Electrocardiogram-based prediction of conduction disturbances after transcatheter aortic valve replacement with convolutional neural network.

Aims: Permanent pacemaker implantation and left bundle branch block are common complications after transcatheter aortic valve replacement (TAVR) and are associated with impaired prognosis. This study aimed to develop an artificial intelligence (AI) model for predicting conduction disturbances after TAVR using pre-procedural 12-lead electrocardiogram (ECG) images. Methods and results: We collected pre-procedural 12-lead ECGs of patients who underwent TAVR at West China Hospital between March 2016 and March 2022. A hold-out testing set comprising 20% of the sample was randomly selected. We developed an AI model using a convolutional neural network, trained it using five-fold cross-validation and tested it on the hold-out testing cohort. We also developed and validated an enhanced model that included additional clinical features. After applying exclusion criteria, we included 1354 ECGs of 718 patients in the study. The AI model predicted conduction disturbances in the hold-out testing cohort with an area under the curve (AUC) of 0.764, accuracy of 0.743, F1 score of 0.752, sensitivity of 0.876, and specificity of 0.624, based solely on pre-procedural ECG images. The performance was better than the Emory score (AUC = 0.704), as well as the logistic (AUC = 0.574) and XGBoost (AUC = 0.520) models built with previously identified high-risk ECG patterns. After adding clinical features, there was an increase in the overall performance with an AUC of 0.779, accuracy of 0.774, F1 score of 0.776, sensitivity of 0.794, and specificity of 0.752. Conclusion: Artificial intelligence-enhanced ECGs may offer better predictive value than traditionally defined high-risk ECG patterns.

The mitochondria-related gene risk mode revealed p66Shc as a prognostic mitochondria-related gene of glioblastoma.

Numerous studies have highlighted the pivotal role of mitochondria-related genes (MRGs) in the initiation and progression of glioblastoma (GBM). However, the specific contributions of MRGs coding proteins to GBM pathology remain incompletely elucidated. The identification of prognostic MRGs in GBM holds promise for the development of personalized targeted therapies and the enhancement of patient prognosis. We combined differential expression with univariate Cox regression analysis to screen prognosis-associated MRGs in GBM. Based on the nine MRGs, the hazard ratio model was conducted using a multivariate Cox regression algorithm. SHC-related survival, pathway, and immune analyses in GBM cohorts were obtained from the Biomarker Exploration of the Solid Tumor database. The proliferation and migration of U87 cells were measured by CCK-8 and transwell assay. Apoptosis in U87 cells was evaluated using flow cytometry. Confocal microscopy was employed to measure mitochondrial reactive oxygen species (ROS) levels and morphology. The expression levels of SHC1 and other relevant proteins were examined via western blotting. We screened 15 prognosis-associated MRGs and constructed a 9 MRGs-based model. Validation of the model's risk score confirmed its efficacy in predicting the prognosis of patients with GBM. Furthermore, analysis revealed that SHC1, a constituent MRG of the prognostic model, was upregulated and implicated in the progression, migration, and immune infiltration of GBM. In vitro experiments elucidated that p66Shc, the longest isoform of SHC1, modulates mitochondrial ROS production and morphology, consequently promoting the proliferation and migration of U87 cells. The 9 MRGs-based prognostic model could predict the prognosis of GBM. SHC1 was upregulated and correlated with the prognosis of patients by involvement in immune infiltration. Furthermore, in vitro experiments demonstrated that p66Shc promotes U87 cell proliferation and migration by mediating mitochondrial ROS production. Thus, p66Shc may serve as a promising biomarker and therapeutic target for GBM.

Effect of pyrite particle size on the denitrification performance of autotrophic or split-mixotrophic bioreactors supported by pyrite/polycaprolactone.

