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Aims: This study aims to explore the association between the implementation of the adverse event reporting system (AERS), burnout, and job satisfaction among psychiatric nurses, with a focus on examining the mediating effect of workplace violence from patients. Background: Many organizational and personal factors contribute to burnout and job satisfaction experienced by nurses. AERS, serving as a key component of organizational‐level quality improvement system, impacts the overall workplace wellness of nurses. Methods: A national sample of 9,744 psychiatric nurses from 41 psychiatric hospitals across 29 provinces in China participated. Burnout was measured by the Maslach Burnout Inventory. Job satisfaction was measured using the Minnesota Satisfaction Questionnaire. Workplace violence was assessed by nurses' experience of verbal and physical violence. Multilevel linear regression analyses were carried out to examine if AERS impacts burnout and job satisfaction and to identify the mediating role of workplace violence. Results: AERS was positively associated with job satisfaction, but negatively with burnout and workplace violence. Workplace violence exhibited a positive association with burnout and a negative association with job satisfaction. Mediation analyses indicated that the associations between AERS, burnout, and job satisfaction were mediated by workplace violence. Conclusions: The application of AERS is associated with a reduction in workplace violence in hospitals, which contributes to the diminished burnout and heightened job satisfaction among psychiatric nurses. Implications for nursing practice and health policy: The study highlights the importance of organizational efforts and mechanisms in promoting nurses' well‐being. It is necessary for hospital management to create a safe workplace through the implementation of AERS. [ABSTRACT FROM AUTHOR]

Quantitative analysis of the slip rate of active faults and their seismic parameters is important for seismic hazard analysis. In this study, we first construct an elastic block model to obtain the slip rate of boundary faults based on the distribution characteristics of active faults, seismicity, and global navigation satellite system (GNSS) observations in Sichuan–Yunnan, China. Then, the long-term seismic risks of the boundary faults are quantitatively evaluated based on the principle of seismic moment balance. The Sichuan–Yunnan region can be divided into 17 relatively independent and stable subblocks. There is clear zoning in the distribution and mechanisms of boundary fault movement and deformation. The boundary faults exhibit an alternating dextral–sinistral–dextral–sinistral strike-slip pattern from northeast to southwest. Among these boundary faults, the Xianshuihe–Xiaojiang fault zone has a high sinistral strike-slip rate, and the Jinshajiang fault plays an important role in accommodating the movement and deformation of the subblocks in the Chuandian block. The dextral strike-slip rate is approximately 10 mm/yr, which is diffusely transferred to the secondary boundary faults in the Chuandian block. Comparison of the rates of moment accumulation and release reveals that the southern segment of the Xiaojiang fault, the Longriba fault, the Daliangshan fault, and the Yuanmou fault exhibit significant moment deficits, with corresponding moment magnitudes exceeding Mw 7.5. More attention should be given to the strong earthquake risks of these faults. The Xianshuihe–Xiaojiang, Jiali–Lancangjiang, and Red River faults, which are arc shaped, dominate the regional deformation and determine the motion and deformation model of the subblocks and secondary boundary faults within the Chuandian block and the area southwest of the Red River fault. [ABSTRACT FROM AUTHOR]

Background: Numerous studies indicate that visceral adipose tissue (VAT) significantly contribute to metabolic syndrome (MetS) development. This study aims to assess the distinguishing value of novel obesity markers, specifically lipid accumulation products (LAP) and cardiometabolic index (CMI), in relation to MetS. Considering the gender disparity in MetS prevalence, it is essential to explore whether LAP and CMI exhibit differential distinguishing capabilities by gender. Method: The investigation included a total of 11,687 qualified individuals who participated in the NHANES survey spanning a 14-year period from 2005 to 2018. Biochemical analysis of blood and body measurements were utilized to determine LAP and CMI values for each participant. Inclusion of gender as a variable was a key factor in the examination of all data. Restricted cube plots (RCS) were utilized to analyze the strength of the relationship between LAP, CMI, and MetS. The study delved into potential connections between LAP and CMI with MetS, all-cause and cardiovascular mortality using various statistical models such as multivariate logistic regression and Cox regression. Results: The findings revealed a significant nonlinear association between CMI, LAP, and MetS (P-non-linear < 0.001), irrespective of gender, with all models exhibiting a J-shaped trend. The multivariable logistic regression analysis considered both LAP and CMI as continuous variables or tertiles, revealing significant associations with MetS in male, female, and general populations (All the P < 0.001). Although males displayed a higher risk of MetS, no gender differences were observed in the area under the curve (AUC) values of LAP and CMI for distinguishing (P > 0.005) MetS. Impressively, LAP and CMI were identified as the primary predictors of MetS in both genders from AUC (P < 0.005). More specifically, the cutoff points for distinguishing MetS in females were LAP = 49.87 or CMI = 0.56, while for males, they were LAP = 52.76 or CMI = 0.70. Additionally, the Cox regression analysis revealed that LAP and CMI were correlated with all-cause mortality in both general population and females (P < 0.005), but not in males. Conclusion: In comparison to other measures of obesity, LAP and CMI demonstrated superior diagnostic accuracy for MetS in both males and females. Additionally, LAP and CMI were found to be predictive of all-cause mortality in both general population and females. These markers are cost-effective, easily accessible, and widely applicable for the early identification and screening of MetS in clinical settings. [ABSTRACT FROM AUTHOR]

Background: Obesity and overweight, as determined by the body mass index (BMI), are harmful to metabolic health. However, the BMI can not reflect body composition or fat distribution. The fat-free mass index (FFMI) and the fat mass index (FMI) can provide more information on body composition. The aim of the observational research was to determine whether the FMI and the FFMI are significantly associated with the risk of developing diabetes and prediabetes. Methods: The investigators included data for 10,085 National Health and Nutrition Examination Survey (2011–2018) participants aged over 20 years who underwent dual-energy X-ray absorptiometry (DXA). The FFMI and the FMI were determined based on total fat mass and lean mass measured by DXA. Diabetes and prediabetes status were determined by medical history and laboratory examination. Logistic regression analyses were performed to explore the correlations between the FMI/FFMI and the risk of developing diabetes/prediabetes. Restricted cubic spline analysis was used to explore underlying nonlinear associations. Results: In the present study, 1,135 patients were diagnosed with diabetes, 3,258 had prediabetes, and 5,692 were classified as control participants. The FFMI (odds ratio (OR) = 1.10, 95% confidence interval (CI) = 1.04–1.16) and the FMI (OR = 1.08, 95% CI = 1.04–1.12) were independently related to an increased risk of developing diabetes. Moreover, the FFMI (OR 1.08, 95% CI 1.02–1.16) and the FMI (OR 1.07, 95% CI 1.02–1.13) also independently correlated with a rising risk of developing prediabetes. The restricted cubic spline (RCS) outcomes suggested that the associations are approximately linear. Conclusions: Both the FMI and the FFMI significantly correlated with the danger of developing diabetes and prediabetes, and the correlations are approximately linear. [ABSTRACT FROM AUTHOR]

Pulmonary arterial hypertension (PAH) is a severe cardiopulmonary disease characterized by elevated pulmonary artery pressure and cardiac dysfunction, often leading to heart failure and even death. Despite the complexity of its mechanisms, the molecular basis of PAH remains unclear. tRNA-derived small RNAs (tsRNAs) are noncoding RNAs that play regulatory roles in various diseases. We collected plasma samples from PAH patients and healthy controls for small RNA microarray, and we established a monocrotaline-induced PAH rat model to collect right ventricular and lung tissues for tsRNA sequencing. Our analysis revealed 2,716 unique tsRNAs in human plasma and 4,733 in rat tissues, with a 7.84% overlap. Additionally, 204 tsRNAs were highly conserved across plasma, lung tissue, and right ventricle samples. The reproducibility of the expression profiles was confirmed through Pearson correlation and principal component analysis. KEGG pathway enrichment analysis indicated that tsRNAs are involved in key pathways, such as the MAPK and cancer signalling pathways. These datasets offer valuable insights for researching the epigenetic mechanisms underlying PAH and potential therapeutic targets. [ABSTRACT FROM AUTHOR]

