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Message framing materials applied to healthy eating decision-making for pregnant women with gestational diabetes mellitus: An exploratory study

Aims To develop and initially validate message framing materials for promoting healthy dietary decisions in GDM populations. Methods The Delphi survey involved 17 experts, and consensus was obtained after two rounds. In Pre-survey I, 30 participants randomly selected one material (gain framing vs. loss framing) and complete a manipulation check item to ensure that the stimulus material manipulation was valid. Pre-survey II involved 60 participants who rated all messages using a Likert 5 rating questionnaire, a Wilcoxon signed rank sum test was used to examine the message framing effects. Results After two rounds of Delphi surveys, experts reached consensus on the final materials, which contained two message framings, each containing 11 entries. The manipulation test for materials achieved 100% validity. The findings indicated significant message framing effects on healthy eating decisions among GDM populations, with loss-framed messages proving more persuasive. Conclusion Scientifically valid message framing materials were developed and initially applied, providing an empirical basis and direction for future related research.

Impact of formal credit and social capital on the scalability of agricultural operations

Combined immunoinformatic approaches with computational biochemistry for development of subunit-based vaccine against Lawsonia intracellularis

Lawsonia intracellularis (LI) are obligate intracellular bacteria and the causative agent of proliferative hemorrhagic enteropathy that significantly impacts the health of piglets and the profitability of the swine industry. In this study, we used immunoinformatic and computational methodologies such as homology modelling, molecular docking, molecular dynamic (MD) simulation, and free energy calculations in a novel three stage approach to identify strong T and B cell epitopes in the LI proteome. From ∼ 1342 LI proteins, we narrowed our focus to 256 proteins that were either not well-identified (unknown role) or were expressed at a higher frequency in pathogenic strains relative to non-pathogenic strains. At stage 1, these proteins were analyzed for predicted virulence, antigenicity, solubility, and probability of residing within a membrane. At stage 2, we used NetMHCPan4-1 to identify over ten thousand cytotoxic T lymphocyte epitopes (CTLEs) and 286 CTLEs were ranked as having high predicted binding affinity for the SLA-1 and SLA-2 complexes. At stage 3, we used homology modeling to predict the structures of the top ranked CTLEs and we subjected each of them to molecular docking analysis with SLA-1*0401 and SLA-2*0402. The top ranked 25 SLA–CTLE complexes were selected to be an input for subsequent MD simulations to fully investigate the atomic-level dynamics of proteins under the natural thermal fluctuation of water and thus potentially provide deep insight into the CTLE-SLA interaction. We also performed free energy evaluation by Molecular Mechanics/Poisson−Boltzmann Surface Area to predict epitope interactions and binding affinities to the SLA-1 and SLA-2. We identified the top five CTLEs having the strongest binding energy to the indicated SLAs (-305.6 kJ/mol, -219.5 kJ/mol, -214.8 kJ/mol, -139.5 kJ/mol and -92.6 kJ/mol, respectively.) W also performed B-cell epitope prediction and the top-ranked 5 CTLEs and 3 B-cell epitopes were organized into a multi-epitope subunit antigen vaccine construct joined using EAAAK, AAY, KK, and GGGGG linkers with 40 residues of the LI DnaK protein attached to the N-terminus to further enhance the antigenicity of the vaccine construct. Blind docking studies showed strong interactions between our vaccine construct with swine Toll-like receptor 5. Collectively, these molecular modeling and immunoinformatic analyses present a useful in silico protocol for the discovery of candidate antigen in many viral and bacterial pathogens.