In this study, a pyrite-based autotrophic denitrification (PAD) system, a polycaprolactone (PCL)-supported heterotrophic denitrification (PHD) system, and a pyrite+PCL-based split-mixotrophic denitrification (PPMD) system were constructed. The pyrite particle size was controlled in 1-3, 3-5, or 5-8 mm in both the PAD and PPMD systems to investigate the effect of pyrite particle size on the denitrification performance of autotrophic or split-mixotrophic bioreactors. It was found that the PAD system achieved the best denitrification efficiency with an average removal rate of 98.98% in the treatment of 1- to 3-mm particle size, whereas it was only 19.24% in the treatment of 5- to 8-mm particle size. At different phases of the whole experiment, the nitrate removal rates of both the PHD and PPMD systems remained stable at a high level (>94%). Compared with the PAD or PHD system, the PPMD system reduced the concentrations of sulfate and chemical oxygen demand in the final effluent efficiently. The interconnection network diagram explained the intrinsic metabolic pathways of nitrogen, sulfur, and carbon in the three denitrification systems at different phases. In addition, the microbial community analysis showed that the PPMD system was beneficial for the enrichment of Firmicutes. Finally, the impact mechanism of pyrite particle size on the performance of the PPMD system was proposed. PRACTITIONER POINTS: The reduction of pyrite particle size was beneficial for improving the efficiency of the PAD process. The change in particle size had an effect on NO2 --N accumulation in the PAD system. The accumulation of NH4 +-N in the PPMD system increased with the decrease in particle size. The reduction of pyrite particle size increased the production of SO4 2- in the PAD and PPMD systems. The correlations among the effluent indicators of the PAD and PPMD systems could be well explained.

Sex dimorphic response to osteocyte miR21 deletion in murine calvaria bone as determined by RNAseq analysis.

Low levels of microRNA (miR) 21 may explain the higher osteocyte apoptosis with Cx43-deficient and aged female mice. However, miR21 exerts a sex-divergent role in osteocytes, regulating bone mass and architecture through non-cell autonomous effects on osteoblasts and osteoclasts, via sex-specific regulation of osteocyte cytokine production. miR21 deficiency improves bone strength in females, and, to a higher extent, in male miR21-deficient mice. To understand the molecular basis for the effects of miR21 deletion, mRNA was isolated from miR21fl/fl (controls) or miR21-deficient (by deletion in cells expressing Cre recombinase under the control of the 8 kb fragment of the DMP1 promoter: miR21ΔOt mice). miR21 was 50% lower in miR21ΔOt whole calvaria bone compared to control mice of the corresponding sex. RNAseq was performed in 4 samples/sex and genotype. There were 152 genes with <.05 P-value and >1 absolute log2 fold change in the male data analysis, and expression of most genes was higher in the miR21fl/fl group. Two of the genes, Actn3 and Myh4, had a false discovery rate < 0.1. Gene enrichment analysis of significant genes on both KEGG pathways and gene ontology (GO) gene sets shows that the significant genes were enriched in muscle contraction. Some muscle-related genes like Actn3 were included in multiple significant pathways. For females, only 65 genes had P-value <.05 and >1 absolute log2 fold change. Yet, no significant KEGG or GO pathways, including ≥5 significant genes, were seen, and no overlap of significant genes was found between male and female samples. Therefore, deletion of miR21 has a stronger effect on male transcriptome in calvaria, compared to females. Further, no enrichment of any pathway was detected in female samples. Thus, either there are no differences between 2 groups in female or the effect size is small, and a larger sample size is needed to uncover miR21-dependent differences.

Posterior circulation ischemic stroke: radiomics-based machine learning approach to identify onset time from magnetic resonance imaging.

PURPOSE: Posterior circulation ischemic stroke (PCIS) possesses unique features. However, previous studies have primarily or exclusively relied on anterior circulation stroke cases to build machine learning (ML) models for predicting onset time. To date, there is no research reporting the effectiveness and stability of ML in identifying PCIS onset time. We aimed to build diffusion-weighted imaging-based ML models to identify the onset time of PCIS patients. METHODS: Consecutive PCIS patients within 24 h of definite symptom onset were included (112 in the training set and 49 in the independent test set). Images were processed as follows: volume of interest segmentation, image feature extraction, and feature selection. Five ML models, naïve Bayes, logistic regression, tree ensemble, k-nearest neighbor, and random forest, were built based on the training set to estimate the stroke onset time (binary classification: ≤ 4.5 h or > 4.5 h). Relative standard deviations (RSD), receiver operating characteristic (ROC) curves, and the calibration plot was performed to evaluate the stability and performance of the five models. RESULTS: The random forest model had the best performance in the test set, with the highest area under the curve (AUC, 0.840; 95% CI: 0.706, 0.974). This model also achieved the highest accuracy, sensitivity, specificity, positive predictive value, and negative predictive value (83.7%, 64.3%, 91.4%, 75.0%, and 86.5%, respectively). Furthermore, the model had high stability (RSD = 0.0094). CONCLUSION: The PCIS case-based ML model was effective for estimating the symptom onset time and achieved considerably high specificity and stability.

