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Association of eosinophil major basic protein with intraocular lens dislocation in atopic dermatitis
Assessing newborn scoring with each resuscitation (ANSWER): Protocol for identifying and testing an Apgar score for the 21st century
Background The status of infants in the minutes after birth has been summarized by the Apgar score for the last 70 years and is applied at most medically attended deliveries around the world. It has not, however, adapted to changes in neonatal resuscitation over the decades. There are issues with application to premature newborns, how to account for the interventions outlined in the Newborn Resuscitation Program (NRP), inter-rater reliability, and local custom. Developing a modern newborn assessment score will require a series of steps, the first of which is to identify which observations or data can best differentiate a normal newborn transition from an abnormal one. Methods Video recordings of at least 35 random normal (meeting NRP goals for heart rate and saturation without intervention, normal physical exam and requiring only normal postnatal care) and 35 random abnormal (not meeting at least 2 normal criteria) from 7 centers participating in the VERIFI study. The presence or absence of observable elements, including vital signs, appearance, and interventions will be recorded every 30 seconds for the first 5 minutes of life. Observations, as well as any changes over time or after intervention will be compared between normal and abnormal, and those that are significant and independent based on logistic regression will become candidate newborn assessment score components. Expected results There are likely to be ten or more observations/elements from videos of the first five minutes of life that will differ between normal and abnormal newborns, and these will be tested in all combinations to identify the 1–3 score sets that will be applied to a new set of VERIFI videos to identify which has the best sensitivity/specificity. Conclusions Bringing newborn assessment into modern practice will build on the legacy of Dr. Apgar. A series of steps, beginning with identifying the observations/elements that best identify newborns who may need further care can lead to a universal validated tool for the 21st century.
Comprehensive bioinformatics analysis of MEX3 family genes in hepatocellular carcinoma
Association between lipid accumulation product and endometriosis: A cross-sectional study from NHANES 1999–2006
The association of lipid accumulation product (LAP) and the likelihood of endometriosis prevalence has not been previously mentioned. The research aimed to assess the possible potential association between LAP and endometriosis in nationwide research. This cross-sectional analysis was conducted on 2,216 participants selected from the National Health and Nutrition Examination Survey (NHANES) in the 1999–2006 cycles. Logistic regression and stratified analysis by age, race, level of education, BMI, marital status, PIR, glycohemoglobin, drinking, and smoking status were used to analyze the association of the LAP index and odds of endometriosis prevalence. Moreover, smoothed curve fitting was used to evaluate the relevancy of LAP and endometriosis. The multivariate logistic regression model showed a positive association between ln LAP and endometriosis. This trend remained after a full adjustment (odds ratio = 1.37, 95% confidence interval:1.08–1.75, P = 0.010). Compared to the minimum ln LAP quartile, participants in the highest ln LAP had a 93% higher chance of endometriosis incidence (odds ratio = 1.93, 95% confidence interval: 1.08–3.46, P = 0.027). After conducting subgroup analysis and interaction testing, it was found that this positive association was most prominent among women aged 35 years and above and participants with glycohemoglobin≥6%. This nationwide study suggested that an elevated ln LAP was related to an increased endometriosis prevalence. Therefore, LAP may be a valuable tool for predicting the occurrence of endometriosis. Follow-up studies are critical to assess the association between LAP and odds of endometriosis prevalence and explain the potential mechanisms of this relationship.
Acute effects of isometric conditioning activity with different distribution contraction on countermovement jump performance in resistance trained participants
Publisher Correction: irCLIP-RNP and Re-CLIP reveal patterns of dynamic protein assemblies on RNA
Influence of sinker timing on loop shape, width and areal density of weft-knitted cotton plain jersey fabric
This study aims to explore the influence of sinker timing—a relative positional setting of two primary knitting elements, i.e., needle and sinker, on some important knitted fabric parameters and related properties. Plain jersey fabric samples were produced from cotton yarn (linear density of 19.68 Tex) at three different quality values (loop lengths of 2.77 mm, 2.84 mm, and 2.90 mm respectively) on a positive feed-based multi-feeder circular knitting machine. Three different sinker timings (regular, forwarding, and retracting) were used for each quality setting; thus, a total of 9 (nine) fabric samples were developed for experimental purposes. It was found that forward sinker timing resulted in an increase in the loop shape factor concerning regular sinker timing and vice versa. However, stitch densities were almost the same for all settings of sinker timing at a particular value of loop length. Consequently, fabric width was highest for forward timing and fabric areal density remained almost unchanged. Also visual inspection revealed no noticeable differences among the fabric samples.
