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In the realm of precision cattle health monitoring, this paper introduces the development and evaluation of a novel wearable continuous health monitoring device designed for cattle. The device integrates a sustainable solar-powered module, real-time signal acquisition and processing, and a storage module within an animal ergonomically designed curved casing for non-invasive cattle health monitoring. The curvature of the casing is tailored to better fit the contours of the cattle’s neck, significantly enhancing signal accuracy, particularly in temperature signal acquisition. The core module is equipped with precision temperature sensors and inertial measurement units, utilizing the Arduino MKR ZERO board for data acquisition and processing. Field tests conducted on a cohort of ten cattle not only validated the accuracy of temperature sensing but also demonstrated the potential of machine learning, particularly the Support Vector Machine algorithm, for precise behavior classification and step counting, with an average accuracy of 97.27%. This study innovatively combines real-time temperature recognition, behavior classification, and step counting organically within a self-powered device. The results underscore the feasibility of this technology in enhancing cattle welfare and farm management efficiency, providing clear direction for future research to further enhance these devices for large-scale applications.

The receptive field (RF) plays a crucial role in convolutional neural networks (CNNs) because it determines the amount of input information that each neuron in a CNN can perceive, which directly affects the feature extraction ability. As the number of convolutional layers in CNNs increases, there is a decay of the RF according to the two-dimensional Gaussian distribution. Thus, an effective receptive field (ERF) can be used to characterize the available part of the RF. The ERF is calculated by the kernel size and layer number within the neural network architecture. Currently, ERF calculation methods are typically applied to single-channel input data that are both independent and identically distributed. However, such methods may result in a loss of effective information if they are applied to more general (i.e., multi-channel) datasets. Therefore, we proposed a multi-channel ERF calculation method. By conducting a series of numerical experiments, we determined the relationship between the ERF and the convolutional kernel size in conjunction with the layer number. To validate the new method, we used the recently published global wave surrogate model for climate simulation (GWSM4C) and its accompanying dataset. According to the newly established relationship, we refined the kernel size and layer number in each neural network of the GWSM4C to produce the same ERF but lower RF attenuation rates than those of the original version. By visualizing the gradient map at several points in West African and East Pacific areas, the high gradient value regions confirmed the known swell sources, which indicated effective feature extraction in these areas. Furthermore, the new version of the GWSM4C yielded better prediction accuracy for significant wave height in global swell pools. The root mean square errors in the West African and East Pacific regions reduced from approximately 0.3 m, in the original model to about 0.15 m, in the new model. Moreover, these improvements were attributed to the higher efficiency of the newly modified neural network structure that allows the inclusion of more historical winds while maintaining acceptable computational consumption.

BackgroundImage-guided surgical navigation systems are widely regarded as the benchmark for computer-assisted surgical robotic platforms, yet a persistent challenge remains in addressing intraoperative image drift and mismatch. It can significantly impact the accuracy and precision of surgical procedures. Therefore, further research and development are necessary to mitigate this issue and enhance the overall performance of these advanced surgical platforms.ObjectiveThe primary objective is to improve the precision of image guided puncture navigation systems by developing a computed tomography (CT) and structured light imaging (SLI) based navigation system. Furthermore, we also aim to quantifying and visualize intraoperative image drift and mismatch in real time and provide feedback to surgeons, ensuring that surgical procedures are executed with accuracy and reliability.MethodsA CT-SLI guided orthopedic navigation puncture system was developed. Polymer bandages are employed to pressurize, plasticize, immobilize and toughen the surface of a specimen for surgical operations. Preoperative CT images of the specimen are acquired, a 3D navigation map is reconstructed and a puncture path planned accordingly. During surgery, an SLI module captures and reconstructs the 3D surfaces of both the specimen and a guiding tube for the puncture needle. The SLI reconstructed 3D surface of the specimen is matched to the CT navigation map via two-step point cloud registrations, while the SLI reconstructed 3D surface of the guiding tube is fitted by a cylindrical model, which is in turn aligned with the planned puncture path. The proposed system has been tested and evaluated using 20 formalin-soaked lower limb cadaver specimens preserved at a local hospital.ResultsThe proposed method achieved image registration RMS errors of 0.576 ± 0.146 mm and 0.407 ± 0.234 mm between preoperative CT and intraoperative SLI surface models and between preoperative and postoperative CT surface models. In addition, preoperative and postoperative specimen surface and skeletal drifts were 0.033 ± 0.272 mm and 0.235 ± 0.197 mm respectively.ConclusionThe results indicate that the proposed method is effective in reducing intraoperative image drift and mismatch. The system also visualizes intraoperative image drift and mismatch, and provides real time visual feedback to surgeons.

BackgroundPulmonary fibrosis (PF) emerges as a significant pulmonary sequelae in the convalescent phase of coronavirus disease 2019 (COVID-19), with current strategies neither specifically preventive nor therapeutic. Licoricesaponin G2 (LG2) displays a spectrum of natural activities, including antibacterial, anti-inflammatory, and antioxidant properties, and has been effectively used in treating various respiratory conditions. However, the potential protective effects of LG2 against PF remain underexplored.MethodsNetwork analysis and molecular docking were conducted in combination to identify the core targets and pathways through which LG2 acts against PF. In the model of bleomycin (BLM)-induced C57 mice and transforming growth factor-β1 (TGF-β1)-induced A549 and MRC5 cells, techniques such as western blot (WB), quantitative Real-Time PCR (qPCR), Immunohistochemistry (IHC), Immunofluorescence (IF), and Transwell migration assays were utilized to analyze the expression of Epithelial-mesenchymal transition (EMT) and inflammation proteins. Based on the analysis above, we identified targets and potential mechanisms underlying LG2’s effects against PF.ResultsNetwork analysis has suggested that the mechanism by which LG2 combats PF may involve the TNF-α pathway. Molecular docking studies have demonstrated a high binding affinity of LG2 to TNF-α and MMP9. Observations from the study indicated that LG2 may mitigate PF by modulating EMT and extracellular matrix (ECM) remodeling. It is proposed that the therapeutic effect is likely arises from the inhibition of inflammatory expression through regulation of the TNF-α pathway.ConclusionLG2 mitigates PF by suppressing TNF-α signaling pathway activation, modulating EMT, and remodeling the ECM. These results provide compelling evidence supporting the use of LG2 as a potential natural therapeutic agent for PF in clinical trials.

Predicting nearshore significant wave heights (SWHs) with high accuracy is of great importance for coastal engineering activities, marine and coastal resource studies, and related operations. In recent years, the prediction of SWHs in two-dimensional fields based on deep learning has been gradually emerging. However, predictions for nearshore areas still suffer from insufficient resolution and poor accuracy. This paper develops a NS (NearShore) model based on the GWSM4C model (Global Wave Surrogate Model for Climate simulations). In the training area, the GWSM4C -NS model achieved a correlation coefficient (CC) of 0.977, with a spatial Root Mean Square Error (RMSE), annual mean spatial relative error (MAPE), and annual mean spatial absolute error (MAE) of 0.128 m, 10.7%, and 0.103 m, respectively. Compared to the GWSM4C model’s predictions, the RMSE and MAE decreased by 59% and 60% respectively, demonstrating the model’s effectiveness in enhancing nearshore SWH predictions. Additionally, applying this model to untrained sea areas to further validate its learning capability in wave energy propagation resulted in a CC of 0.951, with RMSE, MAPE, and MAE of 0.161m, 12.9%, and 0.137m, respectively. The RMSE and MAE were 43% and 39% lower than the GWSM4C model’s interpolated predictions. The results shown above suggest that the newly proposed model can effectively improve the performance of GWSM4C in nearshore areas.

