respectively. Regression analysis confirmed a strong linear relationship between predicted and reference values for both outputs, with correlation coefficients exceeding 0.99 at low and moderate flow rates and remaining above 0.96 at the highest flow rate. Further analysis of relative and absolute errors indicated high predictive accuracy, with mean relative errors below 5% for Reynolds number and below 1.3% for pressure drop across all scenarios. Sensitivity analysis consistently identified temperature as the primary source of predictive variability, with volume fraction being the secondary contributor. Pressure drop showed significantly lower sensitivity than Reynolds number, suggesting a smoother, less nonlinear relationship with the governing inputs.

TRPC4/TRPC5 are critical for neuronal modulation by transcranial focused ultrasound in retrosplenial cortex in male mice

Extraction and characterization of microcrystalline cellulose from kelp (Laminaria japonica) waste

Kelp, an economically important brown alga widely cultivated in East Asia, produces kelp waste rich in cellulose as a byproduct of alginate extraction. In this study, kelp cellulose (KC) was first extracted from the kelp waste. Subsequently, 2 wt% hydrochloric acid was used to hydrolyze the kelp cellulose at 100 °C for 30 min to isolate kelp microcrystalline cellulose (KMCC) from the KC. Characterization by X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR) revealed that the chemical structures and cellulose I crystal form remained intact during hydrolysis, with the crystallinity index increasing from 76.4% to 78.1%. Thermogravimetric analysis (TGA) and derivative TGA indicated enhanced thermostability of KMCC compared to KC. Scanning electron microscopy (SEM) observations showed that acid hydrolysis transformed the irregular thin-sheet structure of KC into smaller-sized KMCC with a morphology distinct from the rod-like structure of commercial microcrystalline cellulose (CMCC). The level-off degree of polymerization (LODP) of KMCC measured around 164.3, closely resembling the value for CMCC at 166.5, with a yield of 85.5%. This study proposes a novel method to utilize kelp waste by converting it into MCC, offering a potential avenue for its valorization.

Anticancer potential of geranyl acetate through RelA gene downregulation in acute myeloid leukemia cells

The long tail of nitrate pollution in groundwater challenges governance of global water quality

In silico-predicted B-cell epitopes for bovine brucellosis serodiagnosis: Preliminary analytical evaluation of synthetic peptide- and multi-epitope protein-based indirect ELISAs

Serological methods are valuable diagnostic tools for bovine brucellosis, a zoonotic infectious disease with a worldwide distribution. Currently employed diagnostic methods utilize crude bacterial extract or regions of LPS, a molecule that can exhibit cross-reactions with other infectious agents. The goal of this study was to develop an indirect enzyme-linked immunosorbent assay (ELISAi) using synthetic peptides or a multi-epitope protein based on in silico- predicted B cell epitopes. Peptides were synthesized on a cellulose membrane using spot synthesis, and immunoblots were performed to evaluate reactivity by densitometry against bovine sera of interest. Peptides reacting with serum from positive cattle and non-reactive to the serum from negative controls were selected, synthesized in a soluble form, and used as antigens for the development of the ELISAi. Two peptides (P1 and P2) were selected and, after standardization of the ELISAi, positive (25) and negative (175) samples were tested, resulting in a sensitivity of 84% (21/25) and specificity of 83.43% (146/175). The sequence of the two peptides in replicates with spacers were inserted into a multi-epitope protein, which was also used as antigen in an ELISAi resulting in a sensitivity of 72% (18/25) and a specificity of 61.71% (108/175). This study provided a preliminary analytical assessment of in silico -predicted epitopes for developing novel serologic diagnostic tests.

Invisible poison attacks and holistic defence strategy for pyramid vision transformers in medical imaging

Unified bilayer membranes with mechanically reinforced interface for stage-adaptive bone regeneration

Abstract Guided bone regeneration using double-layered membranes is often hindered by poor interfacial integration, insufficient stability, and limited adaptability to regulate the complex healing process. Herein, we develop a unified bilayer membrane featuring a reinforced dual-crosslinking interface between barrier and porous layers through a homogeneous isomeric in-situ fabrication strategy. Its superior mechanical strength (~156 MPa in dry state and ~8.6 MPa in wet state) ensures the long-term degradation stability and bioactivity in vivo. Combined with sequentially released bioactive components, we show that the unified bilayer membrane regulates antibacterial functions, immunomodulation, neurovascularization, and osteogenesis, thereby enabling stage-adaptive bone regeneration. We test in a rat critical-sized cranial defect model to demonstrate that the membrane significantly outperforms the clinical collagen membrane, achieving ~2.7-fold greater bone volume regeneration after 8 weeks. This work further elucidates the spatiotemporal osteogenic mechanisms of the unified bilayer membrane, which constructs a well-integrated regenerative microenvironment and promotes a tightly interconnected neurovascular-osteogenic communication network during stage-adaptive bone repair.

