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Development of a clinical predictive score for allergic reactions during oral food challenges in pediatric patients

Background The oral food challenge (OFC) is the gold standard for diagnosing food allergies; but, it carries risks ranging from mild to life-threatening reactions, including anaphylaxis. Understanding and predicting these reactions is critical for safe clinical practice. Objectives This study aimed to develop and validate a clinically predictive score for allergic reactions during OFCs in pediatric patients. Methods Using a retrospective database of pediatric patients undergoing OFCs at a pediatric outpatient clinic in Southern Thailand from January 2014 to December 2022, a multivariable predictive model was developed. Data on the reaction rates, demographics, and treatments were collected. Logistic regression analysis with predictor selection using a backward stepwise approach, was employed. The model’s performance was assessed using the area under the receiver operating characteristic curve (ROC), calibration, and classification measures. Results This study included 179 patients with an allergic reaction incidence of 12.3%. Predictors encompassed female, anaphylaxis and positive skin prick testing. The developed model achieved an ROC of 0.71. The patients were categorized into the low-risk (score 0–1) and high-risk (score 2–3) groups. Reaction rates during the OFCs were 6.7% in the low-risk group and 29.5% in the high-risk group. Conclusions Our scoring model demonstrated predictive ability for OFC reactions in pediatric patients, offering valuable insights for clinical risk assessment.

Exploring Erythrina flavonoids as potential SARS-CoV-2 RdRp inhibitors through virtual screening, in silico ADMET evaluation, and molecular dynamics simulation studies

Abstract The COVID-19 pandemic, caused by SARS-CoV-2, has intensified the search for effective antiviral agents. This study investigates the inhibitory potential of 473 flavonoids from the genus Erythrina against the key enzyme of SARS-CoV-2, RNA-dependent RNA polymerase (RdRp). Virtual screening campaign using molecular docking identified 128 flavonoids with stronger binding energies to RdRp than remdesivir, a WHO-endorsed drug. Lipinski’s Rule of Five and ADMET profiling suggested butein (119) as the promising RdRp inhibitor. Moreover, molecular dynamics simulations revealed that 119 binds effectively to RdRp and interacts with the RNA template and primer, suggesting a multi-faceted inhibitory mechanism. Our findings highlight the potential of Erythrina-derived flavonoids, particularly compound 119, as potent RdRp inhibitors, warranting further experimental studies.

Dispositional goal orientation and perceptions of coach motivational climate on attitudes towards doping among Kenyan endurance runners

Changing athletes’ attitudes towards doping has been shown as crucial in prevention efforts in combating doping in sports, with dispositional goal orientation and perceptions of coach motivational climate identified as factors shaping doping attitudes among athletes. The purpose of this study was to examine the relationships between dispositional goal orientation and motivational climate on attitudes towards doping among Kenyan Endurance runners. A cross-sectional survey design was used to collect data from 323 Kenyan runners with 215 males (66.6%) and 108 females (33.3%). The study assessed athletes’ goal orientation through the Task and Ego Goal Orientation Sport Questionnaire, perceptions of coach motivational climate through Perceived Motivational Climate in Sport Questionnaire, and attitudes towards doping through Performance Enhancement Attitude Scale. Descriptive statistics, correlation analysis, Mann-Whitney U tests and Kruskal-Wallis H tests was used for data analysis. The study found significant inverse relationships between mastery climate and doping attitudes (rho = -.242; p <.001), as well as between task orientation and doping attitudes (rho = -.158; p <.004). Conversely, performance climate (rho =.362; p <.001) and ego orientation (rho =.362; p <.001) showed significant positive relationships with doping attitudes. There were no significant differences in doping attitudes based on age (U = 11582.500, p <.191), gender (U = 11437.500, p <.827) and athlete’s length of experience (χ2 (2) = 1.359, p <.507). The study concludes that fostering mastery-oriented coach motivational climate and promoting task-oriented goal orientation could effectively cultivate anti-doping attitudes among athletes and enhance clean sport.