Maternal Childhood Adversity and Infant Epigenetic Aging: Moderation by Restless Sleep During Pregnancy.

Maternal exposure to childhood adversity is associated with detrimental health outcomes throughout the lifespan and may have implications for offspring. Evidence links maternal adverse childhood experiences (ACEs) to detrimental birth outcomes, yet the impact on the infant's epigenome is unclear. Moreover, maternal sleep habits during pregnancy may influence this association. Here, we explore whether restless sleep during pregnancy moderates the association between exposure to maternal childhood adversity and infant epigenetic age acceleration in 332 mother-infant dyads (56% female; 39% Black; 25% Hispanic). During the 2nd trimester, mothers self-reported childhood adversity and past-week restless sleep; DNA methylation from umbilical vein endothelial cells was used to estimate five epigenetic clocks. Multivariable linear regression was used to test study hypotheses. Despite no evidence of main effects, there was evidence of an interaction between maternal ACEs and restless sleep in predicting infant epigenetic age acceleration using the EPIC Gestational Age clock. Only infants whose mothers reported exposure to both ACEs and restless sleep demonstrated accelerated epigenetic aging. Results provide preliminary evidence that maternal childhood adversity and sleep may influence the infant epigenome.

Prognostic Value of Preoperative MRI-derived 3D Quantitative Tumor Arterial Burden in Patients with Hepatocellular Carcinoma Receiving Transarterial Chemoembolization.

Purpose To investigate the association of tumor arterial burden (TAB) on preoperative MRI with transarterial chemoembolization refractoriness (TACER) and progression-free survival (PFS) in patients with hepatocellular carcinoma (HCC). Materials and Methods This retrospective study included patients with HCC who underwent repeated transarterial chemoembolization (TACE) treatments between January 2013 and December 2020. HCC was confirmed with pathology or imaging, and patients with other tumors, lost follow-up, or with a combination of other treatments were excluded. TACER was defined as viable lesions of more than 50% or increase in tumor number after two or more consecutive TACE treatments, continuous elevation of tumor markers, extrahepatic spread, or vascular invasion. TAB assessed with preoperative MRI was divided into high and low groups according to the median. A Cox proportional hazards model was used to determine the predictors of TACER and PFS. Results A total of 355 patients (median age, 61 years [IQR, 54-67]; 306 [86.2%] men, 49 [13.8%] women) were included. During a median follow-up of 32.7 months, the high TAB group had significantly faster TACER and decreased PFS than the low TAB group (all log-rank P < .001). High TAB was the strongest independent predictor of TACER and PFS in multivariable Cox regression analyses (hazard ratio [HR], 2.23 [95% CI: 1.51, 3.29]; HR, 2.30 [95% CI: 1.61, 3.27], respectively), especially in patients with Barcelona Clinic Liver Cancer stage A or a single tumor. The restricted cubic spline plot demonstrated that the HR of TACER and PFS continuously increased with increasing TAB. Conclusion High preoperative TAB at MRI was a risk factor for faster refractoriness and progression in patients with HCC treated with TACE. Keywords: Interventional-Vascular, MR Angiography, Hepatocellular Carcinoma, Transarterial Chemoembolization, Progression-free Survival, MRI Supplemental material is available for this article. © RSNA, 2024.

Failure mechanism and bearing force of CFRP strengthened square hollow section under compressive load.