IntroductionTo enhance the precision of evaluating the impact of urban environments on resident health, this study introduces a novel fuzzy intelligent computing model designed to address health risk concerns using multi-media environmental monitoring data.MethodsThree cities were selected for the study: Beijing (B City), Kunming (K City), and Wuxi (W City), representing high, low, and moderate pollution levels, respectively. The study employs a Fuzzy Inference System (FIS) as the chosen fuzzy intelligent computing model, synthesizing multi-media environmental monitoring data for the purpose of urban health risk assessment.Results(1) The model reliably estimates health risks across diverse cities and environmental conditions. (2) There is a positive correlation between PM2.5 concentrations and health risks, though the impact of noise levels varies by city. In cities B, K, and W, the respective correlation coefficients are 0.65, 0.55, and 0.7. (3) The Root Mean Square Error (RMSE) values for cities B, K, and W, are 0.0132, 0.0125, and 0.0118, respectively, indicating that the model has high accuracy. The R2 values for the three cities are 0.8963, 0.9127, and 0.9254, respectively, demonstrating the model’s high explanatory power. The residual values for the three cities are 0.0087, 0.0075, and 0.0069, respectively, indicating small residuals and demonstrating robustness and adaptability. (4) The model’s p-values for the Indoor Air Quality Index (IAQI), Thermal Comfort Index (TCI), and Noise Pollution Index (NPI) all satisfy p < 0.05 for the three cities, affirming the model’s credibility in estimating health risks under varied urban environments.DiscussionThese results showcase the model’s ability to adapt to diverse geographical conditions and aid in the accurate assessment of existing risks in urban settings. This study significantly advances environmental health risk assessment by integrating multidimensional data, enhancing the formulation of comprehensive environmental protection and health management strategies, and providing scientific support for sustainable urban planning.

IntroductionThis paper aims to explore the intersection of corporate social responsibility (CSR) and public health within the context of digital platforms. Specifically, the paper explores the impact of digital platforms on the sustainable development practices of enterprises, seeking to comprehend how these platforms influence the implementation of environmental protection policies, resource management, and social responsibility initiatives.MethodsTo assess the impact of digital platforms on corporate environmental behavior, we conducted a questionnaire survey targeting employees in private enterprises. This survey aimed to evaluate the relationship between the adoption of digital platforms and the implementation of environmental protection policies and practices.ResultsAnalysis of the survey responses revealed a significant positive correlation between the use of digital platforms and the environmental protection behavior of enterprises (r=0.523;p

Objective: The aim of this study was to compare the pharmacokinetics and steady-state serum concentrations of lenvatinib in adult and juvenile rats.Experimental study: An ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) method was developed to quantify lenvatinib in the serum and liver of rats. Six juvenile and six adult rats in each group were orally administered with a single dose of 7.0 mg/kg lenvatinib suspension for pharmacokinetics. Another 12 juvenile and adult rats were subjected to oral gavage with 7.0 mg/kg lenvatinib once daily for 5 days. Biofluild samples were pre-treated by protein precipitation and sorafenib was used as the internal standard for UPLC-MS analysis. The pharmacokinetic parameters were estimated by compartment and statistical model. The mRNA expression of CYP3A2 and SLC22A1 in liver of adult and juvenile rats was measured by real-time fluorescence quantitative PCR (RT-qPCR).Results: The UPLC-MS method met the requirements for quantitative analysis of lenvatinib in serum and liver. The pharmacokinetic results showed that the mean retention time (MRT(0-∞)) was 19.64 ± 7.64 h and 126.38 ± 130.18 h, with AUC(0-∞) values of 3.97 ± 0.73 μg‧mL-1 h and 5.95 ± 2.27 μg mL-1 h in adult and juvenile rats, respectively. When comparing adult rats (0.35 ± 0.15 μg/mL) to juvenile rats, no significant differences were observed in steady-state serum lenvatinib (0.32 ± 0.11 μg/mL), but a noteworthy decrease to one-third of steady-state liver lenvatinib was observed after multiple oral doses of lenvatinib in juvenile rats. Additional findings revealed that the mRNA expression of CYP3A2 and SLC22A1 was notably increased by 6.86 and 14.67 times, respectively, in juvenile rats compared to adult rats.Conclusion: Juvenile rats exhibit lower levels of lenvatinib in the liver’s steady-state, potentially due to the disparity in CYP3A2 mRNA expression. These results imply that the dosage of lenvatinib for pediatric patients may need to be augmented in order to attain the desired clinical outcome.

Airborne forward-looking radar (AFLR) has been more and more impoatant due to its wide application in the military and civilian fields, such as automatic driving, sea surveillance, airport surveillance and guidance. Recently, sparse deconvolution technique has been paid much attention in AFLR. However, the azimuth resolution performance gradually decreases with the complexity of the imaging scene. In this paper, a data-driven airborne Bayesian forward-looking superresolution imaging algorithm based on generalized gaussian distribution (GGD- Bayesian) for complex imaging scene is proposed. The generalized gaussian distribution is utilized to describe the sparsity information of the imaging scene, which is quite essential to adaptively fit different imaging scenes. Moreover, the mathematical model for forward-looking imaging was established under the maximum a posteriori (MAP) criterion based on the Bayesian framework. To solve the above optimization problem, quasi-Newton algorithm is derived and used. The main contribution of the paper is the automatic selection for the sparsity parameter in the process of forward-looking imaging. The performance assessment with simulated data has demonstrated the effectiveness of our proposed GGD- Bayesian algorithm under complex scenarios.

BackgroundChildren with influenza B virus infection have a higher susceptibility and higher severity of illness. The activation and disorder of immune function play an important role in the severity of influenza virus infection. This study aims to investigate whether early lymphocyte count and cytokines can provide predictive value for the progression in children with influenza B virus pneumonia.MethodsA retrospective cohort study was conducted to analyze the clinical data of children with influenza B virus pneumonia from December 1, 2021, to March 31, 2022, in the National Children’s Regional Medical Center (Shengjing Hospital of China Medical University). According to the severity of the disease, the children were divided into a mild group and a severe group, and the clinical characteristics, routine laboratory examination, lymphocyte subsets, and cytokines were compared.ResultsA total of 93 children with influenza B virus pneumonia were enrolled, including 70 cases in the mild group and 23 cases in the severe group. Univariate analysis showed that drowsiness, dyspnea, white blood cell (WBC), lymphocytes, monocytes, procalcitonin, alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatine kinase-MB (CK-MB), lactate dehydrogenase (LDH), fibrinogen (FIB), Immunoglobulin M (IgM), lung consolidation, total T cell count, CD4+ T cell count, CD8+ T cell count, NK cell count, NK cell % and B cell % had statistical differences between the mild and severe groups (P

IntroductionGlioblastoma is a malignant brain tumor with poor prognosis. Lactate is the main product of tumor cells, and its secretion may relate to immunocytes’ activation. However, its role in glioblastoma is poorly understood. MethodsThis work performed bulk RNA-seq analysis and single cell RNA-seq analysis to explore the role of lactate in glioblastoma progression. Over 1400 glioblastoma samples were grouped into different clusters according to their expression and the results were validated with our own data, the xiangya cohort. Immunocytes infiltration analysis, immunogram and the map of immune checkpoint genes’ expression were applied to analyze the potential connection between the lactate level with tumor immune microenvironment. Furthermore, machine learning algorithms and cell-cell interaction algorithm were introduced to reveal the connection of tumor cells with immunocytes. By co-culturing CD8 T cells with tumor cells, and performing immunohistochemistry on Xiangya cohort samples further validated results from previous analysis.DiscussionIn this work, lactate is proved that contributes to glioblastoma immune suppressive microenvironment. High level of lactate in tumor microenvironment can affect CD8 T cells’ migration and infiltration ratio in glioblastoma. To step further, potential compounds that targets to samples from different groups were also predicted for future exploration.

BackgroundPioglitazone is considered a potential therapy for non-alcoholic fatty liver disease (NAFLD). However, different effects of pioglitazone on NAFLD have been demonstrated in diabetic and non-diabetic patients. Herein, a meta-analysis of randomized, placebo-controlled trials was carried out to indirectly compare pioglitazone in NAFLD patients with vs. without type 2 diabetes.MethodsRandomized controlled trials (RCTs) of pioglitazone vs. placebo involving NAFLD patients with or without type 2 diabetes/prediabetes collected from databases were enrolled into this analysis. Methodological quality was employed to evaluate the domains recommended by the Cochrane Collaboration. The analysis covered the changes in histology (fibrosis, hepatocellular ballooning, inflammation, steatosis), liver enzymes, blood lipids, fasting blood glucose (FBS), homeostasis model assessment-IR (HOMA-IR), weight and body mass index (BMI) before and after treatment, and adverse events.ResultsThe review covered seven articles, with 614 patients in total, of which three were non-diabetic RCTs. No difference was found in patients with vs. without type 2 diabetes in histology, liver enzymes, blood lipids, HOMA-IR, weight, BMI, and FBS. Moreover, no significant difference was revealed in adverse effects between NAFLD patients with diabetes and without DM, except the incidence of edema that was found to be higher in the pioglitazone group than in the placebo group in NAFLD patients with diabetes.ConclusionsPioglitazone could exert a certain effect on alleviating NAFLD, which was consistent between non-diabetic NAFLD patients and diabetic NAFLD patients in improving histopathology, liver enzymes, and HOMA-IR and reducing blood lipids. Furthermore, there were no adverse effects, except the incidence of edema which is higher in the pioglitazone group in NAFLD patients with diabetes. However, large sample sizes and well-designed RCTs are required to further confirm these conclusions.

