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Abstract This study uses the Large Eddy Simulation (LES) technique to conduct an exhaustive analysis of the flow characteristics within the Rectangular-to-Elliptical shape Transition (REST) inlet under Mach 6 conditions. It mainly focuses on investigating the influence of the shock wave-turbulence interaction on the swirl distortion at the inlet exit. At the design condition, characterized by 0° Attack and 0° Sideslip, the incident shock wave at the inlet lip undergoes multiple reflections within the boundary layer of the domain wall, culminating in the formation of turbulent structures. The first reflected shock wave has the highest energy, exerting a significant impact on the boundary layer and the exit swirl distortion. On the contrary, the energy of the incident shock wave is progressively reduced due to repeated reflections, which results in reducing the exit swirl distortion. Under off-design conditions, characterized by 6° Attack and 0° Sideslip as well as 6° Attack with 6° Sideslip, variations in the incoming flow make the incident shock wave move inward, decreasing the frequency of shock wave reflections and even significantly reducing the reflected shock waves under conditions of 6° Attack and 6° Sideslip. However, this results in significantly increasing the exit swirl angle and distortion intensity. The obtained results demonstrate that changes in the incoming flow conditions significantly affect the level of exit swirl distortion by modulating the shock wave-turbulence interaction, especially in terms of the positioning of the incident shock wave and the quantity of reflected shock waves. In addition, this paper studies the wall heat transfer coefficient of the inlet. The obtained results show that the interaction between shock waves and the boundary layer significantly affects the heat transfer coefficient. This study provides a foundation for the comprehension and prediction of the performance of hypersonic inlets across a spectrum of flight conditions, and for the guidance of the design and optimization of such inlets.

Abstract Since the birth of cognitive science, researchers have used reaction time and accuracy to measure cognitive ability. Although recognition of these two measures is often based on empirical observations, the underlying consensus is that most cognitive behaviors may be along two fundamental dimensions: cognitive processing speed (CPS) and cognitive processing accuracy (CPA). In this study, we used genomic-wide association studies (GWAS) data from 14 cognitive traits to show the presence of those two factors and revealed the specific neurobiological basis underlying them. We identified that CPS and CPA had distinct brain phenotypes (e.g. white matter microstructure), neurobiological bases (e.g. postsynaptic membrane), and developmental periods (i.e. late infancy). Moreover, those two factors showed differential associations with other health-related traits such as screen exposure and sleep status, and a significant causal relationship with psychiatric disorders such as major depressive disorder and schizophrenia. Utilizing an independent cohort from the Adolescent Brain Cognitive Development (ABCD) study, we also uncovered the distinct contributions of those two factors on the cognitive development of young adolescents. These findings reveal two fundamental factors underlying various cognitive abilities, elucidate the distinct brain structural fingerprint and genetic architecture of CPS and CPA, and hint at the complex interrelationship between cognitive ability, lifestyle, and mental health.

Abstract Background Effective response and reducing the burden of family care for children with cancer is critical, and China currently lacks a specific assessment tool. Aims This study aimed to translate and validate the Caregiving Burden Scale for Family Caregivers of Children with Cancer (CBSFC-CC) and then test and implement the tool. Methods According to the Beaton cross-cultural debugging guide, preliminary Chinese version of CBSFC-CC scale was formed, which was suitable for Chinese language environment and clinical context. Exploratory factor analyses (EFA) and confirmatory factor analyses (CFA) were performed to verify structural validity. Convergent validity, discriminant validity and reliability were also conducted. Results A total of 529 family caregivers of children with cancer participated in the survey. EFA extracts and combines four factors and explained 65.80% of the total variation. CFA proved that all the goodness-of-fit indicators were acceptable. The Cronbach’s alpha of the Chinese version of CBSFC-CC was .96, and the test–retest reliability coefficient was .95. Four dimensions and 29 items were identified in the final Chinese version of CBSFC-CC. Conclusion The chinese version CBSFC-CC is scientifically reasonable and has good reliability and validity, which can be applied to the investigation of the nursing burden of family caregivers of children with cancer in China.

Objective: Abnormal metabolism is the underlying reason for breast cancer progression. Decreased lactate dehydrogenase B (LDHB) has been detected in breast cancer but the function of LDHB remains unknown. Methods: Western blot was used to analyze LDHB expression in breast cancer cells. The impact of LDHB on tumor cell migration and invasion was determined using Transwell assays, wound healing assays, and a mouse lung metastasis model. Subcutaneous tumor formation, a natural killer (NK) cell cytotoxicity assay, and flow cytometry evaluated NK cell activation. Immunofluorescence and quantitative real-time PCR detected NK cell activation markers. Kaplan-Meier analysis evaluated the effect of immune cell infiltration on prognosis. Single-sample gene set enrichment analysis determined NK cell activation scores. A support vector machine predicted the role of LDHB in NK cell activation. Results: In this study we showed that LDHB inhibits the breast cancer cell metastasis and orchestrates metabolic reprogramming within tumor cells. Our results revealed that LDHB-mediated lactic acid clearance in breast cancer cells triggers NK cell activation within the tumor microenvironment. Our findings, which were confirmed in a murine model, demonstrated that LDHB in tumor cells promotes NK cell activation and ultimately results in the eradication of malignant cells. Clinically, our study further validated that LDHB affects immune cell infiltration and function. Specifically, its expression has been linked to enhanced NK cell-mediated cytotoxicity and improved patient survival. Furthermore, we identified LDHB expression in tumors as an important predictor of NK cell activation, with strong predictive ability in some cancers. Conclusions: Our results suggest that LDHB is a promising target for activating the tumor immune microenvironment in breast cancer, where LDHB-associated lactic acid clearance leads to increased NK cell activity. This study highlights the critical role of LDHB in regulating immune responses and its potential as a therapeutic target for breast cancer.

Abstract Background Schizophrenia (SZ), a psychiatric disorder for which there is no precise diagnosis, has had a serious impact on the quality of human life and social activities for many years. Therefore, an advanced approach for accurate treatment is required. New method In this study, we provide a classification approach for SZ patients based on a spatial–temporal residual graph convolutional neural network (STRGCN). The model primarily collects spatial frequency features and temporal frequency features by spatial graph convolution and single-channel temporal convolution, respectively, and blends them both for the classification learning, in contrast to traditional approaches that only evaluate temporal frequency information in EEG and disregard spatial frequency features across brain regions. Results We conducted extensive experiments on the publicly available dataset Zenodo and our own collected dataset. The classification accuracy of the two datasets on our proposed method reached 96.32% and 85.44%, respectively. In the experiment, the dataset using delta has the best classification performance in the sub-bands. Comparison with existing methods Other methods mainly rely on deep learning models dominated by convolutional neural networks and long and short time memory networks, lacking exploration of the functional connections between channels. In contrast, the present method can treat the EEG signal as a graph and integrate and analyze the temporal frequency and spatial frequency features in the EEG signal. Conclusion We provide an approach to not only performs better than other classic machine learning and deep learning algorithms on the dataset we used in diagnosing schizophrenia, but also understand the effects of schizophrenia on brain network features.

Abstract Objective This research aimed to identify the fundamental and geographic characteristics of the primary healthcare personnel mobility in Nanning from 2000 to 2021 and clarify the determinants that affect their transition to non-primary healthcare institutions. Methods Through utilizing the Primary Healthcare Personnel Database (PHPD) for 2000–2021, the study conducts descriptive statistical analysis on demographic, economic, and professional aspects of healthcare personnel mobility across healthcare reform phases. Geographic Information Systems (QGIS) were used to map mobility patterns, and R software was employed to calculate spatial autocorrelation (Moran’s I). Logistic regression identified factors that influenced the transition to non-primary institutions. Results Primary healthcare personnel mobility is divided into four phases: initial (2000–2008), turning point (2009–2011), rapid development (2012–2020), and decline (2021). The rapid development stage saw increased mobility with no spatial clustering in inflow and outflow. From 2016 to 2020, primary healthcare worker mobility reached its peak, in which the most significant movement occurred between township health centers and other institutions. Aside from their transition to primary medical institutions, the primary movement of grassroots health personnel predominantly directs towards secondary general hospitals, tertiary general hospitals, and secondary specialized hospitals. Since 2012, the number and mobility distance of primary healthcare workers have become noticeably larger and remained at a higher level from 2016 to 2020. The main migration of primary healthcare personnel occurred in their districts (counties). Key transition factors include gender, education, ethnicity, professional category, general practice registration, and administrative division. Conclusions This study provides evidence of the features of primary healthcare personnel mobility in the less developed western regions of China, in which Nanning was taken as a case study. It uncovers the factors that impact the flow of primary healthcare personnel to non-primary healthcare institutions. These findings are helpful to policy refinement and support the retention of primary healthcare workers.