Carbon fibre-reinforced polymer (CFRP) plates can efficiently repair or enhance the mechanical properties of the square hollow section. However, the loading end of such a CFRP-strengthened member is prone to local bearing failure under compressive load. Given this limitation, an innovative CFRP-plate-strengthened square hollow section composite member (CFRP-SHSCM) was raised, and the thick-walled section was welded on both ends of the thin-walled steel column. The mechanical properties of CFRP-SHSCMs were investigated through parameter finite element (FE) analysis, focusing on the influence of the amount of CFRP layers (nc), the slenderness ratio (λ), the initial geometric imperfections (v0), the CFRP layouts (2S and 4S) and the length of the exposed steel column (Le). The load-displacement curves, the bearing force, and typical failure modes were also acquired. Results indicated that with increasing nc and v0, and decreasing λ, the conventional CFRP-SHSCMs were prone to local bearing failure with poor ductility, leading to the insufficient use of the CFRP plate, in contrast, the improved CFRP-SHSCMs primarily underwent overall buckling failure and exhibited better bearing force and ductility. Finally, the modified Perry-Robertson formula was put forward to predict the ultimate load of the CFRP-SHSCMs. The coefficients of variation between the FE simulation and the theoretical results were 0.00436 and 0.0292, respectively.

Deletion of FNDC5/irisin modifies murine osteocyte function in a sex-specific manner.

Irisin, released from exercised muscle, has been shown to have beneficial effects on numerous tissues but its effects on bone are unclear. We found significant sex and genotype differences in bone from wildtype (WT) mice compared to mice lacking Fndc5 (knockout [KO]), with and without calcium deficiency. Despite their bone being indistinguishable from WT females, KO female mice were partially protected from osteocytic osteolysis and osteoclastic bone resorption when allowed to lactate or when placed on a low-calcium diet. Male KO mice have more but weaker bone compared to WT males, and when challenged with a low-calcium diet lost more bone than WT males. To begin to understand responsible molecular mechanisms, osteocyte transcriptomics was performed. Osteocytes from WT females had greater expression of genes associated with osteocytic osteolysis and osteoclastic bone resorption compared to WT males which had greater expression of genes associated with steroid and fatty acid metabolism. Few differences were observed between female KO and WT osteocytes, but with a low-calcium diet, the KO females had lower expression of genes responsible for osteocytic osteolysis and osteoclastic resorption than the WT females. Male KO osteocytes had lower expression of genes associated with steroid and fatty acid metabolism, but higher expression of genes associated with bone resorption compared to male WT. In conclusion, irisin plays a critical role in the development of the male but not the female skeleton and protects male but not female bone from calcium deficiency. We propose irisin ensures the survival of offspring by targeting the osteocyte to provide calcium in lactating females, a novel function for this myokine.

Giant bile duct dilatation in newborn: A case report.

BACKGROUND: Giant congenital biliary dilation (CBD) is a rare condition observed in clinical practice. Infants born with this condition often experience a poor overall health status, and the disease progresses rapidly, leading to severe biliary obstruction, infections, pressure exerted by the enlarged CBD on abdominal organs, disturbances in the internal environment, and multiple organ dysfunction. The treatment of giant CBD using laparoscopy is challenging due to the high degree of variation in the shape of the bile duct and other organs, making it difficult to separate the bile duct wall from adjacent tissues or to control bleeding. CASE SUMMARY: Herein, we present the details of an 11-d-old male newborn who was diagnosed with giant CBD. The patient was admitted to the neonatal surgery department of our hospital due to a history of common bile duct cyst that was detected more than 3 mo ago, and also because the patient had been experiencing yellowish skin for the past 9 d. The abnormal echo in the fetal abdomen was first noticed by the patient's mother during a routine ultrasound examination at a local hospital, when the patient was at 24 wk + 6 d of pregnancy. This finding raised concerns about the possibility of congenital biliary dilatation (22 mm × 21 mm). Subsequent ultrasound examinations at different hospitals consistently confirmed the presence of a congenital biliary dilatation. No specific treatment was administered for biliary dilatation during this period. A computed tomography scan conducted during the hospitalization revealed a large cystic mass in the right upper quadrant and pelvis, measuring approximately 9.2 cm × 7.4 cm × 11.3 cm. Based on the scan, it was classified as a type I biliary dilatation. CONCLUSION: The analysis reveals that prenatal imaging techniques, such as ultrasound and magnetic resonance imaging, play a crucial role in the early diagnosis, fetal prognosis, and treatment plan for giant CBD. Laparoscopic surgery for giant CBD presents certain challenges, including difficulties in separating the cyst wall, anastomosis, and hemostasis, as well as severe biliary system infection and ulceration. Consequently, there is a high likelihood of converting to laparotomy. The choice between surgical methods like hepaticojejunostomy (HJ) or hepaticoduodenostomy has not been standardized yet. However, we have achieved favorable outcomes using HJ. Preoperative management of inflammation, biliary drainage, liver function protection, and supportive treatment are particularly vital in improving children's prognosis. After discharge, it is essential to conduct timely reexamination and close follow-up to identify potential complications.

