Browse Articles

Geospatial variability and nutrient partitioning of potassium, calcium, and magnesium in Iranian wheat grains: implications for flour and bread quality

Examining relationship between unhealthy lifestyle and life satisfaction among new students at Tehran University of Medical Sciences

Background Transitioning to university is a critical period marked by lifestyle changes, academic pressures, and increasing autonomy, which can influence students’ overall well-being. Previous research suggests that unhealthy lifestyle behaviors—including poor diet, insufficient physical activity, inadequate sleep, and ineffective stress management—may negatively impact life satisfaction among young adults. Methods This cross-sectional study examined the relationship between lifestyle and life satisfaction among newly enrolled undergraduate students at Tehran University of Medical Sciences in 2024. Participants completed structured questionnaires assessing multiple lifestyle domains (diet, physical activity, sleep, smoking, alcohol use) and life satisfaction using validated Iranian questionnaires. Lifestyle scores were categorized as “healthy” or “unhealthy,” and life satisfaction as “good” or “poor.” Associations were analyzed using Pearson’s chi-square test and multivariable logistic regression, adjusting for age, sex, socioeconomic status, and anxiety. Results Overall, of the 419 students, 294 (70.2%) reported good life satisfaction. Socioeconomic status and anxiety levels differed significantly across life satisfaction groups (p < 0.001). Students with healthier dietary patterns reported higher life satisfaction (76.6% vs. 60.4%, p = 0.02). Multivariable analysis indicated that students with healthy lifestyles had significantly higher odds of good life satisfaction compared to those with unhealthy lifestyles (adjusted odds ratio [aOR = 1.91; 95% confidence interval [CI]: 1.10,3.35; p = 0.02). Each one-unit increase in lifestyle score was associated with a 28% increase in the odds of good life satisfaction (aOR = 1.28; 95% CI: 1.05,1.57; p = 0.02). Conclusion Unhealthy lifestyle behaviors are negatively associated with life satisfaction among new university students. Interventions promoting balanced nutrition, regular physical activity, adequate sleep, and overall health-conscious behaviors may enhance students’ life satisfaction and well-being.

Chemical profile and in vitro antischistosomal activity of Crotalaria madurensis different extracts

Abstract Chromatographic isolation of Crotalaria madurensis Wight & Arn leaves aqueous methanol extract availed a new potassium sulfonate acylated flavonol glycosides named quercetin 8-potassium sulfonate 3- O -[2- O -sulfonyl]- β - D - 4 C 1 -glucopyranosyl-(1’’’’→3’’’)-4- O -[ E - caffeoyl]- β - D - 4 C 1 -glucopyranosyl-(1’’’→2’’)-3- O -[ E -caffeoyl]- β - D - 4 C 1 -glucopyranoside ( Crotalamad oside A) ( 1 ), along with three known flavonoids identified as quercetin 7- O -neohispredoside ( 2 ), 3’,4’-dimethoxy quercetin 3- O -neohispredoside ( 3 ) and isoquercetin ( 6 ) besides two triterpene saponin compounds named as hedragenin 3- O - β - D - 4 C 1 -glucopyranoside ( 4 ) and hedragenin 3- O - α - L - 1 C 4− rhamnopyranoside ( 5 ). This was in addition, to two cinnamic acid derivatives named as E -caffeic acid 4- O - β - D - 4 C 1− glucopranoside ( 7 ) and E -caffeic acid ( 8 ). Identification of the isolated compounds relied on their chromatographic properties and spectral data (UV, ESI-MS, 1 H NMR, 13 C NMR, 1 H- 1 H COSY, HSQC, and HMBC). The antischistosomal activity of the C. madurensis different extracts were assessed in vitro using schistosome worm killing, findings revealed that the aqueous methanol extract was the most effective extract, chromatographic fractionation of this extract revealed significant antischistosomal activity for fractions number V and VI rich in flavonoids and triterpene saponins, respectively.