Abstract Objectives To compare the characteristics of body compositions between metabolic syndrome (MetS) and frailty, and determine the independent and overlapping of MetS and frailty with postoperative complications among older patients with gastric cancer. Design A prospectively observational study. Setting and Participants Two hundred and eighty six older patients from 60 to 80 years undergoing radical gastrectomy for the first time. Measurements MetS was diagnosed by the criteria from the 2020 edition of Chinese guideline for the prevention and treatment of type 2 diabetes mellitus, and frailty was defined by frailty phenotype. An InBody770 impedance analyzer was used to measure body compositions and with 10 fat‐ and muscle‐related indicators being included in this study. Based on the presence of frailty and MetS, patients were divided into the frailty group, MetS group, frailty+MetS group, and normal group, and the body compositions indicators of these groups were compared. Clavien–Dindo classification was used to grade the severity of postoperative complications. Univariate and multivariate regression models were performed to explore the independent and joint association of MetS and frailty with postoperative complications. Results The incidence rate of MetS, frailty, and frailty+MetS being 20.3%, 15.7%, and 4.2% respectively. Compared with the normal group, both fat and muscle compositions were decreased significantly in the frailty group (p 0.05). In contrast, except SVR, the other indicators of the MetS group were higher than the normal group (p 0.05). There was an association of frailty with postoperative total (OR = 3.068, 95% CI: 1.402–6.713) and severe (OR = 9.423, 95% CI: 2.725–32.589) complications, but no association was found of MetS alone. MetS coexisting with frailty was associated with the highest risk of both total (OR = 3.852, 95% CI: 1.020–14.539) and severe (OR = 12.096, 95% CI: 2.183–67.024) complications. Conclusions Both frailty and MetS coexisting with frailty had adverse effects on postoperative complications, which appeared greatly different characteristics in body compositions and therefore reinforced the importance of targeted nutritional or metabolic intervention. Although MetS alone were not significantly associated with postoperative complications, it is essential to focus on the causal relationship and development trend between MetS and frailty to prevent MetS from shifting into frailty, considering the highest risk in their coexistence state.

ObjectiveThis study aims to develop risk prediction models for neck and shoulder musculoskeletal disorders among healthcare professionals.MethodsA stratified sampling method was employed to select employees from medical institutions in Nanning City, yielding 617 samples. The Boruta algorithm was used for feature selection, and various models, including Tree-Based Models, Single Hidden-Layer Neural Network Models (MLP), Elastic Net Models (ENet), and Support Vector Machines (SVM), were applied to predict the selected variables, utilizing SHAP algorithms for individual-level local explanations.ResultsThe SVM model excels in both Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) and exhibits more stable performance when generalizing to unseen data. The Random Forest model exhibited relatively high overall performance on the training set. The MLP model emerges as the most consistent and accurate in predicting shoulder musculoskeletal disorders, while the SVM model shows strong fitting capabilities during the training phase, with occupational factors identified as the main contributors to WMSDs.ConclusionThis study successfully constructs work-related musculoskeletal disorder risk prediction models for healthcare professionals, enabling a quantitative analysis of the impact of occupational factors. This advancement is beneficial for future economical and convenient work-related musculoskeletal disorder screening in healthcare professions.

Chronic hepatitis B infection (CHB) is a major risk factor for the development of hepatocellular carcinoma (HCC) globally and continues to pose a significant global health challenge. Jiawei Yinchenhao decoction (JWYCH) is a modified version of Yinchenhao decoction (YCHD), which is widely used to treat liver diseases including icteric hepatitis, cholelithiasis, and hepatic ascites. However, the effectiveness and underlying mechanism of JWYCH on CHB are still unclear. This study aimed to investigate the impact of JWYCH on CHB and explore the underlying mechanism via network pharmacology and metabolomics. C57BL/6 mice were administered rAAV-HBV1.3 via hydrodynamic injection (HDI) to establish the CHB model. The infected mice were orally administered JWYCH for 4 weeks. HBsAg, HBeAg, HBV DNA, the serum liver function index, and histopathology were detected. In addition, network pharmacology was used to investigate potential targets, whereas untargeted metabolomics analysis was employed to explore the hepatic metabolic changes in JWYCH in CHB mice and identify relevant biomarkers and metabolic pathways. JWYCH was able to reduce HBeAg levels and improve liver pathological changes in mice with CHB. Additionally, metabolomics analysis indicated that JWYCH can influence 105 metabolites, including pipecolic acid, alpha-terpinene, adenosine, and L-phenylalanine, among others. Bile acid metabolism, arachidonic acid metabolism, and retinol metabolism are suggested to be potential targets of JWYCH in CHB. In conclusion, JWYCH demonstrated a hepatoprotective effect on a mouse model of CHB, suggesting a potential alternative therapeutic strategy for CHB. The effect of JWYCH is associated mainly with regulating the metabolism of bile acid, arachidonic acid, and retinol. These differentially abundant metabolites may serve as potential biomarkers and therapeutic targets for CHB.

The relationship between brain entropy (BEN) and early brain development has been established through animal studies. However, it remains unclear whether the BEN can be used to identify age-dependent functional changes in human neonatal brains and the genetic underpinning of the new neuroimaging marker remains to be elucidated. In this study, we analyzed resting-state fMRI data from the Developing Human Connectome Project, including 280 infants who were scanned at 37.5–43.5 weeks postmenstrual age. The BEN maps were calculated for each subject, and a voxel-wise analysis was conducted using a general linear model to examine the effects of age, sex, and preterm birth on BEN. Additionally, we evaluated the correlation between regional BEN and gene expression levels. Our results demonstrated that the BEN in the sensorimotor-auditory and association cortices, along the ‘S-A’ axis, was significantly positively correlated with postnatal age (PNA), and negatively correlated with gestational age (GA), respectively. Meanwhile, the BEN in the right rolandic operculum correlated significantly with both GA and PNA. Preterm-born infants exhibited increased BEN values in widespread cortical areas, particularly in the visual-motor cortex, when compared to term-born infants. Moreover, we identified five BEN-related genes (DNAJC12, FIG4, STX12, CETN2, and IRF2BP2), which were involved in protein folding, synaptic vesicle transportation and cell division. These findings suggest that the fMRI-based BEN can serve as an indicator of age-dependent brain functional development in human neonates, which may be influenced by specific genes.