Automatic quantitative stroke severity assessment based on Chinese clinical named entity recognition with domain-adaptive pre-trained large language model.

BACKGROUND: Stroke is a prevalent disease with a significant global impact. Effective assessment of stroke severity is vital for an accurate diagnosis, appropriate treatment, and optimal clinical outcomes. The National Institutes of Health Stroke Scale (NIHSS) is a widely used scale for quantitatively assessing stroke severity. However, the current manual scoring of NIHSS is labor-intensive, time-consuming, and sometimes unreliable. Applying artificial intelligence (AI) techniques to automate the quantitative assessment of stroke on vast amounts of electronic health records (EHRs) has attracted much interest. OBJECTIVE: This study aims to develop an automatic, quantitative stroke severity assessment framework through automating the entire NIHSS scoring process on Chinese clinical EHRs. METHODS: Our approach consists of two major parts: Chinese clinical named entity recognition (CNER) with a domain-adaptive pre-trained large language model (LLM) and automated NIHSS scoring. To build a high-performing CNER model, we first construct a stroke-specific, densely annotated dataset "Chinese Stroke Clinical Records" (CSCR) from EHRs provided by our partner hospital, based on a stroke ontology that defines semantically related entities for stroke assessment. We then pre-train a Chinese clinical LLM coined "CliRoberta" through domain-adaptive transfer learning and construct a deep learning-based CNER model that can accurately extract entities directly from Chinese EHRs. Finally, an automated, end-to-end NIHSS scoring pipeline is proposed by mapping the extracted entities to relevant NIHSS items and values, to quantitatively assess the stroke severity. RESULTS: Results obtained on a benchmark dataset CCKS2019 and our newly created CSCR dataset demonstrate the superior performance of our domain-adaptive pre-trained LLM and the CNER model, compared with the existing benchmark LLMs and CNER models. The high F1 score of 0.990 ensures the reliability of our model in accurately extracting the entities for the subsequent automatic NIHSS scoring. Subsequently, our automated, end-to-end NIHSS scoring approach achieved excellent inter-rater agreement (0.823) and intraclass consistency (0.986) with the ground truth and significantly reduced the processing time from minutes to a few seconds. CONCLUSION: Our proposed automatic and quantitative framework for assessing stroke severity demonstrates exceptional performance and reliability through directly scoring the NIHSS from diagnostic notes in Chinese clinical EHRs. Moreover, this study also contributes a new clinical dataset, a pre-trained clinical LLM, and an effective deep learning-based CNER model. The deployment of these advanced algorithms can improve the accuracy and efficiency of clinical assessment, and help improve the quality, affordability and productivity of healthcare services.

The application value of 3D ASL in evaluating the effectiveness of stent implantation for vertebrobasilar artery stenosis.

OBJECTIVE: To evaluate the effect of stent implantation for vertebrobasilar artery stenosis，by using 3D arterial spin labeling (3D ASL) technique. METHODS: A retrospective analysis was conducted on the clinical and 3D ASL data of 48 patients who underwent vertebral-basilar artery stenting. Post-labeling delay times (PLD) of 1.5 s and 2.5 s were chosen, and the average regional cerebral blood flow (rCBF) values were measured in nine brain regions of the posterior circulation: bilateral thalamus, bilateral occipital lobes, bilateral cerebellar hemispheres, midbrain, pons, and medulla. The 48 patients were divided into two groups based on the presence or absence of acute ischemic stroke in the posterior cerebral circulation region detected by diffusion-weighted imaging (DWI). The preoperative and postoperative rCBF results were statistically analyzed. RESULTS: In the infarct group, there were significant increases in rCBF values of all nine brain regions at both PLD = 1.5 s and 2.5 s postoperatively compared to preoperatively. At PLD = 1.5 s, statistically significant differences in rCBF values between the preoperative and postoperative periods were found in the right thalamus, left cerebellum, midbrain, and pons regions (P < 0.05). At PLD = 2.5 s, statistically significant differences in rCBF values between the preoperative and postoperative periods were observed in the left occipital lobe, right cerebellum, midbrain, and pons regions (P < 0.05). When analyzing the rCBF values of the brain regions with recent infarcts in the infarct group, there was a significant increase in postoperative rCBF values compared to preoperative values (P < 0.05). After excluding the data from brain regions with recent infarcts, the CBF values in the remaining brain regions were also increased postoperatively, and some brain regions showed statistically significant differences in rCBF values between the preoperative and postoperative periods (P < 0.05). In the non-infarct group, there were no statistically significant differences in the preoperative and postoperative rCBF values in all brain regions at both PLD = 1.5 s and 2.5 s (P > 0.05). CONCLUSION: The application of 3D ASL technology shows significant value in assessing the surgical efficacy of vertebral-basilar artery stenting, especially in patients with acute posterior circulation infarction.

