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Behavioural variability and repeatability in adult zebrafish (Danio rerio) using the novel tank dive test

Zebrafish ( Danio rerio ) are widely used in behavioural neuroscience as a model for studying anxiety-like and stress-related behaviours. However, substantial variability exists within and among individuals, influenced by factors such as sex, age, and environmental conditions, making the interpretation of anxiety-related behaviours challenging. Here we characterized longitudinal patterns of stability and variability in anxiety-like behaviours across individual adult zebrafish and assessed whether distinct behavioural profiles emerged over time. Using the novel tank dive test, we tracked anxiety-related behaviours in zebrafish across multiple time points over a 21-week period (90, 120, and 150 days post-fertilization). Behavioural metrics, including time spent in tank zones, swimming velocity, and immobility, were analyzed for age- and sex-related effects, repeatability, and group variation. Results indicated significant changes in anxiety-like behaviours with age, with fish spending more time in the upper zone and displaying increased swimming velocity over time. While no significant sex differences were observed in zone preference, males exhibited greater within-individual variation in time spent in the lower zone, while females demonstrated higher among-individual variation and repeatability over time. Furthermore, zebrafish were classified into high, medium, and low-anxiety groups based on cumulative behavioural scores, revealing stable individual differences in anxiety-like behaviours. These findings highlight the importance of considering age, sex and both intra- and inter-individual variation when interpreting zebrafish behaviour and provide a foundation for future research exploring selective breeding, anxiety level interactions, and pharmacological modulation of anxiety-related phenotypes.

Optimizing tissue sampling during medical pleuroscopy for diagnosis of malignant pleural effusion due to lung cancer

Minimally invasive detection of early-stage opisthorchiasis-associated cholangiocarcinoma using label-free surface-enhanced Raman spectroscopy (SERS) of hamster serum

Background Cholangiocarcinoma (CCA) is a deadly cancer often detected late. Current diagnostic methods, such as ultrasound and invasive biopsies, have limitations; there is a critical need for a rapid, minimally invasive and effective strategy for the early diagnosis and staging of CCA. Methods We aimed to address this need using serum samples and label-free surface-enhanced Raman spectroscopy (SERS) combined with machine learning. CCA development was induced in hamsters using a combination of Opisthorchis viverrini infection and administration of N -nitrosodimethylamine, with induction time courses spanning 1–5 month(s). Normal and pathological stages (inflammation, precancerous lesion, and CCA) were assigned based on histopathological features, as well as the expression of cytokeratin 19 and alpha-fetoprotein. Raman spectra were subjected to dimensionality reduction using principal component analysis, and diagnostic clusters were acquired using partial least-squares discriminant analysis. Results Histopathological analysis confirmed a clear path towards CCA, initiated by marked inflammation, progressing to include significant cholangiofibrosis and cholangiofibroma in the precancerous stage, and culminating in definitive CCA tumor development. The integration of SERS and machine learning achieved a diagnostic sensitivity of 93%, specificity of 95%, and accuracy of ≥ 67% for precancerous lesions and CCA, with an area under the receiver operating characteristic curve exceeding 0.67. Conclusions Our findings demonstrate that this cost-effective, label-free SERS approach can accurately detect precancerous and cancerous stages of cholangiocarcinoma in a hamster model, highlighting its strong potential for future development as a community-based screening tool.

Scalable InAs/InGaAs DWELL structures for broadband infrared emission spanning the E- to O-band

Analysis of engineering data with an innovative generalization of the Lomax distribution

As the amount and complexity of engineering data that need to be analyzed and interpreted continue to increase, the development of new distributions with outstanding adaptability is necessary. The aim of this work is to improve the precision of data modeling, particularly with respect to reliability and lifetime analyses. In this regard, a novel distribution called the Lomax Kavya Manoharan exponential (LKME) distribution derived from the exponential form of a hazard rate function is proposed. The introduction of the Kavya Manoharan exponential distribution with the properties of the Lomax distribution promotes the adaptability to capture different patterns of failure rates, thereby providing a better fit for lifetime data. The LKME distribution is highly flexible and accommodates almost all possible forms of densities, including symmetric, skewed, and inverted J-shaped, as well as diverse shapes of the hazard rate function. This ensures its suitability for modeling various applications in engineering and other fields. Monte Carlo simulations are performed to examine the performance of several classical estimation methods according to benchmarks, such as absolute bias and mean squared error. Furthermore, five engineering datasets are analyzed using the novel LKME distribution, which provides a better fit than comparison distributions, as demonstrated by different goodness-of-fit metrics.