Background and aimsMetabolic reprogramming has been found to be a typical feature of tumors. Hepatocellular carcinoma (HCC), a cancer with high morbidity and mortality, has been extensively studied for its metabolic reprogramming-related mechanisms. Our study aims to identify the hotspots and frontiers of metabolic reprogramming research in HCC and to provide guidance for future scientific research and decision-making in HCC metabolism.MethodsRelevant studies on the metabolic reprogramming of HCC were derived from the Web of Science Core Collection (WoSCC) database up until November 2023. The bibliometrix tools in R were used for scientometric analysis and visualization.ResultsFrom 2011 to 2023, a total of 575 publications were obtained from WoSCC that met the established criteria. These publications involved 3,904 researchers and 948 organizations in 37 countries, with an average annual growth rate of 39.11% in research. These studies were published in 233 journals, with Cancers (n = 29) ranking first, followed by Frontiers in Oncology (n = 20) and International Journal of Molecular Sciences (n = 19). The top ten journals accounted for 26% of the 575 studies. The most prolific authors were Wang J (n = 14), Li Y (n = 12), and Liu J (n = 12). The country with the most publications is China, followed by the United States, Italy, and France. Fudan University had the largest percentage of research results with 15.48% (n = 89). Ally A’s paper in Cell has the most citations. A total of 1,204 keywords were analyzed, with the trend themes such as “glycolysis,” “tumor microenvironment,” “Warburg effect,” “mitochondria,” “hypoxia ,” etc. Co-occurrence network and cluster analysis revealed the relationships between keywords, authors, publications, and journals. Moreover, the close collaboration between countries in this field was elucidated.ConclusionThis bibliometric and visual analysis delves into studies related to metabolic reprogramming in HCC between 2012 and 2023, elucidating the characteristics of research in this field, which has gradually moved away from single glycolipid metabolism studies to the integration of overall metabolism in the body, pointing out the trend of research topics, and the dynamics of the interaction between the tumor microenvironment and metabolic reprogramming will be the future direction of research, which provides blueprints and inspirations for HCC prevention and treatment programs to the researchers in this field.Systematic Review Registration: [https://www.bibliometrix.org].

BackgroundEmerging evidence indicates that individuals with type 2 diabetes (T2D) are more prone to mental health issues than the general population; however, there is a significant lack of data concerning the mental health burden in Chinese Americans with T2D. ObjectiveThe aim of this study was to explore the comorbid mental health status, health-seeking behaviors, and mental service utilization among Chinese Americans with T2D. MethodsA cross-sectional telephone survey was performed among 74 Chinese Americans with T2D in New York City. We used standardized questionnaires to assess mental health status and to gather data on mental health–seeking behaviors and service utilization. Descriptive statistics were applied for data analysis. ResultsA total of 74 Chinese Americans with T2D completed the survey. Most participants (mean age 56, SD 10 years) identified as female (42/74, 57%), were born outside the United States (73/74, 99%), and had limited English proficiency (71/74, 96%). Despite nearly half of the participants (34/74, 46%) reporting at least one mental health concern (elevated stress, depressive symptoms, and/or anxiety), only 3% (2/74) were currently using mental health services. Common reasons for not seeking care included no perceived need, lack of information about Chinese-speaking providers, cost, and time constraints. The cultural and language competence of the provider was ranked as the top factor related to seeking mental health care. ConclusionsChinese Americans with T2D experience relatively high comorbid mental health concerns yet have low service utilization. Clinicians may consider team-based care to incorporate mental health screening and identify strategies to provide culturally and linguistically concordant mental health services to engage Chinese Americans with T2D.

Psycholinguistic models of metaphor processing remain a subject of debate. A prime-probe design using Chinese materials with a specific time span (300 ms) was applied to test the mechanisms of metaphor processing. Conventional and familiarized metaphors were designed as primes, followed by a probe word semantically related to the prime metaphor (MT), a probe word related to the literal meaning of the final word of the prime metaphor (LT), control/unrelated probe word (UT), or non-word. Event-related potentials (ERPs) elicited by the probes were recorded to examine metaphor processing. In N400, results revealed that UT and LT elicited significantly more negative waveforms than MT in both primes. MTs and LTs showed no difference between conventional and familiarized metaphors, suggesting that metaphorical meaning may be accessed directly, regardless of whether conventional or familiarized metaphors. The results were generally compatible with the direct processing model.

Natural bioactive compounds and plant constituents are considered to have a positive anti-inflammatory effect. This study aimed to establish a screening technique for anti-inflammatory function in foods based on label-free Raman imaging. A visible anti-inflammatory analysis method based on coherent anti-Stokes Raman scattering (CARS) was established with an LPS-induced RAW264.7 cell model. Dynamic changes in proteins and lipids were determined at laser pump light wavelengths of 2956 cm−1 and 2856 cm−1, respectively. The method was applied to a plant-based formula (JC) with anti-inflammatory activity. Q-TOF-MS and HPLC analyses revealed the main active constituents of JC as quercetin, kaempferol, l-glutamine, and sodium copper chlorophyllin. In in vitro and in vivo verification experiments, JC showed significant anti-inflammatory activity by regulating the TLR4/NF-κB pathway. In conclusion, this study successfully established a label-free and visible method for screening anti-inflammatory constituents in plant-based food products, which will facilitate the evaluation of functional foods.

IntroductionIn recent years, graph neural network has been extensively applied to drug discovery research. Although researchers have made significant progress in this field, there is less research on bibliometrics. The purpose of this study is to conduct a comprehensive bibliometric analysis of graph neural network applications in drug discovery in order to identify current research hotspots and trends, as well as serve as a reference for future research.MethodsPublications from 2017 to 2023 about the application of graph neural network in drug discovery were collected from the Web of Science Core Collection. Bibliometrix, VOSviewer, and Citespace were mainly used for bibliometric studies.Results and DiscussionIn this paper, a total of 652 papers from 48 countries/regions were included. Research interest in this field is continuously increasing. China and the United States have a significant advantage in terms of funding, the number of publications, and collaborations with other institutions and countries. Although some cooperation networks have been formed in this field, extensive worldwide cooperation still needs to be strengthened. The results of the keyword analysis clarified that graph neural network has primarily been applied to drug-target interaction, drug repurposing, and drug-drug interaction, while graph convolutional neural network and its related optimization methods are currently the core algorithms in this field. Data availability and ethical supervision, balancing computing resources, and developing novel graph neural network models with better interpretability are the key technical issues currently faced. This paper analyzes the current state, hot spots, and trends of graph neural network applications in drug discovery through bibliometric approaches, as well as the current issues and challenges in this field. These findings provide researchers with valuable insights on the current status and future directions of this field.

Abstract Poor renal distribution of antibody-based drugs is the key factor contributing to low treatment efficiency for renal diseases and side effects. Here, we prepare F(ab′)2 fragmented vascular endothelial growth factor receptor 2 antibody (anti-VEGFR2 (F(ab′)2) to block VEGFR2 overactivation in diabetic nephropathy (DN). We find that the anti-VEGFR2 F(ab′)2 has a higher accumulation in DN male mice kidneys than the intact VEGFR2 antibody, and simultaneously preserves the binding ability to VEGFR2. Furthermore, we develop an antibody fragment drug conjugate, anti-VEGFR2 F(ab′)2-SS31, comprising the anti-VEGFR2 F(ab′)2 fragment linked to the mitochondria-targeted antioxidant peptide SS31. We find that introduction of SS31 potentiates the efficacy of anti-VEGFR2 F(ab′)2. These findings provide proof of concept for the premise that antibody fragment drug conjugate improves renal distribution and merits drug validation in renal disease therapy.

Abstract Background Alzheimer’s disease (AD) and Parkinson’s disease (PD), two common irreversible neurodegenerative diseases, share similar early stage syndromes, such as olfaction dysfunction. Yet, the potential comorbidity mechanism of AD and PD was not fully elucidated. Methods The gene expression profiles of GSE5281 and GSE8397 were downloaded from the Gene Expression Omnibus (GEO) database. We utilized a series of bioinformatics analyses to screen the overlapped differentially expressed genes (DEGs). The hub genes were further identified by the plugin CytoHubba of Cytoscape and validated in the hippocampus (HIP) samples of APP/PS-1 transgenic mice and the substantial nigra (SN) samples of A53T transgenic mice by real-time quantitative polymerase chain reaction (RT-qPCR). Meanwhile, the expression of the target genes in the olfactory epithelium/bulb was detected by RT-qPCR. Finally, molecular docking was used to screen potential compounds for the target gene. Results One hundred seventy-four overlapped DEGs were identified in AD and PD. Five of the top ten enrichment pathways mainly focused on the synapse. Five hub genes were identified and further validated. As a common factor in AD and PD, the changes of synaptosomal-associated protein 25 (SNAP25) mRNA in olfactory epithelium/bulb were significantly decreased and had a strong association with those in the HIP and SN samples. Pazopanib was the optimal compound targeting SNAP25, with a binding energy of − 9.2 kcal/mol. Conclusions Our results provided a theoretical basis for understanding the comorbidity mechanism of AD and PD and highlighted that SNAP25 in the olfactory epithelium may serve as a potential target for early detection and intervention in both AD and PD.

