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Crowdsourcing plays an essential role in the Internet of Things (IoT) for data collection, where a group of workers is equipped with Internet-connected geolocated devices to collect sensor data for marketing or research purpose. In this paper, we consider crowdsourcing these worker's hot travel path. Each worker is required to report his real-time location information, which is sensitive and has to be protected. Encryption-based methods are the most direct way to protect the location, but not suitable for resource-limited devices. Besides, local differential privacy is a strong privacy concept and has been deployed in many software systems. However, the local differential privacy technology needs a large number of participants to ensure the accuracy of the estimation, which is not always the case for crowdsourcing. To solve this problem, we proposed a trie-based iterative statistic method, which combines additive secret sharing and local differential privacy technologies. The proposed method has excellent performance even with a limited number of participants without the need of complex computation. Specifically, the proposed method contains three main components: iterative statistics, adaptive sampling, and secure reporting. We theoretically analyze the effectiveness of the proposed method and perform extensive experiments to show that the proposed method not only provides a strict privacy guarantee, but also significantly improves the performance from the previous existing solutions., This paper appears in IEEE Transactions on Services Computing. https://doi.org/10.1109/TSC.2020.3039336

Recently, multilabel classification has generated considerable research interest. However, the high dimensionality of multilabel data incurs high costs; moreover, in many real applications, a number of labels of training samples are randomly missed. Thus, multilabel classification can have great complexity and ambiguity, which means some feature selection methods exhibit poor robustness and yield low prediction accuracy. To solve these issues, this paper presents a novel feature selection method based on multilabel fuzzy neighborhood rough sets (MFNRS) and maximum relevance minimum redundancy (MRMR) that can be used on multilabel data with missing labels. First, to handle multilabel data with missing labels, a relation coefficient of samples, label complement matrix, and label-specific feature matrix are constructed and implemented in a linear regression model to recover missing labels. Second, the margin-based fuzzy neighborhood radius, fuzzy neighborhood similarity relationship, and fuzzy neighborhood information granule are developed. The MFNRS model is built based on multilabel neighborhood rough sets combined with fuzzy neighborhood rough sets. Based on algebra and information views, certain fuzzy neighborhood entropy-based uncertainty measures are proposed for MFNRS. The fuzzy neighborhood mutual information-based MRMR model with label correlation is improved to evaluate the performance of candidate features. Finally, a feature selection algorithm is designed to improve the performance for multilabel data with missing labels. Experiments on twenty datasets verify that our method is effective not only for recovering missing labels but also for selecting significant features with better classification performance.

Novel therapies are urgently needed to improve global treatment of SARS-CoV-2 infection. Herein, we briefly provide a concise report on the medicinal chemistry strategies towards the development of effective SARS-CoV-2 inhibitors with representative examples in different strategies from the medicinal chemistry perspective., Graphical abstract This review summarizes major medicinal chemistry strategies of developing SARS-CoV-2 inhibitors, including drug repositioning, large-scale screening, rational drug design based on target and utilization of natural compounds.Image 1

To discover the condition of roads, a large number of detection algorithms have been proposed, most of which apply machine learning methods by time and frequency processing in acceleration and velocity data. However, few of them pay attention to the similarity of the data itself when the vehicle passes over the road anomalies. In this article, we propose a method to detect road anomalies by comparing the data windows with various length using Dynamic Time Warping(DTW) method. We propose a model to prove that the maximum acceleration of a vehicle passing through a road anomaly is linear with the height of the road barrier, and it's verified by an experiment. This finding suggests that it is reasonable to divide the window by threshold detection. We also apply a brief random forest filter to roughly distinguish normal windows from anomaly windows using the aforementioned theory, in order to reduce the time consumption. From our study, a system is proposed that utilizes a series of acceleration data to discover where might be anomalies on the road, named as Quick Filter Based Dynamic Time Warping (QFB-DTW). We show that our method performs clearly beyond some existing methods. To support this conclusion, experiments are conducted based on three data sets and the results are statistically analyzed. We expect to lay the first step to some new thoughts to the field of road anomalies detection in subsequent work.

