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The first complete hand-rearing of two neonatal finless porpoises
Hand-rearing of marine mammals is an essential technique for the husbandry of orphans in captivity or the wild, especially endangered cetacean species. The purpose of the present study was to establish a method for successful hand-rearing and evaluate the nutritional state of neonatal finless porpoises. Two neonate finless porpoises maternally neglected at 5 days of age (Day 5) (neonate A, animal A) and Day 4 (neonate B, animal B) were hand reared. The amount of each tube feeding and daily number of nursings for animals A and B during the lactation period were gradually increased to 1,355 and 1,120 ml and 16 and 14 times, respectively. The mean daily caloric intake during the lactation period and average increase in body weight of animals A and B were 2,048 ± 207 and 2,206 ± 169 kcal and 65.4 and 66.9 g/day, respectively. Hypoproteinemia and hypertriglyceridemia were observed in the two neonates during the early stage of hand-rearing. The plasma concentrations of 24 free amino acids in the neonatal porpoises were significantly higher compared with adult porpoises. Plasma valine, leucine, and isoleucine levels in the neonates were dramatically higher than those in adults. Hyperlipoproteinemia, characterized by a higher percentage of very-low-density lipoprotein and the appearance of midband, was also observed in the two neonates, along with hypertriglyceridemia. A hand-rearing method for finless porpoises was successfully established in this research. Nutritional evaluation of serum protein, free amino acids, and lipid components is needed to improve the survivability of hand-reared neonatal porpoises. The hand-rearing method established in the present study is an essential technique for the husbandry of finless porpoises and can be applied to the conservation of other members of the porpoise family, including vaquita and Yangtze finless porpoises, which are the most endangered dolphins in the world.
Versatile waste sorting in small batch and flexible manufacturing industries using deep learning techniques
Evaluation of the practical application of the category-imbalanced myeloid cell classification model
The incidence of acute myeloid leukemia (AML) is increasing annually, and timely diagnostic and treatments can substantially improve patient survival rates. AML typing traditionally relies on manual microscopy for classifying and counting myeloid cells, which is time-consuming, laborious, and subjective. Therefore, developing a reliable automated model for myeloid cell classification is imperative. This study evaluated the performance of five widely-used classification models on the largest publicly available bone marrow cell dataset (BM). However, the accuracy of the classification model is significantly affected by the imbalance in the distribution of bone marrow cell types. To address this issue, this study analyzed five different Loss functions and seven different attention mechanisms. When the classification models is chosen, Swin Transformer V2 was found to perform the best. However, the lightweight model RegNetX-3.2gf had significantly fewer parameters and a significantly faster inference speed than Swin Transformer V2, and its F1 Score was only 0.032 lower than that of Swin Transformer V2. Accordingly, RegNetX-3.2gf is strongly recommended for practical applications. During the evaluation of Loss function and attention mechanism, the Cost-Sensitive Loss Function (CS) and the channel attention mechanism Squeeze-and-Excitation Networks (SE) demonstrated superior performance. The optimal model (RegNetX-3.2gf + CS + SE) achieved an average precision of 68.183%, an average recall of 63.722%, and an average F1 Score of 65.155%. This model exhibited significantly improved performance compared to the original dataset results, achieving an enhancement of 17.183% in precision and 10.655% in the F1 Score. Finally, the class activation maps demonstrate that our model focused on the cells themselves, especially on the nucleus when making classifications. It proved that our model was reliable. This study provided an important reference for the study of bone marrow cell classification and a practical application of the model, promoting the development of the intelligent classification of AML.