Background: Glomerulonephritis (GN) encompasses a heterogeneous group of kidney diseases, often presenting with subclinical manifestations in children, leading to frequent missed diagnoses. Renal biopsy, while considered the gold standard, is invasive, prone to sampling errors, and time-consuming, thus hindering rapid diagnosis. This study aimed to develop a noninvasive diagnostic model for childhood GN using renal ultrasound images through the integration of deep learning and radiomics techniques. Methods: Ultrasound images were acquired from children undergoing ultrasound-guided biopsy. A total of 469 renal ultrasound images were selected and divided into training and validation sets at a ratio of 8:2 to train a U-Net model for precise kidney image segmentation. Using radiomics, a comprehensive set of radiomic features were extracted from the segmented kidney regions. The extracted features were categorized based on GN types: IgA nephropathy (127 cases), minimal change disease (83 cases), and Henoch–Schönlein purpura nephritis (103 cases). These categories were further randomly split into training and validation sets at a ratio of 8:2. Within the training set, analysis of variance (ANOVA) was used for feature selection, followed by supervised Least Absolute Shrinkage and Selection Operator (LASSO) regression for dimensionality reduction, resulting in the selection of 37 features. These features were then integrated with a random forest algorithm to develop a GN classification model. The model's performance was comprehensively evaluated using the validation set. Results: The segmentation model exhibited remarkable performance during training, achieving an accuracy of 95.19% in the validation set. Thirty-seven features were identified through feature selection, leading to the development of a robust classification model. Evaluation on the validation set revealed high accuracy and predictive power across different GN categories, with Area Under the Curve (AUC) values ranging from 0.91 to 0.98. Conclusions: The combined use of deep learning and radiomics techniques utilizing renal ultrasound images demonstrates significant potential for classifying childhood GN subtypes. This noninvasive approach holds promise for improving diagnostic efficiency and patient outcomes in GN. [ABSTRACT FROM AUTHOR]

Semi-supervised learning has gained significant attention in the field of remote sensing due to its ability to effectively leverage both a limited number of labeled samples and a large quantity of unlabeled data. An effective semi-supervised learning approach utilizes unlabeled samples to enforce prediction consistency under minor perturbations, thus reducing the model's sensitivity to noise and suppressing false positives in change-detection tasks. This principle underlies consistency regularization-based methods. However, while these methods enhance noise robustness, they also risk overlooking subtle but meaningful changes, leading to information loss and missed detections. To address this issue, we introduce a simple yet efficient method called Sample Inflation Interpolation (SII). This method leverages labeled sample pairs to mitigate the information loss caused by consistency regularization. Specifically, we propose a novel data augmentation strategy that generates additional change samples by combining existing supervised change samples with calculated proportions of change areas. This approach increases both the quantity and diversity of change samples in the training set, effectively compensating for potential information loss and reducing missed detections. Furthermore, to prevent overfitting, small perturbations are applied to the generated sample pairs and their labels. Experiments conducted on two public change detection (CD) datasets validate the effectiveness of our proposed method. Remarkably, even with only 5% of labeled training data, our method achieves performance levels that closely approach those of fully supervised learning models. [ABSTRACT FROM AUTHOR]

Purpose: This study examines the relationship between tumor burden score (TBS) and survival and recurrence following radical resection of hepatocellular carcinoma through a cohort study conducted in the Guangxi population of China. Methods: This cohort study eventually recruited 576 HCC patients undergoing radical resection of HCC in the People's Hospital of Guangxi Zhuang Autonomous Region during 2013–2022. After determining the best threshold TBS, all cases were grouped to evaluate the relationship between TBS versus overall survival (OS) and cumulative recurrence. Using X-Tile software, the best threshold TBS to judge patient prognostic outcome following radical resection of HCC was 10.77. Results: Kaplan–Meier curve analysis revealed that patients with high TBS showed considerably decreased OS relative to the control group, accompanied by an increased recurrence rate. According to multivariate Cox proportional regression, the patients with high TBS were associated with poorer OS (HR = 2.56, 95% CI 1.64–3.99, P < 0.001) and recurrence-free survival (RFS) (HR = 1.55, 95% CI 1.02–2.35, P < 0.001). Conclusion: In patients undergoing radical resection for HCC, higher TBS was significantly related to shorter OS and RFS. [ABSTRACT FROM AUTHOR]

Intercropping can increase the utilization rate of light and water and can also improve plant growth. The objective of this study was to investigate the growth and selenium (Se) content in seedlings of three genotypes of cherry tomato under intercropping while applying Se. The pot experiment was conducted in a greenhouse. The monoculture of red, yellow and purple cherry tomato; among the three genotypes of cherry tomatoes, intercropping of two genotypes with each other, at the same time intercropping of three genotypes. These results show that the biomass increased under intercropping compared with monoculture. The chlorophyll b content of purple cherry tomato increased in different intercropping combinations. Furthermore, the net photosynthetic rate, stomatal conductance, and transpiration rate of purple were increased by intercropping with red and purple cherry tomatoes. The soluble protein and soluble sugar contents in yellow and purple cherry tomato increased by 49.13% and 8.37%, respectively, under mutual intercropping. Similarly, soluble sugar increased in purple cherry tomato by intercropping with yellow and red. The activities of superoxide and peroxidase in red and yellow cherry tomato seedlings were higher in all intercropping combinations than in monoculture, whereas free proline content and relative conductivity in all cherry tomatoes decreased. The Se content of roots, stem, and leaves in seedlings increased with intercropping. Therefore, intercropping can improve the growth and Se content of cherry tomatoes, and the combination of red, yellow and purple is better, which can be used to cultivate strong seedlings. [ABSTRACT FROM AUTHOR]

The phosphoric acid (PA) leakage problem has been a major constraint in the practical utilization of PA-doped polybenzimidazole for high-temperature proton exchange membranes (HT-PEMs). Increasing the retaining ability of the proton exchange membranes for free PA while decreasing the amount of PA doping seems to be a viable approach to reduce the possibility of PA leakage. In this work, the mild ester exchange reaction was introduced for the first time to prepare phosphonic acid grafted polybenzimidazoles containing pyridine (g-p-X). The phosphonic acid groups act as transport sites for proton conduction, effectively reducing the need for free PA in g-p-X membranes. Meanwhile, the pyridine immobilizes a portion of the PA through strong ionic interactions, and the membranes exhibit a high PA retention capacity. Among them, the g-p-20 membrane reaches 84.6% PA retention after the 120 h test. Thanks to the dual effects of the phosphonic acid groups and pyridine, the g-p-20 membrane shows a proton conductivity of 42 mS cm−1 at 180 °C without humidification. Moreover, with only 175.3 wt% PA doping, its highest single cell power density achieves 951 mW cm−2 (180 °C). Notably, after 120 h of steady operation at 140 °C, the voltage decay rate of the g-p-20 is only 10 μV h−1. This work presents a viable concept for addressing the problem of PA leakage from HT-PEMs in long-term operation. [ABSTRACT FROM AUTHOR]

Background: Mental health symptoms such as anxiety, depression, stress, and burnout are common among healthcare workers. However, the interconnections among them remain under-explored. This study aimed to address the interrelationships among these symptoms in psychiatric nurses. Methods: We conducted a nationwide survey in the early stage of the COVID-19 pandemic (January to March 2021) to investigate the interconnectedness of depression, anxiety, stress, and burnout among psychiatric nurses. Using network analysis, we identified central symptoms, important bridge symptoms, and the correlations among these central symptoms. Results: Of the 9,224 psychiatric nurses (79.2% female) included in the statistical analyses, 27.6% reported clinically significant depression, 31.2% anxiety, 14.5% stress, and 23.8% burnout. Network analysis revealed that stress had the highest expected influence (EI) value (0.920) and the highest strength among all nodes. The node for depression scored the highest in both closeness and betweenness. Emotional exhaustion (EE) had the highest bridge expected influence (BEI) of 0.340, with the strongest intergroup association between EE and depression. No significant differences were found in gender or frontline work experience (all p > 0.05). Conclusions: Burnout, depression, anxiety, and stress are relatively common among psychiatric nurses in the context of the COVID-19 pandemic. While anxiety was the most prevalent, stress emerged as the core symptom, and depression as an important bridging node. Interventions targeting the core symptoms and bridging nodes may improve the mental health of psychiatric nurses. [ABSTRACT FROM AUTHOR]