Objectives: Our study analyzed the performance of Xpert MTB/RIF Ultra (Ultra) on stool and gastric aspirate (GA) samples for the diagnosis of pediatric pulmonary tuberculosis (TB) caused by Mycobacterium tuberculosis in a high-burden area of China. Methods: Children with presumptive TB were enrolled in two hospitals in Sichuan Province (July 2019–Oct 2020). Because of the unavailability of sputum for etiological testing, gastric samples were aspirated and tested by bacterial culture, acid-fast bacillus microscopy, and Ultra. Stool samples were tested simultaneously using Ultra and Xpert. Results: In total, 141 children with active TB and 34 with non-TB respiratory tract infections were enrolled. Ultra-stool (60.3%, 85/141) and Ultra-GA (52.5%, 74/141) tests were similarly sensitive (p = 0.187). Among the subset of 48 children with confirmed TB, Ultra testing was equally sensitive on stool and GA samples (85.4%, 41/48). The agreement between Ultra-stool and Ultra-GA was moderate in children with active TB (kappa value = 0.527). After integrating Ultra-GA and Ultra-stool outcomes, 70.9% (100/141) of the children were considered to have confirmed TB. The specificities of Ultra-stool and Ultra-GA were 97.1% (33/34) and 100% (34/34), respectively (p = 0.314). Conclusions: In children, stools can be used as alternative samples to GAs for Ultra tests. Stool- and GA-based Ultra tests are appropriate for bacteriological TB confirmation.

Thermoelectric devices enable direct conversion between thermal and electrical energy. Recent studies have indicated that the thin film/substrate heterostructure is effective in achieving high thermoelectric performance via decoupling the Seebeck coefficient and electrical conductivity otherwise adversely inter-dependent in homogenous bulk materials. However, the mechanism underlying the thin film/substrate heterostructure thermoelectricity remains unclear. In addition, the power output of the thin film/substrate heterostructure is limited to the nanowatt scale to date, falling short of the practical application requirement. Here, we fabricated the CrN/SrTiO3−x heterostructures with high thermoelectric output power and outstanding thermal stability. By varying the CrN film thickness and the reduction degree of SrTiO3−x substrate, the optimized power output and the power density have respectively reached 276 μW and 108 mW/cm2 for the 30 nm CrN film on a highly reduced surface of SrTiO3−x under a temperature difference of 300 K. The performance enhancement is attributed to the CrN/SrTiO3−x heterointerface, corroborated by the band bending as revealed by the scanning Kelvin probe microscopy. These results will stimulate further research efforts towards interface thermoelectrics.

Background The correlation between modified bladder outlet obstruction index (MBOOI) and surgical efficacy still remains unknown. The purpose of the study was to investigate the clinical value of the MBOOI and its use in predicting surgical efficacy in men receiving transurethral resection of the prostate (TURP). Methods A total of 403 patients with benign prostate hyperplasia (BPH) were included in this study. The International Prostate Symptom Score (IPSS), quality of life (QoL) index, transrectal ultrasonography, and pressure flow study were conducted for all patients. The bladder outlet obstruction index (BOOI) (PdetQmax–2Qmax) and MBOOI (Pves–2Qmax) were calculated. All patients underwent TURP, and surgical efficacy was accessed by the improvements in IPSS, QoL, and Qmax 6 months after surgery. The association between surgical efficacy and baseline factors was statistically analyzed. Results A comparison of effective and ineffective groups based on the overall efficacy showed that significant differences were observed in PSA, Pves, PdetQmax, Pabd, BOOI, MBOOI, TZV, TZI, IPSS-t, IPSS-v, IPSS-s, Qmax, and PVR at baseline (p max, and the overall efficacy. Additionally, the ROC analysis further verified that MBOOI was more optimal than BOOI, TZV and TZI in predicting the surgical efficacy. Conclusion Although both MBOOI and BOOI can predict the clinical symptoms and surgical efficacy of BPH patients to a certain extent, however, compared to BOOI, MBOOI may be a more useful factor that can be used to predict the surgical efficacy of TURP. Trial registration retrospectively registered.