Editorial Note: Terahertz Irradiation Promotes Angiogenesis in vitro by Enhancing Permeability of the Voltage-Gated Calcium Channel

Degradation of small-strain shear modulus of expansive soils under repeated wetting–drying cycles: experimental evidence and damage-based modeling

Adaptable centriole biogenesis via the intrinsically disordered protein ALMS1

Brucella canis outbreak management towards rehoming strategies: The Italian experience

Canine brucellosis, caused by Brucella canis , is a contagious disease leading to reproductive disorders in both male and female dogs. In April 2020, Italy reported its first outbreak of B. canis in a central breeding kennel housing over 680 toy breed dogs. Following confirmation, animal movement was restricted, and a no-kill strategy was implemented to manage the outbreak. A structured protocol, integrating castration and neutering and serological testing, was developed to identify and rehome B. canis -negative dogs. This study describes the procedure used to select non-infected dogs and the follow-up monitoring protocol applied post-adoption. Over 300 dogs were successfully rehomed, with laboratory investigations confirming no occurrence of late infection in the adopted animals. These results support the inclusion of rehoming strategies as a viable option in B. canis outbreak management.

Down-staging depth score could be a survival predictor for locally advanced breast cancer patients after neoadjuvant chemotherapy

AI-driven molecular diversification and ligand-based optimization of macitentan derivatives targeting VEGFR1 and endothelin signaling pathways

Preeclampsia is a hypertensive disorder of pregnancy marked by angiogenic imbalance and endothelial dysfunction, driven largely by over expression of soluble fms-like tyrosine kinase-1 (sFlt-1) and up-regulation of endothelin-1 (ET-1). Targeting both VEGFR1 and ET-1 receptor could offer a dual-action therapeutic approach. In this study, macitentan, a dual ETA/ ETB antagonist, was used as a scaffold for AI-assisted derivative generation aimed at dual inhibition of these receptors. A comprehensive computational pipeline was applied including molecular docking, pharmacophore modeling, molecular dynamics (MD) simulation, DFT, MM/GBSA, and ADMET analysis. Derivative 24 showed high binding affinity toward VEGFR1 (–7.7 kcal/mol), while Derivative 15 exhibited superior interaction with ET-1 receptor (–9.2 kcal/mol), both outperforming macitentan. MD simulations over 500 ns confirmed complex stability with RMSD stabilization around 0.2–0.3 nm and consistent hydrogen bonds. MM/GBSA binding energies further supported strong receptor interactions (–17.15 kcal/mol for Derivative 24–VEGFR1; –28.72 kcal/mol for Derivative 15–ET-1 receptor). DFT results showed reduced HOMO–LUMO gaps (3.55 eV for Derivative 24; 3.30 eV for Derivative 15), while MEP analysis indicated favorable electrostatic potential for target interaction. Pharmacophore and ADMET profiling revealed improved drug-likeness, high GI absorption, and reduced predicted toxicity. This study presents Derivatives 15 and 24 as promising dual-target leads against preeclampsia-induced endothelial dysfunction. However, experimental validation remains necessary to confirm efficacy and safety before translational application.

Structural-budgeted QUBO learning of Bayesian networks with spectral and credibility diagnostics

Invaders taking over—Mollusc faunal change in volcanic barrier lakes of the Albertine Rift biodiversity hotspot