Hemodialysis pathway types influence wound healing complications and survival in end-stage renal disease patients in a retrospective cohort study
Abstract This study evaluates the impact of different hemodialysis access types—central venous catheter (CVC), arteriovenous graft (AVG), and autologous arteriovenous fistula (AVF)—on wound healing, complication rates, and long-term survival in patients with end-stage renal disease (ESRD). A retrospective analysis of 323 ESRD patients receiving hemodialysis over a ten-year period revealed significant differences in outcomes across the three groups. AVF patients experienced the shortest wound healing times and the highest dialysis efficacy, while the CVC group had the highest infection and reoperation rates. Although there were no significant differences in cardiac function or cause-specific mortality, AVF patients had the longest median survival time, followed by those in the CVC and AVG groups. These findings suggest that while AVF provides superior dialysis efficiency and survival outcomes with fewer complications, patient suitability and individual health conditions must be carefully considered when selecting the appropriate vascular access for hemodialysis.
Socioecological benefits of academic greenspace for human health, plant, and pollinator diversity: A mixed-method study protocol
Introduction Significant risks to the health of humans and ecosystems are posed by environmental pollution, urban warming, and fragmentation, which are primary urban factors that contribute to the deterioration of urban ecosystems. The purpose of this multidisciplinary study is to compare greenspaces in university campuses and the host cities in order to assess how valuable they are for promoting human and ecosystem health in Nigeria. Methods Mixed-methods research that will be conducted in five tertiary institutions and their host cities in southwestern Nigeria. Based on the objectives, the study is divided into four work packages (WP). WP 1 will use suitable sampling traps and scheduled field observations to quantify the diversity of plants and pollinators. Quantitative evaluation of well-being and mental health will be done in WP 2. In WP 3, the relationship between ecosystem health and mental health will be examined and in-depth interviews will be used to explore the socioecological perceptions and interaction of people with specific indicators of ecosystem health in greenspace. In WP 4, a nature-based intervention will be developed and evaluated in a pilot study to determine its feasibility and acceptability. Results The 2023 TETFund National Research Fund Intervention provided funding for this work, which is currently ongoing and results are not yet available. Conclusion This project will provide scientific knowledge to support evidence-based policy for relevant stakeholders and regulatory organisations, with the goal of promoting greenspace infrastructure in Nigerian tertiary institutions. This article is focused on describing the research design, as the study is currently on-going hence, there is no conclusion yet.
End-to-end Chinese clinical event extraction based on large language model
Integrating multimodal imaging and peritumoral features for enhanced prostate cancer diagnosis: A machine learning approach
Background Prostate cancer is a common malignancy in men, and accurately distinguishing between benign and malignant nodules at an early stage is crucial for optimizing treatment. Multimodal imaging (such as ADC and T2) plays an important role in the diagnosis of prostate cancer, but effectively combining these imaging features for accurate classification remains a challenge. Methods This retrospective study included MRI data from 199 prostate cancer patients. Radiomic features from both the tumor and peritumoral regions were extracted, and a random forest model was used to select the most contributive features for classification. Three machine learning models—Random Forest, XGBoost, and Extra Trees—were then constructed and trained on four different feature combinations (tumor ADC, tumor T2, tumor ADC+T2, and tumor + peritumoral ADC+T2). Results The model incorporating multimodal imaging features and peritumoral characteristics showed superior classification performance. The Extra Trees model outperformed the others across all feature combinations, particularly in the tumor + peritumoral ADC+T2 group, where the AUC reached 0.729. The AUC values for the other combinations also exceeded 0.65. While the Random Forest and XGBoost models performed slightly lower, they still demonstrated strong classification abilities, with AUCs ranging from 0.63 to 0.72. SHAP analysis revealed that key features, such as tumor texture and peritumoral gray-level features, significantly contributed to the model’s classification decisions. Conclusion The combination of multimodal imaging data with peritumoral features moderately improved the accuracy of prostate cancer classification. This model provides a non-invasive and effective diagnostic tool for clinical use and supports future personalized treatment decisions.
An improved artificial potential field with RRT star algorithm for autonomous vehicle path planning
Navigational health literacy and health service use among higher education students in Alentejo, Portugal - A cross-sectional study
Introduction The navigational health literacy of higher education students is fundamental to effective health management and successful health navigation, thereby improving health outcomes and overall well-being. Assessing the general and navigational health literacy levels of these students is crucial for developing targeted interventions and facilitating informed decision-making on health-related issues. This study aimed to identify the levels of general and navigational health literacy, characterise access to and utilisation of healthcare services, and analyse the differences between the mean general and navigational health literacy indices and determinants among higher education students in the Alentejo region of southern Portugal. Methodology A descriptive and cross-sectional study was conducted between 25 May and 12 September 2023 with 1979 higher education students. An online structured questionnaire comprising the Portuguese version of the European Health Literacy Survey Questionnaire – 16 items (HLS-EU-PT-Q16) and the Navigational Health Literacy Scale (HLS19-NAV), both from the European Consortium, was used. Sociodemographic data, presence of chronic disease, perceived health status, perceived availability of money for expenses, and healthcare access and utilisation variables were included. The study data were analysed using independent samples t-test, one-way ANOVA, and post hoc Bonferroni test, followed by multiple linear regression analyses at a significance level of 0.05. Multiple linear regression analysis was performed to identify factors associated with both general and navigational health literacy. The study protocol was approved by the ethics committee of the University of Évora, and all participants provided written informed consent. Results Most students (86.8%) exhibited limited general health literacy, while 13.2% demonstrated adequate health literacy. Inadequate navigational health literacy was observed in 73.4% of students. Students with lower mean general and navigational health literacy were more likely to have utilised health services. Students with chronic conditions, recent use of urgent or emergency services, and difficulties in accessing healthcare had lower health literacy. Conversely, those enrolled in health-related courses, those with good financial resources and those who had not used health services during their course had higher health literacy. In addition, lower navigational health literacy was found among displaced students, those with chronic conditions and those who had recently consulted a doctor. Higher navigational health literacy was associated with enrolment in health-related courses and adequate general health literacy. Conclusion The findings highlight the significant influence of demographic and academic factors on general and navigational health literacy among higher education students. The prevalence of limited general and navigational health literacy underscores a significant challenge for students, institutions, and health policy makers. Effective health literacy interventions should take these factors into account. Future research should examine longitudinal changes in health literacy and evaluate the impact of targeted educational programmes.