Background: Mental health symptoms such as anxiety, depression, stress, and burnout are common among healthcare workers. However, the interconnections among them remain under-explored. This study aimed to address the interrelationships among these symptoms in psychiatric nurses. Methods: We conducted a nationwide survey in the early stage of the COVID-19 pandemic (January to March 2021) to investigate the interconnectedness of depression, anxiety, stress, and burnout among psychiatric nurses. Using network analysis, we identified central symptoms, important bridge symptoms, and the correlations among these central symptoms. Results: Of the 9,224 psychiatric nurses (79.2% female) included in the statistical analyses, 27.6% reported clinically significant depression, 31.2% anxiety, 14.5% stress, and 23.8% burnout. Network analysis revealed that stress had the highest expected influence (EI) value (0.920) and the highest strength among all nodes. The node for depression scored the highest in both closeness and betweenness. Emotional exhaustion (EE) had the highest bridge expected influence (BEI) of 0.340, with the strongest intergroup association between EE and depression. No significant differences were found in gender or frontline work experience (all p > 0.05). Conclusions: Burnout, depression, anxiety, and stress are relatively common among psychiatric nurses in the context of the COVID-19 pandemic. While anxiety was the most prevalent, stress emerged as the core symptom, and depression as an important bridging node. Interventions targeting the core symptoms and bridging nodes may improve the mental health of psychiatric nurses. [ABSTRACT FROM AUTHOR]

Background: G1, a specific agonist targeting the G protein–coupled receptor 30 (GPR30), has demonstrated significant involvement in combating obesity and regulating glucose homeostasis. Nevertheless, the beneficial effects of G1 treatment have solely been investigated in animal models under normal feeding conditions, leaving its therapeutic potential in high‐fat feeding scenarios unexplored. Material and Methods: To address this gap, our study employed an ovariectomized high‐fat diet mouse model to assess the therapeutic effects of G1 in combating obesity and metabolic dysfunction. Results: The findings revealed that G1 treatment resulted in weight loss, but concurrently led to increased blood glucose levels and insulin resistance. Treatment with G1 resulted in an amplification of fat mobilization and an enhancement of pyruvate carboxylase activity in mice fed a high‐fat diet. Moreover, the combined impact of G1 treatment and a high‐fat diet on pyruvate metabolism, as well as the regulation of crucial gluconeogenesis enzymes such as pyruvate dehydrogenase kinase 4 (PDK4), phosphoenolpyruvate carboxykinase (PEPCK), and glucose transporter 2 (GLUT2), expedites the elevation of blood glucose and the progression of insulin resistance. Conclusions: These findings indicate that G1 treatment is influenced by a high‐fat diet, potentially disrupting glucolipid metabolism and promoting insulin resistance alongside its antiobesity effects. Consequently, further investigation is imperative to thoroughly explore this potential toxic side effect of G1 therapy. [ABSTRACT FROM AUTHOR]

A nonlinear energy sink (NES) has such advantages as controlling broader band responses and better robustness than conventional control devices like tuned mass dampers (TMDs). In this research, a cubic stiffness NES mitigating the dynamic responses of a multi-degree-of-freedom structure under white noise, harmonic and seismic excitations was tested using a shake table, and the influences of the parameters of the NES on vibration mitigation effects were investigated. The test results indicate that the NES has the same vibration mitigation effects on the acceleration responses under the white noise and harmonic excitations as TMDs, even though the mass ratio of the NES is less than that of a TMD. The average control effects of the NES on the acceleration responses of the structure under the effect of 100 seismic waves are better than those of a TMD, which indicates that an NES has better robustness than a TMD. [ABSTRACT FROM AUTHOR]

Saline–alkali (SA) stress is an abiotic stress that exists widely in the natural environment, seriously affecting the growth and development of crops. Tiger nut (Cyperus esculentus L.), a perennial herb of Cyperus in Cyperaceae, is considered a pioneer crop for growing and improving SA land due to its excellent adaptability and SA tolerance. This study is the first to evaluate the SA tolerance of tiger nut and the alleviative effects of nanomaterials (nano-selenium and multi-walled carbon nanotubes) and Arbuscular mycorrhizas (AMs) on SA stress. The results showed that the seedling fresh weight of tiger nut was the most suitable parameter to describe the dose–response effect of plant growth with increased SA concentration. Based on the log-logistic dose–response curve, the GR50 values of NaCl and NaHCO3 (the concentrations causing a 50% reduction in seedling fresh weight) were determined to be 163 mmol L−1 and 63 mmol L−1, respectively. Under these stresses, the exogenous application of MWCNTs at 100 mg L−1 or Nano-Se at 10 mg L−1 showed that the effect of SA on tiger nut was alleviated. Field evaluation further showed that the exogenous application of MWCNTs, Nano-Se, or AMs could effectively alleviate SA stress on tiger nut. Compared to the untreated control, the application of these substances significantly improved the plant photosynthesis-related parameter, antioxidant enzyme activity, plant height (height: 66.0–69.9 cm), tuber yield (yield: 23.4–27.4 g plant−1), and oil quality of tiger nut under SA stress. The results of this study indicate that the application of MWCNTs, Nano-Se, or AMs, to tiger nut can alleviate SA stress and maintain seed yield, providing the possibility of using these nanoparticles to improve the SA tolerance of tiger nut in agricultural practice. [ABSTRACT FROM AUTHOR]

As the large-scale development of wind farms (WFs) progresses, the connection of WFs to the regional power grid is evolving from the conventional receiving power grid to the sending power grid with a high proportion of wind power (WP). Due to the randomness of WP output, higher requirements are put forward for the voltage stability of each node of the regional power grid, and various reactive power compensation devices (RPCDs) need to be rationally configured to meet the stable operation requirements of the system. This paper proposes an optimal configuration method for multi-type RPCDs in regional power grids with a high proportion of WP. The RPCDs are located according to the proposed static voltage stability index (VSI) and dynamic VSI based on dynamic voltage drop area, and the optimal configuration model of RPCDs is constructed with the lowest construction cost as the objective function to determine the installed capacity of various RPCDs. Finally, the corresponding regional power grid model for intensive access to WFs is constructed on the simulation platform to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a gradient-based optimisation method of antenna array for null controlling in specific regions and sidelobe suppression. The optimisation problem is formulated as optimising the electronic control parameters (excitation amplitude and phase) of the array to achieve that the maximum value of the peak sidelobe levels (PSLLs) is minimised and the depths of the nulls in specific regions are not greater than a threshold. The Kreisselmeier – Steinhauser (KS) function is used to describe the maximum value of the PSLLs, in this way, the optimisation problem becomes differentiable and can be solved efficiently by gradient-based algorithm. The sensitivities of the objective with respect to the design variables are analytically derived. Typical numerical examples and detailed evaluations are provided to validate the effectiveness of the proposed method. The results show that the null controlling in the predefined specific single, single-wide, dual, multiple, and annular regions is realised, and the PSLL suppression is performed comparing to the uniform planar arrays. In the 28 GHz base station transmitting antenna-array example, the proposed method effectively suppresses the PSLL and greatly saves the calculation time while maintaining the various specific null regions controlling. [ABSTRACT FROM AUTHOR]

