Explore the vast range of titles available.

Gas-involving electrochemical reactions, like oxygen reduction reaction (ORR), oxygen evolution reaction (OER), and hydrogen evolution reaction (HER), are critical processes for energy-saving, environment-friendly energy conversion and storage technologies which gain increasing attention. The development of according electrocatalysts is key to boost their electrocatalytic performances. Dramatic efforts have been put into the development of advanced electrocatalysts to overcome sluggish kinetics. On the other hand, the electrode interfaces-architecture construction plays an equally important role for practical applications because these imperative electrode reactions generally proceed at triple-phase interfaces of gas, liquid electrolyte, and solid electrocatalyst. A desirable architecture should facilitate the complicate reactions occur at the triple-phase interfaces, which including mass diffusion, surface reaction and electron transfer. In this review, we will summarize some design principles and synthetic strategies for optimizing triple-phase interfaces of gas-involving electrocatalysis systematically, based on the electrode reaction process at the three-phase interfaces. It can be divided into three main optimization directions: exposure of active sites, promotion of mass diffusion and acceleration of electron transfer. Furthermore, we especially highlight several remarkable works with comprehensive optimization about specific energy conversion devices, including metal-air batteries, fuel cells, and water-splitting devices are demonstrated with superb efficiency. In the last section, the perspectives and challenges in the future are proposed.

Background Ovarian clear cell carcinoma (OCCC) has a disproportionately high incidence among women in East Asia. Patients diagnosed with OCCC tend to experience worse clinical outcomes than those with high-grade serous carcinoma (HGSC) at advanced stages. The unfavorable prognosis of OCCC can be partly attributed to its frequent resistance to conventional chemotherapy. Within a precision medicine framework, we sought to provide a comprehensive molecular characterization of OCCC using whole-exome sequencing to uncover potential molecular targets that may inform novel therapeutic strategies. Methods We performed whole-exome sequencing analysis on tumor-normal paired samples from 102 OCCC patients. This comprehensive genomic characterization of a substantial cohort of OCCC specimens was coupled with an analysis of clonal progression. Results On analyzing 102 OCCC samples, ARID1A (67%) and PIK3CA (49%) emerged as the most frequently mutated driver genes. We identified tier 1 or 2 clinically actionable molecular targets in 40% of cases. This included DNA mismatch repair deficiency ( n  = 1), as well as BRCA2 ( n  = 1), PIK3CA ( n  = 36), KRAS G12C ( n  = 1), and ATM ( n  = 4) mutations. Furthermore, 45% of OCCC samples displayed ARID1A biallelic loss. Interestingly, we identified previously unreported mutations in the 5’ untranslated region of the TERT gene that harbored an adverse prognostic significance. Clock-like mutational processes and activated APOBECs were major drivers of somatic point mutations. Mutations arising from DNA mismatch repair deficiency were uncommon. Reconstruction of clonal evolution revealed that early genetic events likely driving tumorigenesis included mutations in the ARID1A , PIK3CA , TERT , KRAS , and TP53 genes. Conclusions Our study provides a comprehensive characterization of the genomic landscape and clonal evolution in OCCC within a substantial cohort. These findings unveil potentially actionable molecular alterations that could be leveraged to develop targeted therapies.

Hydrogen sulfide (H2S) could act as a versatile signaling molecule in delaying fruit ripening and senescence. Ethylene (C2H4) also plays a key role in climacteric fruit ripening, but little attention has been given to its interaction with H2S in modulating fruit ripening and senescence. To study the role of H2S treatment on the fruit quality and nutrient metabolism, tomato fruits at white mature stage were treated with ethylene and ethylene plus H2S. By comparing to C2H4 treatment, we found that additional H2S significantly delayed the color change of tomato fruit, and maintained higher chlorophyll and lower flavonoids during storage. Moreover, H2S could inhibit the activity of protease, maintained higher levels of nutritional-related metabolites, such as anthocyanin, starch, soluble protein, ascorbic acid by comparing to C2H4 treatment. Gene expression analysis showed that additional H2S attenuated the expression of beta-amylase encoding gene BAM3 , UDP-glycosyltransferase encoding genes, ethylene-responsive transcription factor ERF003 and DOF22 . Furthermore, principal component analysis suggested that starch, titratable acids, and ascorbic acid were important factors for affecting the tomato storage quality, and the correlation analysis further showed that H2S affected pigments metabolism and the transformation of macromolecular to small molecular metabolites. These results showed that additional H2S could maintain the better appearance and nutritional quality than C2H4 treatment alone, and prolong the storage period of post-harvest tomato fruits.