A neural architecture search optimized lightweight attention ensemble model for nutrient deficiency and severity assessment in diverse crop leaves

Abstract The growth and productivity of banana crops are critically affected by micronutrient deficiencies, which are often difficult to detect at early stages. Lightweight deep learning models, optimized through neural architecture search (NAS) and attention mechanisms, are hypothesized to provide accurate and efficient classification of such deficiencies for real-time agricultural applications. In this study, multiple convolutional neural networks (CNNs) and mobile-friendly architectures, including ResNet50, VGG16, NASNetMobile, and MobileNet variants (V1, V2, V3), were evaluated using transfer learning on a curated banana leaf deficiency dataset. To improve robustness and prediction accuracy, modified classification layers and ensemble strategies–initially average ensembling and later a NAS-guided dynamic attention weighting mechanism were employed. This optimization resulted in a novel lightweight model, NASMobV2 (NASNetMobile + MobileNetV2), capable of both classifying nutrient deficiencies and assessing their severity levels. The proposed model achieved a validation accuracy of 98.57%, outperforming baseline and state-of-the-art counterparts in precision, recall, and F1 score. To improve generalization, banana crop diseases along with an additional Coffee crop dataset were included for evaluation. Finally, the practical utility of the model was demonstrated by deploying the trained system in both mobile and web applications, enabling farmers and agronomists to perform fast and accurate diagnostics directly in the field.

Suitability of paddy cultivation in the Western province of Sri Lanka under different climate change scenarios

Climate change poses a significant threat to global agriculture, with implications for food security. Regions that rely heavily on rain-fed agriculture, especially in developing countries, such as the Western province of Sri Lanka are particularly vulnerable. The current research aims to assess future climate expectations and their impacts on paddy cultivation in Sri Lanka’s Western province for the purpose of identifying measures to address the multi-faceted consequences of climate change. The main objective of the study was to determine the spatial suitability of paddy in the Western province for the years 2030 and 2050 under different climate change scenarios. Rice occurrence points and bioclimatic variables were employed to model the spatial suitability of paddy under current, 2030 SSP 245, 2030 SSP 585, 2050 SSP 245, and 2050 SSP 585 climatic conditions using ‘biomod2’ package of RStudio software. The results revealed that areas unsuitable for paddy cultivation increased under 2030 SSP 245 (1,437.30 km 2 ), 2030 SSP 585 (1,594.80 km 2 ), 2050 SSP 245 (2,624.40 km 2 ), and 2050 SSP 585 (2,627.10 km 2 ) conditions when compared with current (1,044 km 2 ) climatic conditions. Further, the simulation indicated that the species range change between the current climatic conditions and 2030 SSP 245 (−16.58), 2030 SSP 585 (−13.62), 2050 SSP 245 (−37.03), and 2050 SSP 585 (−50.51) is negative. The percentage loss in paddy range between current and 2030 SSP 245, 2030 SSP 585, 2050 SSP 245 and 2050 SSP 585 climatic conditions were shown to be 52.94%, 47.89%, 22.07% and 67.85%, respectively. Therefore, the results of the present study highlight the need for a comprehensive approach that integrates climate change adaptation and mitigation in agriculture to ensure food security and to protect vital ecosystems. The findings of this study can be utilized by researchers, policymakers, and practitioners aiming to achieve global sustainability goals.

Molecular and agronomic assessment of faba bean genotypes identifies resistance to Orobanche crenata infestation

Frailty and nutritional inadequacy in older Korean adults: A gender-stratified analysis using National Survey Data