Background: Respiratory diseases are common and frequent diseases. Due to the high pathogenicity and side effects of respiratory diseases, the discovery of new strategies for drug treatment is a hot area of research. Scutellaria baicalensis Georgi (SBG) has been used as a medicinal herb in China for over 2000 years. Baicalin (BA) is a flavonoid active ingredient extracted from SBG that BA has been found to exert various pharmacological effects against respiratory diseases. However, there is no comprehensive review of the mechanism of the effects of BA in treating respiratory diseases. This review aims to summarize the current pharmacokinetics of BA, baicalin-loaded nano-delivery system, and its molecular mechanisms and therapeutical effects for treating respiratory diseases.Method: This review reviewed databases such as PubMed, NCBI, and Web of Science from their inception to 13 December 2022, in which literature was related to “baicalin”, “Scutellaria baicalensis Georgi”, “COVID-19”, “acute lung injury”, “pulmonary arterial hypertension”, “asthma”, “chronic obstructive pulmonary disease”, “pulmonary fibrosis”, “lung cancer”, “pharmacokinetics”, “liposomes”, “nano-emulsions”, “micelles”, “phospholipid complexes”, “solid dispersions”, “inclusion complexes”, and other terms.Result: The pharmacokinetics of BA involves mainly gastrointestinal hydrolysis, the enteroglycoside cycle, multiple metabolic pathways, and excretion in bile and urine. Due to the poor bioavailability and solubility of BA, liposomes, nano-emulsions, micelles, phospholipid complexes, solid dispersions, and inclusion complexes of BA have been developed to improve its bioavailability, lung targeting, and solubility. BA exerts potent effects mainly by mediating upstream oxidative stress, inflammation, apoptosis, and immune response pathways. It regulates are the NF-κB, PI3K/AKT, TGF-β/Smad, Nrf2/HO-1, and ERK/GSK3β pathways.Conclusion: This review presents comprehensive information on BA about pharmacokinetics, baicalin-loaded nano-delivery system, and its therapeutic effects and potential pharmacological mechanisms in respiratory diseases. The available studies suggest that BA has excellent possible treatment of respiratory diseases and is worthy of further investigation and development.

ObjectivesPost-stroke depression (PSD) is a common and serious psychiatric complication which hinders functional recovery and social participation of stroke patients. Stroke is characterized by dynamic changes in metabolism and hemodynamics, however, there is still a lack of metabolism-associated effective and reliable diagnostic markers and therapeutic targets for PSD. Our study was dedicated to the discovery of metabolism related diagnostic and therapeutic biomarkers for PSD.MethodsExpression profiles of GSE140275, GSE122709, and GSE180470 were obtained from GEO database. Differentially expressed genes (DEGs) were detected in GSE140275 and GSE122709. Functional enrichment analysis was performed for DEGs in GSE140275. Weighted gene co-expression network analysis (WGCNA) was constructed in GSE122709 to identify key module genes. Moreover, correlation analysis was performed to obtain metabolism related genes. Interaction analysis of key module genes, metabolism related genes, and DEGs in GSE122709 was performed to obtain candidate hub genes. Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and random forest, were used to identify signature genes. Expression of signature genes was validated in GSE140275, GSE122709, and GSE180470. Gene set enrichment analysis (GSEA) was applied on signature genes. Based on signature genes, a nomogram model was constructed in our PSD cohort (27 PSD patients vs. 54 controls). ROC curves were performed for the estimation of its diagnostic value. Finally, correlation analysis between expression of signature genes and several clinical traits was performed.ResultsFunctional enrichment analysis indicated that DEGs in GSE140275 enriched in metabolism pathway. A total of 8,188 metabolism associated genes were identified by correlation analysis. WGCNA analysis was constructed to obtain 3,471 key module genes. A total of 557 candidate hub genes were identified by interaction analysis. Furthermore, two signature genes (SDHD and FERMT3) were selected using LASSO and random forest analysis. GSEA analysis found that two signature genes had major roles in depression. Subsequently, PSD cohort was collected for constructing a PSD diagnosis. Nomogram model showed good reliability and validity. AUC values of receiver operating characteristic (ROC) curve of SDHD and FERMT3 were 0.896 and 0.964. ROC curves showed that two signature genes played a significant role in diagnosis of PSD. Correlation analysis found that SDHD (r = 0.653, P < 0.001) and FERM3 (r = 0.728, P < 0.001) were positively related to the Hamilton Depression Rating Scale 17-item (HAMD) score.ConclusionA total of 557 metabolism associated candidate hub genes were obtained by interaction with DEGs in GSE122709, key modules genes, and metabolism related genes. Based on machine learning algorithms, two signature genes (SDHD and FERMT3) were identified, they were proved to be valuable therapeutic and diagnostic biomarkers for PSD. Early diagnosis and prevention of PSD were made possible by our findings.

BackgroundJuvenile polyposis syndrome (JPS) is a rare autosomal dominant disorder that is a type of hamartomatous polyp syndrome, and its incidence rate is approximately 1/100000. The main clinical feature is the presence of multiple juvenile polyps in the gastrointestinal tract, most often in the colorectal tract. We present a case of juvenile polyposis syndrome with massive gastric polyposis.Case presentationA 50-year-old male was admitted to the hospital due to abdominal distension and poor appetite. Gastroscopy revealed a large number of gastric polyps. Pathological findings revealed gastric juvenile polyps. Genetic testing revealed that he and his brother both carried SMAD4: c.266_269del germline pathogenic variant. The final diagnosis was juvenile polyposis syndrome of the stomach. He once suffered from colon cancer and bladder cancer. One of his brothers died of colon cancer, and the other brother suffered from colon polyps.ConclusionsGastric involvement in juvenile polyposis syndrome is relatively rare. When massive gastric polyposis is found, gene detection should be carried out as soon as possible, so that rapid diagnosis and treatment can be obtained.

We show how reinforcement learning can be used in conjunction with quantile regression to develop a hedging strategy for a trader responsible for derivatives that arrive stochastically and depend on a single underlying asset. We assume that the trader makes the portfolio delta-neutral at the end of each day by taking a position in the underlying asset. We focus on how trades in options can be used to manage gamma and vega. The option trades are subject to transaction costs. We consider three different objective functions. We reach conclusions on how the optimal hedging strategy depends on the trader's objective function, the level of transaction costs, and the maturity of the options used for hedging. We also investigate the robustness of the hedging strategy to the process assumed for the underlying asset.

BackgroundThe incidence and mortality of uterine corpus endometrial carcinoma (UCEC) are increasing yearly. There is currently no screening test for UCEC, and progress in its treatment is limited. It is important to identify new biomarkers for screening, diagnosing and predicting the outcomes of UCEC. A large number of previous studies have proven that KNL1 is crucial in the development of lung cancer, colorectal cancer and cervical cancer, but there is a lack of studies about the role of KNL1 in the development of UCEC.MethodsThe mRNA and protein expression data of KNL1 in The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and UALCAN databases and related clinical data were used to analyze the expression differences and clinical correlations of KNL1 in UCEC. A total of 108 clinical samples were collected, and the results of bioinformatics analysis were verified by immunohistochemistry. KNL1 and its related differentially expressed genes were used to draw a volcano map, construct a PPI protein interaction network, and perform gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA) and immune infiltration analysis to predict the function of KNL1 during UCEC progression. The prognostic data of TCGA and 108 clinical patients were used to analyze the correlation of KNL1 expression with the survival of patients, and KM survival curves were drawn. The UCEC cell lines Ishikawa and Hec-1-A were used to verify the function of KNL1.ResultsKNL1 is significantly overexpressed in UCEC and is associated with a poor prognosis. KNL1 overexpression is closely related to cell mitosis, the cell cycle and other functions and is correlated with the International Federation of Gynecology and Obstetrics (FIGO) stage, histological grade and other characteristics of UCEC patients. Knockdown of KNL1 expression in UCEC cell lines can inhibit their proliferation, invasion, metastasis and other phenotypes.ConclusionKNL1 is a prognostic and diagnostic biomarker associated with immune evasion in patients with UCEC.