Abstract Aim To explore the employment intention and career planning of male nursing students at different levels of colleges and universities and provide references for formulating individualized training content. Design Phenomenological research method in qualitative research. Methods Using a phenomenological research method, 15 male nursing students from three levels of colleges and universities were interviewed in a one‐to‐half structure, and the data were analysed using NVivo12.0 software and the Colaizzi seven‐step analysis method. Results Four themes and 10 sub‐themes were extracted. The four themes included professional identity experience, nursing learning experience, career expectation and planning and educational needs. The 10 sub‐themes included the negative effects of traditional impressions, the gradual establishment of professional identity, public health events promote professional identity, negative experiences in learning, positive growth from learning, varied career plans, career expectations and influencing factors, a reasonable schedule, diversity of content requirements and the positive effect of teaching teachers. Conclusions Influenced by many factors, the employment intention and career planning of male nursing students at different higher education levels are varied. Schools and clinical practice units should strengthen the training of employment intention and career planning and make reasonable time adjustments to the training content. Public Contribution In total, 15 male interns accepted our interview request. We utilized their break time to conduct the interviews, resulting in significant contributions to the content of the article.

ObjectiveThe objective of this study was to investigate the impact of electro-acupuncture (EA) on sepsis-related intestinal injury and its relationship with macrophage polarization.MethodsA sepsis model was established using cecal ligation and puncture (CLP) to assess the effectiveness of EA. The extent of pathological injury was evaluated using Chiu’s score, the expression of ZO-1 and Ocludin, and the impact on macrophage polarization was examined through flow cytometry and immunofluorescence staining. The expression of spermidine, one type of polyamine, and ornithine decarboxylase (ODC) was measured using ELISA and PCR. Once the efficacy was determined, a polyamine depletion model was created, and the role of polyamines was reassessed by evaluating efficacy and observing macrophage polarization.ResultsEA treatment reduced the Chiu’s score and increased the expression of ZO-1 and Ocludin in the intestinal tissue of septic mice. It inhibited the secretion of IL-1β and TNF-α, promoted the polarization of M2-type macrophages, increased the secretion of IL-10, and upregulated the expression of Arg-1, spermidine, and ODC. However, after depleting polyamines, the beneficial effects of EA on alleviating intestinal tissue damage and modulating macrophage polarization disappeared.ConclusionThe mechanism underlying the alleviation of intestinal injury associated with CLP-induced sepsis by EA involves with the promotion of M2-type macrophage polarization mediated by spermidine expression.

Background: The occurrence and development of Hepatic fibrosis (HF) are closely related to the gut microbial composition and alterations in host metabolism. Qijia Rougan decoction (QJ) is a traditional Chinese medicine compound utilized clinically for the treatment of HF with remarkable clinical efficacy. However, its effect on the gut microbiota and metabolite alterations is unknown. Therefore, our objective was to examine the impact of QJ on the gut microbiota and metabolism in Carbon tetrachloride (CCl4)-induced HF.Methods: 40% CCl4 was used to induce HF, followed by QJ administration for 6 weeks. Serum biochemical analyses, histopathology, immunohistochemistry, RT-PCR, 16S rRNA gene sequencing, and non-targeted metabolomics techniques were employed in this study to investigate the interventional effects of QJ on a CCl4-induced HF model in rats.Results: This study demonstrated that QJ could effectively ameliorate CCl4-induced hepatic inflammation and fibrosis. Moreover, QJ upregulated the expression of intestinal tight junction proteins (TJPs) and notably altered the abundance of some gut microbes, for example, 10 genera closely associated with HF-related indicators and TJPs. In addition, metabolomics found 37 key metabolites responded to QJ treatment and strongly associated with HF-related indices and TJPs. Furthermore, a tight relation between 10 genera and 37 metabolites was found post correlation analysis. Among them, Turicibacter, Faecalibaculum, Prevotellaceae UCG 001, and unclassified Peptococcaceae may serve as the core gut microbes of QJ that inhibit HF.Conclusion: These results suggest that QJ ameliorates hepatic inflammation and fibrosis, which may be achieved by improving intestinal tight junctions and modulating gut microbiota composition as well as modulating host metabolism.

Abstract The rise of new media has greatly changed the lifestyles, leading to increased time on these platforms and less time spent reading. This shift has particularly profound impacts on early adolescents, who are in a critical stage of brain development. Previous studies have found associations between screen use and mental health, but it remains unclear whether screen use is the direct cause of the outcomes. Here, the Adolescent Brain Cognitive Development (ABCD) dataset is utlized to examine the causal relationships between screen use and brain development. The results revealed adverse causal effects of screen use on language ability and specific behaviors in early adolescents, while reading has positive causal effects on their language ability and brain volume in the frontal and temporal regions. Interestingly, increased screen use is identified as a result, rather than a cause, of certain behaviors such as rule‐breaking and aggressive behaviors. Furthermore, the analysis uncovered an indirect influence of screen use, mediated by changes in reading habits, on brain development. These findings provide new evidence for the causal influences of screen use on brain development and highlight the importance of monitoring media use and related habit change in children.

Landscape patterns and water cycle processes have changed significantly in recent decades as a result of intensive interference from human activities. Although the intensification of the global water cycle is well illustrated from a climate change perspective, using landscape index to characterize the evolution of water cycle have been less explored. This study aimed to investigate the water cycle status and its evolution from the perspective of landscape patterns. A water cycle intensity (WCI) evaluation model based on the landscape index was developed. Defined as the ratio of the water resource circulation to the natural circulation, the WCI was used to analyze the water cycle evolution trend in each region of the Haihe River Basin. Through correlation and dynamic change trend analyses, the patch density (PD) of the urban areas and runoff landscape index (RLI) were identified as synchronizing with the WCI changes. The mathematical relationships between the landscape indicators (PD and RLI) and WCI were explored. Thereafter, according to the WCI development and its impact on the ecological environment, three categories of water cycle statuses (WCSs) were proposed: the natural circulation status (NCS), moderately developed status (MDS), and overdeveloped status (ODS). The WCS evolution trend in the Haihe River Basin was evaluated and the results showed all regions have evolved into a state of ODS with WCIs above 35% in 2010 and five of the plain regions greater than 80%. The proposed approach can be effectively applied to evaluating and predicting WCS in ungauged basins or future landcover scenarios, thereby providing a new perspective and effective tools for water resource management.

Abstract Ferroelectricity, a spontaneous and reversible electric polarization, is found in certain classes of van der Waals (vdW) materials. The discovery of ferroelectricity in twisted vdW layers provides new opportunities to engineer spatially dependent electric and optical properties associated with the configuration of moiré superlattice domains and the network of domain walls. Here, we employ near-field infrared nano-imaging and nano-photocurrent measurements to study ferroelectricity in minimally twisted WSe2. The ferroelectric domains are visualized through the imaging of the plasmonic response in a graphene monolayer adjacent to the moiré WSe2 bilayers. Specifically, we find that the ferroelectric polarization in moiré domains is imprinted on the plasmonic response of the graphene. Complementary nano-photocurrent measurements demonstrate that the optoelectronic properties of graphene are also modulated by the proximal ferroelectric domains. Our approach represents an alternative strategy for studying moiré ferroelectricity at native length scales and opens promising prospects for (opto)electronic devices.

Non-contact temperature sensors utilising the fluorescence intensity ratio and the unique up-conversion (UC) luminescence of rare-earth ions have numerous benefits; however, their operational temperature range has remained limited. In this study, NaLuF4:Yb3+/Ho3+ samples were prepared by the hydrothermal method. The samples exhibited exceptional UC luminescence properties at low temperatures. The intensity of the green emission (with peak wavelengths of 540 and 546 nm) gradually decreased with increasing temperature, and the green emissions showed a unique change at low temperatures. In addition, we studied the dependence of the UC luminescence intensity on the excitation power and the variation in the decay lifetime with temperature. The experiments revealed excellent luminous performance and significantly enhanced sensitivity at low temperatures; the maximum absolute sensitivity Sa and relative sensitivity Sr of the 540 and 546 nm thermally coupled energy levels were 1.02% and 0.55% K−1, respectively. The potential temperature sensing properties of Yb3+/Ho3+-co-doped NaLuF4 makes it suitable for temperature sensing applications at temperatures as low as 30 K. This study offers a novel approach for the advancement of temperature sensing technology at low temperatures.