Peripheral nerve regeneration using a bioresorbable silk fibroin-based artificial nerve conduit fabricated via a novel freeze–thaw process
Risk of childlessness in help-seeking men with Peyronie’s disease—A Swedish longitudinal study
Peyronie’s disease (PD) is a disorder of the penis that is associated with poor mental health, lowered psychosocial- and sexual wellbeing, which may increase the risk of childlessness in men affected by the disorder. Although this is an issue of significant clinical importance, it has not been addressed in research to date. We conducted a longitudinal cohort study based on data from Swedish national registers utilizing a large sample of help-seeking men with PD, along with matched subjects from the general population. We assessed the probability and odds ratio of childlessness, modeled with logistic regressions, and offspring rate ratio, modeled with Poisson regression. We found that the probability of childlessness was somewhat lowered for men with PD aged between 35 and 71 years at end of follow-up. Men with PD aged 35 or less showed slightly elevated probabilities of childlessness. Specifically, odds ratios for childlessness were between 0.5 and 1.0 for men aged above 35, and between 1 and 1.5 for men aged less than 35, although the confidence intervals for increased odds partly included the null. Analyses of men’s rate of offspring showed similar pattern, with higher rate ratios for older men and lower for younger men. Although more research is needed, the findings of this study suggest that clinical urological practice may be enhanced by a proactive discussions about the potential issue of childlessness in younger men with PD.
Equilibrium study of logistics demand and logistics resource allocation in Guangdong Province
Prevalence of advanced hepatic fibrosis and individualization of associated risk factors by Bayesian analysis in MASLD patients in French cardio-metabolic health networks
The aim of this study was to determine the prevalence of advanced hepatic fibrosis and to individualize using Bayesian analysis its associated risk factors in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) being cared for in three Alsatian cardio-metabolic health networks in the North East of France. Overall, 712 patients aged ≥18 years with a female predominance were included into a prospective, cross-sectional, and observational study. Advanced fibrosis and severe steatosis were evaluated using transient elastography (FibroScan®). The proportion of MASLD patients was 80% and 84% in women and men (difference -4.2% [-10.0; 1.9]), respectively. Advanced fibrosis was observed in 11% of patients, being more common in men (16.9%) than women (7.5%) (difference 9.4 [4.3–15.0]). Severe steatosis was also more common in men (74.9%) than women (63.4%) (difference 11.4 [4.2–18.2]). Only three of the tested variables were likely associated with advanced fibrosis: gender (OR: 1.78 [1.17–2.68]; Pr [OR >1] = 1), T2DM (OR: 1.54 [1–2.37]; Pr [OR >1] = 0.97) and hypertriglyceridemia (OR: 1.49 [0.97–2.27]; Pr (OR >1) = 0.97). In conclusion, this study confirmed the usefulness of assessing hepatic fibrosis in patients with metabolic dysfunction. Therefore, access to FibroScan® should be facilitated in all cardio-metabolic health networks.
Study on the catalytic mechanism and water resistance of Cu-Mn-Snx catalyst for CO elimination
Editorial Note: Methionine-induced regulation of growth, secondary metabolites and oxidative defense system in sunflower (Helianthus annuus L.) plants subjected to water deficit stress
Essential oils modulate virulence phenotypes in a multidrug-resistant pyomelanogenic Pseudomonas aeruginosa clinical isolate
Probing spin-electric transitions in a molecular exchange qubit
Predicting the risk of bone metastases in patients with newly diagnosed prostate cancer – Development and validation of a nomogram model
Objectives The aim of this study was to develop and validate a nomogram model that predicts the risk of bone metastasis (BM) in a prostate cancer (PCa) population. Methods We retrospectively collected and analyzed the clinical data of patients with pathologic diagnosis of PCa from January 1, 2013 to December 31, 2022 in two hospitals in Yangzhou, China. Patients from the Affiliated Hospital of Yangzhou University were divided into a training set and patients from the Affiliated Clinical College of Traditional Chinese Medicine of Yangzhou University were divided into a validation set. Chi-square test, independent sample t-test, and logistic regression were used to screen key risk factors. Receiver operating characteristic (ROC) curves, c-index, calibration curves, and decision curves analysis (DCA) were used for the validation, calibration, clinical benefit assessment, and external validation of nomogram models. Results A total of 204 cases were collected from the Affiliated Hospital of Yangzhou University, including 64 cases diagnosed as PCa BM and 50 cases collected from the Affiliated Clinical College of Traditional Chinese Medicine of Yangzhou University, including 12 cases diagnosed as PCa BM. Results showed that history of alcohol consumption, prostate stiffness on Digital rectal examination(DRE), prostate nodules on DRE, FIB, ALP, cTx, and Gleason score were high-risk factors for BM in PCa and nomogram was established. The c-index of the final model was 0.937 (95% CI: 0.899–0.975). And the model was validated by external validation set (c-index: 0.929). The ROC curves and calibration curves showed that the nomogram had good predictive accuracy, and DCA showed that the nomogram had good clinical applicability. Conclusions Our study identified seven high-risk factors for BM in PCa and these factors would provide a theoretical basis for early clinical prevention of PCa BM.