Corrosion assessment in aluminum pipe based on nonlinear ultrasonic technique using macro fiber composite transducers

Pipe corrosion, specifically pitting corrosion, is the main cause of destructive pipe leakage, driven by the harsh working environment of liquid and gas transportation. Therefore, detecting pitting corrosion is essential for ensuring the safe operation of metal pipes. This study investigates a nonlinear ultrasonic technique using macro fiber composite transducers, aiming to assess pitting corrosion in metal pipes at an early stage, with a focus on characterizing the influence of temperature on the ultrasonic nonlinearity. Macro fiber composite transducers with flexibility and high ultrasonic performance were used to actuate and detect ultrasonic guided waves propagating in pipes with curved surfaces. Considering the multi-mode propagation characteristics, the 1.4 MHz second-harmonic ultrasonic component generated by the nonlinear interaction between ultrasonic guided waves and pitting corrosion was extracted. Repeated experiments revealed that both the second-harmonic amplitude and relative nonlinear parameter exhibited a monotonic increase with the number of cycles and area of pitting corrosion. For comparison with the nonlinear results, statistical metrics including the mean slopes, coefficient of determination, and relative standard deviation of the linear fitting parameter were determined alongside the linear ultrasonic experiments. These results indicate that, despite some inherent data variability, the proposed nonlinear ultrasonic technique exhibits comparatively better sensitivity, goodness-of-fit and repeatability than linear ultrasonic methods for identifying pitting corrosion. Thus, the proposed nonlinear ultrasonic technique using macro fiber composites offers a promising complementary alternative for early corrosion assessment in metal pipes.

Assessment of health-related quality of life and determinants among pulmonary tuberculosis patients, Northern Ethiopia: a cross-sectional study

Editorial Note: Study on optimization of inspection mechanism of concrete beam bridge

FDEM-BEM simulation of hydraulic fracture propagation and control factors in conglomerate reservoirs

miR-132 overexpression is associated with modulation in miR-21 expression and glioblastoma cell behavior

Glioblastoma multiforme (GBM) is the most aggressive and lethal primary tumor of the central nervous system. MicroRNAs (miRNAs) are key post transcriptional regulators of gene expression, and increasing evidence suggests that miRNA relationships may contribute to regulatory complexity in cancer biology. In this study, we combined in silico analyses of ten independent miRNA expression datasets (TCGA and GEO) with functional validation in GBM cell models to investigate the association between miR-132 and miR-21 in GBM. Differential expression analysis consistently demonstrated significant overexpression of miR-21-5p and downregulation of miR-132-3p in GBM tissues compared with normal brain. These findings were validated in U87 and C6 GBM cell lines using qRT-PCR, confirming consistent dysregulation of both miRNAs in vitro (p < 0.05). Functional experiments demonstrated that miR-132 overexpression is associated with reduced miR-21 expression and increased expression of established miR-21 target genes, including BMPR2 and BCL11B at both mRNA and protein levels. These molecular changes were accompanied by reduced metabolic activity, impaired wound closure, and increased apoptotic cell death in both U87 and C6 GBM models. Collectively, these findings support a strong functional association between miR-132 expression and miR-21 related regulatory networks and phenotypic changes in GBM. However, the present study does not provide evidence for a direct physical or fundamental interaction between miR-132 and miR-21. Further mechanistic studies, including rescue experiments and direct binding assays, are required to clarify the underlying regulatory mechanisms.

Proteomic analysis reveals lipid metabolism disruption and key targets in ARPE-19 cells after RNF13 knockdown

Prevalence and risk factors of hypertension in rural Bangladesh: A population-based cross-sectional study

