Confidence score calculation for the carcinogenic potency categorization approach (CPCA) predictions for N-nitrosamines

Pathologists’ perspective on the study design, analysis, and interpretation of proliferative lesions in a lifetime rodent carcinogenicity bioassay of sucralose

Introduction: Recent studies reveal deficiencies in educating women about stroke. The vast majority of stroke education is presented as gender neutral or with a male bias. This study examined if a computer-based, gender-specific education program (HER-Stroke) increased women’s awareness of stroke signs and symptoms. Methods: This 2-phase prospective study with 2-week follow-up examined gender-specific education based on Knowles’ Theory, enrolled 225 women with at least one stroke risk factor from any inpatient setting or neurology outpatient setting. Phase I, 75 women received standard stroke education (Group A). Phase II, 150 women randomized to standard (Group B) vs HER-Stroke education (Group C). Knowledge is scored as the percent of questions answered correctly; confidence is the percent of questions attempted; and accuracy is percent correct of those attempted. Results: Mean age was similar for Group A, B, C (54.4, 57.9, 52.5 years) respectively. There were no statistically significant differences in mean knowledge scores comparing groups A B and C: (69.4%, 71.6%, 69.0%; p=0.67), mean confidence scores for groups A, B, and C respectively (80.8%, 83.2%, 80.2%; p=0.77), or mean accuracy scores for group A B and C (86.2%, 85.6%, 85.0%; p=0.75). Regression analysis revealed that older age was associated with lower knowledge scores (p<.001) and lower confidence scores (p<.001). After controlling for age, the intervention was associated with a statistically significant difference in knowledge and confidence (p<.001). Conclusions: Enhanced efficacy among younger participants may reflect experience and comfort using technology. While the intervention was not associated with a change in overall scores, after controlling for age there was a statistically significant difference among groups. Further research including unmeasured covariates is needed to explore optimal stroke education formats for older learners.

Accurately identifying drug-target interactions (DTIs) is a critical step in drug discovery. While structure-based drug design methods demonstrate impressive docking prediction accuracy, their heavy computational demands and resource intensive nature make them impractical for directly processing vast chemical spaces containing a large number of compounds. This limitation highlights the need for a computational tool that balance speed and accuracy to rank and filter potential drug candidates efficiently. In contrast, existing ligand-based drug design methods, which learn representations from diverse protein and molecule features, often fail to make consistent predictions on unseen data or external databases, limiting their applicability for ranking and filtering potential drug candidates accurately. To address these challenges, we propose EnsDTI, a novel framework that bridges the gap between structure-based and ligand-based drug design approaches. EnsDTI utilizes a mixture-of-experts architecture to enhance DTI predictions using existing deep learning models and incorporates an inductive conformal predictor to assess prediction quality with confidence scores, ensuring reliability. Experimental results on four widely used benchmark datasets show that EnsDTI consistently achieves high performance in both prediction accuracy and confidence estimation. In addition, its candidate rankings correlate well with actual docking affinities, suggesting its practical utility in drug discovery. The source code and datasets are publicly available at https://github.com/solanoon/EnsDTI.

Quantitative structure–activity relationship (QSAR) methods have been widely applied in drug discovery, lead optimization, toxicity prediction, and regulatory decisions. Despite major advances in algorithms and software, QSAR models have inherent limitations associated with a size and chemical-structure diversity of the training set, experimental error, and many characteristics of structure representation and correlation algorithms. Whereas excellent fit to the training data may be readily attainable, often models fail to predict accurately chemicals that are outside their domain of applicability. A QSAR’s utility and, in the case of regulatory decisions, justification for usage increasingly depend on the ability to quantify a model’s potential for predicting unknown chemicals with some known degree of certainty. It is never possible to predict an unknown chemical with absolute certainty. Here we report on two QSAR models based on different data sets for classification of chemicals according to their ability to bind to the estrogen receptor. The models were developed by using a novel QSAR method, Decision Forest, which combines the results of multiple heterogeneous but comparable Decision Tree models to produce a consensus prediction. We used an extensive cross-validation process to define an applicability domain for model predictions based on two quantitative measures: prediction confidence and domain extrapolation. Together, these measures quantify the accuracy of each prediction within and outside of the training domain. Despite being based on large and diverse training sets, both QSAR models had poor accuracy for chemicals within the domain of low confidence, whereas good accuracy was obtained for those within the domain of high confidence. For prediction in the high confidence domain, accuracy was inversely proportional to the degree of domain extrapolation. The model with a larger training set of 1,092, compared with 232 for the other, was more accurate in predicting chemicals at larger domain extrapolation, and could be particularly useful for rapidly prioritizing potential endocrine disruptors from large chemical universe.

