BACKGROUND: Brazil is one of the countries with the highest rates of caesarean sections (CS), reaching almost 90% of births in the private sector. A quality improvement project called \"Adequate Childbirth Project (PPA)\" was conceived to reduce CS in the private sector. This project consisted of four primary components: \"Governance\", \"Participation of Women\", \"Reorganization of Care\" and \"Monitoring\". This paper aims to evaluate: (1) which specific activities of the PPA had the largest effect on the probability of a woman having a vaginal delivery; (2) which primary component of the PPA had the largest effect on the probability of vaginal delivery and (3) which scenarios combining the implementation of different activities planned in the PPA had a higher effect on the probability of vaginal delivery.
METHODS: A sample of 12 private hospitals participating in the PPA was evaluated. We used a Bayesian Network (BN) to capture both non-linearities and complex cause-effect relations. The BN integrated knowledge from experts and data from women to estimate 26 model parameters. The PPA was evaluated in 2473 women belonging to groups 1-4 of the Robson classification, who were divided into two groups: those participating or not participating in the PPA.
RESULTS: The probability of a woman having a vaginal delivery was 37.7% higher in women participating in the PPA. The most important component of the project that led to an increase in the probability of vaginal delivery was \"Reorganization of Care\", leading to a 73% probability of vaginal delivery among women in labor. The activity that had the greatest effect on the type of delivery was access to best practices during labor, with a 72% probability of vaginal delivery. Considering the 12 scenarios combining the different activities of the PPA, the best scenarios included: a non-scheduled delivery, access to information about best practices, access to at least 4 best practices during labor and respect of the birth plan, with an 80% probability of vaginal delivery in the best combinations.
CONCLUSIONS: PPA has been shown to be an effective quality improvement program, increasing the likelihood of vaginal delivery in private Brazilian hospitals.
BACKGROUND: Brazil boasts one of the highest rates of caesarean sections (CS) globally, with nearly 90% of births in private facilities being delivered via CS. In response, the \'Adequate Childbirth Project – PPA\' was launched as a quality improvement initiative aimed at curbing CS rates in private healthcare. Its goal is to improve the quality of childbirth and reduce the number of CS in private healthcare. The project has four main parts: \'Governance\', \'Participation of Women\', \'Reorganization of Care\', and \'Monitoring\'.
METHODS: an evaluative study was conducted across 12 private hospitals involved in the PPA, involving 2473 women who were categorized into PPA participants and non-participants. They used a method called a cause-effect network to see which parts of the PPA helped more women have vaginal deliveries.
RESULTS: They found that women in the PPA were 37.7% more likely to have a vaginal delivery. Giving women access to good practices during labor and birth was really important. Also, \'Reorganization of Care\' was the most important part of the project. It led to a 73% chance of vaginal delivery for women in labor.
CONCLUSIONS: The PPA is effective in helping more women in private hospitals have vaginal deliveries. This means it\'s a good program for improving childbirth in Brazil\'s private hospitals.

BACKGROUND: Persons with dementia in nursing homes often experience cognitive decline (e.g., memory and visuospatial/construction problems), behavioural and psychological symptoms of dementia (BPSD), and impaired activities of daily living. Therefore, comprehensive interventions for this population are needed. We assessed whether a multimodal non-pharmacological intervention improved cognitive functions, BPSD, and activities of daily living in persons with dementia in nursing homes.
METHODS: This was a multicentre randomised controlled trial. Participants were 40 persons with dementia (38 women) living in four nursing homes (intervention group = 21; control group = 19). The intervention was conducted for 8 weeks, followed by an 8-week follow-up. Outcome measures were scores on the Japanese version of the Neurobehavioral Cognitive Status Examination Five and the ABC Dementia Scale. In the analysis, parameters were estimated using Bayesian statistics and a mixed-effects linear regression model for the change in each outcome measure.
RESULTS: There were significant between-group differences in changes in ABC Dementia Scale BPSD scores (8-week: posteriori median = 1.66, 95% Bayesian confidence interval 0.36-3.01; 16-week: median = 2.37, 95% Bayesian confidence interval 0.05-4.65). There was also a significant between-group difference in changes in Neurobehavioral Cognitive Status Examination Five constructional ability scores (16-week: median = 0.93, 95% Bayesian confidence interval 0.35-1.50).
CONCLUSIONS: This intervention may have a maintenance and improvement effect on BPSD in persons with dementia in nursing homes, and a sustained effect on constructional ability post-intervention. The intervention may be useful and easy to apply in practice.