BackgroundGlioma is one of the most common, primary, and lethal adult brain tumors because of its extreme aggressiveness and poor prognosis. Several recent studies relevant to the immune function of CD44, a transmembrane glycoprotein as a significant hyaluronic acid receptor, have achieved great success, revealing the critical role of CD44 in immune infiltration in gliomas. The overexpression of CD44 has been verified to correlate with cancer aggressiveness and migration, while the clinical and immune features of CD44 expression have not yet been thoroughly characterized in gliomas.MethodsMolecular and clinical data of glioma collected from publicly available genomic databases were analyzed.ResultsCD44 was up-expressed in malignant gliomas, notably in the 1p/19q non-codeletion cases, isocitrate dehydrogenase (IDH) wild-type, and mesenchymal subtypes in GBM samples. CD44 expression level strongly correlates with stromal and immune cells, mainly infiltrating the glioma microenvironment by single-cell sequencing analysis. Meanwhile, CD44 can be a promising biomarker in predicting immunotherapy responses and mediating the expression of PD-L1. Finally, RUNX1/CD44 axis could promote the proliferation and migration of gliomas.ConclusionsTherefore, CD44 was responsible for glioma growth and progression. It could potentially lead to a novel target for glioma immunotherapy or a prognostic biomarker.

Bioluminescence imaging is a non-invasive technology used to visualize physiological processes in animals and is useful for studying the dynamics of metabolic syndrome. Metabolic syndrome is a broad spectrum of diseases which are rapidly increasing in prevalence, and is closely associated with obesity, type 2 diabetes, nonalcoholic fatty liver disease, and circadian rhythm disorder. To better serve metabolic syndrome research, researchers have established a variety of animal models expressing luciferase, while also committing to finding more suitable luciferase promoters and developing more efficient luciferase-luciferin systems. In this review, we systematically summarize the applications of different models for bioluminescence imaging in the study of metabolic syndrome.

BackgroundBiliopancreatic diversion with duodenal switch (BPD-DS) is a bariatric procedure used in the treatment of obesity and related metabolic disorders. However, to date, the data on BPD-DS among Chinese patients with obesity is completely lacking.ObjectiveThis is the first study to evaluate the safety and efficacy of BPD-DS in the treatment of Chinese patients with obesity.MethodsData from 12 patients undergoing BPD-DS between September 2019 and March 2020 were analyzed retrospectively to evaluate complications, weight loss, comorbidity resolution, and nutritional status.ResultsAll patients completed the 1-year follow-up. There was no conversion to laparotomy or death. Mean operative time was 257.08 ± 29.27 min. The median length of stay was 7 days (ranging from 4–38 days). Complications occurred in three patients. The 1-year body mass index was 25.13 ± 4.71 kg/m2 with a mean excess weight loss of 100.11 ± 33.29% and a mean total weight loss of 43.22 ± 7.71%. Remission was achieved in 100% (7/7 cases) for type 2 diabetes, in 83.3% (10/12 cases) for hypertension, and in 62.5% (5/8 cases) for hyperuricemia. At 1 year after BPD-DS, the prevalence of albumin deficiency was 16.7%, for iron deficiency was 16.7%, and for zinc deficiency was 50%. There were 8.3% of the patients who were anemic. High deficiency rates for vitamins were presented mainly in vitamin A and vitamin E: vitamin A in 58.3% of the patients and vitamin E in 50% of the patients. The prevalence of asymptomatic gallstones increased significantly from 0% preoperatively to 41.7% postoperatively.ConclusionBPD-DS had excellent weight loss and resolution of comorbidities among Chinese patients with obesity. However, high rates of nutritional deficiencies and complications were found after BPD-DS, especially for vitamin A and vitamin E.

EEG phase-amplitude coupling (PAC), the amplitude of high-frequency oscillations modulated by the phase of low-frequency oscillations (LFOs), is a useful biomarker to localize epileptogenic tissue. It is commonly represented in a comodulogram of coupling strength but without coupled phase information. The phase-amplitude coupling is also found in the normal brain, and it is difficult to discriminate pathological phase-amplitude couplings from normal ones. This study proposes a novel approach based on complex-valued phase-amplitude coupling (CV-PAC) for classifying epileptic phase-amplitude coupling. The CV-PAC combines both the coupling strengths and the coupled phases of low-frequency oscillations. The complex-valued convolutional neural network (CV-CNN) is then used to classify epileptic CV-PAC. Stereo-electroencephalography (SEEG) recordings from nine intractable epilepsy patients were analyzed. The leave-one-out cross-validation is performed, and the area-under-curve (AUC) value is used as the indicator of the performance of different measures. Our result shows that the area-under-curve value is .92 for classifying epileptic CV-PAC using CV-CNN. The area-under-curve value decreases to .89, .80, and .88 while using traditional convolutional neural networks, support vector machine, and random forest, respectively. The phases of delta (1–4 Hz) and alpha (8–10 Hz) bands are different between epileptic and normal CV-PAC. The phase information of CV-PAC is important for improving classification performance. The proposed approach of CV-PAC/CV-CNN promises to identify more accurate epileptic brain activities for potential surgical intervention.

BackgroundCD161 has been linked to the appearance and development of various cancers.MethodsThe mutation map and the variation of CNVs and SNVs of CD161 were displayed according to cBioportal and GSCALite. We also evaluated the pathway enrichment and drug sensitivity of CD161 according to GSCALite. We performed a single-cell sequencing analysis of cancer cells and T cells in melanoma. The cell communication patterns related to CD161 were further explored. Multiplex immunofluorescence staining of tissue microarrays was used to detect the association between CD161 expression and macrophages and T cells.ResultsA high CD161 level was related to neoantigens expression, pathway enrichment, and drug sensitivity. In addition, single-cell sequencing analysis showed that CD161 was mainly expressed in T cells, M1 and M2 Macrophages, neoplastic, microglial cells, neurons, and cancer cells in many tumor types. Further study on pseudotime trajectories and functional annotation of CD161 proved the critical role of CD161 in tumor progression and T cell immunity in melanoma. Multiplex immunofluorescence revealed that CD161 is closely correlated with the immune infiltration of T cells and macrophages in multiple cancers. In addition, high CD161 expression predicted a favorable immunotherapy response.ConclusionCD161 is involved in the immune infiltration of T cells and macrophages and might be a promising target for tumor immunotherapy.

Gliomas, originating from the glial cells, are the most lethal type of primary tumors in the central nervous system. Standard treatments like surgery have not significantly improved the prognosis of glioblastoma patients. Recently, immune therapy has become a novel and effective option. As a conserved group of transcriptional regulators, the Sry-type HMG box (SOX) family has been proved to have a correlation with numerous diseases. Based on the large-scale machine learning, we found that the SOX family, with significant immune characteristics and genomic profiles, can be divided into two distinct clusters in gliomas, among which SOX10 was identified as an excellent immune regulator of macrophage in gliomas. The high expression of SOX10 is related to a shorter OS in LGG, HGG, and pan-cancer groups but benefited from the immunotherapy. It turned out in single-cell sequencing that SOX10 is high in neurons, M1 macrophages, and neural stem cells. Also, macrophages are found to be elevated in the SOX10 high-expression group. SOX10 has a positive correlation with macrophage cytokine production and negative regulation of macrophages’ chemotaxis and migration. In conclusion, our study demonstrates the outstanding cluster ability of the SOX family, indicating that SOX10 is an immune regulator of macrophage in gliomas, which can be an effective target for glioma immunotherapy.

BackgroundPrevious studies have shown that the hemoglobin glycation index (HGI) can be used as a predictor of diabetic complications. However, limited information is currently available to indicate the correlation between HGI and comorbidity of coronary heart disease (CHD) and diabetes. This study aimed to evaluate the potential of HGI to predict major adverse cardiovascular events (MACEs) in CHD patients with type 2 diabetes mellitus (T2DM) undergoing percutaneous coronary intervention (PCI).Materials and methodsA total of 918 CHD patients with T2DM were enrolled in a 3-year retrospective cohort study, from December 2017 to December 2020 at the First Affiliated Hospital of Zhengzhou University. Data including fasting blood glucose (FPG/FBG) and glycated hemoglobin A1c (HbA1c) were collected. HGI was calculated as actual measured HbA1c minus predicted HbA1c. Three groups were further divided based on the levels of HGI, including low, medium, and high levels.ResultKaplan Meier analysis indicated that elevated HGI was strongly associated with the occurence of MACE (log-rank P < 0.001). Multivariate Cox regression analysis revealed that elevated HGI was an independent risk factor for incident MACE in CHD patients with T2DM [adjusted hazard ratio (HR): 1.473; 95% confidence interval (CI): 1.365-1.589, P < 0.001].ConclusionsHemoglobin glycation index is an independent predictor of MACE events in CHD patients with T2DM. High HGI indicates a higher risk of MACE occurrence.