Mental toughness is a psychological construct related to successful performance in academics, management, and sports among other sectors. However, studies on the determinants of mental toughness with respect to different human endeavours have remained inconclusive. This study explored mental toughness characteristics of male university athletes in selected sports in relation to contextual factors of athletes’ age, playing experience, year of study, and the type of sport. The Mental Toughness Questionnaire (MTQ48) was used to collect data from male university athletes (n = 140). Results of this study showed significant difference in the following components of MT: lower scores in challenge (p = .015), emotional control (p = .005), and life control (p = .002) among athletes with shorter playing experience, and higher scores in life control (p < .001), emotional control (p = .021), and confidence in abilities (p = .009) in handball as compared to soccer players. Soccer players had significantly higher scores in the challenge component (p = .038) of mental toughness as compared to handball players. It was concluded that playing experience and the type of sport influenced characteristics of mental toughness among university athletes. Coaches, trainers, and sports psychologists need to consider these contextual factors to optimize mental toughness of athletes. Future studies should explore how specific contextual factors influence training environments and outcomes, as well as how stakeholders can leverage on the relationships between playing experience, the type of sport and mental toughness to augment athletes’ mental toughness and sports performance.

The challenge pays off: Early enhanced nutritional intake for VLBW small-for-gestation neonates improves long-term outcome

All members of the Oxa1/Alb3/YidC family have been implicated in the biogenesis of respiratory and energy transducing proteins. In Escherichia coli, YidC functions together with and independently of the Sec system. Although the range of proteins shown to be dependent on YidC continues to increase, the exact role of YidC in insertion remains enigmatic. Here we show that YidC is essential for the insertion of subunit K of the NADH:ubiquinone oxidoreductase and that the dependence is due to the presence of two conserved glutamate residues in the transmembrane segments of subunit K. The results suggest a model in which YidC serves as a membrane chaperone for the insertion of the less hydrophobic, negatively charged transmembrane segments of NuoK.

Study question What is the relationship between qualitative and quantitative morphokinetic parameters automatically annotated using CHLOE(Fairtility), an AI-based tool? Summary answer CHLOE score is associated with ploidy. DUC embryos have lower blastulation, form fewer good blastocysts, have increased fragmentation, slower development, lower implantation than non-DUCs. What is known already The introduction of time-lapse technologies in IVF has led to the discovery of quantitiative and qualitative morphokinetic parameters which are predictive of embryo viability (ESHRE Workshop group, 2020). The challenges of annotating videos manually remain: (i)operator variation, (ii)time-consuming; (iii)complexity of how to prioritise numerous features when determining which embryos to transfer, freeze or discard. CHLOE (Fairtility) is an AI-based tool designed to automatically capture these parameters from the time-lapse videos, removing the “black box” associated with AI, and, instead, bringing transparency and support to the embryologist responsible for the decision, thus, enhancing personalisation of care down to each individual embryo. Study design, size, duration Prospective cohort analysis on time-lapse data retrospectively collected at a single private fertility clinic in Spain between 2018-2020. 693 videos were automatically annotated (without training) using the CHLOE Artificial Intelligence (AI) tool for the following quantitative features: tPNa,tPNf,t2,t3,t4,t5,t6,t7,t8,t9,tM,tsB,tB,teB, size of ICM; and the following qualitative parameters: number of pronucleates, morphological quality of Inner Cell Mass and Trophectoderm (CHLOE Morphological scoring), identification of unusual embryo cleavages i.e. Direct Uneven Cleavage (DUCs), amongst other features. Participants/materials, setting, methods All embryos were cultured using the Embryoscope (Vitrolife) incubator. Using a range of algorithms, CHLOE generated a prediction of blastulation (at 30hpi) and implantation which were compared to outcome (blastocysts vs non-blastocysts; euploids vs Aneuploids&amp;Mosaics; Mosaics vs euploids&amp;aneuploids). Embryos identified as DUCS by CHLOE were compared with non-DUCs in terms of outcomes and in terms of endpoints generated by CHLOE (parametric continuous data assessed using 2-tail t-test, categorical data using chi-square). Main results and the role of chance Within all cleaved embryos analysed (n = 693), 29% were DUCs. DUC embryos were less likely to blastulate (DUCvsNonDUCs: 25vs50%,p&amp;lt;0.001), had a higher proportion of embryos with severe fragmentation (26% vs 3%,p&amp;lt;0.001), less likely to be suitable for biopsy (23vs87%, p &amp;lt; 0.001) lower blastulation prediction score (0.53vs0.76,p&amp;lt;0.001), lower implantation prediction score (0.21vs0.48,p&amp;lt;0.001) and slower embryo development across the all morphokinetic time-points assessed(p &amp;lt; 0.001), except for t5 (NS); than non-DUCs. DUCs and non-DUCs had similar proportion of 1,2,3PNs(5,83,5%vs 7,84,3%, NS). Within embryos that blastulated (n = 581), 25% were DUCs. DUC blastocysts were less likely to have a good quality ICM (7vs33%,p&amp;lt;0.001) or a good quality trophectoderm (9vs35%,p&amp;lt;0.05), lower implantation score (0.29vs0.52,p&amp;lt;0.05) and slower embryo development across the following morphokinetics time-points than non-DUC blastocysts. DUCs (n = 38) and non-DUC (n = 292) blastocysts had similar euploidy rate (50vs43%,NS), mosaicism rate (8vs11%,NS), and similar ratio of Euploids:Aneuploid:Mosaics (19:16:3vs126:133:33, NS). One DUC embryo was transferred, leading to an ongoing clinical pregnancy. Blastulation score was predictive of blastulation (AUC of 0.91, p &amp;lt; 0.001). Mosaic embryos had similar implantation score to non-mosaics (0.61vs0.67, NS). Euploid embryos had a higher implantation score than aneuploid blastocysts (0.71bs0.62, p &amp;lt; 0.02), so implantation score was predictive of ploidy. Limitations, reasons for caution This study involved the validation of (i) a specific AI based tool which may not be generalised across other AI tools; (ii) in a single centre. Results obtained did not involve training, suggestive of CHLOE’s ability to generalise across clinics. Presenting a framework for responsibly incorporating AI into clinical practice. Wider implications of the findings CHLOE can simplify the processing of time-lapse data to effectively, consistently, and efficiently quantify parameters that can help explain a comprehensive prediction of embryo viability. This provides a useful tool which will ultimately assist clinicians with selecting the most optimal embryos for transfer and avoid wastage from discarding viable embryos. Trial registration number not applicable