European bat lyssavirus 1 (EBLV-1, Lyssavirus hamburg) is predominantly detected in serotine bats (Eptesicus serotinus) and is responsible for the majority of bat rabies cases in mainland Europe. A passive bat rabies surveillance scheme detected the virus in a serotine bat in the UK for the first time in October 2018. As of May 2024, 34 cases have been reported, 20 of which involved contact with an animal and 5 reported human contact. We investigated the emergence of EBLV-1 by undertaking comprehensive sequence analysis and Bayesian phylogenetics, based on complete virus genomes of 33 UK sequences and 108 sequences covering six countries in mainland Europe (1968-2023), including 21 French EBLV-1-positive RNA samples sequenced for this study. Sequence analysis revealed extreme similarity among UK EBLV-1 sequences (99.9%-100%), implying a single source of introduction rather than multiple independent introductions. Bayesian analysis revealed that the UK EBLV-1 sequences shared their most recent common ancestor with an EBLV-1 sequence from a serotine bat detected in Brittany, France, in 2001, with an estimated date of divergence of 1997. Within the UK sequences, the earliest divergence was estimated to occur in 2007. This study provides valuable insights into the molecular epidemiology of an emerging zoonotic pathogen and improved understanding of the risks posed to public and animal health.

BACKGROUND: Understanding the multifaceted nature of attractiveness (A), which encompasses physical beauty (PB), genuineness (GEN), self-confidence (SC), and prior experience (RE), is crucial for various domains, including psychology and clinical aesthetics. Previous studies have often isolated specific elements, failing to capture their intricate interplay. This study aims to develop a comprehensive equation for attractiveness using computational neuroaesthetics.
METHODS: The study began with a pilot study involving 250 participants (50 experts and 200 laypersons) who prerated 500 facial images on a Likert scale for traits such as physical beauty, genuineness, self-confidence, and perceived prior experience. Following the pilot, the main study recruited 11,780 participants through diverse media channels to rate a new set of 1,000 facial images. Advanced computational techniques, including multiple linear regression and Bayesian hierarchical modelling, were employed to analyse the data and formulate an attractiveness equation.
RESULTS: The analysis identified genuineness as the most significant factor, followed by physical beauty, self-confidence, and prior experience. The proposed equation for attractiveness, refined through Bayesian modelling, is: A = β 0 + ( β 1 · PB + β 2 · GEN + β 3 · SC + β 4 · PE ) + ϵ A = 1.82 + ( 0.34 · PB + 0.44 · GEN + 0.26 · SC + 0.16 · PE ) + ϵ (β0 is the intercept; β1, β2, β3, β4 are the coefficients for each factor; and ϵ is the error term) CONCLUSION: The findings underscore the paramount importance of psychological traits in attractiveness assessments, suggesting a shift from purely physical enhancements to holistic interventions in clinical settings. This model provides a robust framework for understanding attractiveness and has potential applications in psychology, marketing, and AI.
METHODS: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