Photodegradation and van der Waals Passivation of Violet Phosphorus.

Violet phosphorus (VP), a novel two-dimensional (2D) nanomaterial, boasts structural anisotropy, a tunable optical bandgap, and superior thermal stability compared with its allotropes. Its multifunctionality has sparked widespread interest in the community. Yet, the VP's air susceptibility impedes both probing its intrinsic features and device integration, thus making it of urgent significance to unveil the degradation mechanism. Herein, we conduct a comprehensive study of photoactivated degradation effects on VP. A nitrogen annealing method is presented for the effective elimination of surface adsorbates from VP, as evidenced by a giant surface-roughness improvement from 65.639 nm to 7.09 nm, enabling direct observation of the intrinsic morphology changes induced by photodegradation. Laser illumination demonstrates a significant thickness-thinning effect on VP, manifested in the remarkable morphological changes and the 73% quenching of PL intensity within 160 s, implying its great potential for the efficient selected-area etching of VP at high resolution. Furthermore, van der Waals passivation of VP using 2D hexagonal boron nitride (hBN) was achieved. The hBN-passivated channel exhibited improved surface roughness (0.512 nm), reduced photocurrent hysteresis, and lower responsivity (0.11 A/W @ 450 nm; 2 µW), effectively excluding adsorbate-induced electrical and optoelectrical effects while disabling photodegradation. Based on our experimental results, we conclude that three possible factors contribute to the photodegradation of VP: illumination with photon energy higher than the bandgap, adsorbed H2O, and adsorbed O2.

LFSPROShiny: An Interactive R/Shiny App for Prediction and Visualization of Cancer Risks in Families With Deleterious Germline TP53 Mutations.

PURPOSE: LFSPRO is an R library that implements risk prediction models for Li-Fraumeni syndrome (LFS), a genetic disorder characterized by deleterious germline mutations in the TP53 gene. To facilitate the use of these models in clinics, we developed LFSPROShiny, an interactive R/Shiny interface of LFSPRO that allows genetic counselors (GCs) to perform risk predictions without any programming components and further visualize the risk profiles of their patients to aid the decision-making process. METHODS: LFSPROShiny implements two models that have been validated on multiple LFS patient cohorts: a competing risk model that predicts cancer-specific risks for the first primary and a recurrent-event model that predicts the risk of a second primary tumor. Starting with a visualization template, we keep regular contact with GCs, who ran LFSPROShiny in their counseling sessions, to collect feedback and discuss potential improvement. On receiving the family history as input, LFSPROShiny renders the family into a pedigree and displays the risk estimates of the family members in a tabular format. The software offers interactive overlaid side-by-side bar charts for visualization of the patients' cancer risks relative to the general population. RESULTS: We walk through a detailed example to illustrate how GCs can run LFSPROShiny in clinics from data preparation to downstream analyses and interpretation of results with an emphasis on the utilities that LFSPROShiny provides to aid decision making. CONCLUSION: Since December 2021, we have applied LFSPROShiny to over 100 families from counseling sessions at the MD Anderson Cancer Center. Our study suggests that software tools with easy-to-use interfaces are crucial for the dissemination of risk prediction models in clinical settings, hence serving as a guideline for future development of similar models.

The Impact of Social Media on Users' Self-Efficacy and Loneliness: An Analysis of the Mediating Mechanism of Social Support.