Deciphering the prognostic impact of aberrant DNA methylation on ANGPT1 gene in breast cancer

Protective effects of psychiatric medications against COVID-19 mortality before vaccines

The coronavirus disease pandemic caused by the coronavirus SARS-CoV-2, which emerged in the United States in late 2019 to early 2020 and quickly escalated into a national public health crisis. Research has identified psychiatric conditions as possible risk factors associated with COVID-19 infection and symptom severity. This study aims to determine whether specific classes of psychiatric medications could reduce the likelihood of infection and alleviate the severity of the disease. The objective of this study is to investigate the relationship between neuropsychiatric medication usage and COVID-19 outcomes before the widespread utilization of COVID-19 vaccines. This cross-sectional study used Optum’s de-identified Clinformatics Data Mart Database to identify patients diagnosed with COVID-19 in 2020 and their psychiatric medication prescriptions in the United States. Ordered logistic regression was used to predict the likelihood of a higher COVID-19 severity level for long-term and new users. Results were adjusted for demographic characteristics and medical and psychiatric comorbidities. Most users were classified into the long-term user analysis group. Long-term users were 9% less likely to have a higher severity score (CI: 0.89–0.93, p-value < 0.001) than non-users. SSRI antidepressant users, both long-term (OR: 1.09; CI: 1.06–1.12) and short-term (OR: 1.17; CI: 1.07–1.27) were significantly more likely to have a lower severity score. However, the results varied across long-term and short-term users for all medication classes. Results of the current study suggest that psychopharmacological agents are associated with reduced COVID-19 severity levels and that antidepressant medications may have a protective role against COVID-19.

Analysis of critical 3D imaging data of surrounding cervical nerves and bone markers in spinal endoscopic surgery

Preoperative antihypertensives and hypotension during bladder tumor resection with oral 5-aminolevulinic acid administration

5-Aminolevulinic acid hydrochloride (5-ALA), a photodynamic diagnostic agent, visualizes bladder cancer. Previous research has indicated that preoperative intake of 5-ALA leads to a higher incidence of hypotension. Particularly in patients with hypertension, suggestions include discontinuing antihypertensive medications on the morning of surgery to prevent hypotension. However, the effects of antihypertensive drugs on hypotension in patients taking 5-ALA before surgery remains unexamined. We conducted a single-center observational study that included patients aged 20 and above who were regularly taking antihypertensives and underwent transurethral resection of bladder tumors (TURBT) after taking 5-ALA. Patients who took antihypertensives on the morning of surgery were defined as the continued group, whereas those who did not were defined as the discontinued group. Hypotension was defined as a mean blood pressure (MBP) of less than 65 mmHg for 20 min or longer. To adjust for confounding factors, we used propensity scores for inverse probability weighting and performed modified Poisson regression analysis to calculate risk ratios (RRs) and 95% confidence intervals (CIs). We analyzed 132 cases. The crude incidence of hypotension was higher in the continued group compared to the discontinued group (33/51 [64.7%] vs 38/81 [46.9%]; RR 1.38, 95% CI 1.01–1.88; p =  0.041). However, no significant difference was observed between groups after adjustment (RR 1.05, 95% CI 0.66–1.68). In conclusion, the adjusted results suggested no significant association between the continuation of antihypertensive medication and the incidence of intraoperative hypotension. No substantial justification was provided for routinely discontinuing antihypertensive medications.

Association between social media use, physical activity level, and depression and anxiety among college students: a cross-cultural comparative study

Result of reclamation of man-made dumps from phosphorite deposits in the semi-desert zone of Kazakhstan

Pollution from industrial activities, including heavy metal contamination, poses severe environmental challenges, especially in industrialized regions. This study evaluates reclamation efforts at the Kokzhon phosphorite deposit in Kazakhstan’s semi-desert zone, where over 67 million tons of industrial waste have accumulated across 3.3 thousand hectares. Reclamation efforts encompassed the treatment of 6,400 hectares using carbamide amendments and the planting of resilient phytomeliorants, including Russian Olive, Black Saxaul, Androsov Elm, and Salt Cedar. While tree survival rates were low (11%), herbaceous vegetation achieved remarkable success, with legumes and cereals attaining 95% growth rates. Herbaceous productivity increased from 2,200 kg/ha in 2013 to 3,300 kg/ha in 2018, alongside vegetation cover expanding from 60% to 80%. Soil fertility also improved significantly, with humus content rising from 0.18% in 2012 to 1.14% in 2023. Despite these improvements, the long-term impacts of industrial phosphorite mining continue to challenge ecosystem recovery. Over a 12-year period, reductions in humus content (47.6%) and herbaceous productivity (28.4%) have been observed, highlighting the need for enhanced soil management strategies to sustain reclamation outcomes. The results emphasize the potential of biological reclamation to restore degraded semi-desert ecosystems while underscoring the necessity of scalable, cost-effective solutions and long-term monitoring to mitigate ongoing environmental damage.