The molecular underpinnings of seromucinous borderline tumor (SMBT) – an uncommon ovarian epithelial neoplasm characterized by association with endometriosis, frequent bilateral ovarian involvement, and occasional progression to invasive carcinoma – remain poorly understood. Here, we sought to comprehensively characterize the mutational landscape of SMBT and elucidate the clonal relationship between bilateral ovarian SMBTs. We also compared the mutational profiles between SMBTs and concurrent invasive carcinomas. Formalin-fixed, paraffin-embedded tissue specimens were retrieved from 28 patients diagnosed with SMBT. Massively parallel sequencing of 409 cancer-related genes was conducted to identify somatic mutations in 33 SMBT samples and four concurrent invasive carcinoma specimens. TERT promoter mutations were assessed by Sanger sequencing, whereas immunohistochemistry was used as a surrogate tool for detecting deletions or epigenetic silencing of relevant tumor suppressor genes. Twenty-six (92.9%) of the 28 patients were diagnosed with stage I SMBTs. Seven (25%) cases showed bilateral ovarian involvement and 13 (46%) had concomitant endometriosis. Concurrent ovarian carcinomas were identified in three patients, whereas one case had a synchronous endometrial carcinoma. Somatic mutations in the KRAS, PIK3CA, and ARID1A genes were identified in 100, 60.7, and 14.3% of SMBT samples, respectively. In contrast, TERT promoter mutations and DNA mismatch repair deficiencies were absent. Sequencing of paired specimens from patients with bilateral SMBT revealed the presence of at least two shared somatic mutations, suggestive of a clonal relationship. Similarly, we identified shared somatic mutations between SMBT samples and concurrent ovarian carcinoma specimens. Taken together, these findings demonstrated a distinct mutational landscape of SMBT in which (1) KRAS is invariably mutated, (2) PIK3CA is frequently mutated, and (3) TERT promoter mutations and DNA mismatch repair deficiencies are absent. Our findings represent the first extensive characterization of this rare ovarian neoplasm, with potential implications for disease classification and molecular diagnostics.

Wireless Rechargeable Sensor Networks (WRSN) are not yet fully functional and robust due to the fact that their setting parameters assume fixed control velocity and location. This study proposes a novel scheme of the WRSN with mobile sink (MS) velocity control strategies for charging nodes and collecting its data in WRSN. Strip space of the deployed network area is divided into sub-locations for variant corresponding velocities based on nodes energy expenditure demands. The points of consumed energy bottleneck nodes in sub-locations are determined based on gathering data of residual energy and expenditure of nodes. A minimum reliable energy balanced spanning tree is constructed based on data collection to optimize the data transmission paths, balance energy consumption, and reduce data loss during transmission. Experimental results are compared with the other methods in the literature that show that the proposed scheme offers a more effective alternative in reducing the network packet loss rate, balancing the nodes’ energy consumption, and charging capacity of the nodes than the competitors.

Purpose To develop machine learning (ML) models to predict the surgical risk of children with pancreaticobiliary maljunction (PBM) and biliary dilatation. Methods The subjects of this study were 157 pediatric patients who underwent surgery for PBM with biliary dilatation between January, 2015 and August, 2022. Using preoperative data, four ML models were developed, including logistic regression (LR), random forest (RF), support vector machine classifier (SVC), and extreme gradient boosting (XGBoost). The performance of each model was assessed via the area under the receiver operator characteristic curve (AUC). Model interpretations were generated by Shapley Additive Explanations. A nomogram was used to validate the best-performing model. Results Sixty-eight patients (43.3%) were classified as the high-risk surgery group. The XGBoost model (AUC = 0.822) outperformed the LR (AUC = 0.798), RF (AUC = 0.802) and SVC (AUC = 0.804) models. In all four models, enhancement of the choledochal cystic wall and an abnormal position of the right hepatic artery were the two most important features. Moreover, the diameter of the choledochal cyst, bile duct variation, and serum amylase were selected as key predictive factors by all four models. Conclusions Using preoperative data, the ML models, especially XGBoost, have the potential to predict the surgical risk of children with PBM and biliary dilatation. The nomogram may provide surgeons early warning to avoid intraoperative iatrogenic injury.

Chinese mitten crab ( Eriocheir sinensis ) as a commercially important species is widely cultured in China. However, E. sinensis is prone to agonistic behavior, which causes physical damage and wastes energy resources, negatively impacting their growth and survival. Therefore, understanding the regulatory mechanisms that underlie the switching of such behavior is essential for ensuring the efficient and cost-effective aquaculture of E. sinensis . The 5-HT2B receptor is a key downstream target of serotonin (5-HT), which is involved in regulating animal behavior. In this study, the full-length sequence of 5-HT2B gene was cloned. The total length of the 5-HT2B gene was found to be 3127 bp with a 236 bp 5′-UTR (untranslated region), a 779 bp 3′-UTR, and a 2112 bp open reading frame encoding 703 amino acids. Phylogenetic tree analysis revealed that the 5-HT2B amino acid sequence of E. sinensis is highly conserved with that of Cancer borealis . Using in vitro co-culture and luciferase assays, the miR-143 targets the 5-HT2B 3′-UTR and inhibits 5-HT2B expression was confirmed. Furthermore, RT-qPCR and Western blotting analyses revealed that the miR-143 mimic significantly inhibits 5-HT2B mRNA and protein expression. However, injection of miR-143 did not decrease agonistic behavior, indicating that 5-HT2B is not involved in the regulation of such behavior in E. sinensis .