The prime aim of this research was to determine both demotivating and motivating factors for Pakistani college students of Quetta in learning English language. A quantitative design was employed in which 150 freshman college students studying in three different disciplines: Pre-medical, Pre-engineering and I.C.S at Government Girls college students of Quetta, Pakistan were included. A demotivation questionnaire was adopted from the study by Sakai &amp; Kikuchi(2009) consisting of one open-ended question and 35 close-ended items on six factors of demotivation: grammar-based teaching, teacher’s behaviour, course contents and teaching materials, effects of low test score, classroom environment and lack of self-confidence and interest. Additionally, a modified 20-items AMTB motivation questionnaire along with one open-ended question was adapted from the study by Gardner (1985) which identifies the integrative and instrumental motivation. The closed ended questionnaire was analyzed applying descriptive statistics in SPSS (version, 22) whereas content analysis was performed on narrative data extracted from open-ended questionnaire and was quantified to establish the order and rank of factors causing motivation and demotivation among students in learning English language. The findings revealed that course content and teaching material emerged as the most salient demotivating factor. On the other hand, instrumental motivation emerged as the most influential source of motivation among students. The findings have implication on both teaching and learning of English language in Pakistan.

BackgroundChanging family practice (voluntary disenrollment) without changing address may indicate dissatisfaction with care. We investigate the potential to use voluntary disenrollment as a quality indicator for primary care.MethodsData from the English national GP Patient Survey (2,169,718 respondents), the number of voluntary disenrollments without change of address, data relating to practice characteristics (ethnicity, deprivation, gender of patients, practice size and practice density) and doctor characteristics were obtained for all family practices in England (n = 8450). Poisson regression analyses examined associations between rates of voluntary disenrollment, patient experience, and practice and doctor characteristics.ResultsMean and median rates of annual voluntary disenrollment were 11.2 and 7.3 per 1000 patients respectively. Strongest associations with high rates of disenrollment were low practice scores for doctor-patient communication and confidence and trust in the doctor (rate ratios 4.63 and 4.85). In a fully adjusted model, overall satisfaction encompassed other measures of patient experience (rate ratio 3.46). Patients were more likely to move from small practices (single-handed doctors had 2.75 times the disenrollment rate of practices with 6–9 doctors) and where there were other local practices. After allowing for these, substantial unexplained variation remained in practice rates of voluntary disenrollment.ConclusionFamily practices with low levels of patient satisfaction, especially for doctor patient communication, are more likely to experience high rates of disenrollment. However substantial variation in disenrollment rates remains among practices with similar levels of patient satisfaction, limiting the utility of voluntary disenrollment as a performance indicator for primary care in England.