BackgroundTracheostomy is a lifesaving procedure provided for patients with severe neurological injury. However, there is a lack of clarity about whether patients can be decannulated within 6 months in those receiving tracheostomy and what factors can be detected as a predictor for decannulation.ObjectiveThe objective of this study was to explore predictive factors of decannulation in patients with neurological injury receiving tracheostomy within 6 months and construct a novel nomogram model for clinical diagnosis and treatment.MethodsThis retrospective observational study enrolled patients with neurological injury who were admitted to the ICU of neurosurgical department in the First Affiliated Hospital of Nanjing Medical University between January 2016 and March 2021. Patients were divided into decannulation group and cannulation group according to whether tracheostomy tube removal was performed within 6 months after tracheostomy. Multivariable logistic regression analysis was performed to determine associated risk factors with a bootstrap backward selection process. The nomogram to assess the probability of decannulation at 6 months was constructed based on the regression coefficients of the associated factors and validated by bootstrap resampling. Model performance was measured by examining discrimination (Harrell's C-index), calibration (calibration plots), and utility (Kaplan–Meier curves stratified by the tertile of the predicted probability calculated and subgroup analysis stratified by age and intervention).ResultsA total of 40.1% (147/367) of patients decannulated within 6 months. Significant variables in multivariable logistic regression analysis were age (odds ratio [OR], 0.972; 95% confidence interval [CI], 0.954–0.990), National Institutes of Health Stroke Scale (NIHSS) score (OR, 0.936; 95% CI, 0.911–0.963), early rehabilitation (OR, 5.062; 95% CI, 2.889–8.868), shock (OR, 0.175; 95% CI, 0.058–0.533), and secondary surgery (OR, 0.210; 95% CI, 0.078–0.566). The area under receiver operating characteristic curve estimated with these variables was of 0.793 (95% CI, 0.747–0.838; P < 0.001). A nomogram prediction model was constructed to predict the probability of decannulation in tracheostomized patients with a concordance index of 0.788 after internal validation.ConclusionWe developed a nomogram that can predict the probability of decannulation within 6 months in tracheostomized neurological injury patients. The nomogram, including age, NIHSS scores, early rehabilitation, shock, and secondary surgery, may assist clinicians in estimating patients' prognosis.

BackgroundProstate cancer (PCa), a prevalent malignant cancer in males worldwide, screening for patients might benefit more from immuno-/chemo-therapy remained inadequate and challenging due to the heterogeneity of PCa patients. Thus, the study aimed to explore the metabolic (Meta) characteristics and develop a metabolism-based signature to predict the prognosis and immuno-/chemo-therapy response for PCa patients.MethodsDifferentially expressed genes were screened among 2577 metabolism-associated genes. Univariate Cox analysis and random forest algorithms was used for features screening. Multivariate Cox regression analysis was conducted to construct a prognostic Meta-model based on all combinations of metabolism-related features. Then the correlation between MetaScore and tumor was deeply explored from prognostic, genomic variant, functional and immunological perspectives, and chemo-/immuno-therapy response. Multiple algorithms were applied to estimate the immunotherapeutic responses of two MeteScore groups. Further in vitro functional experiments were performed using PCa cells to validate the association between the expression of hub gene SLC17A4 which is one of the model component genes and tumor progression. GDSC database was employed to determine the sensitivity of chemotherapy drugs.ResultsTwo metabolism-related clusters presented different features in overall survival (OS). A metabolic model was developed weighted by the estimated regression coefficients in the multivariate Cox regression analysis (0.5154*GAS2 + 0.395*SLC17A4 - 0.1211*NTM + 0.2939*GC). This Meta-scoring system highlights the relationship between the metabolic profiles and genomic alterations, gene pathways, functional annotation, and tumor microenvironment including stromal, immune cells, and immune checkpoint in PCa. Low MetaScore is correlated with increased mutation burden and microsatellite instability, indicating a superior response to immunotherapy. Several medications that might improve patients` prognosis in the MetaScore group were identified. Additionally, our cellular experiments suggested knock-down of SLC17A4 contributes to inhibiting invasion, colony formation, and proliferation in PCa cells in vitro.ConclusionsOur study supports the metabolism-based four-gene signature as a novel and robust model for predicting prognosis, and chemo-/immuno-therapy response in PCa patients. The potential mechanisms for metabolism-associated genes in PCa oncogenesis and progression were further determined.

BackgroundThis study aimed to evaluate the efficacy and adverse events of esophageal variceal ligation (EVL) vs. EVL combined with endoscopic injection sclerosis (EIS) in the therapy of esophageal varices.MethodsPatients from January 2017 to August 2021 who received EVL alone (control group) or EVL plus EIS (intervention group) were enrolled in this retrospective study. Efficacy, including rebleeding (clinically hematemesis or melena, confirmed by endoscopy as esophagogastric varices bleeding), variceal recurrence rate (the presence of esophagogastric varices which is needed to be treated again) the number of sessions performed to complete eradication of varices, and safety (adverse events) were compared. The variceal recurrence-associated factors were derived by univariate and multivariate logistic regression analyses.ResultsThe variceal recurrence and rebleeding rate in the intervention group showed significantly lower than the control group (2.6% vs 10.3%, P = 0.006 and 20.7% vs 37.5%, P = 0.029, P = 0.006, respectively, in the 12-month follow-up). The adverse events (fever, chest pain, swallowing, and esophageal stricture) showed no significant difference between the two groups (P > 0.05). Further research showed that the efficacy of the intervention group was better than the control group only achieved in prophylactically endoscopic treatment patients. The diameter of esophageal varices and gastric varices co-exist showed significant effects on variceal recurrence in intervention group [odds ratio (OR) = 15.856; 95% confidence interval (CI), 1.709–160.143; P = 0.016 and OR = 4.5; 95% CI, 1.42–20.028; P = 0.021; respectively].ConclusionsThe intervention group may obtain lower recurrence, rebleeding rate, and fewer sessions performed to complete eradication of varices (number of sessions) and similar incidence of adverse events, especially for prophylactically treatment. Among the intervention group, the diameter of esophageal varices and gastric varices were closely associated with variceal recurrence.

The purpose of this paper is to promote the construction of digital healthy cities and improve the living standards of urban residents. Based on this, this paper analyzes the development of healthy cities, and studies community public health safety emergency management and nursing insurance service optimization methods for healthy urban environment construction. First, the concept of digital healthy urban environment construction is discussed. Then, the role of environmental health is discussed. Finally, two methods are designed to study the emergency management of public health safety and nursing insurance services in urban communities under the condition of environmental health. The results show that in the environmental health score of the city, the scores of X1 (the urban air quality excellent rate) and X6 (citizens' satisfaction with the environmental quality) were relatively low between 2016 and 2018, below 0.5 points. The scores for the remaining 3 years were relatively high, above 0.5. The scores of X2 (green coverage rate of built-up area), X3 (average grade sound effect of environmental noise in urban area), X4 (harmless treatment rate of domestic waste) and X5 (centralized treatment rate of domestic sewage) were relatively high from 2016 to 2018, above 0.5 points, and relatively low in the remaining 3 years, below 0.5 points. Meanwhile, residents are very satisfied with information collection and information management in public health and safety emergency management, and the number of very satisfied people is basically more than 40%. Satisfaction with resource allocation and privacy management is high, and the number of very satisfied people is basically above 30%. However, the satisfaction with risk perception and management measures is very low, and the number of very satisfied people is basically below 20%. It shows that the current construction of the community's public health and safety emergency management system is relatively poor in terms of X2–X5, while the development of X1 and X6 is relatively mature. The research not only provides a reference for the construction and improvement of a digital healthy city, but also contributes to the improvement of the healthy life of urban residents.

