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Improving the Prediction Performance (PP) of crack pipeline Failure Assessment Model (FAM) is of great significance for the safety of pipeline structure and engineering. However, conventional optimizations for PP always focus on either safety or accuracy, failing to balance the overall requirements of structural applications. Therefore, this paper proposes an optimization procedure for comprehensively improving FAM’s PP. The establishment of the procedure can be divided into three parts: 1. setting a rational and robust optimization target, where the Improved Guo-Ni Model (IGNM) is raised to provide an absolute score s for fully quantifying FAM’s PP in terms of the multi-dimensional performances, including stability and Distributional Location Characterizations (DLCs) of FAM’s prediction results; 2. determining the candidate solutions which are selected as the Critical Safety Factor (CSF) values related to FAM’s prediction confidence level (R [sub.1]) in this paper; 3. constructing the optimization framework based on the Particle Swarm Optimization algorithm to search for the optimal CSF (OCSF) that can maximize s. Finally, empirical verification results show that the procedure enhances the overall s values of BS 7910:2019 and CorLAS models by 3.32% and 6.09%, respectively, through balancing DLCs, which increases the applicability of FAM across different projects and provides a new approach for the optimization control of FAM’s overall performance.

Objectives To identify molecular clusters and establish a scoring model based on mechanical stimulus-related genes (MSRGs) for predicting the prognosis of breast cancer patients and understanding the role of mechanical stimuli in the breast tumor microenvironment (TME). Methods We utilized bulk and single-cell RNA sequencing analysis to characterize MSRGs associated with breast cancer prognosis. Unsupervised consensus molecular clustering was applied to identify distinct clusters based on overall survival-associated MSRGs from The Cancer Genome Atlas (TCGA) database. The scoring model was constructed by LASSO-Cox method and validated. Additionally, single-cell RNA sequencing analysis, along with in vitro and in vivo experiments, were conducted to further investigate the role of the model in breast cancer. Results We identified 23 overall survival-associated MSRGs and established two molecular subgroups with distinct survival outcomes. A prognostic signature incorporating 15 MSRGs was developed and validated, demonstrating its predictive capability for overall survival of breast cancer patients. The nomogram integrating clinical characteristics and the mechanical stimulus-related risk score exhibited promising predictive accuracy. The low-risk group displayed an immune \"hot\" phenotype with increased immune cell infiltration, while the high-risk group exhibited resistance to conventional chemotherapy but potential sensitivity to Sepantronium bromide. By using the SCISSOR algorithm, we provide evidence at single-cell resolution for the impact of mechanical stimulation on tumor immune microenvironment. The in vivo and in vitro assays demonstrated that knockdown of TEX19 significantly suppressed breast tumor proliferation. Conclusion We developed a pioneering prognostic signature incorporating MSRGs in breast cancer, with a particular focus on mechanical stimuli may influence breast cancer prognosis by remodeling the immune microenvironment. The findings highlighted the importance of personalized treatment strategies and provide new insights into the role of mechanical forces in breast tumor biology.

Due to the lack of devices and the difficulty of gathering patients, the small sample size is one of the most challenging problems in functional brain network (FBN) analysis. Previous studies have attempted to solve this problem of sample limitation through data augmentation methods, such as sample transformation and noise addition. However, these methods ignore the unique spatial-temporal information of functional magnetic resonance imaging (fMRI) data, which is essential for FBN analysis. To address this issue, we propose a spatial-temporal data-augmentation-based classification (STDAC) scheme that can fuse the spatial-temporal information, increase the samples, while improving the classification performance. Firstly, we propose a spatial augmentation module utilizing the spatial prior knowledge, which was ignored by previous augmentation methods. Secondly, we design a temporal augmentation module by random discontinuous sampling period, which can generate more samples than former approaches. Finally, a tensor fusion method is used to combine the features from the above two modules, which can make efficient use of spatial-temporal information of fMRI simultaneously. Besides, we apply our scheme to different types of classifiers to verify the generalization performance. To evaluate the effectiveness of our proposed scheme, we conduct extensive experiments on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset and REST-meta-MDD Project (MDD) dataset. Experimental results show that the proposed scheme achieves superior classification accuracy (ADNI: 82.942%, MDD: 63.406%) and feature interpretation on the benchmark datasets. The proposed STDAC scheme, utilizing both spatial and temporal information, can generate more diverse samples than former augmentation methods for brain disorder classification and analysis.