Non-communicable diseases (NCDs), such as hypertension, are amongst the most fatal conditions afflicting people living in low- and middle-income countries (LMIC), including Bangladesh. This study addresses the lack of population-based studies in rural Bangladesh by examining the prevalence and distribution of hypertension and its associated risk factors. To this end, we surveyed adults aged ≥18 years (i.e., household heads and their spouses) from 7384 households across 149 villages in rural Bangladesh in 2017 using a semi-structured questionnaire to collect data on blood pressure, anthropometric, socioeconomic, lifestyle, and behavioral risk factors. Multivariate logistic regression analyses identified age, gender, and socioeconomic status as potential predictors of hypertension. The findings also showed that men and women from higher socioeconomic status (SES) groups had higher rates of overweight and obesity, risk factors for the development of hypertension (4.29% and 1.4% in adult men; 5.8% and 2.29% in adult women), as well as higher rates of fruit and vegetable consumption (10.29% and 7.25% in adult men; 9.95% and 6.84% in adult women). A significant association between tobacco consumption and age was observed for women (p=<0.0001), while higher levels of physical activity were found among men aged 45–54 years [OR:1.9, CI 95% (1.1–3.1)]. Furthermore, women in the highest SES brackets were 1.3 times as likely to engage in “moderate” physical activity as those in the lowest brackets. Age and overweight/obesity were found to be the strongest risk factors for hypertension in both genders, while education was not found to be significantly associated with hypertension in women. Notably, the findings revealed that 33.7% of men and 28.6% of women had elevated blood pressure, qualifying them as either prehypertensive or hypertensive. As such, we recommend that policy interventions aimed at stemming the growth of hypertension among Bangladesh’s rural populations should take gender-specific risk factors, rural-urban disparities, and socioeconomic context into serious policy consideration.

Role of umbilical cord and maternal blood levels of IL-6 and IL-8 in the diagnosis and prediction of early-onset neonatal sepsis

NLOS/LOS identification with LightGBM ensemble

Non-Line-of-Sight (NLOS)/Line-of-Sight (LOS) identification is crucial to accurate Ultra-Wideband (UWB) positioning. The current Machine Learning solutions to this problem have either too many parameters to tune or too simple features to input, which lead to unsatisfactory performance. To address this issue, this paper proposed a novel binary classifier called LightGBM Ensemble which integrates multiple LightGBMs in parallel with multi-scale patch extraction. The heterogeneous LightGBM ensemble architecture boosts the prediction power of individuals. The multi-scale patch extraction scheme extracts informative features from time-frequency domains. Extensive experiments on an open-source dataset were conducted to evaluate the proposed approach, which proves its superior classification performance and generalization performance with feasible complexity compared to the state-of-the-art Deep Learning and Decision Trees methods.

Selaginella sellowii gene regulatory networks reveal distinct transcriptional strategies for dehydration stress and recovery

Intuitionistic fuzzy PAMSSEM method for MAGDM incorporating cumulative prospect theory and its application to the assessment on water resource carrying capacity

Assessing water resources carrying capacity (WRCC) is essential for regional high-quality development. However, most existing WRCC assessment models fail to handle uncertainties and mixed data arising from multiple criteria, which compromises their practical applicability. To address this limitation, this study integrates cumulative prospect theory (CPT) with the PAMSSEM outranking method to develop a novel intuitionistic fuzzy CPT-PAMSSEM model. Then the proposed method is validated through a case study of four cities in the middle and lower reaches of the Tuojiang River Basin. Results show that: (1) WRCC varies significantly across the four cities: Luzhou and Ziyang show favorable conditions, Zigong is near the critical threshold, and Neijiang faces a severe water resource shortage crisis. (2) the proposed model markedly improves the discrimination of different evaluation results, achieving a differentiation level approximately 3–6 times greater than that of conventional methods. These findings provide actionable insights for sustainable water management.