BackgroundSingle-anastomosis duodenal-ileal bypass with sleeve gastrectomy (SADI-S) is one of the most effective bariatric procedures in the treatment of type 2 diabetes mellitus (T2DM). However, the mechanisms by which SADI-S improves T2DM are not well-known.ObjectiveTo explore the effects of SADI-S on metabolites in the stool of rats with T2DM.MethodsTwenty rats were fed on high-fat diet and administered with a low-dose (30mg/kg) of streptozotocin to establish T2DM models. The rats were then randomly assigned to the SADI-S group (n=10) and sham operation group (n=9). Stool samples were collected from all rats at 8 weeks after surgery and stored at -80 °C. Metabolomics analysis was performed to identify differential metabolites through ultra- performance liquid chromatography-mass spectrometry.ResultsAt 8-week after surgery, rats of the SADI-S group showed significantly decreased fasting blood glucose, glucose tolerance test 2-hour, glycated haemoglobin, and body weight compared with those of the sham group. A total of 245 differential metabolites were identified between the two groups, among which 8 metabolites were detectable under both the positive ion model and negative ion model. Therefore, a total of 237 differential metabolites were identified in our study which were mainly involved in tryptophan metabolism; cysteine and methionine metabolism; phenylalanine metabolism; phenylalanine; tyrosine and tryptophan biosynthesis; arginine biosynthesis; alanine, aspartate and glutamate metabolism; Arginine and proline metabolism; glyoxylate and dicarboxylate metabolism; alpha-Linolenic acid metabolism; Linoleic acid metabolism; riboflavin metabolism; nicotinate and nicotinamide metabolism; pyrimidine metabolism; porphyrin and chlorophyll metabolism.ConclusionSADI-S significantly improved the glucose metabolism in T2DM rats. In addition, SADI-S significantly changed the composition of metabolites in T2DM rats which were involved in tryptophan metabolism pathway, linoleic acid metabolism pathway and so on. This may be the mechanism by which SADI-S improved T2DM.

Immunogenic cell death (ICD) is a type of cell death that leads to the regulation and activation of the immune response, which is marked by the exposure and delivery of damage‐associated molecular patterns (DAMPs) in the tumor microenvironment. Accumulating evidence has revealed the significance of ICD-related genes in tumor progression and therapeutic response. In this study, we obtained two ICD-related clusters for glioblastoma (GBM) by applying consensus clustering, and further constructed a risk signature on account of the prognostic ICD genes. Based on the risk signature, we found that higher risk scores were associated with worse patient prognosis. Besides, the results illustrated that ferroptosis regulators/markers were highly enriched the high-risk group, and ferroptosis were correlated with cytokine signaling pathway and other immune-related pathways. We also discovered that high-risk scores were correlated to specific immune infiltration patterns and good response to immune checkpoint blockade (ICB) treatment. In conclusion, our study highlights the significance of ICD-related genes as prognostic biomarkers and immune response indicators in GBM. And the risk signature integrating prognostic genes possessed significant potential value to predict the prognosis of patients and the efficacy of ICB treatment.

Ischemic and hemorrhagic stroke (including intracerebral hemorrhage, intraventricular hemorrhage, and subarachnoid hemorrhage) is the dominating cause of disability and death worldwide. Neuroinflammation, blood–brain barrier (BBB) disruption, neuronal death are the main pathological progress, which eventually causes brain injury. Increasing evidence indicated that lipocalin 2 (LCN2), a 25k-Da acute phase protein from the lipocalin superfamily, significantly increased immediately after the stroke and played a vital role in these events. Meanwhile, there exists a close relationship between LCN2 levels and the worse clinical outcome of patients with stroke. Further research revealed that LCN2 elimination is associated with reduced immune infiltrates, infarct volume, brain edema, BBB leakage, neuronal death, and neurological deficits. However, some studies revealed that LCN2 might also act as a beneficial factor in ischemic stroke. Nevertheless, the specific mechanism of LCN2 and its primary receptors (24p3R and megalin) involving in brain injury remains unclear. Therefore, it is necessary to investigate the mechanism of LCN2 induced brain damage after stroke. This review focuses on the role of LCN2 and its receptors in brain injury and aiming to find out possible therapeutic targets to reduce brain damage following stroke.

Accumulating evidence has demonstrated that the immune cells have an emerging role in controlling anti-tumor immune responses and tumor progression. The comprehensive role of mast cell in glioma has not been illustrated yet. In this study, 1,991 diffuse glioma samples were collected from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). xCell algorithm was employed to define the mast cell-related genes. Based on mast cell-related genes, gliomas were divided into two clusters with distinct clinical and immunological characteristics. The survival probability of cluster 1 was significantly lower than that of cluster 2 in the TCGA dataset, three CGGA datasets, and the Xiangya cohort. Meanwhile, the hypoxic and metabolic pathways were active in cluster 1, which were beneficial to the proliferation of tumor cells. A potent prognostic model based on mast cell was constructed. Via machine learning, DRG2 was screened out as a characteristic gene, which was demonstrated to predict treatment response and predict survival outcome in the Xiangya cohort. In conclusion, mast cells could be used as a potential effective prognostic factor for gliomas.

The aberrant protein disulfide isomerase A5 (PDIA5) expression was relevant to the poor prognosis of patients with human cancers. However, its relationship with the epigenetic and genetic alterations and its effect on tumor immunity is still lacking. In the present study, we comprehensively analyzed the immune infiltration role of PDIA5 in human cancers based on large-scale bioinformatics analyses and in vitro experiments. Obvious DNA methylation and moderate alteration frequency of PDIA5 were observed in human cancers. The expression level of PDIA5 was significantly correlated with infiltrated immune cells, immune pathways, and other immune signatures. We found that cancer cells and macrophages exhibited high PDIA5 expression in human cancers using the single-cell RNA sequencing analysis. We also demonstrated the interaction between PDIA5 and immune cells in glioblastoma multiforme (GBM). Multiplex immunofluorescence staining showed the upregulated expression level of PDIA5 and the increased number of M2 macrophage markers-CD163 positive cells in pan-cancer samples. Notably, PDIA5 silencing resulted in upregulated expression of PD-L1 and SPP1 in U251 cells. Silencing of PDIA5 in hepG2 cells, U251 cells, and PC3 cells contributed to a decline in their ability of proliferation, clone formation, and invasion and inhibited the migration of cocultured M2 macrophages. Additionally, PDIA5 also displayed predictive value in the immunotherapy response of both murine and human cancer cohorts. Overall, our findings indicated that PDIA5 might be a potential target for immunotherapies in cancers.

With the rapid development of digital information technology, life has become more convenient for people; however, the digital divide for the elderly was even more serious, so they became a forgotten group in the internet age over time. Residents' demand for healthcare is rising, but the wisdom healthcare service supported by digital information technology is less acceptable to the elderly due to the digital divide. Based on the knowledge gap theory and combining the value perception and satisfaction model, this study explores the influence of the digital divide for the elderly on wisdom healthcare satisfaction and takes the perceived value of wisdom healthcare as a mediator, and artificial intelligence and big data as moderators into the research framework. Based on the data of 1,052 elderly people in China, the results show that the digital divide for the elderly has a negative influence on wisdom healthcare satisfaction and perceived value. Moreover, it is found that wisdom healthcare perception value mediated the relationship between the digital divide for the elderly and the wisdom healthcare satisfaction, which enhances the negative effect of the digital divide for the elderly on wisdom healthcare satisfaction. Furthermore, the moderating effect of artificial intelligence and big data on the relationship between the digital divide for the elderly and the perceived value of wisdom healthcare is opposite to that between the perceived value of wisdom healthcare and wisdom healthcare satisfaction. Therefore, this study has a reference value for the development and optimization of smart medical industry.

Ignition of magnesium alloys during casting processes limits their processability and applications. For identifying the ignition mechanism of magnesium alloys during solidification, a Mg-Al-Zn alloy was solidified with different cooling rates and pouring temperatures. The oxide scale morphologies and thicknesses were identified by SEM and energy dispersive spectrometer. Based on the experimental results, the oxidation kinetics and heat released were calculated and the relationship between oxidation and ignition was discussed in detail. The calculation results indicate that oxide rupture directly induces combustion of the melt. The rupture route of the oxide scale was determined to be buckling cracks according to the experimental and calculation results. Based on the buckling mechanism of the oxide scale, the ignition criterion during solidification was correlated to the pouring temperature, cooling rate and casting modulus. This work reveals the underlying relationship between ignition and casting process parameters, and it helps to develop new technology for inhibiting ignition of molten magnesium alloys.