fNIRS experimental study on the impact of AI-synthesized familiar voices on brain neural responses
Investigating the Key Trends in Applying Artificial Intelligence to Health Technologies: A Scoping Review
Background The use of Artificial Intelligence (AI) is exponentially rising in the healthcare sector. This change influences various domains of early identification, diagnosis, and treatment of diseases. Purpose This study examines the integration of AI in healthcare, focusing on its transformative potential in diagnostics and treatment, and the challenges and methodologies. shaping its future development. Methods The review included 68 academic studies retracted from different databases (WOS, Scopus and Pubmed) from January 2020 and April 2024. After careful review and data analysis, AI methodologies, benefits and challenges, were summarized. Results The number of studies showed a steady rise from 2020 to 2023. Most of them were the results of a collaborative work with international universities (92.1%). The majority (66.7%) were published in top-tier (Q1) journals and 40% were cited 2–10 times. The results have shown that AI tools such as deep learning methods and machine learning continue to significantly improve accuracy and timely execution of medical processes. Benefits were discussed from both the organizational and the patient perspective in the categories of diagnosis, treatment, consultation and health monitoring of diseases. However, some challenges may exist, despite these benefits, and are related to data integration, errors related to data processing and decision making, and patient safety. Conclusion The article examines the present status of AI in medical applications and explores its potential future applications. The findings of this review are useful for healthcare professionals to acquire deeper knowledge on the use of medical AI from design to implementation stage. However, a thorough assessment is essential to gather more insights into whether AI benefits outweigh its risks. Additionally, ethical and privacy issues need careful consideration.
SpectroFusionNet a CNN approach utilizing spectrogram fusion for electric guitar play recognition
An unexpected diversity of powdery mildew species infecting the Fabaceae in Australia
The Fabaceae family has been reported to host more than fifty species of powdery mildew worldwide. Despite being commonly found on fabaceous hosts throughout Australia, the accurate identification of many powdery mildew species remains uncertain. The objective of this study was to identify powdery mildew species that naturally occur on fabaceous hosts in Australia and provide insight into those native and weedy species that may host crop pathogens and contribute to disease in cropping systems. The ribosomal DNA internal transcribed spacer (ITS) sequences and morphology of 34 fresh and 40 herbarium powdery mildew specimens infecting diverse Fabaceae species in Australia were characterised in this study. Altogether, a total of eleven powdery mildew species were identified from 51 Fabaceae species. Podosphaera xanthii was the most common powdery mildew in this study and was detected on 18 host species across ten genera. Ten species of Erysiphe were confirmed on 37 host species covering 17 host genera, with E. diffusa and E. cf. trifoliorum the most prevalent. This work provides the most comprehensive catalogue of powdery mildew species infecting legume hosts throughout Australia.
ITGAV, a specific biomarker associated with the pathogenesis of idiopathic pulmonary fibrosis
Customizing egg incubators for Cameroon: A design and construction guide
In Cameroon, poultry farming represents an important source of income for many families and is a key sector for economic development and food security. However, there is a deficiency in suitable infrastructure, especially high-performance and affordable incubators, leading many poultry farmers to resort to manual incubation techniques, which are often inefficient and labor-intensive. This paper aims to build an automatic incubator using locally accessible materials, optimized techniques, and modern, simple technologies. This paper also serves as a construction guide. Its initiative offers a significant opportunity to improve poultry farming practices, increase local productivity, and contribute to sustainable development. The incubator is built using the prototyping method, and the optimization of energy efficiency for the system was achieved through the mathematical modeling of heat transfer. The study’s findings indicate that the incubator is a dependable and effective solution for hatching poultry eggs. Its user-friendly design, ease of maintenance, and affordability make it an excellent choice for local poultry farmers.