Background Obesity is associated with electrophysiological remodeling, which manifests as detectable changes on the surface electrocardiogram (ECG). Objective To develop neural networks (NN) to predict body mass index (BMI) from ECGs and test the hypothesis that discrepancies between NN-predicted BMI and measured BMI are indicative of underlying adiposity and/or concurrent cardiometabolic ill-health. Methods NN models were developed using 36,856 12-lead resting ECGs from the UK Biobank. Two architectures were developed for continuous and categorical BMI estimation (normal weight [BMI, Graphical abstract

Objective. Analyze the influencing factors of hospitalization expenses of breast cancer patients in a tertiary hospital in Chengdu and provide a basis and suggestion for controlling the unreasonable increase of medical expenses. Methods. The first pages of all inpatient medical records of patients with breast malignant tumor from 2017 to 2020 were extracted, and the descriptive analysis, single-factor analysis, and multifactor analysis were conducted by using the statistical method and data mining method to explore the influencing factors of hospitalization expenses. Results. In 2017–2020, the average hospitalization cost and the average surgical treatment cost increased year by year, and the number of operations, actual hospitalization days, and CCI were the important influencing factors. Conclusion. It is suggested to strengthen the supervision of medical rationality and eliminate the waste of medical resources; and we should improve the efficiency of diagnosis and treatment services, so as to shorten the actual length of hospitalization; at the same time, the combination of DRG grouping and fine management can be used to control the hospitalization expenses.

Microbiological confirmation is rare in children with active tuberculosis; therefore, a more accurate test is needed to detect pulmonary tuberculosis in children. In this multicenter study, we evaluated the utility of the Xpert MTB/RIF Ultra (Ultra) on sputum, an assay recommended by the World Health Organization to test for childhood tuberculosis in high-burden settings. Children with symptoms suggestive of tuberculosis were enrolled at three hospitals in China and categorized as having active tuberculosis or nontuberculosis. The sensitivity and specificity of Ultra were 42.1% (48/114) and 99.0% (208/210), respectively. Using three MTB culture results as the reference, the sensitivity of Ultra in the subset of 38 children with culture-positive and 76 children with culture-negative was 68.4% (26/38) and 28.9% (22/76), respectively(p

In recent years, feature selection for multilabel classification has attracted attention in machine learning and data mining . However, some feature selection methods ignore the correlations among labels, resulting in low performance, and most of them face challenges in determining an appropriate neighborhood radius for neighborhood systems and suffer from expensive time cost. To overcome the issues, we propose a novel feature selection method using Fisher score and multilabel neighborhood rough sets (MNRS) in multilabel neighborhood decision systems. First, to identify the correlations between labels under a binary distribution, two types of new mutual information between labels are considered, and their balance coefficients are defined. By enhancing strong correlations and weakening weak correlations between labels, a mutual information-based Fisher score model with a second-order correlation between labels is designed to fit multilabel data. Second, to address the problem of automatically choosing a neighborhood radius, a subset of heterogeneous and homogeneous samples is employed to develop a new classification margin as a neighborhood radius, and some concepts of neighborhood, neighborhood class, and upper and lower approximations are formulated for multilabel neighborhood decision systems. The weight and dependency degree are presented to effectively measure the uncertainty of samples in multilabel neighborhood decision systems. Thus, we further present a new classification margin-based MNRS model. Finally, a filter-wrapper preprocessing algorithm for feature selection using the improved Fisher score model is proposed to decrease the spatiotemporal complexity of multilabel data, and a heuristic feature selection algorithm is designed for improve classification performance on multilabel datasets. Experimental results on thirteen multilabel datasets show that the proposed algorithm is effective in selecting significant features, demonstrating its excellent classification ability in multilabel datasets.

DNA ligase (LIG) plays a key role in connecting the 3′-OH end of a DNA strand to the 5′-P end of another DNA strand, resulting in the formation of a phosphodiester bond. It has been reported that LIGs (including LIG1, LIG3 and LIG4) play important roles in the occurrence and progression of many cancers. However, the role of LIGs in breast cancer (BC) is still unclear. In this study, we aim to reveal the expression level, function, and prognostic value of LIGs in BC. Bioinformatic tools were used to study the expression level, potential function and prognostic value of LIG1 and LIG3 in BC patients. ENCORI was used to predict microRNAs (miRNAs) that regulate LIG1 and LIG3 and established a valuable miRNA–mRNA regulation network for BC. We found that the expression of LIG1 and LIG3 was upregulated in BC and predicted high relapse-free survival (RFS) in BC patients. Functional annotation analysis was performed to reveal the role of LIG1 and LIG3 in BC. In addition, hsa-miR-22-3p was identified to be potentially involved in the regulation of LIG3. We suggest that LIG1 and LIG3 are novel valuable prognostic biomarkers for BC and has-miRNA-22-3p may be a potential therapeutic target for BC.