We introduce a measure of regret for stock market investors and investigate its cross-sectional asset pricing implications. According to our regret-based framework, investors experience regret due to not achieving the highest possible return from a similar set of stock investments, and equity portfolios with high regret generate 6.84% more annualized alpha than portfolios with low regret. Using investor-trading activity of 78,000 households at a large U.S.-based brokerage firm, we develop an investor-based regret index and show that this household-level regret measure predicts stock returns in a similar way to our proposed regret measure. We also show that regret is not spanned by established risk or behavioral factors that have been documented to be robust predictors of equity returns. This paper was accepted by David Sraer, finance. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.03389. [ABSTRACT FROM AUTHOR]

Paper-based cultural relics inevitably face a variety of diseases such as acidification, yellowing, and strength loss during long-term preservation, where weakly alkaline inorganic materials play an important role in their deacidification treatments. In this work, by simply adjusting the supersaturation of crystal growing solution without the use of any organic additives, one-dimensional (1D) and two-dimensional (2D) weakly alkaline materials—magnesium carbonate hydrates (MCHs)—were controllably synthesized. It is worth noting that the coatings of 1D/2D MCHs not only cause little change in chromatic aberration and water wettability, but also ensure their safety for alkali-sensitive pigments. Meanwhile, the deacidification, anti-aging, strength-enhancing, and flame-retardant effects of these materials have been tested on ancient book papers, all of which achieved good protective effects. In contrast, 1D MCH materials brought about significant enhancement in both mechanical strengths and flame-retardant effects, and the related effects were investigated. Based on this facile micromorphology control strategy, more low-dimensional nanomaterials are expected to be synthesized by design for the protection of paper-based relics, which will expand our knowledge on functional deacidification and protection mechanisms. [ABSTRACT FROM AUTHOR]

Background: Dementia with Lewy Bodies (DLB) is a complex neurodegenerative disorder that often overlaps clinically with Alzheimer's disease (AD), presenting challenges in accurate diagnosis and underscoring the need for novel biomarkers. Lipidomic emerges as a promising avenue for uncovering disease-specific metabolic alterations and potential biomarkers, particularly as the lipidomics landscape of DLB has not been previously explored. We aim to identify potential diagnostic biomarkers and elucidate the disease's pathophysiological mechanisms. Methods: This study conducted a lipidomic analysis of plasma samples from patients with DLB, AD, and healthy controls (HCs) at Xuanwu Hospital. Untargeted plasma lipidomic profiling was conducted via liquid chromatography coupled with mass spectrometry. Machine learning methods were employed to discern lipidomic signatures specific to DLB and to differentiate it from AD. Results: The study enrolled 159 participants, including 57 with AD, 48 with DLB, and 54 HCs. Significant differences in lipid profiles were observed between the DLB and HC groups, particularly in the classes of sphingolipids and phospholipids. A total of 55 differentially expressed lipid species were identified between DLB and HCs, and 17 between DLB and AD. Correlations were observed linking these lipidomic profiles to clinical parameters like Unified Parkinson's Disease Rating Scale III (UPDRS III) and cognitive scores. Machine learning models demonstrated to be highly effective in distinguishing DLB from both HCs and AD, achieving substantial accuracy through the utilization of specific lipidomic signatures. These include PC(15:0_18:2), PC(15:0_20:5), and SPH(d16:0) for differentiation between DLB and HCs; and a panel includes 13 lipid molecules: four PCs, two PEs, three SPHs, two Cers, and two Hex1Cers for distinguishing DLB from AD. Conclusions: This study presents a novel and comprehensive lipidomic profile of DLB, distinguishing it from AD and HCs. Predominantly, sphingolipids (e.g., ceramides and SPHs) and phospholipids (e.g., PE and PC) were the most dysregulated lipids in relation to DLB patients. The lipidomics panels identified through machine learning may serve as effective plasma biomarkers for diagnosing DLB and differentiating it from AD dementia. [ABSTRACT FROM AUTHOR]

Background: The pedagogy of computational thinking has gained extensive traction across numerous nations globally, with a particular emphasis on nurturing computational thinking in the formative years of early childhood. Nevertheless, the efficacy of diverse instructional approaches in the domain of programming education, with regards to fostering the advancement of computational thinking abilities in young children, remains a subject of ongoing debate. Objectives: The primary aim of this research is to evaluate the efficacy of programming education in fostering computational thinking skills in young children. The central focus revolves around a meticulous exploration of the influence exerted by diverse modalities of programming education on the cultivation of computational thinking abilities in early learners. Methods: A total of 32 empirical studies were incorporated into the analysis. Out of these, 77 effect sizes were deemed to meet the predefined inclusion criteria for the present study. The statistical analysis was executed utilizing Stata version 17.0 software. Results and Conclusions: The acquisition of programming skills can enhance the advancement of computational thinking in young children (Hedges's g = 0.49, 95% confidence interval [0.40, 0.58]), thereby yielding a moderate effect. When considering the triad of programming education modalities, it becomes evident that graphical programming surpasses both tangible programming and unplugged programming in terms of its efficacy in fostering the growth of computational thinking in young learners. Implications: The foregoing contributes significantly to the systematic cultivation and augmentation of computational thinking skills in young children. It establishes a foundational framework for early childhood educators and instructional tool designers to effectively and purposefully impart programming knowledge to children. Lay Description: What is already known about this topic?: Computational thinking represents a fundamental skill that should be universally acquired, with the cultivation of this cognitive capacity during early childhood deemed an indispensable prerequisite for one's future endeavours.The influence of programming education on the development of computational thinking in young children is a multifaceted outcome, arising from an intricate interplay of various factors.The practical implementation of computational thinking within preschool education remains at an exploratory stage, beset by numerous challenges. What this paper adds?: Programming education moderately fosters the advancement of computational thinking in young children.Different types of programming education have varying effects on the computational thinking of young children.Graphical programming emerges as a superior modality for fostering computational thinking in young children. Implications for practice and/or policy: The strategic utilization of programming education modalities tailored to the unique learning styles and developmental characteristics of children emerges as a strategically advantageous approach for nurturing the advancement of their computational thinking abilities.Programming education for preschoolers is inherently intertwined with the indispensable support and expert guidance provided by educators and other professionals. [ABSTRACT FROM AUTHOR]

In the field of Meta-Learning, traditional methods for addressing few-shot learning problems often rely on leveraging prior knowledge for rapid adaptation. However, when faced with insufficient data, meta-learning models frequently encounter challenges such as overfitting and limited feature extraction capabilities. To overcome these challenges, an innovative meta-learning approach based on Sparse Dictionary and Consistency Learning (SDCL) is proposed. The distinctive feature of SDCL is the integration of sparse representation and consistency regularization, designed to acquire both broadly applicable general knowledge and task-specific meta-knowledge. Through sparse dictionary learning, SDCL constructs compact and efficient models, enabling the accurate transfer of knowledge from the source domain to the target domain, thereby enhancing the effectiveness of knowledge transfer. Simultaneously, consistency regularization generates synthetic data similar to existing samples, expanding the training dataset and alleviating data scarcity issues. The core advantage of SDCL lies in its ability to preserve key features while ensuring stronger generalization and robustness. Experimental results demonstrate that the proposed meta-learning algorithm significantly improves model performance under limited training data conditions, particularly excelling in complex cross-domain tasks. On average, the algorithm improves accuracy by 3%. [ABSTRACT FROM AUTHOR]