Evaluating the slope behavior for geophysical flow prediction with advanced machine learning combinations

Determinants of decision-making among ever-married women in Indian households: A cross-sectional study based on binary logistic regression and multinomial logistic regression

Empowerment of women is intrinsically linked to their participation in household decision-making, a crucial component for achieving gender equality and improving family well-being. Women’s decision-making is frequently cited as a proxy for empowerment and recognized as goal 5 of sustainable development goals. It remains a significant challenge in Indian households to achieve gender parity and poor concentration has been given in the studies of the Indian context. This study evaluates the types of decision-making among ever-married women in Indian households by investigating the socio-demographic factors that influence their role in household decisions. Utilizing data from the National Family Health Survey-5 (2019–21), which includes a sample of 51,758 women aged 15–49 years. This study employs a bivariate analysis to explore the association between predictive factors and women’s decision-making status. Before implementing a valid conclusion of multinomial logistic regression dealing with multinomial outcome variables, such as independent, joint, and dependent decisions, binary logistic regression was applied in the context of binary outcomes, specifically not making decisions alone and making decisions alone. Results reveal that only 3% of women make decisions independently. In contrast, 15% of women relied on dependently making decisions, and a majority of 82% of respondents reported jointly making decisions within their households. The conclusive model reveals that the likelihood of independent decision-making relative to joint decisions for rural women in India is 25% lower than for urban women, while dependent decision-making is 23% more often in rural areas than in urban ones as compared to jointly made decisions. Working women were 1.52 times more likely to make independent decisions, apart from that, the result indicates that 25% lower relative risk (RRR = 0.75, 95% CI = 0.69–0.81) of dependent decisions compared to joint ones. In contrast to the poorest households, women in the richest households are 42% less likely to make decisions independently as opposed to jointly. Regional variations are also evident, compared to women in northern regions, women from the South had the highest prevalence of independent decision-making power than joint decisions, with a relative risk ratio of 2.53 (RRR = 2.53, 95% CI= 2.04–3.14) and the lowest in central regions (RRR = 0.92, 95% CI= 0.73–1.17). Age emerges as a significant factor, compared to jointly making decisions, individuals in the age group of 35–45 have a relative risk ratio of 1.44 (RRR = 1.44, 95% CI= 1.18–1.77), and women over 45 years of 1.67 (RRR = 1.67, 95% CI=1.30–2.13) times greater autonomy than those in the age group below 25. Furthermore, compared to their counterparts who do not consume substances, women whose husbands do so have 1.44 (RRR = 1.44, 95% CI= 1.27–1.64) times higher probability of autonomy in making decisions relative to decisions made jointly. The study underscores the necessity for comprehensive educational programs, financial literacy workshops, improvement of transportation and healthcare decision-making, and region-specific cultural interventions among discriminatory castes by improving employment scenarios. Especially for rural women under the 25-age group can be a significant step in household decisions toward attaining gender equality.

Association of pan-immune inflammation value with mortality in patients with pulmonary embolism: a cohort study

How does round goby (Neogobius melanostomus) affect fish abundance in the Swedish coastal areas of the Baltic Sea?

Quantifying the effects of species invasions is particularly challenging, as it requires accurate measurements of the ecosystem before and after the invasion. The round goby (Neogobius melanostomus), a highly successful invasive species from the Ponto-Caspian region, has had significant ecological impacts on native communities in the invaded ecosystems. However, there are currently no studies examining the impact of the round goby invasion on the abundance of coastal fish in the Baltic Sea. Using 17–23 years of monitoring data from four areas, we quantified the changes in fish abundance (mostly representing coastal fish indicators and key coastal fish species) associated with the round goby invasion in the Swedish coastal areas. A generalized additive mixed model suggests that round goby invasion will lead to an increase in the abundance of perch, cyprinids, piscivores, and ruffe, while whitefish and flounder abundance will decrease. In addition, the abundance of sprat and herring may not be affected by round goby invasion. Abundance of perch, cyprinids, flounder, perch ( ≥20 cm total length), cod, pikeperch, and pike were increased with water temperature and were decreased with water depth and wave exposure. We observed a decreasing trend in the abundance of whitefish, sprat, and herring with an increase in water temperature and a decrease in water depth. Given the low abundance of several piscivorous species in the Baltic Sea and the role of predators to control exotic prey, reinforcing piscivore populations might be useful for the Baltic Sea ecosystem and regulating round goby populations at a local scale.