Species within the Aspergillus spp. cause a wide range of infections in humans, including invasive pulmonary aspergillosis, chronic pulmonary aspergillosis, and allergic bronchopulmonary aspergillosis, and are associated with high mortality rates. The incidence of pulmonary aspergillosis (PA) is on the rise, and the emergence of triazole-resistant Aspergillus spp. isolates, especially Aspergillus fumigatus, limits the efficacy of mold-active triazoles. Therefore, host-directed and novel adjunctive therapies are required to more effectively combat PA. In this review, we focus on PA from a microbiome perspective. We provide a general overview of the effects of the lung and gut microbiomes on the growth of Aspergillus spp. and host immunity. We highlight the potential of the microbiome as a therapeutic target for PA.

Glioma is the most malignant cancer of the central nervous system. There are various therapies for treating gliomas, but their outcomes are not satisfactory. Therefore, new targets for glioma treatment are needed. This study examined the cadherin-6 (CDH6) expression in gliomas using The Cancer Genome Atlas and Chinese Glioma Genome Atlas datasets. CDH6 expression positively correlated with the World Health Organization (WHO) tumor grade and negatively correlated with patient prognosis. A significant decrease in CDH6 promoter methylation was identified with an increase in the WHO grade severity. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses suggested that CDH6 might be involved in cell–cell interactions and immune processes in the glioma microenvironment. Weighted gene co-expression network analysis revealed a correlation between CDH6 and cell adhesion molecules, focal adhesions, phosphatidylinositol 3-kinase-protein kinase B signaling pathways, nuclear division, chromosome segregation, mitotic nuclear division, and immune-related pathways. CDH6 strongly correlated with immunosuppressive cells, including regulatory T cells, monocytes, macrophages, tumor-associated macrophages, and myeloid-derived suppressor cells. It also showed correlations with immune-active cells such as B cells, CD8+ T cells, and dendritic cells. Single-cell analysis showed that CDH6 was expressed mainly in astrocyte (AC)-like malignant cells. Differentially expressed genes of AC-like malignant cells were found to be associated with stress response, membranous processes, viral infections, and several types of cancers. Potential drugs associated with high CDH6 expression were also predicted, including AMG-22, rutin, CCT128930, deforolimus, bis(maltolato)oxovanadium, anagrelide, vemurafenib, CHIR-98014, and AZD5582. Thus, this study showed that CDH6 correlates with glioma immune infiltration, it is expressed mainly in AC-like malignant cells, and it may act as a new target for glioma therapy.

Group A streptococcus (GAS, Streptococcus pyogenes) is a common pathogen that can cause a variety of human diseases. Streptolysin O (SLO) is an exotoxin produced by GAS. It is a pore-forming toxin (PFT) that exhibits high in vivo toxicity. SLO enables GAS to evade phagocytosis and clearance by neutrophils, induces eukaryotic cell lysis, and activates inflammatory bodies. Luteolin is a natural compound that is produced by a wide range of plant species, and recent studies have shown that luteolin can inhibit the growth and alter the morphological of GAS. Here, we reported that luteolin can weaken the cytotoxicity and hemolytic activity of SLO in vitro. Briefly, luteolin bound SLO with high affinity, inhibited its dissolution of erythrocytes, affected its conformational stability and inhibited the formation of oligomers. To further verify the protective effect of luteolin, we used an in vitro SLO-induced human laryngeal carcinoma epithelial type-2 cells (HEp-2) model. Notably, our results showed luteolin protected HEp-2 cells from SLO induced cytotoxicity and changed in cell membrane permeability. In addition, we explored the role of luteolin in protecting mice from GAS-mediated injury using an aerosolized lung delivery model, and our results indicate that luteolin increases murine survival rate following inoculation with a lethal dose of GAS, and that survival was also associated with decreased pathological damage to lung tissue. Our results suggest that luteolin may be a novel drug candidate for the treatment of GAS infection.

ObjectiveTo investigate the treatment concept of Chinese urologists for anterior urethral strictures based on actual cases.MethodsA self-designed case-based questionnaire was distributed to the members of Official WeChat account of Learning Union from March 19, 2020, to April 10, 2020. Questionnaires requested respondents' demographic information and responses to five cases of anterior urethral stricture: short obliterative bulbar urethral stricture caused by straddle injury (Case 1), idiopathic bulbar urethral stricture after failure of multiple endoscopic therapy (Case 2), iatrogenic long penile urethral stricture (Case 3), lichen sclerosis-related urethral stricture (Case 4), and anterior urethral stricture in indwelling catheter after multiple failure of endoscopic surgery (Case 5). Data was described by frequency and percentage.ResultsA total of 1,267 valid anonymous questionnaires were received. Urethroplasty was recommended more frequently than endoscopic surgery (Case 1: 47.8% vs. 32.8%,Case 2: 42.5% vs. 33.8%, Case 3: 36.1% vs. 26.7%). Referrals patients to other urologists engaged in urethral repair and reconstruction account for a high portion of the treatment (Case 1:18.4%, Case 2:23.1%, Case 3:36.5%, Case 4:27.7%,Case 5:9.3%). Excision and primary anastomosis urethroplasty (EPA) was preferred for treatment of Case 1 (42.5%). For Case 2, the most popular choice was EPA (30.6%). Although the patient has a history of failure in endoscopic surgery, 33.8% of urologists continue to choose endoscopic surgery. For Case 3, 20.0% of urologists would perform oral mucosal urethroplasty. Surprisingly, 5.9% chose EPA. For Case 4, 37.3% of urologists selected meatotomy, 30.4% suggested that glans and urethral biopsies should be performed. 21.0% chose to use steroid ointment after surgery. For Case 5, 26.3% of the respondents believed that urethrography should be performed after removing catheter more than one week, if the urine is obstructed during the period, performing cystostomy firstly.ConclusionsIn China, the concept of urethroplasty is more widely accepted than endoscopic surgery for the treatment of anterior urethral strictures. The concept of referral has been widely formed among Chinese urologists. Better understanding of the comprehensive treatment of lichen sclerosis related anterior urethral stricture and the principle of urethral rest should be strengthened.

BackgroundJMJD8 has recently been identified as a cancer-related gene, but current studies provide limited information. We aimed to clarify its roles and the potential mechanisms in pan-cancer.MethodsPan-cancer bulk sequencing data and online web tools were applied to analyze JMJD8’s correlations with prognosis, genome instability, cancer stemness, DNA repair, and immune infiltration. Moreover, single-cell datasets, SpatialDB database, and multiple fluorescence staining were used to validate the association between JMJD8 expression and M2 macrophages. Further, we utilized ROCplotter and cMap web tool to analyze the therapeutic responses and screened JMJD8-targeted compounds, respectively, and we used AlphaFold2 and Discovery Studio to conduct JMJD8 homology modeling and molecular docking.ResultsWe first noticed that JMJD8 was an oncogene in many cancer types. High JMJD8 was associated with lower genome stability. We then found that high JMJD8 correlated with high expression of mismatch repair genes, stemness, homologous repair gene signature in more than 9 cancers. ESTIMATE and cytokine analyses results presented JMJD8’s association with immunosuppression. Also, immune checkpoint CD276 was positively relevant to JMJD8. Subsequently, we validated JMJD8 as the M2 macrophage marker and showed its connection with other immunosuppressive cells and CD8+ T-cell depression. Finally, potential JMJD8-targeted drugs were screened out and docked to JMJD8 protein.ConclusionWe found that JMJD8 was a novel oncogene, and it correlated with immunosuppression and DNA repair. JMJD8 was highly associated with immune checkpoint CD276 and was an M2 macrophage biomarker in many cancers. This study will reveal JMJD8’s roles in pan-cancer and its potential as a novel therapeutic target.