ObjectiveThe early days of the COVID-19 pandemic placed enormous pressure and subsequent negative psychological problems on nurses, but at this stage of the year-long COVID-19 outbreak, the level of stress and negative emotions that nurses experience is unclear. Our study attempted to assess the factors influencing mental health status in nurses during the postepidemic period of COVID-19.DesignCross-sectional study.SettingCOVID-19 designated hospitals.Participants1284 Chinese nurses.Main outcome measuresElectronic questionnaires, including the Chinese version of the Perceived Stress Scale (CPSS) and Symptom Checklist-90 (SCL-90), were distributed for self-evaluation. Regression analysis was used to analyse the associated factors of psychological stress among variables such as age, years of nursing experience, weekly working hours, anxiety symptoms, somatisation symptoms and compulsive symptoms.ResultsA total of 1284 respondents from COVID-19-designated hospitals in Guangdong Province were studied. The average CPSS score for all respondents was 22.91±7.12. A total of 38.5% of respondents scored ≥26 on the CPSS, indicating a significant degree of psychological stress. Nurses with high psychological stress had higher levels of anxiety symptoms (41.7% vs 8.0%), somatisation symptoms (31.4% vs 7.7%) and compulsion symptoms (62.3% vs 27.0%) than nurses with low psychological stress. Stepwise multiple linear regression revealed that weekly working hours, years of nursing experience, anxiety symptoms, somatisation symptoms and compulsion symptoms had a linear relationship with the participants’ psychological stress scores.ConclusionNurses experienced significant physical and psychological risk while working in the postepidemic period. Our findings suggest that nurses still need support to protect their physical and mental health.

Purpose To develop and validate an explainable machine learning (ML) model to predict postoperative cholangitis (POC) in pediatric patients with pancreaticobiliary maljunction (PBM) using readily accessible clinical data. Methods We analyzed 337 children with PBM who underwent surgery, dividing them into training ( n  = 243, center I) and testing ( n  = 94, center II) sets. Six ML algorithms were applied, and the best-performing model was identified by area under the receiver operating characteristic curves (ROC-AUC) and precision-recall curves (PR-AUC). Model calibration, clinical applicability, and interpretability were further evaluated using calibration curves, decision curve analysis (DCA), and Shapley Additive Explanations (SHAP). Results After a median follow-up of 21.8 months, 13.2% (32/243) of patients from center I and 14.9% (14/94) from center II developed POC. The final random forest (RF) model exhibited the best performance, with ROC-AUC of 0.890 and PR-AUC of 0.764 in testing set, with good calibration across both sets. DCA confirmed that the final RF model was clinically useful. Nine key features were identified and ranked using SHAP analysis, with cholangial inflammatory infiltration and diameter of common bile duct being the most important. Conclusion This explainable ML model could effectively predict POC, aiding clinicians in identifying high-risk patients and supporting individualized management in PBM.

Background To identify radiomic features that can predict the pathological type of neuroblastic tumor in children. Methods Data on neuroblastic tumors in 104 children were retrospectively analyzed. There were 14 cases of ganglioneuroma, 24 cases of ganglioneuroblastoma, and 65 cases of neuroblastoma. Stratified sampling was used to randomly allocate the cases into the training and validation sets in a ratio of 3:1. The maximum relevance–minimum redundancy algorithm was used to identify the top 10 of two clinical features and 851 radiomic features in portal venous–phase contrast-enhanced computed tomography images. Least absolute shrinkage and selection operator regression was used to classify tumors in two binary steps: first as ganglioneuroma compared to the other two types, then as ganglioneuroblastoma compared to neuroblastoma. Results Based on 10 clinical-radiomic features, the classifier identified ganglioneuroma compared to the other two tumor types in the validation dataset with sensitivity of 100.0%, specificity of 81.8%, and an area under the receiver operating characteristic curve (AUC) of 0.875. The classifier identified ganglioneuroblastoma versus neuroblastoma with a sensitivity of 83.3%, a specificity of 87.5%, and an AUC of 0.854. The overall accuracy of the classifier across all three types of tumors was 80.8%. Conclusion Radiomic features can help predict the pathological type of neuroblastic tumors in children.