In this study, we investigate micrometer-sized NaYF4 crystals double-doped with Yb3+/Er3+ lanthanide ions, designed for temperature-sensing applications. In contrast to previous studies, which focused predominantly on the high-temperature regime, our investigation spans a comprehensive range of both high and ultralow temperatures. We explore the relationship between temperature and the upconversion luminescence (UCL) spectra in both frequency and time domains. Our findings highlight the strong dependence of these spectral characteristics of lanthanide-doped NaYF4 crystals on temperature. Furthermore, we introduce a dual-mode luminescence temperature measurement technique, leveraging the upconversion emission intensity ratio for both green and red emissions. This study also examines the correlation between temperature sensing, energy level disparities, and thermal coupling in Er3+ ions across various temperature scales. Our research contributes to advancing the understanding and application of lanthanide-doped materials, setting a foundation for future innovations in temperature sensing across diverse fields.

Glass waste products represent a significant environmental concern, with an estimated 1.4 billion tons being landfilled globally and 200 million tons annually. This results in a significant use of land resources. Therefore, it would be highly advantageous to develop a new method for disposing of waste glass. Waste glass can be recycled and ground into waste glass powder (WGP) for use in solidified soil applications as a sustainable resource. This study is based on solidified soil research, wherein NaOH, Ca(OH)2, and Na2SO4 were incorporated as activators to enhance the reactivity of WGP. The optimal solidified soil group was determined based on unconfined compressive strength tests, which involved varying the activator concentrations and WGP content in combination with cement. X-ray diffraction (XRD) was used to study the composition of solidified soil samples. Microscopic pore characteristics were investigated using scanning electron microscopy (SEM), and the Image J software was employed to quantify the number and size of pores. Fourier-transform infrared spectroscopy (FTIR) was employed to examine the activation effect of waste glass powder. This study investigated the solidification mechanism and porosity changes. The results demonstrate that the addition of activated WGP to solidified soil enhances its strength, with a notable 12% increase in strength achieved using a 6% Ca(OH)2 solution. The use of 2% concentration of Na2SO4 and NaOH also shows an increase in strength of 7.6% and 8.6%, respectively, compared to the sample without WGP. The XRD and SEM analyses indicate that activated WGP enhances the content of hydrates, reduces porosity, and fosters the formation of a more densely packed solidified soil structure.

Abstract Background Prevention, screening, and early treatment are the aims of postoperative delirium management. The scoring system is an objective and effective tool to stratify potential delirium risk for patients undergoing cardiac surgery. Methods Patients who underwent cardiac surgery between January 1, 2012, and January 1, 2019, were enrolled in our retrospective study. The patients were divided into a derivation cohort (n = 45,744) and a validation cohort (n = 11,436). The AD predictive systems were formulated using multivariate logistic regression analysis at three time points: preoperation, ICU admittance, and 24 h after ICU admittance. Results The prevalence of AD after cardiac surgery in the whole cohort was 3.6% (2,085/57,180). The dynamic scoring system included preoperative LVEF ≤ 45%, serum creatinine > 100 µmol/L, emergency surgery, coronary artery disease, hemorrhage volume > 600 mL, intraoperative platelet or plasma use, and postoperative LVEF ≤ 45%. The area under the receiver operating characteristic curve (AUC) values for AD prediction were 0.68 (preoperative), 0.74 (on the day of ICU admission), and 0.75 (postoperative). The Hosmer‒Lemeshow test indicated that the calibration of the preoperative prediction model was poor (P = 0.01), whereas that of the pre- and intraoperative prediction model (P = 0.49) and the pre, intra- and postoperative prediction model (P = 0.35) was good. Conclusions Using perioperative data, we developed a dynamic scoring system for predicting the risk of AD following cardiac surgery. The dynamic scoring system may improve the early recognition of and the interventions for AD.

The increased global incidence of chronic metabolic diseases, a vital threat to human health and a burden on our healthcare systems, includes a series of clinical metabolic syndromes such as obesity, diabetes, hypertension, and dyslipidemia. One of the well-known probiotic microorganisms, Lactiplantibacillus plantarum plays an important role in promoting human health, including inhibiting the occurrence and development of a variety of chronic metabolic diseases. The present study provides an overview of the preventive and therapeutic effects of L. plantarum on diabetes, obesity, non-alcoholic fatty liver disease, kidney stone disease, and cardiovascular diseases in animal models and human clinical trials. Ingesting L. plantarum demonstrated its ability to reduce inflammatory and oxidative stress levels by regulating the production of cytokines and short-chain fatty acids (SCFAs), the activity of antioxidant enzymes, and the balance of intestinal microbial communities to alleviate the symptoms of chronic metabolic diseases. Furthermore, updated applications and technologies of L. plantarum in food and biopharmaceutical industries are also discussed. Understanding the characteristics and functions of L. plantarum will guide the development of related probiotic products and explore the modulatory benefit of L. plantarum supplementations on the prevention and treatment of multiple chronic metabolic diseases.

Short-chain fatty acids (SCFAs) have been increasingly evidenced to be important bioactive metabolites of the gut microbiota and transducers in controlling diverse psychiatric or neurological disorders via the microbiota–gut–brain axis. However, the precise mechanism by which brain SCFAs extert multiple beneficial effects is not completely understood. Our previous research has demonstrated that the acetyl-coenzyme A synthetase short-chain family member 2 (ACSS2) is a novel target of the rapid and long-lasting antidepressant responses. Here, we show that micromolar SCFAs significantly augment both total cellular and nuclear ACSS2 to trigger tryptophan hydroxylase 2 (TPH2) promoter histone acetylation and its transcription in SH-SY5Y cells. In chronic-restraint-stress-induced depression mice, neuronal ACSS2 knockdown by stereotaxic injection of adeno-associated virus in the hippocampus abolished SCFA-mediated improvements in depressive-like behaviors of mice, supporting that ACSS2 is required for SCFA-mediated antidepressant responses. Mechanistically, the peroxisome-proliferator-activated receptor gamma (PPARγ) is identified as a novel partner of ACSS2 to activate TPH2 transcription. Importantly, PPARγ is also responsible for SCFA-mediated antidepressant-like effects via ACSS2–TPH2 axis. To further support brain SCFAs as a therapeutic target for antidepressant effects, d-mannose, which is a naturally present hexose, can significantly reverse the dysbiosis of gut microbiota in the chronic-restraint-stress-exposure mice and augment brain SCFAs to protect against the depressive-like behaviors via ACSS2–PPARγ–TPH2 axis. In summary, brain SCFAs can activate ACSS2–PPARγ–TPH2 axis to play the antidepressive-like effects, and d-mannose is suggested to be an inducer of brain SCFAs in resisting depression.

In view of the strong randomness and non-stationarity of complex system, this study suggests a hybrid multi-strategy prediction technique based on optimized hybrid denoising and deep learning. Firstly, the Sparrow search algorithm (SSA) is used to optimize Variational mode decomposition (VMD) which can decompose the original signal into several Intrinsic mode functions (IMF). Secondly, calculating the Pearson correlation coefficient (PCC) between each IMF component and the original signal, the subsequences with low correlation are eliminated, and the remaining subsequence are denoised by Wavelet soft threshold (WST) method to obtain effective signals. Thirdly, on the basis of the above data noise reduction and reconstruction, our proposal combines Convolutional neural network (CNN) and Bidirectional short-term memory (BiLSTM) model, which is used to analyze the evolution trend of real time sequence data. Finally, we applied the CNN-BiLSTM-SSA-VMD-WST to predict the real time sequence data together with the other methods in order to prove it's effectiveness. The results show that SNR and CC of the SSA-VMD-WST are the largest (the values are 20.2383 and 0.9342). The performance of the CNN-BiLSTM-SSA-VMD-WST are the best, MAE and RMSE are the smallest (which are 0.150 and 0.188), the goodness of fit R2 is the highest(its value is 0.9364). In contrast with other methods, CNN-BiLSTM-SSA-VMD-WST method is more suitable for denoising and prediction of real time series data than the traditional and singular deep learning methods. The proposed method may provide a reliable way for related prediction in various industries.