The identification and classification of carcinogens is critical in cancer epidemiology, necessitating updated methodologies to manage the burgeoning biomedical literature. Current systems, like those run by the International Agency for Research on Cancer (IARC) and the National Toxicology Program (NTP), face challenges due to manual vetting and disparities in carcinogen classification spurred by the volume of emerging data. To address these issues, we introduced the Carcinogen Detection via Transformers (CarD-T) framework, a text analytics approach that combines transformer-based machine learning with probabilistic statistical analysis to efficiently nominate carcinogens from scientific texts. CarD-T uses Named Entity Recognition (NER) trained on PubMed abstracts featuring known carcinogens from IARC groups and includes a context classifier to enhance accuracy and manage computational demands. Using this method, journal publication data indexed with carcinogenicity & carcinogenesis Medical Subject Headings (MeSH) terms from the last 25 years was analyzed, identifying potential carcinogens. Training CarD-T on 60% of established carcinogens (Group 1 and 2A carcinogens, IARC designation), CarD-T correctly to identifies all of the remaining Group 1 and 2A designated carcinogens from the analyzed text. In addition, CarD-T nominates roughly 1500 more entities as potential carcinogens that have at least two publications citing evidence of carcinogenicity. Comparative assessment of CarD-T against GPT-4 model reveals a high recall (0.857 vs 0.705) and F1 score (0.875 vs 0.792), and comparable precision (0.894 vs 0.903). Additionally, CarD-T highlights 554 entities that show disputing evidence for carcinogenicity. These are further analyzed using Bayesian temporal Probabilistic Carcinogenic Denomination (PCarD) to provide probabilistic evaluations of their carcinogenic status based on evolving evidence. Our findings underscore that the CarD-T framework is not only robust and effective in identifying and nominating potential carcinogens within vast biomedical literature but also efficient on consumer GPUs. This integration of advanced NLP capabilities with vital epidemiological analysis significantly enhances the agility of public health responses to carcinogen identification, thereby setting a new benchmark for automated, scalable toxicological investigations.

Eating behaviors are influenced by the integration of gustatory, olfactory, and somatosensory signals, which all contribute to the perception of flavor. Although extensive research has explored the neural correlates of taste in the gustatory cortex (GC), less is known about its role in encoding thermal information. This study investigates the encoding of oral thermal and chemosensory signals by GC neurons compared to the oral somatosensory cortex. In this study, we recorded the spiking activity of more than 900 GC neurons and 500 neurons from the oral somatosensory cortex in mice allowed to freely lick small drops of gustatory stimuli or deionized water at varying non-nociceptive temperatures. We then developed and used a Bayesian-based analysis technique to assess neural classification scores based on spike rate and phase timing within the lick cycle. Our results indicate that GC neurons rely predominantly on rate information, although phase information is needed to achieve maximum accuracy, to effectively encode both chemosensory and thermosensory signals. GC neurons can effectively differentiate between thermal stimuli, excelling in distinguishing both large contrasts (14°C vs. 36°C) and, although less effectively, more subtle temperature differences. Finally, a direct comparison of the decoding accuracy of thermosensory signals between the two cortices reveals that while the somatosensory cortex showed higher overall accuracy, the GC still encodes significant thermosensory information. These findings highlight the GC\'s dual role in processing taste and temperature, emphasizing the importance of considering temperature in future studies of taste processing.

OBJECTIVE: Is there an association between women\'s body mass index (BMI) and the gender of offspring generated from fresh or frozen-thawed embryo transfer (FET) cycles?
METHODS: Between 2018 and 2021, 2670 cycles were performed, comprising 786 fresh embryo transfers and 1884 FET cycles. The study analysed the relationship between the BMI of women undergoing IVF and the sex of the newborn and the male-to-female live birth ratio (secondary sex ratio [SSR]).
RESULTS: After 2670 single-embryo transfers, 483 (50.31%) male and 477 (49.69%) female infants were born, with an SSR of 101.3. In the fresh embryo transfer group, the SSR ranged from 350 (95% CI 82.67-1481.65) in underweight women (although this was based on very small numbers) to 109.7 (95% CI 67.73-176.61) in overweight women, while in the FET group, SSR values varied correspondingly from 130.8 (95% CI 64.47-265.26) to 63.0 (95% CI 46.02-86.24). Results from Bayesian multinomial logistic regression showed that for each unit increase in BMI within the fresh embryo transfer group, the odds of a boy\'s birth decreased by 6% (odds ratio [OR] 0.94, 95% CI 0.90-0.99) and the odds of a girl\'s birth by 5% (OR 0.95, 95% CI 0.90-0.99). Within the FET cohort, the odds of a boy\'s birth decreased by 4% (OR 0.96, 95% CI 0.92-0.99), while the odds of a girl\'s birth increased by 3% (OR 1.03, 95% CI 1.00-1.06).
CONCLUSIONS: An increase in BMI is associated with the birth of fewer boys in fresh or frozen embryo transfer cycles, and a significant increase in the birth of girls in FET cycles.