Whether families using big data-based digital payments will increase household healthcare expenditure is a subject that needs to be investigated in the era of big data. Based on the data from China Family Panel Studies (CFPS), 24,126 samples from 2014 to 2018 are used to examine the impact and mechanism of big data-based digital payments on household healthcare expenditure. The empirical results of this paper show that the use of digital payments by households can significantly increase household healthcare expenditure with the empowerment of big data. This research employs the instrumental variable method to verify and produce consistent estimation results in order to address potential endogeneity issues such as measurement error and missing variables. We learn via mechanism analysis that household adoption of big data-driven digital payments can remove credit limitations and build social capital, resulting in higher household health-care spending. We also perform a heterogeneity analysis. The findings reveal that when a family's traditional financial accessibility is high, the head of the household is young or middle-aged, and the head of the household has a higher level of education, digital payment will play a larger role in encouraging household healthcare expenditure. The conclusions of this paper are still solid after changing the indicators of household healthcare expenditure substituting the indicators of digital payment, and adjusting the variables. As a result, this article provides micro-evidence for the usage of digital payments by households to enhance healthcare spending.JEL ClassificationD12 G21 O30 O53 I12

ObjectiveMalignant meningioma (MM) is a relatively rare disease with poor survival. Few studies had focused on MM in the elderly population. This study aims to explore the prognostic factors and optimal therapeutic strategy in elderly patients with MM.MethodsWe took advantage of the Surveillance, Epidemiology, and End Results (SEER) database to include 275 adult patients with histologically confirmed MM between 2011 and 2018. The Kaplan–Meier curves were plotted by different covariates to reveal the survival probability. Univariate and multivariable Cox proportional hazard regression analyses were applied to identify prognostic factors for cancer-specific survival (CSS).ResultsThe multivariable analysis in the elderly group revealed that when compared with patients receiving gross total resection (GTR), patients receiving biopsy had significantly worse CSS (HR = 3.72; 95% CI: 1.35–10.21; P = 0.011), whereas patients receiving subtotal resection (STR) had nearly the same CSS (HR = 0.83; 95% CI: 0.37–1.86; P = 0.653). Meanwhile, postoperative radiotherapy (PORT) showed no significant association with CSS in the elderly patient group (HR = 0.94; 95% CI: 0.42–2.12; P = 0.888).ConclusionSurgical resection is recommended for elderly patients with MM in the absence of surgical contraindications, but GTR does not present survival benefit in the elderly patients compared with STR. Additional large-scale clinical studies are needed to explore the survival benefit of PORT applied in patients with MM.

BackgroundLung adenocarcinoma (LUAD) is a fatal malignancy in the world. Growing evidence demonstrated that autophagy-related genes regulated the immune cell infiltration and correlated with the prognosis of LUAD. However, the autophagy-based signature that can predict the prognosis and the efficiency of checkpoint immunotherapy in LUAD patients is yet to be discovered.MethodsWe used conventional autophagy-related genes to screen candidates for signature construction in TCGA cohort and 9 GEO datasets (tumor samples, n=2181; normal samples, n=419). An autophagy-based signature was constructed, its correlation with the prognosis and the immune infiltration of LUAD patients was explored. The prognostic value of the autophagy-based signature was validated in an independent cohort with 70 LUAD patients. Single-cell sequencing data was used to further characterize the various immunological patterns in tumors with different signature levels. Moreover, the predictive value of autophagy-based signature in PD-1 immunotherapy was explored in the IMvigor210 dataset. At last, the protective role of DRAM1 in LUAD was validated by in vitro experiments.ResultsAfter screening autophagy-related gene candidates, a signature composed by CCR2, ITGB1, and DRAM1 was established with the ATscore in each sample. Further analyses showed that the ATscore was significantly associated with immune cell infiltration and low ATscore indicated poor prognosis. Meanwhile, the prognostic value of ATscore was validated in our independent LUAD cohort. GSEA analyses and single-cell sequencing analyses revealed that ATscore was associated with the immunological status of LUAD tumors, and ATscore could predict the efficacy of PD-1 immunotherapy. Moreover, in vitro experiments demonstrated that the inhibition of DRAM1 suppressed the proliferation and migration capacity of LUAD cells.ConclusionOur study identified a new autophagy-based signature that can predict the prognosis of LUAD patients, and this ATscore has potential applicative value in the checkpoint therapy efficiency prediction.

VSIR is a critical immunomodulatory receptor that inhibits T cell effector function and maintains peripheral tolerance. However, the mechanism by which VSIR participates in tumor immunity in the pan-cancer tumor microenvironment remains unclear. This study systematically explored the prognostic and immune profile of VSIR in the tumor microenvironment of 33 cancers. We compared the expression patterns and molecular features of VSIR in the normal and cancer samples both from the public databases and tumor chips. VSIR level was significantly related to patients’ prognosis and could be a promising predictor in many tumor types, such as GBM, KIRC, SKCM, READ, and PRAD. Elevated VSIR was closely correlated with infiltrated inflammatory cells, neoantigens expression, MSI, TMB, and classical immune checkpoints in the tumor microenvironment. Enrichment signaling pathways analysis indicated VSIR was involved in several immune-related pathways such as activation, proliferation, and migration of fibroblast, T cell, mast cell, macrophages, and foam cell. In addition, VSIR was found to widely express on cancer cells, fibroblasts, macrophages, and T cells in many tumor types based on the single-cell sequencing analysis and co-express with M2 macrophage markers CD68, CD163 based on the immunofluorescence staining. Finally, we predicted the sensitive drugs targeting VSIR and the immunotherapeutic value of VSIR. In sum, VSIR levels strongly correlated with the clinical outcome and tumor immunity in multiple cancer types. Therefore, therapeutic strategies targeting VSIR in the tumor microenvironment may be valuable tools for cancer immunotherapy.

CD147 plays an important role in promoting tumor proliferation and inhibiting cancer cell apoptosis in the tumor microenvironment. However, the mechanisms by which CD147 is involved in tumorigenesis remains unclear. This study systematically analyzed the prognostic value and immune characteristics of CD147 in 31 cancer types. The expression levels and mutant landscapes of CD147 in pan-cancer were explored. The Kaplan-Meier (KM) analysis was applied to analyze the prognostic value of CD147. The immune characteristics of CD147 in the tumor microenvironment were evaluated via TIMER 2.0 and R package (immunedeconv). We also explored the expression of CD147 on tumor cells and stromal cells through Gene Set Variation Analysis and single-cell sequencing analysis. The co-expression of CD147 and macrophage markers CD68 and CD163 in pan-cancer was detected using multiplex immunofluorescence staining on tissue microarrays. CD147 was found to be overexpressed in almost all cancer types, which was related to poor outcome. CD147 expression exhibited a strong association with immune infiltrates, immune checkpoint molecules, and neoantigen levels in the tumor microenvironment. In addition, CD147 was expressed on various cell types in the tumor microenvironment, including tumor cells, macrophages, T cells, monocytes, fibroblasts, etc. Furthermore, multiplex immunofluorescence revealed the co-expression pattern of CD147 and macrophage markers CD68 and CD163 in many tumor types. Finally, the immunotherapy response and sensitive small molecule drugs based on CD147 expression were predicted. In sum, CD147 has a significant relationship with the clinical outcome and immune infiltrates in multiple cancer types. Inhibiting the CD147-dependent signaling pathways might be a promising therapeutic strategy for tumor immunotherapy.

The Pinghu Formation of the Xihu Sag in the East China Sea shelf basin is influenced by tidal processes, but few studies have focused on its tidal rhythmites. Through detailed observation and description of cores, this article studies the periodicity of the tidal rhythmites of well A-11 by using the grayscale measurement of digital images based on spectral analysis and wavelet transform. According to the statistical data series of millimeter lamination thickness, the sandy lamina thickness, the argillaceous lamina thickness, and the couplet thickness were quantitatively compared and analyzed, to support the interpretation of the main controlling factors of different thickness cycles. The periodicity of sandy laminae, argillaceous laminae, and couplet thickness have distinct differences, which are interpreted to be due to differences in the nature and magnitude of tidal current cycles at the time of deposition. The high-frequency signal represents event deposition, the middle-frequency signal represents tidal current deposition, and the low-frequency signal highlights changes in sedimentary facies. Therefore, the change in the couplet thickness is controlled by event deposition, tidal current deposition, and change of the depositional environment. Our approach to the study of thickness variations in tidal rhythmites supports the reconstruction of the tidal sedimentary environment in the paleostratigraphic sequence.

Organoids well recapitulate organ-specific functions from their tissue of origin and remain fundamental aspects of organogenesis. Organoids are widely applied in biomedical research, drug discovery, and regenerative medicine. There are various cultivated organoid systems induced by adult stem cells and pluripotent stem cells, or directly derived from primary tissues. Researchers have drawn inspiration by combination of organoid technology and tissue engineering to produce organoids with more physiological relevance and suitable for translational medicine. This review describes the value of applying organoids for tumorigenesis modeling and tumor vaccination. We summarize the application of organoids in tumor precision medicine. Extant challenges that need to be conquered to make this technology be more feasible and precise are discussed.