Fuzzy rough set is a theoretical framework of fuzzy uncertainty management, and discernibility matrix offers a mathematical foundation for algorithm construction of feature learning. The approaches of fuzzy rough set and discernibility matrix have been successfully applied in single-label learning. However, few works have been done on investigating the foundation of fuzzy rough discernibility matrix on multi-label data. There will be two pivotal problems to be addressed when using fuzzy rough discernibility matrix for multi-label data analysis. One is how to extract sample-level and label-level correlations; and the other is how to utilize the discernibility matrix for algorithm construction. For this reason, in this paper the fuzzy rough discrimination matrix is introduced to deal with the problem of multi-label feature selection. First, the significance of labels in the label space is captured based on the label correlation. Labels with different significances contribute to different weights for measuring the similarity between samples. Hence, a sample similarity matrix in the label space is computed based on the label weighting strategy. Then, a framework of a fuzzy decision system is formalized, in which the discernibility matrix of fuzzy rough sets is introduced as a foundation to evaluate the sample discrimination ability of features. Under the discernibility matrix criterion, a multi-label learning algorithm is developed to select discriminative features from multi-label data. A series of experimental analysis verifies the effectiveness and efficiency of the proposed method.

Background Early identification of the occurrence of arrhythmia in patients with acute myocardial infarction plays an essential role in clinical decision-making. The present study attempted to use machine learning (ML) methods to build predictive models of arrhythmia after acute myocardial infarction (AMI). Methods A total of 2084 patients with acute myocardial infarction were enrolled in this study. (All data is available on Github: https://github.com/wangsuhuai/AMI-database1.git). The primary outcome is whether tachyarrhythmia occurred during admission containing atrial arrhythmia, ventricular arrhythmia, and supraventricular tachycardia. All data is randomly divided into a training set (80%) and an internal testing set (20%). Apply three machine learning algorithms: decision tree, random forest (RF), and artificial neural network (ANN) to learn the training set to build a model, then use the testing set to evaluate the prediction performance, and compare it with the model built by the Global Registry of Acute Coronary Events (GRACE) risk variable set. Results Three ML models predict the occurrence of tachyarrhythmias after AMI. After variable selection, the artificial neural network (ANN) model has reached the highest accuracy rate, which is better than the model constructed using the Grace variable set. After applying SHapley Additive exPlanations (SHAP) to make the model interpretable, the most important features are abnormal wall motion, lesion location, bundle branch block, age, and heart rate. Among them, RBBB (odds ratio [OR]: 4.21; 95% confidence interval [CI]: 2.42–7.02), ≥ 2 ventricular walls motion abnormal (OR: 3.26; 95% CI: 2.01–4.36) and right coronary artery occlusion (OR: 3.00; 95% CI: 1.98–4.56) are significant factors related to arrhythmia after AMI. Conclusions We used advanced machine learning methods to build prediction models for tachyarrhythmia after AMI for the first time (especially the ANN model that has the best performance). The current study can supplement the current AMI risk score, provide a reliable evaluation method for the clinic, and broaden the new horizons of ML and clinical research. Trial registration Clinical Trial Registry No.: ChiCTR2100041960.

Background Urinary sediment messenger RNAs (mRNAs) have been shown as novel biomarkers of kidney disease. We aimed to identify targeted urinary mRNAs in diabetic nephropathy (DN) based on bioinformatics analysis and clinical validation. Methods Microarray studies of DN were searched in the GEO database and Nephroseq platform. Gene modules negatively correlated with estimated glomerular filtration rate (eGFR) were identified by informatics methods. Hub genes were screened within the selected modules. In validation cohorts, a quantitative polymerase chain reaction assay was used to compare the expression levels of candidate mRNAs. Patients with renal biopsy–confirmed DN were then followed up for a median time of 21 months. End-stage renal disease (ESRD) was defined as the primary endpoint. Multivariate Cox proportional hazards regression was developed to evaluate the prognostic values of candidate mRNAs. Results Bioinformatics analysis revealed four chemokines (CCL5, CXCL1, CXLC6 and CXCL12) as candidate mRNAs negatively correlated with eGFR, of which CCL5 and CXCL1 mRNA levels were upregulated in the urinary sediment of patients with DN. In addition, urinary sediment mRNA of CXCL1 was negatively correlated with eGFR (r = −0.2275, P = 0.0301) and CCL5 level was negatively correlated with eGFR (r = −0.4388, P Conclusions Urinary sediment CCL5 and CXCL1 mRNAs were upregulated in DN patients and associated with a decline in renal function and degree of renal interstitial fibrosis. Urinary sediment CCL5 mRNA could be used as a potential prognostic biomarker of DN.