Objective. The association between vitamin D status and inflammation remains unclear in hospitalized patients. Materials and Methods. We performed the current study based on real-world data from two teaching hospitals. Serum level of vitamin D (assessed by 25-hydroxyvitamin D) was evaluated within 2 days after admission. All the patients were further classified into three groups: deficiency (

ObjectivesTo test the feasibility, acceptability, and potential efficacy of a mHealth intervention tailored for Chinese immigrant families with type 2 diabetes (T2D).MethodsWe conducted a pilot randomized controlled trial (RCT) with baseline, 3-, and 6-month measurements. Participating dyads, T2D patients and families/friends from NYC, were randomized into the intervention group (n = 11) or the wait-list control group (n = 12). Intervention includes 24 videos covering T2D self-management, behavioral techniques, and family-oriented sessions. Feasibility and acceptability were measured respectively by the retention rate and video watch rate, and a satisfaction survey. Patients' HbA1c, weight, and self-management were also assessed to test potential efficacy.ResultsMost T2D patients (n = 23; mean age 56.2±9.4 years; 52.2% male) and families/friends (n = 23, mean age 54.6±11.2 years; 52.2% female) had high school education or less (69.6% and 69.6%), annual household income < $25,000 (65.2% and 52.2%), and limited English proficiency (95.7% and 95.7%). The retention rates were not significantly different between the intervention and the control groups for both the patients (90.91% vs 83.3%, p = 0.589); and their families/friends (3-month: 90.9% vs 75%, p = 0.313; 6-month: 90.9% vs 83.3%, p = 0.589). The mean video watch rate was 76.8% (7%). T2D patients and families/friends rated satisfaction as 9.4 and 10 out of 10, respectively. Despite no between-group differences, the intervention group had significantly lower HbA1c (p = 0.014) and better self-management (p = 0.009), and lost 12 lbs. on average at 6 months (p = 0.079), compared to their baseline levels.ConclusionsA culturally-tailored, family-based mHealth intervention is feasible and acceptable among low-income, limited English-proficient Chinese families with T2D in NYC. Significant changes in HbA1c and self-management within the intervention group indicate this intervention may have potential efficacy. Given the small sample size of this study, a future RCT with adequate power is needed to test efficacy.

This study was conducted to observe the effect of Chinese herbal compound on the treatment of colon cancer using AOM/DSS-induced C57BL/6J colon cancer mice and to validate potential influence on intestinal flora of mice. A colorectal cancer (CRC) mouse model was built with a total of 50 C57BL/6J mice that were induced by administrating AOM/DSS. These experimental animals were split up into 5 groups, a control group, a model group, and low-, medium- and high-dose Chinese herbal compound groups. All mice were given Chinese herbal compound treatment, and the colon tissues of each group were harvested with the length measured and the number of colon polyps accounted. The Ki-67 expression in the colon tissues was detected via immuno-histochemistry. Relative quantification of the expression of genes and proteins was determined through qPCR and WB assays. Contents of IL-6, TNF-α, IFN-γ, and IL-10 in serum and colon tissues of mice were determined by ELISA. An additional 16S rRNA sequencing analysis was implemented for the identification of mouse intestinal flora. The results suggested that all low-, medium- or high-dose Chinese herbal compound could markedly inhibit the shortening of colon length and significant number reduction of colon polyps in the model group. The relative expression of genes and proteins (PCNA, Muc16, and MMP-9) associated with proliferation in mouse colon tissues were inhibited. In addition, compared with the model group, the contents of IL-6, TNF-α, and IFN-γ in serum and colon tissues were substantially decreased in the high-dose Chinese herbal compound group, thereby reducing the structure damage in colon tissues and the infiltration degree of inflammatory cells. Besides, the expression of TLR4/MyD88/NF-κB protein was markedly decreased. The 16S rRNA sequencing analysis demonstrated that mice in the model group had decreased intestinal flora diversity, and there were significant changes in flora abundance and amino acid metabolism between the control group and the model group. Taken together, the treatment of Chinese herbal compound against CRC in this study might be regulated by the TLR4/MyD88/NF-κB signaling pathway, and the imbalance in intestinal flora was also closely related to CRC occurrence.

The development of the cerebral cortex during the fetal period is a complex yet well-coordinated process. MRI-based morphological brain network provides a powerful tool for describing this process at a network level. Due to the challenges of in-utero MRI acquisition and image processing, the fetal morphological brain network has not been established. In this study, utilizing high-resolution in-utero MRI data, we constructed an individual morphometric similarity network for each fetus based on multiple cortical features. The spatiotemporal development of morphological connections was described at the level of edge, node, and lobe, respectively. Based on graph theoretical method, the topology structure of fetal morphological network was characterized. Edge analysis demonstrated an increase of morphological dissimilarity between hemispheres with gestational age, especially for the parietal cortex. The limbic and parieto-occipital regions exhibited the most drastic changes of morphological connections at both the edge and node levels. Between- and within-lobe analysis illustrated that the limbic lobe became more similar to other lobes, while the parietal and occipital lobes became more dissimilar to other lobes. Graph theoretical analysis indicated that the small-world structure of the fetal morphological network appeared as early as 22 weeks and that the network topology exhibited an enhanced integration and reduced segregation during prenatal development. The findings obtained from the preterm-born neonates agreed well with those of the fetuses. In summary, this study fills a gap in prenatal morphological brain network research and provides a piece of important evidence for understanding the normal development of fetal brain connectome during the second-third trimester.

The increasing scale of single-cell RNA-seq studies presents new challenge for integrating datasets from different batches. Here, the authors develop scDML, a tool that simultaneously removes batch effects, improves clustering performance, recovers true cell types, and scales well to large datasets.

Adsorptive removal of heavy metal ions from wastewater is very important, and the key is the development of efficient sorbents. In this work, oxygenated alkynyl carbon materials (OACMs) were synthesized via mechanochemical reaction of CaC2 and a carbonate (CaCO3, Na2CO3, or NaHCO3) at ambient temperature. The resultant OACMs are micro mesoporous carbon nanomaterials with high specific area (>648 m2 g−1), highly crosslinked texture, and rich alkynyl and oxygenated groups. The OACMs exhibit excellent Hg(II) adsorption due to the soft acid-soft base interaction between alkynyl and Hg(II), and OACM-3 derived from CaC2 and NaHCO3 has the saturated Hg(II) adsorbance of 483.9 mg g−1 along with good selectivity and recyclability. The adsorption is mainly chemisorption following the Langmuir mode. OACM-3 also shows high adsorbance for other heavy metal ions, e.g. 256.6 mg g−1 for Pb(II), 232.4 mg g−1 for Zn(II), and 198.7 mg g−1 for Cu(II). This work expands the mechnochemical reaction of CaC2 with carbonates and possibly other oxyanionic salts, provides a new synthesis approach for functional alkynyl carbon materials with excellent adsorption performance for heavy metal ions, as well as a feasible approach for CO2 resource utilization.

Acquired Immunodeficiency Syndrome is caused by the Human Immunodeficiency Virus (HIV), and a significant number of fatalities occur annually. There is a dire need to develop an effective vaccine against HIV-1. Understanding the structural proteins of viruses helps in designing a vaccine based on immunogenic peptides. In the current experiment, we identified gp120 epitopes using bioinformatic epitope prediction tools, molecular docking, and MD simulations. The Gb-1 peptide was considered an adjuvant. Consecutive sequences of GTG, GSG, GGTGG, and GGGGS linkers were used to bind the B cell, Cytotoxic T Lymphocytes (CTL), and Helper T Lymphocytes (HTL) epitopes. The final vaccine construct consisted of 315 amino acids and is expected to be a recombinant protein of approximately 35.49 kDa. Based on docking experiments, molecular dynamics simulations, and tertiary structure validation, the analysis of the modeled protein indicates that it possesses a stable structure and can interact with Toll-like receptors. The analysis demonstrates that the proposed vaccine can provoke an immunological response by activating T and B cells, as well as stimulating the release of IgA and IgG antibodies. This vaccine shows potential for HIV-1 prophylaxis. The in-silico design suggests that multiple-epitope constructs can be used as potentially effective immunogens for HIV-1 vaccine development.