Bioprinting of mesenchymal stem cells in low concentration gelatin methacryloyl/alginate blends without ionic crosslinking of alginate

Abstract Bioprinting allows for the fabrication of tissue-like constructs by precise architecture and positioning of the bioactive hydrogels with living cells. This study was performed to determine the effect of very low concentrations of alginate (0.1, 0.3, and 0.5% w/v) on bioprinting of bone marrow mesenchymal stem cells (BMSC) in gelatin methacryloyl (GelMA; 5% w/v)/alginate blend. Furthermore, while GelMA was photocrosslinked in all bioprinted constructs, the effect of crosslinking alginate with calcium chloride on the physical and biological characteristics of the constructs was investigated. The inclusion of low-concentration alginate improved the viscosity and printability of the formulation as well as the compressive modulus of the hydrogels, particularly when ionically crosslinked with calcium chloride, compared with the group in that alginate was not crosslinked. However, the stability and degradability of 3D printed scaffolds that were only photocrosslinked were comparable to those that were additionally crosslinked with calcium chloride. Noteworthily, ionic crosslinking of alginate deteriorated the viability of BMSC. Morphology and growth of BMSC were improved by adding a low alginate concentration; however, ionic crosslinking of alginate affected these factors adversely. The findings of this study underscore the significance of carefully evaluating the crosslinking strategy used in conjunction with cell-laden GelMA/alginate hydrogel to achieve balanced physical and biological properties as well as less complicated post-bioprinting processing.

Advanced computational approaches for predicting sunflower yield: Insights from ANN, ANFIS, and GEP in normal and salinity stress environments

Prediction of crop yield is essential for decision-makers to ensure food security and provides valuable information to farmers about factors affecting high yields. This research aimed to predict sunflower grain yield under normal and salinity stress conditions using three modeling techniques: artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS), and gene expression programming (GEP). A pot experiment was conducted with 96 inbred sunflower lines (generation six) derived from crossing two parent lines, over a single growing season. Ten morphological traits—including hundred-seed weight (HSW), number of leaves, leaf length (LL) and width, petiole length, stem diameter, plant height, head dry weight (HDW), days to flowering, and head diameter—were measured as input variables to predict grain yield. Salinity stress was induced by applying irrigation water with electrical conductivity (EC) levels of 2 dS/m (control) and 8 dS/m (stress condition) using NaCl, applied after the seedlings reached the 8-leaf stage. The GEP model demonstrated the highest precision in predicting sunflower grain yield, with coefficient of determination (R2) values of 0.803 and 0.743, root mean squared error (RMSE) of 4.115 and 4.022, and mean absolute error (MAE) of 3.177 and 2.803 under normal conditions and salinity stress, respectively, during the testing phase. Sensitivity analysis using the GEP model identified LL, head diameter, HSW, and HDW as the most significant parameters influencing grain yield under salinity stress. Therefore, the GEP model provides a promising tool for predicting sunflower grain yield, potentially aiding in yield improvement programs under varying environmental conditions.

Alloferon and IL-22 receptor expression regulation on the pathogenesis of imiquimod-induced psoriasis

Does the inspiratory muscle warm-up have an acute effect on wrestling recovery performance?