BACKGROUND One of the most common complications following surgery for midshaft clavicle fracture is nonunion/delayed union. Extracorporeal shock wave therapy (ESWT) is an alternative to promote new bone formation without surgical complications. To date, no literature has reported low-intensity ESWT (LI-ESWT) in delayed union of midshaft clavicle fracture. CASE SUMMARY We reported a 66-year-old Chinese amateur cyclist with clavicle delayed union treated with 10 sessions of LI-ESWT (radial, 0.057 mJ/mm2, 3 Hz, 3000 shocks). No anesthetics were applied, and no side effects occurred. At the 4 mo and 7 mo follow-ups, the patient achieved clinical and radiographical recovery, respectively. CONCLUSION In conclusion, our findings indicated that LI-ESWT could be a good option for treating midshaft clavicular delayed union.

In recent years, major large ports in China have realized the business informatization of rail-water intermodal transportation. However, the overall development level of intermodal transportation informatization has been restricted to a great extent due to the unbalanced development of intermodal transportation informatization in different regions, the rigid system architecture, the low degree of information sharing, and the lack of data management and analysis methods. Combined with the structure and business characteristics of intermodal transportation information systems, adopting cloud computing and Big Data technology, we propose an intermodal transportation information process with waybill as the information carrier and FPMS as the service fulcrum in this paper. Illustrated by the example of China’s container export process, this paper explores a series of key technical issues in the cloud environment, such as application management, business information sharing, and Big Data processing, at different levels of the construction of the rail water transport cloud platform, combined with its business characteristics, and makes experimental analysis on the relevant models to verify the feasibility of the reconstruction of the rail water transport cloud platform. It can provide theoretical and practical support for the development of rail water intermodal informatization in China.

Background Fluid administration is a key tool in the maintenance of normovolemia in patients with cardiac surgery. The trials that evaluated the safety of 6% hydroxyethyl starch (HES) 130/0.4 in cardiac surgical patients were inconsistent. It is necessary to compare the efficacy and safety of albumin and 6% HES (130/0.4). Method We searched for the randomized controlled clinical trials that compared human albumin with 6% HES (130/0.4) in cardiac surgery in PubMed, Cochrane, and Embase. Results Ten studies involved a total of 1567 patients were included in our meta-analysis. For the efficiency, there was no difference in total volume of infusion between compared groups [P = 0.64, Fixed Effect Model (FEM): standardized mean difference (SMD) = 0.04, 95% confidence interval (CI) (− 0.12, 0.20)]. As for safety, the albumin show more risk than hydroxyethyl starch 130/0.4 in blood loss [P = 0.02, FEM: SMD: 0.22, 95% CI (0.03, 0.41)]. There was no difference in the frequency of transfusions (P = 0.20, RR = 1.11; 95% CI (0.95, 1.27)) between the two groups. No difference was observed for the days in intensive care unit [P = 0.05, FEM: SMD = − 0.18, 95% CI (− 0.36, 0.00)], and the days in hospital [P = 0.32, FEM: SMD = − 0.11, 95% CI (− 0.32, 0.10)]. Furthermore, both the incidence of AKI, RRT, and mortality were comparable in the two groups. Conclusion This study provided evidence that the 6% HES (130/0.4) might be the substitute for HA, which reduced the economic burden for patients with cardiac surgery. However, the effect of 6% HES (130/0.4) and HA on AKI still needs to be further studied.

BACKGROUND Deep venous thrombosis (DVT) is a serious complication of lumbar spine surgery. Current guidelines recommend pharmacomechanical prophylaxis for patients at high risk of DVT after spine surgery. May-Thurner syndrome (MTS), a venous anatomical variation that may require invasive intervention, is an often overlooked cause of DVT. To date, no case reports of symptomatic MTS caused by isthmic spondylolisthesis or subsequent acute DVT after posterior lumbar surgery have been published. CASE SUMMARY We here present a case of a patient who developed acute DVT 4 h after spondylolisthesis surgery, and MTS was only considered after surgery, during a review of a gynecological enhanced computed tomography image taken before the procedure. CONCLUSION In conclusion, clinicians should consider MTS in the presence of a dangerous triad: spondylolisthesis, elevated D-dimer levels, and sonographically indicated unilateral deep vein dilation. Consultation with a vascular surgeon is also essential to MTS management.