Abstract Wound healing is an urgent clinical challenge, particularly in the case of chronic wounds. Traditional approaches to wound healing have limited therapeutic efficacy due to lengthy healing times, risk of immune rejection, and susceptibility to infection. Recently, adipose‐derived mesenchymal stem cell‐derived exosomes (ADSC‐exos) have emerged as a promising modality for tissue regeneration and wound repair. In this study, the development of a novel extracellular matrix hydrogel@exosomes (ECM@exo) is reported, which entails incorporation of ADSC‐exos into an extracellular matrix hydrogel (ECM hydrogel). This solution forms a hydrogel at physiological temperature (≈37 °C) upon local injection into the wound site. ECM@exo enables sustained release of ADSC‐exos from the ECM hydrogel, which maintains high local concentrations at the wound site. The ECM hydrogel displays good biocompatibility and biodegradability. The in vivo and in vitro results demonstrate that ECM@exo treatment effectively reduces inflammation and promotes angiogenesis, collagen deposition, cell proliferation, and migration, thereby accelerating the wound healing process. Overall, this innovative therapeutic approach offers a new avenue for wound healing via a biological hydrogel with controlled exosome release.

Psoriasis is an inflammatory skin disease that is intricately linked to oxidative stress. Antioxidation and inhibition of abnormal proliferation of keratinocytes are pivotal strategies for psoriasis. Delivering drugs with these effects to the site of skin lesions is a challenge that needs to be solved. Herein, we reported a nanotransdermal delivery system composed of all-trans retinoic acid (TRA), triphenylphosphine (TPP)-modified cerium oxide (CeO2) nanoparticles, flexible nanoliposomes and gels (TCeO2-TRA-FNL-Gel). The results revealed that TCeO2 synthesized by the anti-micelle method, with a size of approximately 5 nm, possessed excellent mitochondrial targeting ability and valence conversion capability related to scavenging reactive oxygen species (ROS). TCeO2-TRA-FNL prepared by the film dispersion method, with a size of approximately 70 nm, showed high drug encapsulation efficiency (>96%). TCeO2-TRA-FNL-Gel further showed sustained drug release behaviors, great transdermal permeation ability, and greater skin retention than the free TRA. The results of in vitro EGF-induced and H2O2-induced models suggested that TCeO2-TRA-FNL effectively reduced the level of inflammation and alleviated oxidative stress in HaCat cells. The results of in vivo imiquimod (IMQ)-induced model indicated that TCeO2-TRA-FNL-Gel could greatly alleviate the psoriasis symptoms. In summary, the transdermal drug delivery system designed in this study has shown excellent therapeutic effects on psoriasis and is prospective for the safe and accurate therapy of psoriasis.

BackgroundThe relationship between gut microbiota and the occurrence of cholecystitis remains unclear. Existing research lacks a clear understanding of how circulating vitamin levels modulate this relationship. Therefore, our study aims to investigate whether circulating vitamin levels mediate the causal relationship between gut microbiota and cholecystitis using a two-step bidirectional Mendelian randomization approach.MethodsIn this study, we initially employed Linkage Disequilibrium Score Regression (LDSC) analysis to assess the genetic correlation of five circulating vitamin level genome-wide association study (GWAS) summary datasets, thereby avoiding potential sample overlap. Subsequently, we conducted a two-step analysis to investigate the causal effects between gut microbiota and cholecystitis. In the second step, we explored the causal relationship between circulating vitamin levels and cholecystitis and identified the mediating role of vitamin D. The primary method used for causal analysis was the inverse variance-weighted approach. We performed additional sensitivity analyses to ensure result robustness, including the cML-MA method and reverse Mendelian randomization (MR) analysis.ResultsAn increment of one standard deviation in RuminococcaceaeUCG003 was associated with a 25% increased risk of cholecystitis (OR = 1.25, 95%CI = 1.01–1.54, p = 0.04), along with a 3% decrease in 25-hydroxyvitamin D levels (OR = 0.97, 95%CI = 0.944–0.998, p = 0.04). However, following the rigorous Bonferroni correction, every one standard deviation decrease in circulating vitamin D levels was associated with a 33% increased risk of cholecystitis (OR = 0.67, 95%CI = 0.49–0.90, p = 0.008, Padjust = 0.04). Thus, the potential link between gut microbiota and cholecystitis risk might be mediated by circulating vitamin D levels (proportion mediated = 5.5%). Sensitivity analyses provided no evidence of pleiotropy.ConclusionOur study results suggest that an elevated abundance of specific gut microbiota is associated with an increased susceptibility to cholecystitis, with the causal relationship being mediated by circulating vitamin D levels. Further large-scale randomized controlled trials are necessary to validate the causal effects of gut microbiota on cholecystitis risk. This study provides novel insights into cholecystitis prevention through the regulation of gut microbiota.

Abstract Background Endoscopic screening is the widely accepted screening strategy for esophageal squmaous cell carcinoma (ESCC). However, massive endoscopic screening is expensive and not cost-efficient, and novel pre-endoscopy detection used as a preliminary screening method arouses new concerns. We are planning to launch an artificial intelligence (AI) assisted sponge cytology for detecting esophageal squmaous high-grade intraepithelial neoplasia (HGIN) and above lesions. The aim of this trail is to investigate the efficiency of AI-assisted sponge cytology in population-based screening of early esophageal squmaous epithelial lesions. Methods The study will be prospectively conducted in five regions with a high prevalence of ESCC. AI-assisted sponge cytology and endoscopic examination will be sequentially performed. Based on our previous data, at least 864 patients with esophageal HGIN and above lesions are needed to achieve enough statistical power. And, a calculated 112,500 individuals with high risks of ESCC will be recruited. In the first stage, each 24,000 participants who meet the inclusion criteria will be recruited on a voluntary basis. Setting pathological results as standard reference, diagnostic threshold and according performance of AI-assisted detection will be evaluated. A prediction model will be constructed by co-analyzing cytological results and relevant risk factors. Then, an external validation cohort will be used for validation of the model efficiency. Also, cost-efficiency analysis will be performed. This study protocol was registered on chineseclinicaltrial.gov (ChiCTR1900028524). Discussion Our study will determine whether this AI-assisted sponge cytology can be used as an effective pre-endoscopy detection tool for large-scale screening for ESCC in high-risk areas.

Silicon is an abundant element on earth and is perfectly compatible with the well-established CMOS processing industry. Here, Sun et al. demonstrate multifunctional neuromorphic devices based on silicon nanosheet stacks, bringing silicon back as a potential material for neuromorphic devices.

Background and purposeBreast cancer is a rapidly raising healthcare problem worldwide. DESTINY-Breast04 demonstrated that trastuzumab deruxtecan (T-Dxd) had a survival advantage comparing to the physician's choice of chemotherapy for patients with HER2-low metastatic breast cancer. But at the same time, this expensive novel treatment also brought an economic burden. This study assessed the cost-effectiveness of T-Dxd based on results of DESTINY-Breast04 from the perspective of Chinese healthcare system.Materials and methodsA three-state partitioned-survival model [progression-free survival (PFS), progressive disease (PD) and death] based on data from DESTINY-Breast04 and Chinese healthcare system was used to estimate the incremental cost-effectiveness ratio (ICER) of T-Dxd vs. the physician's choice of chemotherapy for HER2-low metastatic breast cancer. Costs, quality-adjusted life-years (QALYs) and the ICER in terms of 2022 US$ per QALY gained were calculated for both hormone receptor–positive cohort and all patients. One-way and probabilistic sensitivity analyses were performed to assess the model robustness.ResultsCompared with the physician's choice of chemotherapy, T-Dxd increased costs by $104,168.30, while gaining 0.31 QALYs, resulting in an ICER of $336,026.77 per QALY in all patients. The costs of T-Dxd and the utility of PFS were the crucial factors in determining the ICER. In the hormone receptor–positive cohort, the ICER was lower than that in all patients, with the ICER of $274,905.72 per QALY. The ICER was much higher than the commonly accepted willingness-to-pay threshold ($357,96.83 per QALY).ConclusionT-Dxd as second- or subsequent-line treatment is not a cost-effective treatment option for HER2-low metastatic breast cancer from the perspective of the Chinese healthcare system.