Rising public costs of preterm infant hospitalization in South Korea from a nationwide observational study

Microfinance institutions failure prediction in emerging countries, a machine learning approach

This study is about what matters: predicting when microfinance institutions might fail, especially in places where financial stability is closely linked to economic inclusion. The challenge? Creating something practical and usable. The Adjusted Gross Granular Model (ARGM) model comes here. It combines clever techniques, such as granular computing and machine learning, to handle messy and imbalanced data, ensuring that the model is not just a theoretical concept but a practical tool that can be used in the real world.Data from 56 financial institutions in Peru was analyzed over almost a decade (2014–2023). The results were quite promising. The model detected risks with nearly 90% accuracy in detecting failures and was right more than 95% of the time in identifying safe institutions. But what does this mean in practice? It was tested and flagged six institutions (20% of the total) as high risk. This tool’s impact on emerging markets would be very significant. Financial regulators could act in advance with this model, potentially preventing financial disasters. This is not just a theoretical exercise but a practical solution to a pressing problem in these markets, where every failure has domino effects on small businesses and clients in local communities, who may see their life savings affected and lost due to the failure of these institutions. Ultimately, this research is not just about a machine learning model or using statistics to evaluate results. It is about giving regulators and supervisors of financial institutions a tool they can rely on to help them take action before it is too late when microfinance institutions get into bad financial shape and to make immediate decisions in the event of a possible collapse.

Assessment of untreated and vermifiltration treated pharmaceutical industrial effluent in fish Channa punctata using biochemical, histopathological, ultrastructural and ATR-FTIR analysis

Infertility misperception and improper health-seeking behavior between urban and rural areas

Objectives The prevalence of infertility among reproductive-age couples in Indonesia is around 10-15%. Lack of understanding, misleading myths, and negative attitudes could result in improper behavior. This study aims to reveal the discrepancy between perception and behavior towards infertility in urban and rural areas in Indonesia. Materials and methods A cross-sectional study using an internet-based questionnaire was given to 408 individuals, divided into two groups, Java and outside Java, representing urban and rural populations. The study included Indonesian citizens over 18 who were willing to participate, encompassing individuals of both genders, regardless of their fertility status. All participants completed the questionnaire from October 2020 to April 2021. Results Half of the respondents from both groups consider infertility a disease. All respondents have excellent access to information. Although more than 80% of subjects from each group had been exposed to infertility information, a better understanding was observed in the urban community. Most subjects answered that smoking is the leading risk factor for infertility, followed by stress and advanced age. More respondents in rural areas have the wrong perception that stress causes infertility. Furthermore, they seek unwarranted advice, as 19.5% came to midwives and only 9.1% came to general practitioners. This study showed that 35.6% of subjects in the urban group and 41.6% in the rural group are considered late to seek healthcare assistance. Most respondents from both groups accept using Assisted Reproductive Technology and fertility-enhancing drugs as treatment options. Conclusion Infertility misconceptions are more prevalent in rural groups than in urban groups. Fertility education among both groups needs to be improved to optimize the chance of conceiving and having a healthy baby.

Associations between plasma and urinary heavy metal concentrations and the risk of prostate cancer

BRCA2 prevents PARPi-mediated PARP1 retention to protect RAD51 filaments

Study on the driving force of seasonal changes of soil erosion in Lulang-Tongmai section of Sichuan-Tibet Highway

In the context of global climate change, the section of the Sichuan-Tibet Highway from Lulang to Tongmai has become a focal point for soil erosion research due to its unique geographical location and complex natural environment. Studies have shown that between 2000 and 2023, soil erosion intensity in this area has decreased. However, erosion intensity increases from southwest to northeast, with particularly severe erosion near the Tongmai Grand Bridge and Polong Gou Grand Bridge. Correlation analysis reveals a significant positive correlation between rainfall and soil erosion, while vegetation cover is positively correlated with erosion in the short term but contributes to reduced erosion over the long term. Geodetector analysis indicates that the main driving factors vary by season. In spring, summer, and autumn, temperature and precipitation are the primary drivers, with driving forces of 0.78 and 0.75, 0.80 and 0.78, and 0.75 and 0.73, respectively. In winter, temperature and elevation are the dominant factors, with driving forces of 0.63 and 0.42. The interaction between temperature, precipitation, and other factors significantly influences soil erosion, particularly in spring and summer, where the interaction driving force exceeds 0.75. These findings provide both theoretical support and decision-making guidance for soil erosion control along the Sichuan-Tibet Highway.