Purpose: The integration of social media into all areas of society has become a typical phenomenon of the Internet era. This study's core objective is to dissect the relationship between social media, self-efficacy and loneliness, especially emphasizing the mediating function of social support. Patients and Methods: The research data is derived from the pooled cross-sectional data combined from the four-period data of the China Family Panel Studies (CFPS). The study employs Ordinary Least Squares (OLS) regression as the basic research method, and utilizes Instrumental Variables (IV) and other methods to conduct robustness checks. Results: Social media usage frequency (SMUF) enhances self-efficacy and loneliness through social support. Social support promotes self-efficacy and alleviates users' loneliness. In self-efficacy, social support plays a fully mediating role. Moreover, education (human capital) has a significant moderating effect. There are noticeable differences in the response of different characteristics groups to SMUF. Conclusion: This study reveals how social media impacts self-efficacy and loneliness through social support. Based on the research results, avoiding prolonged usage of social media and improving digital literacy are the crucial means to exert the positive benefits of social media.

Digital economy development boosts urban resilience-evidence from China.

Focusing on the impact of the digital economy on urban resilience is beneficial to the sustainable development of cities. This paper empirically examines the impact of digital economic development on urban resilience and its mechanisms by measuring urban resilience and the level of urban digital economy with the entropy-weighted TOPSIS method using the data of 252 Chinese cities from 2011 to 2020. The findings show that digital economic development effectively promotes urban resilience at the 1% significance level, and this conclusion remains valid after a series of endogeneity and robustness tests. The channel mechanism suggests that the development of the digital economy can improve urban resilience by optimizing urban distributional effects and promoting the upgrading of urban industrial structures. This paper discusses the nonlinear relationship between the two using the MMQR model and the threshold model. The results show that urban resilience development level is in a higher quartile of cities, and digital economy development has a greater impact on urban resilience improvement. Meanwhile, there are two threshold values for the nonlinear impact of the digital economy on urban resilience, which are 0.026 and 0.082, respectively. Further, the spatial effect between the two is also verified. From the perspective of heterogeneity analysis, the digital economy development of high-class cities, key city clusters, and cities in eastern and western regions has a greater effect on urban resilience. This study can provide ideas and inspiration for countries to enhance urban resilience and promote sustainable urban development through the development of the digital economy.

Radiomics and machine learning based on preoperative MRI for predicting extrahepatic metastasis in hepatocellular carcinoma patients treated with transarterial chemoembolization.

Purpose: To develop and validate a radiomics machine learning (Rad-ML) model based on preoperative MRI to predict extrahepatic metastasis (EHM) in hepatocellular carcinoma (HCC) patients receiving transarterial chemoembolization (TACE) treatment. Methods: A total of 355 HCC patients who received multiple TACE procedures were split at random into a training set and a test set at a 7:3 ratio. Radiomic features were calculated from tumor and peritumor in arterial phase and portal venous phase, and were identified using intraclass correlation coefficient, maximal relevance and minimum redundancy, and least absolute shrinkage and selection operator techniques. Cox regression analysis was employed to determine the clinical model. The best-performing algorithm among eight machine learning methods was used to construct the Rad-ML model. A nomogram combining clinical and Rad-ML parameters was used to develop a combined model. Model performance was evaluated using C-index, decision curve analysis, calibration plot, and survival analysis. Results: In clinical model, elevated neutrophil to lymphocyte ratio and alpha-fetoprotein were associated with faster EHM. The XGBoost-based Rad-ML model demonstrated the best predictive performance for EHM. When compared to the clinical model, both the Rad-ML model and the combination model performed better (C-indexes of 0.61, 0.85, and 0.86 in the training set, and 0.62, 0.82, and 0.83 in the test set, respectively). However, the combined model's and the Rad-ML model's prediction performance did not differ significantly. The most influential feature was peritumoral waveletHLL_firstorder_Minimum in AP, which exhibited an inverse relationship with EHM risk. Conclusions: Our study suggests that the preoperative MRI-based Rad-ML model is a valuable tool to predict EHM in HCC patients treated with TACE.

Carbon nitride quantum dots-modified cobalt phosphate for enhanced photocatalytic H2 evolution.