Purpose: We performed the study to investigate the association between heart rate (HR) non-dipping pattern and target organ damage in patients with chronic kidney disease (CKD) and hypertension. Methods: In this cross-sectional study, 447 patients with CKD and hypertension were enrolled. 24 h ambulatory blood pressure monitoring was conducted. Linear regression and logistic regression analysis were conducted to investigate the association between HR non-dipping pattern and target organ damage, including estimated glomerular filtration rate (eGFR), left ventricular mass index (LVMI), and left ventricular hypertrophy (LVH). Results: Overall, 261 patients (58.4%) followed non-dipping patterns of HR. HR non-dipping pattern remained to be significantly associated with reduced eGFR (β: −0.384; 95% CI: −0.719 to −0.050; p = 0.025) and the higher prevalence of CKD stages 4–5 (OR: 2.141; 95% CI: 1.153 to 3.977; p = 0.016). Meanwhile, HR non-dipping pattern was independently associated with LVMI (β: 0.021; 95% CI: 0.000 to 0.041; p = 0.049) and LVH (OR: 1.78; 95% CI: 1.07 to 2.96; p = 0.027) after adjusting for confounding factors. Conclusions: HR non-dipping pattern was independently associated with impaired renal function and cardiac damage. Non-dipping HR deserves further attention and needs to be detected and treated during the management of CKD patients. [ABSTRACT FROM AUTHOR]

Synaptojanin 2 (SYNJ2) has crucial role in various tumors, but its role in papillary thyroid carcinoma (PTC) remains unexplored. This study first detected SYNJ2 protein expression in PTC using immunohistochemistry method and further assessed SYNJ2 mRNA expression through mRNA chip and RNA sequencing data and its association with clinical characteristics. Additionally, KEGG, GSVA, and GSEA analyses were conducted to investigate potential biological functions, while single‐cell RNA sequencing data were used to explore SYNJ2's underlying mechanisms in PTC. Meanwhile, immune infiltration status in different SYNJ2 expression groups were analyzed. Besides, we investigated the immune checkpoint gene expression and implemented drug sensitivity analysis. Results indicated that SYNJ2 is highly expressed in PTC (SMD = 0.66 [95% CI: 0.17–1.15]) and could distinguish between PTC and non‐PTC tissues (AUC = 0.74 [0.70–0.78]). Furthermore, the study identified 134 intersecting genes of DEGs and CEGs, mainly enriched in the angiogenesis and epithelial‐mesenchymal transition (EMT) pathways. Subsequent analysis showed the above pathways were activated in PTC epithelial cells. PTC patients with high SYNJ2 expression showed higher sensitivity to the six common drugs. Summarily, SYNJ2 may promote PTC progression through angiogenesis and EMT pathways. High SYNJ2 expression is associated with better response to immunotherapy and chemotherapy. [ABSTRACT FROM AUTHOR]

Background: Periprosthetic bone loss is a well‐known phenomenon following total hip arthroplasty (THA). However, the choice of drugs for prevention remains controversial. Therefore, the aim of this study was to determine the best drug to treat periprosthetic bone loss by comparing changes in bone mineral density (BMD) at different times after THA. Methods: A comprehensive search of five databases and two clinical trial registration platforms was undertaken from their inception through to August 31, 2023 to identify eligible randomized controlled trials. A Bayesian network meta‐analysis (NMA) was carried out for calculating the standardized mean difference (SMD) and the surface under cumulative ranking curve (SUCRA) of the BMD in calcar (Gruen zone 7) at 6 months, 12 months, and 24 months and over. Results: Twenty‐nine trials involving 1427 patients and 10 different interventions were included. The results demonstrated that at 6 months, denosumab had the highest ranking (SUCRA = 0.90), followed by alendronate (SUCRA = 0.76), and zoledronate (SUCRA = 0.73). At 12 months, clodronate ranked highest (SUCRA = 0.96), followed by denosumab (SUCRA = 0.84) and teriparatide (SUCRA = 0.82). For interventions with a duration of 24 months and over, denosumab had the highest SUCRA value (SUCRA = 0.96), followed by raloxifene (SUCRA = 0.90) and zoledronate (SUCRA = 0.75). Conclusion: Investigating the existing body of evidence revealed that denosumab demonstrates potential as an intervention of superior efficacy at the three specifically examined time points. However, it remains crucial to conduct further research to confirm these findings and determine the most effective treatment strategy. [ABSTRACT FROM AUTHOR]

By integrating TiO2 with rare earth upconversion nanocrystals (NaREF4), efficient energy transfer can be achieved between the two subunits under near‐infrared (NIR) excitation, which hold tremendous potential in the fields of photocatalysis, photodynamic therapy (PDT), etc. However, in the previous studies, the combination of TiO2 with NaREF4 is a non‐epitaxial random blending mode, resulting in a diminished energy transfer efficiency between the NaREF4 and TiO2. Herein, we present a fluorine doping‐mediated epitaxial growth strategy for the synthesis of TiO2‐NaREF4 heteronanocrystals (HNCs). Due to the epitaxial growth connection, NaREF4 can transfer energy through phonon‐assisted pathway to TiO2, which is more efficient than the traditional indirect secondary photon excitation. Additionally, F doping brings oxygen vacancies in the TiO2 subunit, which further introduces new impurity energy levels in the intrinsic band gap of TiO2 subunit, and facilitates the energy transfer through phonon‐assisted method from NaREF4 to TiO2. As a proof of concept, TiO2‐NaGdF4 : Yb,Tm@NaYF4@NaGdF4 : Nd@NaYF4 HNCs were rationally constructed. Taking advantage of the dual‐model up‐ and downconversion luminescence of the delicately designed multi‐shell structured NaREF4 subunit, highly efficient photo‐response capability of the F‐doped TiO2 subunit and the efficient phonon‐assisted energy transfer between them, the prepared HNCs provide a distinctive nanoplatform for bioimaging‐guided NIR‐triggered PDT. [ABSTRACT FROM AUTHOR]

Background: Transcranial alternating current stimulation (tACS) could improve cognition in patients with Alzheimer's disease (AD). However, the effects of tACS on brain activity remain unclear. Objective: The purpose is to investigate the change in regional neuronal activity after tACS in AD patients employing resting-state functional magnetic resonance imaging (rs-fMRI). Methods: A total of 46 patients with mild AD were enrolled. Each patient received 30 one-hour sessions of real or sham tACS for three weeks (clinical trial: NCT03920826). The fractional amplitude of low-frequency fluctuations (fALFF) and the regional homogeneity (ReHo) measured by rs-fMRI were calculated to evaluate the regional brain activity. Results: Compared to baseline, AD patients in the real group exhibited increased fALFF in the left middle frontal gyrus-orbital part and right inferior frontal gyrus-orbital part, as well as increased ReHo in the left precentral gyrus and right middle frontal gyrus at the end of intervention. At the 3-month follow-up, fALFF increased in the left superior parietal lobule and right inferior temporal gyrus, as well as ReHo, in the left middle frontal gyrus and right superior medial frontal gyrus. A higher fALFF in the right lingual gyrus and ReHo in the right parahippocampal gyrus were observed in the response group than in the nonresponse group. Conclusions: The findings demonstrated the beneficial effects of tACS on the neuronal activity of the prefrontal cortex and even more extensive regions and provided a neuroimaging biomarker of treatment response in AD patients. [ABSTRACT FROM AUTHOR]

By integrating TiO2 with rare earth upconversion nanocrystals (NaREF4), efficient energy transfer can be achieved between the two subunits under near‐infrared (NIR) excitation, which hold tremendous potential in the fields of photocatalysis, photodynamic therapy (PDT), etc. However, in the previous studies, the combination of TiO2 with NaREF4 is a non‐epitaxial random blending mode, resulting in a diminished energy transfer efficiency between the NaREF4 and TiO2. Herein, we present a fluorine doping‐mediated epitaxial growth strategy for the synthesis of TiO2‐NaREF4 heteronanocrystals (HNCs). Due to the epitaxial growth connection, NaREF4 can transfer energy through phonon‐assisted pathway to TiO2, which is more efficient than the traditional indirect secondary photon excitation. Additionally, F doping brings oxygen vacancies in the TiO2 subunit, which further introduces new impurity energy levels in the intrinsic band gap of TiO2 subunit, and facilitates the energy transfer through phonon‐assisted method from NaREF4 to TiO2. As a proof of concept, TiO2‐NaGdF4 : Yb,Tm@NaYF4@NaGdF4 : Nd@NaYF4 HNCs were rationally constructed. Taking advantage of the dual‐model up‐ and downconversion luminescence of the delicately designed multi‐shell structured NaREF4 subunit, highly efficient photo‐response capability of the F‐doped TiO2 subunit and the efficient phonon‐assisted energy transfer between them, the prepared HNCs provide a distinctive nanoplatform for bioimaging‐guided NIR‐triggered PDT. [ABSTRACT FROM AUTHOR]