While frailty has traditionally been conceptualized through physical decline, it is increasingly recognized as a complex concept encompassing emotional, psychological, and social factors. This study employed a multidimensional framework to investigate the association between nutritional status and frailty levels across genders. In addition, it aims to provide foundational insights for developing targeted dietary and preventive health policies that support interventions tailored to the characteristics of specific older adult populations. This is a cross-sectional study of the 2009–2020 Korean National Health and Nutrition Examination Survey in 14,242 participants aged 65 and older. The frailty index was constructed using 41 items. Dietary data were obtained through a 24-hour dietary recall, and adequacy of nutrient intake was evaluated based on the Dietary Reference Intakes for Koreans 2020. Multivariable logistic regression analysis was conducted to examine the association between nutritional status and frailty levels. Among participants, 31.6% were categorized as non-frail, 47.8% as pre-frail, and 20.6% as frail. Women exhibited lower total energy intake and higher frailty prevalence than men. Gender-stratified analyses revealed distinct nutritional patterns: frail men showed a significant decreasing trend in riboflavin intake (P-trend = 0.0012), while frail women had increased carbohydrate (P-trend = 0.005) and decreased fat (P-trend = 0.0032) and riboflavin (P-trend = 0.0062) intake. Frailty significantly associated with iron inadequacy in men (OR=1.49, 95% CI:1.15–1.94; P-trend = 0.0018) and riboflavin inadequacy in women (OR=1.45, 95% CI:1.20–1.74; P-trend<0.0001). Frailty in older adults is associated with multidimensional vulnerabilities-including demographic, behavioral, relational, and nutritional factors-with notable gender differences in nutrient intake patterns. These findings underscore the need for gender-specific and integrated nutritional interventions to effectively prevent frailty and improve quality of life in the elderly population.

Regulatory role of serine 59 in the oligomeric dynamics and chaperone function of αB-crystallin

Computational evaluation of AKT2 mutations reveals R274H and R467W as potential drivers of protein instability and inhibitor resistance in cancer therapy

Cancer remains a leading cause of mortality worldwide, with genetic alterations such as single nucleotide polymorphisms (SNPs) playing a critical role in tumor progression and therapy resistance. Non-synonymous SNPs (nsSNPs) in AKT2, a key kinase in the PI3K/AKT signaling pathway, can impact protein structure and function, leading to reduced efficacy of targeted cancer therapies. This study employs computational approaches to investigate the structural and functional consequences of nsSNPs in the AKT2 and their impact on inhibitor interactions. Three structurally and functionally significant nsSNPs (Y265N, R274H, and R467W) were identified where only R274H and R467W were associated with reduced inhibitor binding. R274H, and R467Wwere found to disrupt key molecular mechanisms, including metal binding, loss of allosteric sites, and alterations in post-translational modifications. Molecular docking revealed that R274H, in kinase domain, disrupts key hydrogen bonds with THR292 and GLU279, leading to more flexible binding pocket and significantly reduced binding affinity for Capivasertib and Ipatasertib. Similarly, R467W, in AGC-kinase C-terminal domain, causes the loss of hydrogen bonds with THR292, ASN280, and GLU279, leading to decreased binding affinity for Akt1/Akt2-IN-1, Capivasertib, and Ipatasertib inhibitors. MD simulations further demonstrated that R274H and R467W caused substantial structural deviations and increased residue flexibility, with R467W exhibiting the most pronounced destabilizing effect. These findings suggest that these mutations may contribute to inhibitor resistance by weakening inhibitor interactions and destabilizing the protein-inhibitor complex. This study underscores the importance of genetic screening in optimizing cancer treatment and highlights the need for mutation-specific therapeutic strategies targeting AKT2.

Phishing detection on webpages in European non-English languages based on machine learning

Global lessons from local contexts: The evolution of biomedicine education in Spain

Driven by the presence of faculty with research and clinical backgrounds, and by labor market trends favoring applied training, Biomedicine has emerged as a growing academic field in Spain. This study provides a descriptive analysis of undergraduate Biomedicine programs offered by 18 Spanish universities since 1998, focusing on structural, academic, and outcome-related variables. Data indicate a progressive increase in program availability and student enrollment over the past two decades, reaching a total of 4,614 students in the most recent academic period. Admission criteria remain highly selective, with a mean entry score of 12.5 out of 14. In the absence of guidelines, the curricula from the different universities show a consistent structure, with an emphasis on foundational biomedical sciences in the early academic years – such as Cell Biology, Biochemistry, and Immunology – and the incorporation of advanced subjects in later stages, including Cancer Biology and Bioinformatics. These programs frequently incorporate practical components and research exposure. Over 100 active international collaboration agreements were identified across the institutions studied, reflecting efforts to internationalize their Biomedicine programs. Despite heterogeneity in curricular design, the average graduation rate for the 2022–2023 academic year was 81.8%, and employment outcomes averaged 82.9% over the past decade. The findings suggest a convergence of academic, professional, and institutional factors shaping the development of Biomedicine education in Spain.