Sonodynamic therapy (SDT), a tumor treatment modality with high tissue penetration and low side effects, is able to selectively kill tumor cells by producing cytotoxic reactive oxygen species (ROS) with ultrasound‐triggered sonosensitizers. N‐type inorganic semiconductor TiO2 has low ROS quantum yields under ultrasound irradiation and inadequate anti‐tumor activity. Herein, by using atomic layer deposition (ALD) to create a heterojunction between porous TiO2 and CoOx, the sonodynamic therapy efficiency of TiO2 can be improved. Compared to conventional techniques, the high controllability of ALD allows for the delicate loading of CoOx nanoparticles into TiO2 pores, resulting in the precise tuning of the interfaces and energy band structures and ultimately optimal SDT properties. In addition, CoOx exhibits a cascade of H2O2→O2→·O2− in response to the tumor microenvironment, which not only mitigates hypoxia during the SDT process, but also contributes to the effect of chemodynamic therapy (CDT). Correspondingly, the synergistic CDT/SDT treatment is successful in inhibiting tumor growth. Thus, ALD provides new avenues for catalytic tumor therapy and other pharmaceutical applications. Heterostructures precisely designed and constructed by atomic layer deposition technology have been used in in vivo experiments for the first time. The interfacial and energy band structure of TiO2@CoOx heterojunction can be finely tuned by gradient ALD of CoOx on TiO2, resulting in a synergistic effect between sonodynamic and chemodynamic therapy.

Background “Three-medical linkage” is a key concern of the healthcare system reform deepening in China, while it has not achieved the expected outcomes yet. The issues of “no-linkage” or “linkage without moving” have increasingly become a major challenge. Methods Data was obtained from various Yearbooks in China. Coupling coordination degree and gravity models were employed to analyze the spatio-temporal evolution pattern of the “three-medical linkage” in 31 provinces. The combination forecasting method was used to forecast the development trend of the “three-medical linkage.” We constructed the obstacle degree model to identify the main obstacles to coordinated development. Results The overall development of the three systems exhibited a continuous upward trend. The coupling coordination grade of the “three-medical linkage” system has progressed from the disorderly development stage to the transitional stage in most provinces. The Beijing-Tianjin-Hebei and Yangtze River Delta regions are the most closely connected. Regional disparities in the degree of coupling coordination will widen in the future. The number of people benefiting from maternity insurance, per capita total health expenditure, and new drug research and development (R&D) costs hindered the coordinated development of the three systems. Discussion Highlighting the improvement of the “three-medical linkage” is essential. Under the goals of Healthy China and SDG3 (Good Health and Well-being), further efforts are needed to address systemic barriers and institutional deficiencies. The Chinese government should increase capital input to overcome major obstacles and carefully evaluate the imbalance in regional development.

Introduction The data of Listeria monocytogenes (LM) meningitis in children beyond the neonatal stage has been limited. We aimed to summarize the clinical characteristics, management, and risk factors of neurological complications in LM meningitis children beyond the neonatal stage. Methods We retrospectively reviewed LM meningitis cases from January 2013 to December 2022 at Beijing Children’s Hospital. Clinical characteristics, pathogen detection results and management were analyzed. Results There were 41 LM meningitis patients at our center, with a median age of 2.3 years (ranging from 6 months to 9 years). Most patients (97.6%) were immunocompetent. Fourteen patients (34.1%) had a history of suspected food contamination. The most common symptom was fever (100%), and 29.2% of patients presented with diarrhea in the early stages of the disease. About 61% of patients showed monocyte predominance in their cerebrospinal fluid (CSF). Thirteen patients (31.7%) experienced neurological complications. Multivariate analysis indicated that a diagnosis delay of more than one week and a CRP level of 50 mg/L or higher were significant risk factors for these neurological complications ( p  < 0.05). CSF culture rates were much higher before hospital admission (85.7%) compared to after (31.7%, p  < 0.05). Metagenomic next-generation sequencing (mNGS) identified pathogens in 3 culture-negative cases. In total, 97.5% of patients received meropenem, either alone or with other antibiotics, and all children recorded a Glasgow Outcome Scale (GOS) score of 5. Conclusion LM meningitis can affect immunocompetent children. Strengthening food hygiene and safety education is crucial to prevent LM infection. Penicillin or ampicillin are the preferred treatments, while meropenem may be considered as an alternative treatment.