Duck circovirus (DuCV) is one of the most prevalent infectious viruses in the duck industry in China. Although the clinical signs vary, it often causes immunosuppression in the host and leads to secondary infection with other pathogens. Novel goose parvovirus (NGPV) mainly infects ducks and causes short beak and dwarfism syndrome in ducks. However, the incidence of infection in ducks has increased in recent years, and the phenomenon of mixed infection with DuCV is common, resulting in more severe clinical morbidity. However, there are no systematic studies evaluating the presence of mixed infections. In order to investigate the synergistic pathogenicity of DuCV and NGPV co-infection in SPF ducks, a comparative experiment using DuCV and NGPV co-infection and mono-infection bird models was established. The results showed that the clinical signs of short beak, dwarfism and immunosuppression were more obvious in DuCV and NGPV co-infected ducks; the tissue damage of target organs was more serious, and the viral titre in organs and cloacal swabs were more significant compared with those of SPF ducks infected with only one virus. The results indicated that co-infection with DuCV and NGPV could promote viral replication and cause more severe tissue damage and immunosuppression than single virus infection. The present study reveals that the co-infection of NGPV and DuCV has a synergistic pathogenic effect from the aspect of pathogenicity, and the conclusions drawn not only clarify the direction of the subsequent research on the mechanism of co-infection of NGPV and DuCV, but also provide a scientific basis for the research on the co-infection of immunosuppressive pathogens and other pathogens. [ABSTRACT FROM AUTHOR]

We document distinctly different clientele effects on investor attention and return responses to information. Macro news crowds out retail investor attention to firms' earnings news by 49%. For stocks with high retail ownership, macro news dampens earnings announcement returns by 17% and substantially increases post-announcement drift, especially during high VIX periods. In contrast, macro news increases institutional investor attention to scheduled earnings announcements but not their attention to unscheduled analysts' forecast revisions. The findings confirm the implications of rational inattention models and highlight the importance of considering clientele effects in understanding the effect of news on attention and asset prices. [ABSTRACT FROM AUTHOR]

Objective: Suicidality is a common and serious symptom of depression and patients with depression and suicidality often respond to electroconvulsive therapy (ECT), but the mechanism of its effect is poorly understood. We used resting-state functional magnetic resonance imaging (rs-fMRI) to explore changes in brain connectivity before and after ECT in depressed patients with suicidality. Methods: Twenty-three depressed patients with suicidality underwent rs-fMRI at baseline and after 8–12 ECT sessions. Thirty-two age-, sex-, and education-matched healthy controls (HCs) underwent rs-fMRI once. We used functional connectivity (FC) analysis to identify brain regions with altered connectivity in patients compared to HCs and assess changes in FC before and after ECT. We also assessed the clinical symptoms using the Hamilton Depression Scale, 17-item (HAMD-17), and Beck Scale for Suicide Ideation (BSSI). Results: Compared to HCs, at baseline, patients had reduced FC between the left orbitofrontal cortex (OFC_ Ant_L) and left angular gyrus (Angular_L) (t = 3.849, P < 0.05) with OFC_Ant_L as ROI. With left superior frontal gyrus (Frontal_sup_L) as ROI, patients also had reduced FC between Frontal_sup_L and left superior medial frontal gyrus, medial orbital (Frontal_Med_Orb_L) and left precuneus (Precuneus_L) (t = 3.650, P < 0.05), and increased FC between Frontal_sup_L and right middle frontal gyrus (Frontal_Mid_R) (t = -4.220, P < 0.05). After ECT, with Frontal_sup_L as ROI, patients showed increased FC between Frontal_sup_L and Angular_L after ECT (t = -3.982, P < 0.05) and decreased FC between Frontal_sup_L and right superior and inferior parietal gyrus (Parietal_Sup&Inf_R). In ECT responders, the change in FC between Frontal_sup_L and Angular_L was negatively correlated with the change of the score of BSSI (r = -0.645, P = 0.042), and the change in FC between Frontal_sup_L and Parietal_Sup&Inf_R was positively correlated with the change of the score of BSSI (r = 0.714, P = 0.023). There was no correlation between changes in FC with changes in HAMD-17 score (all P > 0.05). Conclusion: Our findings suggest that FC between Frontal_sup_L and Angular_L, and FC between Frontal_sup_L and Parietal_Sup&Inf_R may be involved in the mechanisms by which ECT exerts its effects on suicidality in patients with depression. Our findings provide insights into the neural underpinnings of ECT and may inform the development of more targeted novel therapeutic strategies for suicidality. Trial registration: Chinese Clinical Trial Registry, ChiCTR2100048182, Registered 04 July 2021, www.chictr.org.cn [ABSTRACT FROM AUTHOR]

Recent evidence has demonstrated that abnormal expression and regulation of circular RNA (circRNAs) are implicated in the development and progression of various tumors. The aim of this study was to investigate the effects of circ_SMA4 in Gastrointestinal Stromal Tumors (GISTs) malignant progression. Human circRNAs microarray analysis was conducted to identify differentially expressed (DE) circRNAs in GISTs. The effect of circ_SMA4 on cell proliferation, invasion, migration, and apoptosis was assessed in both in vitro and in vivo settings. Dual-luciferase reporter assay, RT-qPCR, Western-blot, and rescue assay were employed to confirm the interaction between circ_SMA4/miR-494-3p/ KIT axis. The results revealed that circ_SMA4 was significantly upregulated in GISTs, and exhibited high diagnostic efficiency with an AUC of 0.9824 (P < 0.01). circ_SMA4 promoted cell proliferation, invasion, migration, while inhibiting apoptosis in GISTs cells, both in vitro and in vivo. Silencing circ_SMA4 partially inhibited GISTs malignant progression. Additionally, circ_SMA4 acted as a competing endogenous RNA (ceRNA) by targeting miR-494-3p, and KIT was identified as a functional gene for miR-494-3p in GISTs. Furthermore, the results confirmed that circ_SMA4/miR-494-3p/ KIT axis plays a role in activating the JAK/STAT signaling pathway in GISTs. Therefore, for the first time, we have identified and emphasized that circ_SMA4 is significantly upregulated and plays an oncogenic role in GISTs by sponging miR-494-3p to activate the KIT/JAK/STAT pathway. These findings underscore circ_SMA4 may serve as a novel diagnostic biomarker and therapeutic target for GISTs. [ABSTRACT FROM AUTHOR]

Background: The post-processing technology of CTA offers significant advantages in evaluating left atrial enlargement (LAE) in patients with persistent atrial fibrillation (PAF). This study aims to identify parameters for rapidly and accurately diagnosing LAE in patients with PAF using CT cross-sections. Methods: Left atrial pulmonary venous (PV) CT was performed to 300 PAF patients with dual-source CT, and left atrial volume (LAV), left atrial anteroposterior diameter (LAD1), left atrial transverse diameter (LAD2), and left atrial area (LAA) were measured in the ventricular end systolic (ES) and middle diastolic (MD). LA index (LAI) = LA parameter/body surface area (BSA). Left atrial volume index (LAVIES) > 77.7 ml/m2 was used as the reference standard for the LAE diagnosis. Results: 227 patients were enrolled in the group, 101 (44.5%) of whom had LAE. LAVES and LAVMD (r = 0.983), LAVIES and LAVIMD (r = 0.984), LAAES and LAVIES (r = 0.817), LAAMD and LAVIES (r = 0.814) had strong positive correlations. The area under curve (AUC) showed that all measured parameters were suitable for diagnosing LAE, and the diagnostic efficacy was compared as follows: LAA/LAAI> LAD> the relative value index of LAD, LAD2> LAD1. LAA and LAAI demonstrated comparable diagnostic efficacy, with LAA being more readily available than LAAI. Conclusions: The axial LAA measured by CTA can be served as a parameter for the rapid and accurate diagnosis of LAE in patients with PAF. [ABSTRACT FROM AUTHOR]