In this article, an online condition monitoring (CM) method is proposed for the bond wire degradation of insulated-gate bipolar transistor (IGBT) modules in a single-phase or three-phase three-level neutral-point-clamped (3LNPC) dc–ac, ac–dc converter. The proposed method has the ability to detect the whole IGBTs in a 3LNPC converter, based on finding the idle on-state IGBTs under the specific load current direction and switching sequence of a leg. The detection time is short (0.2 ms) and the influence of online CM on load current can be completely neglected as long as the insertion areas for CM test are chosen reasonably. Meanwhile, an advanced bond wire CM module is designed to conduct the CM test. This module can generate and inject the current pulse trains into IGBT modules, with the high current for CM test and low current for temperature-sensitive electrical parameter measurement, and sample the collector–emitter on-state voltage ( V CE $\_$ ON) stably and precisely. Finally, the experimental work was carried out to verify the effectiveness of the proposed method and the practicality of the developed CM module.

Background Minimal deviation adenocarcinoma is a rare malignancy with a high rate of misdiagnosis and high aggressiveness, and its diagnosis relies on histopathology. Surgical resection is the preferred and most effective treatment, but the outcomes are often unsatisfactory. Case summary A 60-year-old perimenopausal woman was admitted to the hospital and found to have elevated CA19-9 on physical examination without abdominal pain or vaginal bleeding. Clinical examination and positron emission tomography/computed tomography examination were unremarkable, magnetic resonance imaging examination was suggestive of dominant cervical lesions, and methylation examination was suggestive of malignant lesions. Tissue samples were taken from the suspected cervical lesion, and the final pathologic diagnosis was minimal deviation adenocarcinoma. Based on the pathologic diagnosis of suspected minimal deviation adenocarcinoma, radical abdominal total hysterectomy, bilateral oophorectomy, and pelvic and para-aortic lymph node dissection were performed. The final histological report confirmed minimal deviation adenocarcinoma of the cervix, stage IB2, with lymph node metastasis. Minimal deviation adenocarcinoma is a tumor with aggressive clinical behavior. Conclusion Patients with minimal deviation adenocarcinoma have a lower survival rate than patients with conventional human papillomavirus-related cervical adenocarcinoma. A precise preoperative pathologic diagnosis may reduce the mortality rate due to missed optimal treatment with multiple surgical interventions. To date, there is no therapeutic consensus; therefore, each case must be treated individually.

Monocular depth estimation is a very challenging task in computer vision, with the goal to predict per-pixel depth from a single RGB image. Supervised learning methods require large amounts of depth measurement data, which are time-consuming and expensive to obtain. Self-supervised methods are showing great promise, exploiting geometry to provide supervision signals through image warping. Moreover, several works leverage on other visual tasks (e.g. stereo matching and semantic segmentation) to further advance self-supervised monocular depth estimation. In this paper, we propose a novel framework utilizing monocular depth completion as an auxiliary task to assist monocular depth estimation. In particular, a knowledge transfer strategy is employed to enable monocular depth estimation to benefit from the effective feature representations learned by monocular depth completion task. The correlation between monocular depth completion and monocular depth estimation could be fully and effectively utilized in this framework. Only unlabeled stereo images are used in the proposed framework, which achieves a self-supervised learning paradigm. Experimental results on publicly available dataset prove that the proposed approach achieves superior performance to state-of-the-art self-supervised methods and comparable performance with supervised methods.