In the present work, carbon nitride quantum dots (CNQDs)-modified cobalt phosphate (CoPi) composites CNQDs/CoPi-x (x = 1, 2, 3) were prepared at room temperature and characterized by FTIR, XRD, UV-Vis DRS, EIS, SEM, TEM/HR-TEM, XPS, and N2 gas adsorption. The morphologies and surface areas of CNQDs/CoPi-x have no remarkable change after modification of CNQDs, compared with pure CoPi. The obtained CNQDs/CoPi-x shows enhanced activity and stability of photocatalytic H2 evolution compared to pure CoPi using Eosin Y (EY) as a sensitizer and triethanolamine as an electron donor. The CNQDs/CoPi-2 possesses the highest hydrogen evolution rate, 234.5 µmol h-1 g-1 , upon visible light, which outshines that of CoPi by 2.4 times. It was believed that the enhanced photocatalytic performances of the CNQDs/CoPi-2 could result from the boosted electron transfer from radical EY·- to CNQDs/CoPi-2 by the employment of CNQDs; in addition, the visible-light activity of CNQDs contributes to hydrogen evolution. The mechanism of photocatalytic hydrogen production was discussed. This study may contribute toward the development of production of "green hydrogen" using solar.

Injectable dexamethasone-loaded peptide hydrogel for therapy of radiation-induced ototoxicity by regulating the mTOR signaling pathway.

Radiation-induced ototoxicity is associated with inflammation response and excessive reactive oxygen species in the cochlea. However, the effectiveness of many drugs in clinical settings is limited due to anatomical barriers in the inner ear and pharmacokinetic instability. To address this issue, we developed an injectable hydrogel called RADA32-HRN-dexamethasone (RHD). The RHD hydrogel possesses self-anti-inflammatory properties and can self-assemble into nanofibrous structures, ensuring controlled and sustained release of dexamethasone in the local region. Flow cytometry analysis revealed that the uptake of FITC-conjugated RHD gel by hair cells increased in a time-dependent manner. Compared to free dexamethasone solutions, dexamethasone-loaded RHD gel achieved a longer and more controlled release profile of dexamethasone. Additionally, RHD gel effectively protected against the inflammatory response, reduced excessive reactive oxygen species production, and reversed the decline in mitochondrial membrane potentials induced by ionizing radiation, leading to attenuation of apoptosis and DNA damage. Moreover, RHD gel promoted the recovery of outer hair cells and partially restored auditory function in mice exposed to ionizing radiation. These findings validated the protective effects of RHD gel against radiation-induced ototoxicity in both cell cultures and animal models. Furthermore, RHD gel enhanced the activity of the mammalian target of rapamycin (mTOR) signaling pathway, which was inhibited by ionizing radiation, thereby promoting the survival of hair cells. Importantly, intratympanic injections of RHD gel exhibited excellent biosafety and do not interfere with the anti-tumor effects of radiotherapy. In summary, our study demonstrates the therapeutic potential of injectable dexamethasone-loaded RHD hydrogel for the treatment of radiation-induced hearing loss by regulating the mTOR signaling pathway.

Operando Spectroscopy Observation of Mo Clusters-Ti3 C2 TX Catalyst/Support Interface's Dynamic Evolution in Hydrogen Evolution Reaction.

The interaction between catalyst and support plays an important role in electrocatalytic hydrogen evolution (HER), which may explain the improvement in performance by phase transition or structural remodeling. However, the intrinsic behavior of these catalysts (dynamic evolution of the interface under bias, structural/morphological transformation, stability) has not been clearly monitored, while the operando technology does well in capturing the dynamic changes in the reaction process in real time to determine the actual active site. In this paper, nitrogen-doped molybdenum atom-clusters on Ti3 C2 TX (MoACs /N-Ti3 C2 TX ) is used as a model catalyst to reveal the dynamic evolution of MoAcs on Ti3 C2 TX during the HER process. Operando X-ray absorption structure (XAS) theoretical calculation and in situ Raman spectroscopy showed that the Mo cluster structure evolves to a 6-coordinated monatomic Mo structure under working conditions, exposing more active sites and thus improving the catalytic performance. It shows excellent HER performance comparable to that of commercial Pt/C, including an overpotential of 60 mV at 10 mA cm-2 , a small Tafel slope (56 mV dec-1 ), and high activity and durability. This study provides a unique perspective for investigating the evolution of species, interfacial migration mechanisms, and sources of activity-enhancing compounds in the process of electroreduction.