Background Cancer-related deaths for people with human immunodeficiency virus (PWH) are increasing due to longer life expectancies and disparately poor cancer-related outcomes. We hypothesize that advanced biological aging contributes to cancer-related morbidity and mortality for PWH and cancer. We sought to determine the impact of clonal hematopoiesis (CH) on cancer disparities in PWH. Methods We conducted a retrospective study to compare the prevalence and clinical outcomes of CH in PWH and people without HIV (PWoH) and cancer. Included in the study were PWH and similar PWoH based on tumor site, age, tumor sequence, and cancer treatment status. Biological aging was also measured using epigenetic methylation clocks. Results In 136 patients with cancer, PWH had twice the prevalence of CH compared to similar PWoH (23% vs 11%, P =.07). After adjusting for patient characteristics, PWH were 4 times more likely than PWoH to have CH (odds ratio, 4.1 [95% confidence interval, 1.3–13.9]; P =.02). The effect of CH on survival was most pronounced in PWH, who had a 5-year survival rate of 38% if they had CH (vs 59% if no CH), compared to PWoH who had a 5-year survival rate of 75% if they had CH (vs 83% if no CH). Conclusions This study provides the first evidence that PWH may have a higher prevalence of CH than PWoH with the same cancers. CH may be an independent biological aging risk factor contributing to inferior survival for PWH and cancer. [ABSTRACT FROM AUTHOR]

Background: The mechanistic effects of gamma transcranial alternating current stimulation (tACS) on hippocampal gamma oscillation activity in Alzheimer's Disease (AD) remains unclear. This study aimed to clarify beneficial effects of gamma tACS on cognitive functioning in AD and to elucidate effects on hippocampal gamma oscillation activity. Methods: This is a double-blind, randomized controlled single-center trial. Participants with mild AD were randomized to tACS group or sham group, and underwent 30 one-hour sessions of either 40 Hz tACS or sham stimulation over consecutive 15 days. Cognitive functioning, structural magnetic resonance imaging (MRI), and simultaneous electroencephalography–functional MRI (EEG-fMRI) were evaluated at baseline, the end of the intervention and at 3-month follow-up from the randomization. Results: A total of 46 patients were enrolled (23 in the tACS group, 23 in the sham group). There were no group differences in the change of the primary outcome, 11-item cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS-Cog) score after intervention (group*time, p = 0.449). For secondary outcomes, compared to the control group, the intervention group showed significant improvement in MMSE (group*time, p = 0.041) and MoCA scores (non-parametric test, p = 0.025), which were not sustained at 3-month follow-up. We found an enhancement of theta-gamma coupling in the hippocampus, which was positively correlated with improvements of MMSE score and delayed recall. Additionally, fMRI revealed increase of the local neural activity in the hippocampus. Conclusion: Effects on the enhancement of theta-gamma coupling and neural activity within the hippocampus suggest mechanistic models for potential therapeutic mechanisms of tACS. Trial registration: ClinicalTrials.gov, NCT 03920826; Registration Date: 2019-04-19. [ABSTRACT FROM AUTHOR]

Plant community succession can impact greenhouse gas (GHG) emissions from the soil by altering the soil carbon and nitrogen cycles. However, the effects of community landscape diversity on soil GHG emissions have rarely been fully understood. Therefore, this study investigated how plant landscape diversity, structure type, and species composition, affect soil GHG emissions in a riparian zone. Soil GHG emissions were assessed by measuring the air samples collected from four study sites, which have different plant community structure types and species compositions (natural sites with complex plants, landscaped sites with fruit trees and grasses, untended sites with ruderals, and farmland sites), using the static chamber method. Significant differences were observed in soil carbon dioxide (CO2; p < 0.001), nitrous oxide (N2O; p < 0.001), and methane (CH4; p = 0.005) emissions. The untended site with ruderals exhibited the highest CO2 emissions, while N2O emissions increased as plant community diversity decreased. All sites acted as sinks for CH4 emissions, with decreased CH4 uptake efficiency in more diverse plant communities. The Mantel test and variance partitioning analysis revealed soil microbial biomass as an indirect influencer of GHG emissions. This study could help predict soil GHG emissions and their global warming potential under future changes in the island riparian zones. [ABSTRACT FROM AUTHOR]

Aim: To investigate the relationship between thyroid function and weight regain in patients with obesity after metabolic surgery. Methods: This retrospective study enrolled 162 patients who underwent metabolic surgery. Correlations between decreases in thyroid hormone levels and changes in weight, waist circumference (WC) and the Chinese visceral adiposity index (CVAI) were assessed. Binary logistic regression and receiver operating characteristic (ROC) curves were used to identify predictors and clinically useful cut‐off values, respectively. Results: The levels of thyroid‐stimulating hormone (TSH) and free triiodothyronine (FT3) decreased markedly at 1 year after surgery, as did weight, body mass index (BMI), triglycerides, total cholesterol, high‐density lipoprotein cholesterol, low‐density lipoprotein cholesterol, WC and CVAI. Decreases in TSH and FT3 after metabolic surgery were associated with changes in weight, BMI and CVAI. Binary logistic regression and ROC curve analyses confirmed that decreases in TSH can predict good weight loss after metabolic surgery to some extent. Finally, binary logistic regression and ROC curve analyses confirmed that changes in TSH can predict weight regain after metabolic surgery. Conclusions: Changes in TSH and FT3 after metabolic surgery were correlated with changes in weight and CVAI. Changes in thyroid hormones can predict weight regain in patients with obesity who underwent metabolic surgery. [ABSTRACT FROM AUTHOR]

Background: Shift work was associated with elevated dementia risk. Definitive guidelines for sleep duration among shift workers have not been proposed. We aimed to identify sleep durations associated with elimination of excess dementia risk in shift workers. Methods: 285,213 dementia-free UK Biobank participants at baseline, aged 38–71 years, were enrolled between 2006 and 2010 and followed up through 2022 in this cohort study. Cox proportional hazards models were used to examine the associations between shift work, sleep duration, and risk of dementia. Results: The 285,213 participants included 49,079 shift workers and 236,134 non-shift workers. Over a median follow-up of 13.8 years, 1887 dementia cases were documented. Current shift workers had significantly higher dementia risk than non-shift workers (hazard ratio [HR] 1.26; 95% CI 1.11–1.42). However, this excess risk was eliminated in shift workers with 8 h of sleep (HR 1.02; 95% CI 0.80–1.29). Analysis of shift work frequency indicated that "sometimes" and "usually/always" shift work were associated with increased dementia risk compared to that of non-shift workers, but excess dementia risk was eliminated in members of either frequency group receiving 8 h of sleep ("sometimes", HR 1.05; 95% CI 0.75–1.48; "usually/always", HR 0.98; 95% CI 0.70–1.35). Both "non-night shift" and "night shift" workers showed increased dementia risk compared to non-shift workers. Workers with 8 h of sleep mitigated the excess risk (HR 1.13; 95% CI 0.84–1.53 and HR 0.86; 95% CI 0.59–1.26, respectively). Conclusion: 8-h sleep may eliminate excess dementia risk among shift workers, suggesting a potentially effective dementia prevention guideline for shift workers. [ABSTRACT FROM AUTHOR]