Bacterial meningitis is a severe infectious disease. Study of bacterial meningitis of children in recent years are limited. It is unclear whether there have been any changes in the epidemiological characteristics of bacterial meningitis during the years of the COVID-19 pandemic. The purpose of this study was to describe a large, nationwide study of bacterial meningitis in China. We analyzed data of hospitalized patients with bacterial meningitis from 30 hospitals in China from 2016—2021. A total of 16566 episodes of bacterial meningitis were included, of which 13614 episodes (82.18%) occurred in children age under 5-years old. The admission proportion of bacterial meningitis to total hospitalization decreased from 0.24% to 0.16% after COVID -19 pandemic (under COVID -Zero Strategy) ( P  < .0001). The risk of at least one complication was 26.45% (4382/16566). The three most common complications were hydrocephalus (2351, 14.19%), subdural effusions or empyema (1438, 8.68%), and seizures (794, 4.79%). Ninety-one (0.55%) patients died in hospital. Risks of complications and mortality (0.55%) were related to age under 5 years old ( P  < .0001). The median length of stay and inpatient expenditures for children with bacterial meningitis were 16 days and 2,697.38 USD. Conclusions Bacterial meningitis mostly occurred in children aged < 5 y. The percentage of 30 tertiary hospitalized children with bacterial meningitis apparently decreased after the COVID-19 pandemic. Ninety-one (0.55%) patients died in the hospital.

It is discovered that the product of the current and the electric field in a PN junction should be regarded as the rate of work (power) done by the electric field force on moving charges (hole current and electron current), which was previously misinterpreted as solely a Joule heating effect. We clarify that it is exactly the work done by the electric field force on the moving charges to stimulate the emergence of non-equilibrium carriers, which triggers the novel physical phenomena. As regards to Joule heat, we point out that it should be calculated from Ohm’s law, rather than simply from the product of the current and the electric field. Based on this understanding, we conduct thorough discussion on the role of the electric field force in the process of carrier recombination and carrier generation. The thermal effects of carrier recombination and carrier generation followed are incorporated into the thermal equation of energy. The present study shows that the exothermic effect of carrier recombination leads to a temperature rise at the PN interface, while the endothermic effect of carrier generation causes a temperature reduction at the interface. These two opposite effects cause opposite heat flow directions in the PN junction under forward and backward bias voltages, highlighting the significance of managing device heating phenomena in design considerations. Therefore, this study possesses referential significance for the design and tuning on the performance of piezotronic devices.

Background Hepatocellular carcinoma (HCC) one of the most common digestive system tumors, threatens the tens of thousands of people with high morbidity and mortality world widely. The purpose of our study was to investigate the related genes of HCC and discover their potential abilities to predict the prognosis of the patients. Methods We obtained RNA sequencing data of HCC from The Cancer Genome Atlas (TCGA) database and performed analysis on protein coding genes. Differentially expressed genes (DEGs) were selected. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were conducted to discover biological functions of DEGs. Protein and protein interaction (PPI) was performed to investigate hub genes. In addition, a method of supervised machine learning, recursive feature elimination (RFE) based on random forest (RF) classifier, was used to screen for significant biomarkers. And the basic experiment was conducted by lab, we constructe a clinical patients’ database, and obtained the data and results of immunohistochemistry. Results We identified five biomarkers with significantly high expression to predict survival risk of the HCC patients. These prognostic biomarkers included SPC25, NUF2, MCM2, BLM and AURKA. We also defined a risk score model with these biomarkers to identify the patients who is in high risk. In our single-center experiment, 95 pairs of clinical samples were used to explore the expression levels of NUF2 and BLM in HCC. Immunohistochemical staining results showed that NUF2 and BLM were significantly up-regulated in immunohistochemical staining. High expression levels of NUF2 and BLM indicated poor prognosis. Conclusion Our investigation provided novel prognostic biomarkers and model in HCC and aimed to improve the understanding of HCC. In the results obtained, we also conducted a part of experiments to verify the theory described earlier, The experimental results did verify our theory.

Epidemiological studies have suggested that particulate matter (PM) pollution seriously affects human health, particularly it is closely associated with respiratory diseases. The aim of this study is to quantitatively evaluate the effect of PMs (PM10 and PM2.5) on emergency room (ER) visits for respiratory diseases in Lanzhou, a valley basin city in northwest China. Based on the data of the ER visits, daily concentration of particulate matters and daily meteorological elements from January 1, 2013, to July 31, 2017, we used a generalized additive model (GAM) of time series to evaluate the exposure–response relationship between PMs and respiratory ER visits. Seasonal modified effects of PM2.5 and PM10 on different age and gender groups were also performed. Results showed that the highest incidence of respiratory diseases occurred in winter. Respiratory ER visits for the total were significantly associated with PM2.5 (at lag 0 day) and PM10 (at lag 3 days), with relative risks (RRs) of 1.042 (95%CI: 1.036 –1.047) and 1.013 (95%CI: 1.011–1.016), respectively. Effects of PM pollutants on respiratory diseases are different among different age and gender groups. Children under 15 years and the elders over 60 years were the most sensitive to PM pollution, and males were more sensitive than females. The results obtained in the current study would provide a scientific evidence for local government to make policy decision for prevention of respiratory diseases.