Previous studies have shown that asthma is a risk factor for lung cancer, while the mechanisms involved remain unclear. We attempted to further explore the association between asthma and non-small cell lung cancer (NSCLC) via bioinformatics analysis. We obtained GSE143303 and GSE18842 from the GEO database. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) groups were downloaded from the TCGA database. Based on the results of differentially expressed genes (DEGs) between asthma and NSCLC, we determined common DEGs by constructing a Venn diagram. Enrichment analysis was used to explore the common pathways of asthma and NSCLC. A protein-protein interaction (PPI) network was constructed to screen hub genes. KM survival analysis was performed to screen prognostic genes in the LUAD and LUSC groups. A Cox model was constructed based on hub genes and validated internally and externally. Tumor Immune Estimation Resource (TIMER) was used to evaluate the association of prognostic gene models with the tumor microenvironment (TME) and immune cell infiltration. Nomogram model was constructed by combining prognostic genes and clinical features. 114 common DEGs were obtained based on asthma and NSCLC data, and enrichment analysis showed that significant enrichment pathways mainly focused on inflammatory pathways. Screening of 5 hub genes as a key prognostic gene model for asthma progression to LUAD, and internal and external validation led to consistent conclusions. In addition, the risk score of the 5 hub genes could be used as a tool to assess the TME and immune cell infiltration. The nomogram model constructed by combining the 5 hub genes with clinical features was accurate for LUAD. Five-hub genes enrich our understanding of the potential mechanisms by which asthma contributes to the increased risk of lung cancer.

The emergence of ICT-enhanced communication has played a significant role in shaping the mode of behavior, emotional involvement, and self-observed competence within the organizational context. The proposed method is an AI sentiment analysis system that would analyze text-based interactions of emails, chat, and meeting minutes to gauge the effect on employee self-efficacy. The architecture has a combination of BERT to capture the contextual meaning and GRU to track the emotion sequentially. It handles more than 25,000 labeled messages of organizations and derives the sentiment polarity, the confidence scores as well as engagement behavior. The proposed model uses a self-efficacy prediction score of 0.84 and has its accuracy level in sentiment classification standing at <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{9 3. 4 \%}$</tex>. Positive sentiment makes up <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{4 1. 9}$</tex> percent of all communications with a strong relationship to the higher selfefficacy indices and quicker response to tasks. The system also brings down emotional misclassification relative to past procedures. The technology based on this AI concept can allow organizations to track employee morale in real-time and preventively address emotional states and performance with smart insights of ICT communication.

Although many Clinical Practice Guidelines (CPGs) have been published for the care of patients with Cystic Fibrosis (CF), including a variety of nutrition recommendations, the quality of these CPGs has never been evaluated. The aim of this study was to compare, review, and critically appraise CPGs for the nutritional management of CF, throughout the lifespan. We searched PubMed, Guidelines International Network (GIN), ECRI Institute, and Guidelines Central for CPGs, with information on the nutritional management of CF. Retrieved CPGs were appraised by three independent reviewers, using the Appraisal of Guidelines, Research and Evaluation II (AGREE II) instrument and checklist. A total of 22 CPGs (seven solely nutrition oriented), by 14 different publishers, were retrieved. The Thoracic Society of Australia and New Zealand CPGs scored the highest overall quality (94.4%), while the Paediatric Gastroenterology Society/Dietitians Association of Australia CPGs had the lowest score (27.8%). Great variation in AGREE II domain-specific scores was observed in all CPGs, suggesting the existence of different strengths and weaknesses. Despite the availability of several CPGs, many appear outdated, lacking rigor, transparency, applicability, and efficiency, while incorporating bias. Considering that CPGs adherence is associated with better outcomes and the need for improving life expectancy in patients with CF, the development of CPGs of better quality is deemed necessary.

CMV infection associated with severe lung involvement and persistent pulmonary hypertension of the newborn (PPHN) in two preterm twin neonates

A young patient had serious hematochezia for nearly 2 months without obvious cause. Abdominal CT images showed rare features such as serious hemorrhage and multiple miliary nodules in the small bowel. The colonoscopy showed multiple lymphoid follicles in the terminal ileum. The laparotomy showed adverse adhesion in the abdominal cavity and multiple miliary noduli in the surfaces of small bowel wall. The pathology suggested tuberculosis. This patient received anti-TB therapy and the condition improved gradually. There are many variants of GI tuberculosis demonstrating uncommon and rare imaging features. It turned to be difficult in diagnosis when it showed the rare appearance, such as the great amount of intestinal bleeding and multiple noduli in our case. The reason why gastrointestinal bleeding might be attributed to the invasiveness of submucosal vessels by the tuberculosis bacteria. And the multiple noduli on the bowel wall might be the granuloma formation. Therefore, from the experience of our case, gastrointestinal tract might also be the first and only involved site, and it may cause great amount of bleeding to a life danger, even in young people.