East African freshwater are renowned biodiversity hotspots, particularly within the Rift Valley lakes, which exhibit exceptional species richness and endemism. However, research in this region has predominantly focused on large Rift lakes, with smaller volcanic barrier lakes remaining underexplored. This study integrated morphological, DNA barcoding, and ecological analyses to assess mollusc diversity, biogeographical affinities, environmental correlates of distribution, and community differences in lakes Bunyonyi, Mutanda, and Mulehe in Uganda, and Lakes Ruhondo and Burera in Rwanda. Results revealed a relatively high malacofaunal diversity in these lakes compared to some Great Lakes in the region, although these comparisons should be interpreted cautiously because sampling scope differs among studies. Assemblages largely exhibited Nilotic affinities and were dominated by widespread mollusc species. Our findings suggest ongoing homogenisation of mollusc communities, as indicated by reduced dispersion among invaded lakes. While this pattern is consistent with potential influences of anthropogenic activities and invasive species such as the North American crayfish ( Procambarus clarkii ), Physella acuta , and the Asian lineage of Melanoides tuberculata , our analyses do not allow us to disentangle invasion effects from other confounding factors, including lake-specific characteristics and environmental gradients . Therefore, invasion-driven homogenisation should be interpreted with caution. Nevertheless, this trend, coupled with habitat degradation from agriculture, pollution, and infrastructure development, may pose significant threats to the mollusc diversity in these lakes. This research underscores the importance of prioritising these overlooked, fragile ecosystems in the regional biodiversity conservation strategies to safeguard habitats for molluscs and other faunal elements. A comprehensive regional freshwater survey, including metabarcoding, is needed to document molluscan diversity patterns under ongoing environmental change and increasing anthropogenic pressure.

Introducing Actigraphic Data Analyzer (ADA), an open source software for sleep/wake scoring and circadian rhythm analysis with graphical interface

Abstract We introduce Actigraphic Data Analyser (ADA), a user-friendly open source Python package with a graphical user interface (GUI). It reads raw data from GENEActiv and ActiGraph devices, and the MESA dataset, supports multiple methods for collapsing data into epochs, provides sleep/wake scoring via several classical algorithms and the recently published Universal Filter Approach, offers comprehensive circadian rhythms analysis, and outputs common sleep plots and metrics like daily profiles, sleep onset, sleep fragmentation index and more. Apart from the interactive GUI, ADA can be used as a Python library. As an example of its application, we present a simple Python script revealing correlations between different descriptors of circadian rhythms: DFA, variants of cosinor, AR model spectrum, IS, IV, M10 and L5. Correlation matrix produced by this script (a figure included also in this paper) applied to a dataset of 87 weekly recordings (created for this study and freely available) reveals division of these commonly applied descriptors into two groups: one related mostly to the (length of) circadian period, and the other to the strength of the 24-h rhythm. Both the above-mentioned ADA package and set of weekly actigraphic recordings are freely available on GPLv3 and CC-BY licences, respectively.

Dosimetric characterization of CdZnTe radiation detectors under electron-beam irradiation

With the growing complexity of modern radiotherapy, the demand for dosimeters capable of delivering real-time, high-resolution, and reliable measurements has grown significantly. Although cadmium–zinc–tellurite (CZT) detectors have emerged as potential solutions to this growing demand, the lack of comprehensive characterization data for these detectors deters their application in clinical electron-beam dosimetry, especially for high-precision tasks such as small-field and point-dose dosimetry. In this study, we systematically characterized CZT detectors, emphasizing the performance trade-offs associated with detector thickness for therapeutic electron-beam dosimetry. The performance of two CZT detectors (6 × 6 mm²), with thicknesses of 5 and 8 mm, was evaluated using a clinical linear accelerator (LINAC) over an electron energy range of 6–18 MeV. Both detectors demonstrated stable baseline performance, including proportional dose linearity (R² > 0.997), dose-rate independence, and excellent long-term stability (<1.3% variation over two months). Furthermore, a distinct thickness-dependent trade-off was identified: while both configurations exhibited highly comparable dose responses at the 6-MeV baseline, the 8-mm detector exhibited better energy capture efficiency for higher-energy electrons. By contrast, the 5‑mm detector offered enhanced angular isotropy with respect to the gantry angle as well as reduced signal variation (±3.5% vs. ± 6.4%), emerging as more suitable for rotational therapies and geometrically demanding scenarios. Additionally, a nonmonotonic energy dependence was observed, characterized by a pronounced response peak at 15 MeV, which was likely attributable to bremsstrahlung photon contamination from the LINAC head. These findings demonstrate that detector thickness serves as an application-specific optimization factor for sensitivity and angular fidelity, offering a practical framework for deploying CZT detectors in both initial clinical evaluations and challenging extra-clinical radiation environments.

A spatially reconfigured polarization converting metasurface for enhanced radar cross section reduction