This study aims to investigate the acute effects of inspiratory muscle warm-up (IMW) in young wrestlers. Wrestling is a high-intensity sport that demands anaerobic metabolism, with rapid recovery and endurance playing crucial roles in subsequent performance. Inspiratory muscle warm-up specifically targets the inspiratory muscles, reducing fatigue during exercise and helping to sustain performance. Our study compares three different warm-up protocols (traditional wrestling warm-up, wrestling warm-up (WWIW) +  IMW, and wrestling warm-up +  placebo (WWPL)) to analyse changes in inspiratory muscle strength and select respiratory function parameters. The study was conducted with 14 male wrestlers aged 15-16. Participants were subjected to the three different warm-up protocols, followed by simulated wrestling bouts. Results showed that the WWIW protocol increased maximal inspiratory pressure by 17.3% compared to the traditional and placebo warm-ups. Additionally, the WWIW protocol delayed fatigue and improved recovery rates among the wrestlers. Specifically, WWIW enabled a faster return to normal heart rate post-competition, accelerating the recovery process. These findings suggest that WWIW can be effectively used in high-intensity sports like wrestling to enhance recovery between matches and improve overall performance. Further studies with larger sample sizes and in different sports are recommended to validate these results.

Comprehensive analysis of lipid metabolic signatures identified CEBPD promotes breast cancer cell proliferation

Alternative perimetric tests for patients with drug-resistant epilepsy

Objective Visual field assessment is an important presurgical test for patients with drug-resistant epilepsy (DRE), particularly with posterior cortex epilepsy. However, the assessment using conventional perimeters like Humphrey Visual Field Analyzer (HFA) may not always be feasible in some patients. This study aims to determine if alternative methods like tangent screen perimetry or Baby Vision Screener (BaViS) can be used for such patients. Methods This retrospective study included 17 patients (mean age: 18 ±  8.7, range: 6 to 38 years) with DRE. Visual fields were attempted first with HFA and then with one or both alternative methods, by different examiners. Visual field extent was measured using the kinetic perimetry mode in the alternative methods. With HFA, kinetic and/or static perimetry was attempted. Results Only 12% of the patients were able to perform the HFA. Whereas the testability of BaViS was 91% and tangent screen perimetry was 87%. Comparable visual field isopters were obtained on one patient on whom all the 3 tests could be performed, and in two patients on whom at least two tests could be performed reliably. For one patient, visual field isopters could not be quantified on any device. In this patient, a gross visual field assessment was possible using BaViS. Conclusion BaViS or tangent screen perimeter can be used to quantify visual field defects in patients with DRE when conventional perimetry is not possible. Such an approach may help the clinician in assessing the suitability of patients with DRE and visual field deficits, for epilepsy surgery.

An assessment of machine learning methods to quantify blood lactate from neutrophils phagocytic activity

Abstract Phagocytosis is a critical component of innate immunity that helps the body defend itself against infection, foreign particles, and cellular debris. Investigating and quantifying phagocytosis can help understand how the immune system identifies foreign particles and how phagocytosis relates to other biomarkers, e.g., cytokines, cell surface receptors, or blood lactate levels. In particular, increased blood lactate levels can be a potential biomarker to study diseases, e.g., septic shock. Establishing a relationship between phagocytosis and lactate levels can serve as an effective tool to monitor the immune response and may help stratify patients. In this study, we use phagocytosis activity data to classify the patients into two groups of blood lactate levels (High and Low) with machine learning models. The neutrophils extracted from the whole blood samples of 19 patients were used to collect data on phagocytosis, where the neutrophils were allowed to internalize IgG coated fluorescent bioparticles. The data collection process involved collecting whole blood samples, neutrophil isolation, adding fluorescent beads, incubating, and imaging the sample using a fluorescence microscope. The phagocytosis assay images were used to generate a numerical dataset by manually counting the number of particles engulfed by each cell. The study first presents an improved understanding by employing hierarchical clustering and heatmaps to generate the graphical representation of phagocytosis data. By comparing the results of heat maps and clustering techniques, it can be observed that the phagocytosis activity data can be used to differentiate blood lactate levels in two groups (control and high-risk). Later, three machine learning models (Decision Tree, k-nearest Neighbor, and Naïve Bayes) were trained on the original and pruned datasets after the outliers were removed. The AI models classified the data into high-risk and low-risk groups of blood lactate levels. A maximum classification accuracy of 78% and an area under the curve of 0.78 was achieved using the trained models.