Mapping 99 emotion terms with GPT4 prompting reveals nuanced semantic conceptual structure

Editorial Note: Heat health risk assessment analysing heatstroke patients in Fukuoka City, Japan

Hybrid strategy improved dung beetle optimization algorithm based 2D kapur entropy image segmentation method

Burnout in primary healthcare providers: A cross-sectional study from Al-Khobar, Saudi Arabia

Aim Job burnout is one of the emerging challenges in the healthcare sector which caused various issues among the primary healthcare providers. Hence, the present study was designed to evaluate the prevalence of burnout among the healthcare workers working in the primary healthcare clinics situated in the Alkhobar, Eastern Region of Saudi Arabia. Methods The study was also aimed to evaluate the associated factors related to the burnout. This cross-sectional study included 114 healthcare providers working in the different primary health care centers. Maslach Burnout Inventory (MBI) was used to evaluate the burnout among the respondents. Results The other questions were included the demographics and clinical factors. It was found that the prevalence of the burnout was 21.1%. Emotional exhaustion was found significantly high among females compared to males and those who had monthly income less than 12K compared to those with more than 12K monthly income. Daily patient load was another factor causing emotional exhaustion among the respondents. Conclusion In conclusion, the feeling of depersonalization among the participants was found to be very high followed by emotional exhaustion. The identification of the contributing factors would help to reduce the prevalence. Some of those factors were socio-demographic related and some were related to work.

An innovative bis-allyl rhodanine robust red fluorophore for wide-range optical pH sensing with reversible and durable acidic–alkaline OFF/ON fluorescence

Abstract A sustainable, ultrasound-assisted approach for synthesizing a bis -rhodanine derivative (BR) was established using N -allylrhodanine and 5-bromo-2-hydroxyisophthalaldehyde, employing a recyclable glycerol/proline (2:1) deep eutectic solvent. Structural characterization was unequivocally confirmed by NMR, FT-IR, HRMS, and elemental analysis. The red donor–π–acceptor fluorophore (BR) was evaluated as a wide-range spectrofluorometric pH probe. At 5.0 µM, BR exhibits dual absorption maxima at 357 and 568 nm with high molar absorptivity, and a red emission band centered at 718 nm with a 149 nm Stokes shift. Fluorescence is reversibly governed by a protonation/deprotonation equilibrium: acidification (pH 6.5–1.0) quenches emission with strong linearity ( r  ≈ 0.998), whereas alkalinity (pH 8.5–12.0) stabilizes an ICT-favored emissive state and linearly sensitizes fluorescence ( r  ≈ 0.995). The signal stabilizes within ~ 30 s, remains durable under reversible cycling between the fluorescence OFF mode at pH 2.0 and the fluorescence ON mode at pH 10.5. Therefore, BR interestingly functions as a dual-regime fluorescent pH probe, exhibiting acid-induced quenching at low pH and base-induced sensitization at high pH, with an explicitly characterized near-neutral transition (pH 6.5–8.5) that bridges the two operating domains. Moreover, BR is highly selective to pH as it resists common ionic interferents. Finally, the developed BR-derived spectrofluorometric pH probe is validated for the assay of acidic and alkaline pH in real samples of tap and lake waters, as well as in fresh lemon and orange juices, with high accuracy (98.9–102.3% recovery) and precision (% RSD: 0.93–1.13%).

GraphTransDTI: A novel hybrid framework combining graph transformer and CNN-BiLSTM for enhanced Drug-Protein Interaction prediction

Drug-protein interaction (DTI) prediction is a pivotal step in the drug discovery and repurposing process, helping to minimize experimental costs and time. However, existing deep learning methods often face limitations in simultaneously capturing the spatial structure of drug molecules and the deep contextual correlation with protein sequences. To address this issue, we propose GraphTransDTI, a synergistic hybrid framework that integrates a Graph Transformer to represent drug graph structures, a CNN-BiLSTM network to encode protein sequence context, and a Cross-Attention mechanism to model cross-domain interactions. Comprehensive experiments on two benchmark datasets, KIBA and Davis, across three rigorous scenarios: random splits, cold drug splits, and cold target splits demonstrate that GraphTransDTI achieves competitive performance compared to current state-of-the-art baseline models. Our findings confirm that the strategic combination of graph structural information and sequential attention mechanisms significantly enhances prediction accuracy and robustness in cold-start scenarios, offering a reliable and well-validated approach for high-precision virtual drug screening systems.