A 0.5-V MI-OTA-based shadow universal filter with integrated passband gain compensation and low-pass control for low-frequency applications

Correction: Factors affecting microbial safety behavior of beef handlers working in major beef retailers in Mizan-Aman, Southwest Ethiopia

Enhancing the precision of male fertility diagnostics through bio inspired optimization techniques

Adolescents’ attitudes towards healthy eating: A scale development study

The aim of this study is to develop a measurement tool that can reliably and validly measure adolescent individuals’ attitudes toward healthy eating. The study group consisted of 1,006 individuals, including 495 males and 511 females, aged between 11 and 17 years. In this study, an exploratory sequential design was applied. A semi-structured interview form was used to create the item pool, and compositions were written. The “Davis Technique” was employed to assess the content validity of the items. For data analysis, SPSS 25.0 was used for EFA and reliability analysis, and Lisrel 8.7 was utilized for CFA. Based on the result of EFA, a structure consisting of 4 factors and 18 items was formed. The total variance explained is 59.05. According to CFA analysis, factor loadings range from .43 to .81, and X2/df = 1.65, RMSEA = .040 were found. Furthermore, the NFI, NNFI, PNFI, CFI, IFI, GFI, AGFI, PGFI, and RFI fit indices were found to be excellent and within the good range. In the analysis of the lower and upper groups of the scale (27%), statistically significant differences were observed in all items (p < .01). To test the reliability of the scale, Cronbach’s Alpha, Spearman-Brown (Split-half), and Guttman Lambda-6 coefficients were examined. The scale sub-dimension correlations ranged from .526 to .129. In conclusion, the developed scale demonstrates that it can validly and reliably measure adolescents’ attitudes toward healthy eating.

Evaluating voluntary care seeking effects on COVID-19 outcomes and health system costs

Phytochemical characterization and anticancer potential of Psidium cattleianum Sabine aerial parts’ n-hexane extract and its subfractions

Psidium cattleianum Sabine (Family Myrtaceae) is a Brazilian native shrub, valued for its diverse health and therapeutic attributes. The current study investigated the phytochemical profile along with the anticancer activities of the n- hexane extract (HE) of P. cattleianum aerial parts and its subfractions. GC-MS and HPTLC-MS were used for phytochemical analysis. The human breast adenocarcinoma cells (MCF-7) and the human colon cancer cells (HCT-116) were used to investigate the anticancer effect in the viability, migration, and clonogenic assays. The GC-MS analysis of HE identified thirty-two components categorized mainly into terpenes, hydrocarbons, and sterols. β -caryophyllene oxide (12.07%) and humulene (7.42%) were the most abundant oxygenated and non-oxygenated metabolites, respectively. Concerning HE’s subfractions, fraction I is prolific with caryophyllene oxide (19.48%) and humulene (9.96%), while fraction II was rich in caryophyllene oxide (6.89%). HPTLC-MS analysis of fractions III-V identified the presence of nonadecatetraene, heptacosanol, and dihydroxy-oxo-ursenoic acid in fraction III; caryophyllene and littordial C in fraction IV, while guavanoic acid, p -coumaroyl caffeoylquinic acid, cholestane heptol, tocopherol, heptacosanedione, and trans -calamenene in fraction V. Concerning the anticancer results, the HE showed potent cytotoxicity with IC 50 29.18 ± 0.43 μg/mL (MCF-7) and 56.55 ± 6.8 μg/mL (HCT-116). In addition, at maximum tested doses approximating ½ IC 50 (15 and 28 μg/mL) in cytotoxicity assay, it displayed significant percent wound closure of 22.78 ± 2.13% and 12.76 ± 1.88%, respectively. While at doses corresponding to ¼ IC 50 (7.5 and 14 μg/mL), the HE displayed a colony formation efficiency of 2% and 0% on MCF-7 and HCT-116, respectively. Subfractions I and II, rich in caryophyllane sesquiterpenes, such as caryophyllene oxide, showed the best activity in all assays. Molecular docking of β -caryophyllene oxide, as the most identified bioactive metabolite, revealed an energetically favorable binding pose driven through hydrophobic interactions at the estrogen receptor ligand binding domain. The study endorses P. cattleianum HE and its selected fractions in the control of breast and colon cancers; however, further investigation into an appropriate in vivo model is required.

Exergoeconomic and enviroeconomic evaluation of double pass solar air heater with black coated porous wire mesh and galvanized iron packed bed