Maturation of human induced pluripotent stem cell-derived cardiomyocytes promoted by Brachyury priming

Definer: A computational method for accurate identification of RNA pseudouridine sites based on deep learning

Pseudouridine is an important modification site, which is widely present in a variety of non-coding RNAs and is involved in a variety of important biological processes. Studies have shown that pseudouridine is important in many biological functions such as gene expression, RNA structural stability, and various diseases. Therefore, accurate identification of pseudouridine sites can effectively explain the functional mechanism of this modification site. Due to the rapid increase of genomics data, traditional biological experimental methods to identify RNA modification sites can no longer meet the practical needs, and it is necessary to accurately identify pseudouridine sites from high-throughput RNA sequence data by computational methods. In this study, we propose a deep learning-based computational method, Definer, to accurately identify RNA pseudouridine loci in three species, Homo sapiens, Saccharomyces cerevisiae and Mus musculus. The method incorporates two sequence coding schemes, including NCP and One-hot, and then feeds the extracted RNA sequence features into a deep learning model constructed from CNN, GRU and Attention. The benchmark dataset contains data from three species, H. sapiens, S. cerevisiae and M. musculus, and the results using 10-fold cross-validation show that Definer significantly outperforms other existing methods. Meanwhile, the data sets of two species, H. sapiens and S. cerevisiae, were tested independently to further demonstrate the predictive ability of the model. In summary, our method, Definer, can accurately identify pseudouridine modification sites in RNA.

Hemosiderin quantification in hemophilic arthropathy using quantitative magnetic resonance imaging

Abstract The goal of this study is to quantify hemosiderin deposition in the knee joint tissues of hemophilic arthropathy (HA) patients using quantitative susceptibility mapping on MRI. Knee synovial tissues from HA patients and controls without hemophilia were included. The tissues underwent ultrashort echo time quantitative susceptibility mapping (UTE-QSM) and clinical MRI. HA tissues were processed histologically with Perl’s Prussian Blue (PPB) staining to identify iron contents. Seven regions of interest were drawn in each tissue, and the susceptibility values were tested. Moreover, the association between the estimated magnetic susceptibility and the iron contents quantified by histology was investigated. Nine synovial tissues were procured from total knee arthroplasty of hemophilia patients (males, 40.8 ± 9.0 years), and three synovial tissues were harvested from cadaveric knee joints of donors without hemophilia as controls (males, 72.0 ± 12.8 years). The estimated susceptibility values (ESVs) showed significant differences between HA and control samples. Accordingly, HA tissues presented a mean ESV of 0.48 ± 1.08 ppm and control tissues of -0.13 ± 0.12 ppm (p < 0.05). A significant linear correlation was found between the iron level quantified by histology (PPB stain) and the ESV estimated by UTE-QSM (R = 0.908, p < 0.01). There was a significant difference in the susceptibility in high load (HL) tissues compared to low load (LL) tissues (ESV = 5.57 ± 1.23 ppm for HL vs. 0.57 ± 0.85 ppm for LL, p < 0.001). Reliable hemosiderin quantification in joint tissues of HA patients can be achieved using MRI based on quantitative susceptibility mapping.

The impact of a school garden program on children’s food literacy, climate change literacy, school motivation, and physical activity: A study protocol

Objective FoodACT aims to investigate how school gardens affect children’s food literacy (FL), climate change literacy (CCL), school motivation (SM), and physical activity (PA). Design It comprises a multimethod, quasi-experimental inquiry into an existing Danish school garden program, Gardens to Bellies (GtB). Data will be collected using surveys, accelerometry, semi-structured and focus-group interviews. The study is preregistered with ClinicalTrials.gov (#NCT05839080). Setting Six GtB school garden locations across Region Zealand and Region of Southern Denmark. Participants Fourth grade pupils attending GtB (approx. 1600) are recruited to the intervention group. Fourth grade pupils from schools not attending GtB (approx. 1600) are recruited to the control group. Intervention Pupils grow, prepare and cook foods for meals in the school garden during eight garden sessions. Main outcome measures FL, CCL and SM are measured using pre- and post-intervention surveys in both groups. Pupils participating in GtB have their PA assessed using accelerometery, and acute SM by text-message-surveys. Semi-structured and focus-groups interviews are held with garden facilitators and pupils focusing on the implementation of GtB and mechanisms related to developing FL and CCL. Analysis The effect on FL, CCL and SM is assessed using linear mixed models. PA and acute SM are assessed by comparing data on days with and without GtB in a subsample of 900 pupils. Qualitative data will be analysed using thematic analysis.