BACKGROUND: The disease management program (DMP) for type 2 Diabetes Mellitus (T2DM) is the largest DMP in Germany. Our goal was to analyze regional differences in unenrollment rates, suggest areas for intervention and provide background information, which population groups in which locations are currently not enrolled in the DMP for T2DM.
METHODS: In this study, we used data of the 1.7 mil. insurants of the AOK Nordost health insurance. For the visualization of enrollment potential, we used the Besag-York-Mollie model (BYM). The spatial scan statistic (SaTScan) was used to detect areas of unusually high rates of unenrolled diabetics to prioritize areas for intervention. To explore sociodemographic associations, we used Bayesian spatial global regression models. A Spatially varying coefficient model (SVC) revealed in how far the detected associations vary over space.
RESULTS: The proportion of diabetics currently not enrolled in the DMP T2DM was 36.8% in 2019 and varied within northeastern Germany. Local clusters were detected mainly in Mecklenburg-West-Pomerania and Berlin. The main sociodemographic variables associated with unenrollment were female sex, younger age, being unemployed, foreign citizenship, small household size and the proportion of persons commuting to work outside their residential municipality. The SVC model revealed important spatially varying effects for some but not all associations.
CONCLUSIONS: Lower socioeconomic status and foreign citizenship had an ubiquitous effect on not being enrolled. The DMP T2DM therefore does currently not reach those population groups, which have a higher risk for secondary diseases and possible avoidable hospitalizations. Logically, future interventions should focus on these groups. Our methodology clearly suggests areas for intervention and points out, which population group in which locations should be specifically approached.

The objective of the study was to estimate genetic parameters of the growth traits under Bayesian inference in Harnali sheep. The information of pedigree and targeted traits of 2404 Harnali animals born to 159 sires and 695 dams was collected for the period from 1998 to 2021. The growth traits included weight at birth (BWT), 3 (WWT), 6 (6WT) and 12 (YWT) months of age. The genetic evaluation was carried out using six univariate animal models comprising direct and maternal effects using THRGIBBS1F90 and POSTGIBBSF90 programs. The fixed factors adjusted in the analysis were period of birth, sex of lamb and dam\'s weight at lambing. Bayesian estimates of direct heritability under best model for BWT, WWT, 6WT and YWT traits were 0.16 ± 0.04, 0.10 ± 0.04, 0.18 ± 0.04, and 0.05 ± 0.03, respectively. The significant maternal influences observed for BWT and WWT traits with 9% and 8% contribution to total phenotypic variances, respectively. Additionally, maternal permanent environmental influences were observed to BWT (4%) and YWT trait (3%). The genetic and phenotypic correlations among studied traits were high and positive. The genetic changes were positive and significant for WWT only. It was concluded that the weight at 6 months of age can be continued as selection criterion for further genetic improvement through selection. Also, maternal effects should be considered in breeding programme for enhancing early growth performance in Harnali sheep.

Psychological capital (PsyCap) constitutes a positive personal resource that enhances better well-being and academic performance in university students. Initially addressed in the organizational realm and recently in the academic one. This study aimed to establish the differences in PsyCap according to gender and age in Peruvian university students. A quantitative, comparative, non-experimental, and cross-sectional study was conducted with 708 students (77.4 % women and 22.6 % men), aged between 18 and 61 years (M = 22.1; SD = 5.95), selected in a non-probabilistic manner, who completed the Psychological Capital Questionnaire (PCQ-12). The results indicate very strong evidence supporting the existence of significant differences between different age groups, suggesting that the observed variations are not due to chance but reflect real differences between ages. Regarding gender, the data do not provide enough information to confidently assert whether there are significant differences between men and women in relation to psychological capital (PsyCap) and its dimensions. This implies that we cannot confirm whether gender influences these variables. These findings highlight the need to consider age when assessing and intervening in PsyCap in university students.