Aims: As the impact of inclisiran in stroke prevention in atherosclerotic cardiovascular disease (ASCVD) patients or those at high risk of ASCVD is still unclear, we conducted a systematic review and meta-analysis of randomized controlled trials (RCT) to quantify the effectiveness of inclisiran in stroke prevention in these patients.Methods: Literature research was conducted in four electronic databases (PubMed, EMBASE, Web of Science, CENTRAL) and two clinical trials registers (ClinicalTrials.gov, WHO ICTRP) from the inception of the study to 17 October 2022, and was updated by the end of the study on 5 January 2023. Two authors independently screened the studies, extracted the data, and assessed the bias. The risk of bias was assessed using the Cochrane risk-of-bias tool for randomized trials (RoB 2). The intervention effect was estimated by calculating risk ratio (RR), weighted mean difference (WMD), and 95% confidence interval (CI) with R 4.0.5. Sensitivity analysis by changing meta-analysis model was also performed to test the robustness of the pooled results. If this was not possible, a descriptive analysis was conducted.Results: Four RCTs (n = 3,713 patients) were rated as high-risk bias. Meta-analysis of three RCTs (ORION-9, ORION-10, and ORION-11) showed that inclisiran reduced myocardial infarction (MI) risk by 32% (RR = 0.68, 95%CI = 0.48–0.96) but did not reduce stroke (RR = 0.92, 95%CI = 0.54–1.58) and major cardiovascular events (MACE) (RR = 0.81, 95%CI = 0.65–1.02) risk. Sensitivity analysis results were stable. Safety was similar to the placebo group but had frequent injection-site reactions (RR = 6.56, 95%CI = 3.83–11.25), which were predominantly mild or moderate. A descriptive analysis of one RCT (ORION-5) was conducted due to different study designs, and suggested that inclisiran might be given semiannually from the beginning.Conclusion: Inclisiran is not beneficial for stroke or MACE prevention in ASCVD or patients at high risk of ASCVD but is associated with the reduction of MI. Given the limited number and quality of the available studies and the lack of a standardized definition for cardiovascular events, further studies are essential for confirming the results.

Intracerebral hemorrhage (ICH), a subtype of stroke, can lead to long-term disability and is one of the leading causes of death. Unfortunately, the effectiveness of pharmacological therapy for ICH is still uncertain. Long non-coding RNA (lncRNA) was defined as an RNA molecule that consists of more than 200 nt without translational activity. As a vital class of diverse molecules, lncRNAs are involved in developmental and pathological processes and have been attractive for decades. LncRNAs have also become potential targets for therapies, as they were massively identified and profiled. In particular, emerging evidence has revealed the critical role of lncRNAs in ICH while attempts were made to treat ICH via regulating lncRNAs. But the latest evidence remains to be summarized. Thus, in this review, we will summarize the recent advances in lncRNA in ICH, highlighting the regulatory role of lncRNAs and their potential as therapeutic targets.

The neonatal period is a critical window for the development of the human brain and may hold implications for the long-term development of cognition and disorders. Multi-modal connectome studies have revealed many important findings underlying the adult brain but related studies were rare in the early human brain. One potential challenge is the lack of an appropriate and unbiased parcellation that combines structural and functional information in this population. Using 348 multi-modal MRI datasets from the developing human connectome project, we found that the information fused from the structural, diffusion, and functional MRI was relatively stable across MRI features and showed high reproducibility at the group level. Therefore, we generated automated multi-resolution parcellations (300 - 500 parcels) based on the similarity across multi-modal features using a gradient-based parcellation algorithm. In addition, to acquire a parcellation with high interpretability, we provided a manually delineated parcellation (210 parcels), which was approximately symmetric, and the adjacent areas around each boundary were statistically different in terms of the integrated similarity metric and at least one kind of original features. Overall, the present study provided multi-resolution and neonate-specific parcellations of the cerebral cortex based on multi-modal MRI properties, which may facilitate future studies of the human connectome in the early development period.

Hazel leaf, a by-product of hazelnuts, is commonly used in traditional folk medicine in Portugal, Sweden, Iran and other regions for properties such as vascular protection, anti-bleeding, anti-edema, anti-infection, and pain relief. Based on our previous studies, the polyphenol extract from hazel leaf was identified and quantified via HPLC fingerprint. The contents of nine compounds including kaempferol, chlorogenic acid, myricetin, caffeic acid, p-coumaric acid, resveratrol, luteolin, gallic acid and ellagic acid in hazel leaf polyphenol extract (ZP) were preliminary calculated, among which kaempferol was the highest with 221.99 mg/g, followed by chlorogenic acid with 8.23 mg/g. The inhibition of ZP on α-glucosidase and xanthine oxidase activities was determined via the chemical method, and the inhibition on xanthine oxidase was better. Then, the effect of ZP on hyperuricemia zebrafish was investigated. It was found that ZP obviously reduced the levels of uric acid, xanthine oxidase, urea nitrogen and creatinine, and up-regulated the expression ofOAT1 and HPRT genes in hyperuricemia zebrafish. Finally, the targeted network pharmacological analysis and molecular docking of nine polyphenol compounds were performed to search for relevant mechanisms for alleviating hyperuricemia. These results will provide a valuable basis for the development and application of hazel leaf polyphenols as functional ingredients.

Ensuring food security for the global population is a ceaseless and critical issue. However, high-salinity and high-alkalinity levels can harm agricultural yields throughout large areas, even in largely agricultural countries, such as China. Various physical and chemical treatments have been employed in different locations to mitigate high salinity and alkalinity but their effects have been minimal. Numerous researchers have recently focused on developing effective and environmentally friendly biological treatments. Endophytes, which are naturally occurring and abundant in plants, retain many of the same characteristics of plants owing to their simultaneous evolution. Therefore, extraction of endophytes from salt-tolerant plants for managing plant growth in saline–alkali soils has become an important research topic. This extraction indicates that the soil environment can be fundamentally improved, and the signaling pathways of plants can be altered to increase their defense capacity, and can even be inherited to ensure lasting efficacy. This study discusses the direct and indirect means by which plant endophytes mitigate the effects of plant salinity stress that have been observed in recent years.

In order to further realize the waste utilization of PFP and reduce the waste of resources and environmental pollution, PFP pectin was extracted by ultrasonic assisted acid method and its antioxidant activity was studied. By investigating the effects of pH, solid-liquid ratio, ultrasonic time, ultrasonic power and ultrasonic temperature on the extraction ratio of PFP pectin, response surface optimization was carried out on the basis of single factor test to get the best extraction process, and acid method was used as the control. The effects of ultrasonic-assisted acid method on scavenging DPPH free radical (DPPH·), hydroxyl free radical (·OH) and superoxide anion free radical (\begin{document}$ {\text{O}}_{2}^{-} $\end{document}·) of PFP pectin were studied. The results showed that: The optimal extraction parameters of PFP pectin by ultrasonic assisted acid method were pH2.0, ultrasonic time 70 min, ultrasonic power 210 W, ultrasonic temperature 45 ℃, and the yield of pectin was 14.78%±0.21%. The scavenging rates of DPPH·, ·OH and \begin{document}$ {\text{O}}_{2}^{-} $\end{document}· were 60.96%±1.03%, 80.16%±1.78% and 59.13%±2.10%, which were higher than those of acid method.