Sustainable subgrade improvement with calcium carbide residue and rice husk ash

Intelligent anti-jamming communication technology with electromagnetic spectrum feature cognition

Against the backdrop of the rapid development of wireless communication technology, the complex signal interference issues in the electromagnetic spectrum environment have become a key factor affecting the quality and reliability of signal transmission. Existing solutions, such as traditional interference suppression techniques that rely on static spectrum allocation and fixed interference patterns, are no longer able to adapt to the rapidly changing electromagnetic environment and face computational complexity challenges when processing large amounts of real-time data. This study proposes an intelligent anti-interference algorithm that combines deep neural networks and game theory, and constructs a model based on near-end strategy optimization. By extracting and processing signal features through deep neural networks, and dynamically adjusting communication strategies with near-end optimization, the model effectively addresses the recognition and prediction of signal transmission feature parameters in target communication systems, generates interference signals with the same feature parameters, and achieves effective interference suppression. Experiments show that the proposed model achieves an accuracy rate of 95.23% in identifying interference signals and an anti-interference accuracy rate of 85.47%, significantly outperforming random forest and deep Q-network models. The study not only clarifies the limitations of existing solutions but also precisely defines the goals of the new model, which are to reduce error rates and improve adaptability in dynamic environments. The results further explain the significance of the used metrics and test conditions, providing new means and strategies for the development of anti-interference communication technology, especially in dealing with new complex electromagnetic spectrum interference.

Phylogeny and evolutionary dynamics of the Rubia genus based on the chloroplast genome of Rubia tibetica

Collaborative metabolic curation of an emerging model marine bacterium, Alteromonas macleodii ATCC 27126

Inferring the metabolic capabilities of an organism from its genome is a challenging process, relying on computationally-derived or manually curated metabolic networks. Manual curation can correct mistakes in the draft network and add missing reactions based on the literature, but requires significant expertise and is often the bottleneck for high-quality metabolic reconstructions. Here, we present a synopsis of a community curation workshop for the model marine bacterium Alteromonas macleodii ATCC 27126 and its genome database in BioCyc, focusing on pathways for utilizing organic carbon and nitrogen sources. Due to the scarcity of biochemical information or gene knock-outs, the curation process relied primarily on published growth phenotypes and bioinformatic analyses, including comparisons with related Alteromonas strains. We report full pathways for the utilization of the algal polysaccharides alginate and pectin in contrast to inconclusive evidence for one-carbon metabolism and mixed acid fermentation, in accordance with the lack of growth on methanol and formate. Pathways for amino acid degradation are ubiquitous across Alteromonas macleodii strains, yet enzymes in the pathways for the degradation of threonine, tryptophan and tyrosine were not identified. Nucleotide degradation pathways are also partial in ATCC 27126. We postulate that demonstrated growth on nitrate as sole nitrogen source proceeds via a nitrate reductase pathway that is a hybrid of known pathways. Our evidence highlights the value of joint and interactive curation efforts, but also shows major knowledge gaps regarding Alteromonas metabolism. The manually-curated metabolic reconstruction is available as a “Tier-2” database on BioCyc.

Fractional order modeling of hepatitis B virus transmission with imperfect vaccine efficacy

The impact of wide step width on lower limb coordination and its variability in individuals with flat feet

Flat foot is a common condition marked by the collapse of the medial longitudinal arch, leading to altered lower limb biomechanics and increased risk of musculoskeletal injuries. We aimed to investigate if wide step width changes the lower limb inter-joint coordination and its variability in flat feet individuals. Twenty flat-footed individuals participated in this cross-sectional study. Lower limb kinematics were assessed by 3-dimensional motion analysis during walking and running on a treadmill with preferred and wide step widths while receiving visual feedback. Inter-joint coordination was quantified using vector-coding for joint angles in the hip, knee, and ankle. Wide walking showed a shift towards proximal joint motion in sagittal ankle-knee coordination during loading response during LR (p=0.006), an In-phase motion in transverse ankle-hip coordination during push-off (p=0.004), and an In-phase pattern in frontal knee-hip coordination during mid-stance (p=0.027). Frontal ankle and transverse knee coordination during push-off changed to In-phase (p=0.003). Wide running significantly shifted frontal ankle-hip coordination towards proximal joint motion during mid-stance (p=0.05). Transverse ankle-hip coordination showed an in-phase pattern in wide conditions during push-off (p=0.044), during LR (p=0.022). Wide walking, significantly increased coordination variability of the sagittal ankle-knee during LR and decreased transverse ankle-hip during push-off. Wide walking significantly increased coordination variability in ankle-knee in sagittal plane during LR (p<0.001). Wide running significantly decreased the coordination variability in the ankle-knee sagittal during LR (p<0.001) and knee-hip sagittal during LR (p=0.007) and push-off (p=0.016). The results showed that wide step width can affect inter-joint coordination during walking/running in flat-footed individuals at certain points. These results should be considered when using a wide step width as a gait retraining method for managing flat-footed individuals.