Caerin 1.1/1.9-mediated antitumor immunity depends on IFNAR-Stat1 signalling of tumour infiltrating macrophage by autocrine IFNα and is enhanced by CD47 blockade
Declines in anthropogenic mercury emissions in the Global North and China offset by the Global South
Childhood trauma and subclinical PTSD symptoms predict adverse effects and worse outcomes across two mindfulness-based programs for active depression
Within mindfulness-based programs (MBPs), mixed results have been found for the role of childhood trauma as a moderator of depression outcomes. Furthermore, childhood trauma and PTSD symptoms have been identified as possible risk factors for the occurrence of meditation-related adverse effects (MRAE). The present research examined multiple forms of childhood trauma and PTSD symptoms as predictors of depression treatment outcomes and MRAEs. Various forms of childhood trauma (e.g., abuse and neglect) were examined as predictors of depression treatment outcomes and participant attrition using secondary analyses of two MBP clinical trials (N = 52 and 104, respectively). Study 2 also examined meditation-related side effects (MRSE) and MRAE as outcomes and current subclinical and past PTSD symptoms as predictors. Childhood trauma led to worse depression outcomes across both study 1 and study 2, such that total childhood trauma and childhood sexual abuse were significant predictors across both studies. Childhood sexual abuse predicted attrition in study 2. Finally, multiple forms of childhood trauma and PTSD symptoms predicted MRSE, while total childhood trauma, childhood emotional abuse, and subclinical PTSD symptoms predicted lasting MRAE. Childhood trauma and PTSD symptoms may lead to worse outcomes and a greater occurrence of adverse effects within MBPs for active depression. These results call for further trauma-sensitive modifications, safety monitoring, participant screening, and provider education when implementing these programs.
Association between triglyceride-glucose index and carotid atherosclerosis in Chinese steelworkers: a cross-sectional study
Daily briefing: The pros and cons of DeepSeek
Self-rerouting sensor network for electronic skin resilient to severe damage
Non-linear relationship between built environment and non-motorized travel efficiency under the traffic micro-circulation model
The built environment is an important determinant of travel demand and mode choice. Studying the relationship between the built environment and transportation usage can support and assist traffic policy interventions. Previous studies often assumed that this relationship is linear; however, the impact of the built environment on non-motorized travel efficiency may be more complex than the typically modeled linear relationships. This paper focuses on the core area of Chengguan District in Lanzhou City, utilizing multi-source big data including POI, OpenStreetMap, street view images, and built environment data. Using ArcGIS spatial analysis tools combined with the Extreme Gradient Boosting (XGBoost) model, we analyze the non-linear influence mechanisms and threshold effects of the built environment on non-motorized travel efficiency and establish a ranking of the relative importance of all built environment factors. The results indicate that factors such as the branch road/street, land-use mix, land-use density, neighborhood entrance/exit density, bus station density, and dead-end-roads density are key influences on non-motorized travel efficiency. Additionally, based on the non-linear thresholds presented in the partial dependence plots for built environment factors, this paper proposes optimization strategies for small-scale road network patterns, mixed land use, and bus-friendly environments, providing effective threshold ranges and decision-making references for urban planning and traffic management.