Background Since 2012, work-hour alcohol use (WHAU) has been prohibited in China. However, there is a lack of national data on WHAU among healthcare workers, including psychiatrists. Methods We collected data from psychiatrists in 41 tertiary psychiatric hospitals using an online questionnaire, which included demographics, work-related factors, WHAU, and the Alcohol Use Disorder Identification Test-Consumption (AUDIT-C). Results Out of 2911 psychiatrists who completed the survey, 4.29% reported having heard (3.13%) or witnessed (1.17%) WHAU among colleagues, and.51% (95% CI:.26%–.78%) admitted to their own WHAU. Most participants (95.57%) reported awareness of the policy against WHAU. Poisson regression demonstrated the unawareness of WHAU policy (incidence-rate ratios [IRR] 11.08; 95% CI: 3.56–34.52; P  < .001), lower income (IRR.87; 95% CI:.79–0.96; P  = .008), and higher AUDIT-C scores (IRR 1.48; 95% CI: 1.22–1.80; P  < .001) were significantly associated with WHAU occurrences. Conclusions The survey indicates that WHAU among psychiatrists is more prevalent than expected, correlating with insufficient awareness of hospital policies. This suggests a need for targeted educational interventions. [ABSTRACT FROM AUTHOR]

Food web robustness is a critical aspect of ecosystem stability and has been extensively studied in ecology. However, the potential of machine learning techniques in predicting food web robustness and the identification of key network structure indicators have not been fully explored. We compared the suitability of different machine learning methods and assessed the relative importance of network structure indicators for predicting the robustness of food webs. We utilized a variety of food web datasets spanning different ecosystems to calculate network structure indicators, which include average distance (AD), betweenness centrality (BC), directional connectivity (C), closeness centrality (CC), diameter (D), degree centrality (DC), edge betweenness centrality (EBC), number of links (L), linkage density (LD), and number of nodes (N). We then compared the performance of machine learning methods, including artificial neural network (ANN), random forest (RF), least absolute shrinkage and selection operator (LASSO), and decision tree (DT), and evaluated the relative importance of network structure indicators on robustness predictions. The results demonstrate that the RF model has the best performance (MAE = 0.0178, RMSE = 0.0263, R2 = 0.9063). Meanwhile, the CC indicator has a significant impact in predicting robustness of food webs. It is suggested that both the RF model and the CC indicator should be considered seriously in predicting food web robustness. This research elucidates the differential outcomes when various machine learning methodologies and indicators are employed to predict the robustness of food webs. It significantly enhances our understanding by demonstrating the precise capability of machine learning models in forecasting the robustness of food webs. [ABSTRACT FROM AUTHOR]

Silicone rubber (SR), as one kind of highly valuable rubber material, has been widely used in many fields, e.g., construction, transportation, the electronics industry, automobiles, aviation, and biology, owing to its attractive properties, including high- and low-temperature resistance, weathering resistance, chemical stability, and electrical isolation, as well as transparency. Unfortunately, the inherent flammability of SR largely restricts its practical application in many fields that have high standard requirements for flame retardancy. Throughout the last decade, a series of flame-retardant strategies have been adopted which enhance the flame retardancy of SR and even enhance its other key properties, such as mechanical properties and thermal stability. This comprehensive review systematically reviewed the recent research advances in flame-retarded SR materials and summarized and introduced the up-to-date design of different types of flame retardants and their effects on flame-retardant properties and other performances of SR. In addition, the related flame-retardant mechanisms of the as-prepared flame-retardant SR materials are analyzed and presented. Moreover, key challenges associated with these various types of FRs are discussed, and future development directions are also proposed. [ABSTRACT FROM AUTHOR]

Objectives: To explore the efficacy of diffuse magnetic resonance imaging (MRI) for identifying clinicopathological changes in immunoglobulin A nephropathy (IgAN) patients. Methods: The study enrolled IgAN patients and healthy volunteers. IgAN patients were divided into Group 1 [estimated glomerular filtration rate (eGFR) ≥ 90 mL/min/1.73 m2], Group 2 (60 ≤ eGFR < 90 mL/min/1.73 m2), and Group 3 (eGFR < 60 mL/min/1.73 m2). Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and diffusion tensor imaging (DTI) were performed via 3.0 T magnetic resonance. Diffuse MRI, clinical, and pathological indicators were collected and analysed. P < .05 was considered statistically significant. Results: Forty-six IgAN patients and twenty-seven volunteers were enrolled. The apparent diffusion coefficient, diffusion coefficient (D), perfusion fraction (f), and fractional anisotropy (FA) were significantly different among IgAN subgroups and controls. These parameters were positively correlated with eGFR and negatively with creatinine, and inversely correlated with glomerular sclerosis, interstitial fibrosis, and tubular atrophy (all P < .05). They had significantly high area under the curve (AUC) for distinguishing IgAN patients from controls, while FA had the highest AUC in identifying Group 1 IgAN patients from volunteers. Conclusions: DTI and IVIM-DWI had the advantage of evaluating clinical and pathological changes in IgAN patients. DTI was superior at distinguishing early IgAN patients and might be a noninvasive marker for screening early IgAN patients from healthy individuals. Advances in knowledge: DTI and IVIM-DWI could evaluate clinical and pathological changes and correlated with Oxford classification in IgAN patients. They could also identify IgAN patients from healthy populations, while DTI had superiority in differentiating early IgAN patients. [ABSTRACT FROM AUTHOR]

Background: This study sought to assess socioeconomic-related inequalities in health care use among arthritis patients in China and to analyze factors associated with this disparity. Methods: This study used data from the 2018 China Health and Retirement Longitudinal Study. 3255 arthritis patients were included. The annual per capita household expenditure was used to divide individuals into five categories. We calculated actual, need-predicted, and need-standardized distributions of health care use by socioeconomic groups among people with arthritis. The concentration index (Cl) was used to assess inequalities in health service use. Influencing factors of inequalities were measured with the decomposition method. Results: The outpatient and inpatient service use rates among 3255 arthritis patients were 23.13% and 21.41%, respectively. The CIs for actual outpatient and inpatient services use were 0.0449 and 0.0985, respectively. The standardized CIs for both outpatient and inpatient services use increase (CI for outpatient services use = 0.0537; CI for inpatient services use = 0.1260), indicating the emergence of a significant pro-rich inequity. Annual per capita household expenditure was the chief positive contributor to inequity for both outpatient (104.45%) and inpatient services use (105.74%), followed by infrequently social interaction (22.60% for outpatient services use) and Urban Employee Basic Medical Insurance (UEBMI) (11.90% for inpatient services use). By contrast, UEBMI also provided a high negative contribution to outpatient services use (-15.99%). Conclusions: There are significant pro-rich inequalities in outpatient and inpatient services use among patients with arthritis, which are exacerbated by widening economic gaps. Interventions to address inequalities should start by improving the economic situation of lower socioeconomic households. [ABSTRACT FROM AUTHOR]

Clay–gravel mixture is an increasingly popular material used in geotechnical engineering for its engineering adaptability and easy accessibility. Among various granulometric factors, gravel content plays a critical role in the alteration of mixture microstructure. Its influence on mechanical behavior has been comprehensively investigated, yet the hydraulic models accounting for the paired impact of clay and gravel particles are seldomly discussed. In an effort to enhance the permeability prediction capability of this soil, a generalized binary model derived from a theoretical hydraulic conductivity expression is proposed, with the participation of two fundamental compound seepage models. High accuracy between test and calculation results indicates the reliability of this model, as well as its supremacy over conventional models. The parameter sensitivity analysis demonstrates that the proposed model, being of convincing parametric stability regardless of variant particle size distribution characteristics, has the potential to be applicable to a wide range of engineering-adapted CGMs. The predictive formula for cohesive fraction and the anomaly coefficient, as is integrated into the binary model, are explicitly discussed. Suitable for clay–gravel materials under a transitional soil state for engineering applications, this model provides a quantitative and reasonable evaluation of hydraulic conductivity with high practicality. The above findings might work as a perspective for the credible assessment of structure seepage safety behavior, as well as a quantitative evaluation method regarding the mixing quality of CGMs. [ABSTRACT FROM AUTHOR]