Introduction: Autoimmune hemolytic anemia is a potentially lethal disease characterized by autoimmune hemolysis. Although human umbilical cord-derived mesenchymal stem cells (hUC-MSCs) have been reported as a promising therapy, there is limited evidence regarding warm autoimmune hemolytic anemia (wAIHA) patients. This study aimed to investigate the potential therapeutic effects of hUC-MSCs via immune regulation in wAIHA patients. Methods: Peripheral blood mononuclear cells (PBMCs) from 10 wAIHA patients and 8 healthy controls were isolated from peripheral blood and cultured for 3 days with or without the presence of hUC-MSCs; PBMCs were co-cultured with hUC-MSCs using Transwell assays. The supernatant cytokine levels were measured after culture through AimPlex Multiple Immunoassays for Flow, including IL-2, IL-4, IL-10, IFN-γ, TNF-α, and IL-17A. The percentages of regulatory T cells, regulatory B cells, and Th1/Th2 in PBMCs were also assessed before and after culturing. Results: In the wAIHA group, hUC-MSCs could upregulate the Treg and Breg proportions after culturing for 3 days, and the Treg and Breg percentages increased after co-culturing with hUC-MSCs in the wAIHA group compared with PBMC cultured alone for 3 days (8.29 ± 8.59 vs. 6.82 ± 1.32, 3.82 ± 1.87 vs. 1.75 ± 1.20, respectively). Compared with the PBMC wAIHA group, the levels of TNF-α (2.13 ± 2.07 vs. 16.20 ± 21.13 pg/mL, p = 0.019) and IL-10 (10.51 ± 18.42 vs. 37.78 ± 44.20 pg/mL, p = 0.012) were significantly elevated in the PBMC + hUC-MSCs wAIHA group. Conclusion: The hUC-MSCs contributed to the increasing proportion of regulatory cell populations in PBMCs of wAIHA patients, thereby potentially regulating autoimmune response; thus, hUC-MSCs may be a promising approach for wAIHA treatment.

The objective of this study was to explore a new method for the differential diagnosis between fetal double aortic arch (DAA) and right aortic arch with mirror-image branches (RAA-MB). Clinical data and prenatal echocardiographic features of the DAA (n = 22) and RAA-MB (n = 65) confirmed by postnatal or autopsy findings were analyzed retrospectively. The angles between the two aortic arches in the DAA group and between the right aortic arch and the mirror branch were measured. The differences between the two groups and differential diagnosis value of the angles were compared and analyzed based on the receiver operating characteristic curve. The proportion of left-sided ductal arteriosus (100%) was higher in the DAA group than that (32.3%) in the RAA-MB group, (P

Erectile dysfunction (ED) is a common male disorder. Although orally-administered phosphodiesterase type 5 inhibitors (PDE5 inhibitors) are now recognized as the primary pharmacological treatment method for ED, 20%-30% of the patients treated with PDE5 inhibitors exhibit no significant effects. This study aims to investigate the influencing factors of ED in young adults with no response to PDE5 inhibitors. ED patients who would take PDE5 inhibitors were included and investigated with a questionnaire. Patients with no response to PDE5 inhibitors (tadalafil and sildenafil) served as study group, and those with response to PDE5 inhibitors as control group. Then Chi square test and logistic regression analysis were applied to find the potential influencing factors. In total, 378 ED patients were included. Ninety-three (24.6%) cases were non-responsive to PDE5 inhibitors, and the remaining 285 (75.4%) responded to PDE5 inhibitors. In multiple logistic regression analysis, we found that history of drinking (OR=3.152; 95%CI 1.672-6.975), spousal noncooperation (OR=2.994; 95%CI 1.589-5.638), number of fixed sex partners (OR=0.358; 95%CI 0.132-0.651), duration of ED (OR=3.356; 95%CI 1.352-8.333), and depression (OR=3.689; 95%CI 1.579-8.979) could be the influencing factors for ED patients' non-response to PDE5 inhibitors. In conclusion, history of drinking, spousal noncooperation, number of fixed sex partner, long duration of ED, and depression could be the influencing factors for ED patients' non-response to PDE5 inhibitors. Patients and doctors should pay attention to these factors.

Precision grinding is the key process to meet the heavy demands of large-aperture aspherical optical elements in the fields of laser nuclear fusion devices, large-aperture astronomical telescopes and high-resolution space cameras. In this study, the arc envelope grinding process of large-aperture aspherical optics was investigated using the CM1500 precision grinding machine with a maximum machinable diameter of Φ1500 mm. The analytical form error models of aspherical workpiece induced by wheel setting errors were established for both parallel grinding and cross grinding. Result show that the form error is much more sensitive to the wheel setting error along the feed direction than that along the lateral direction. It is a bilinear function of the feed-direction wheel setting error and the distance to optical axis. Based on the above analysis, a method to determine the wheel setting error is proposed. The grinding tests were then performed with the wheel accurately aligned. By using a newly proposed partial error compensation method with an appropriate compensation factor, a form error of 3.4 µm PV for a Φ400 mm elliptical K9 glass surface was achieved.

Automatic text summarization (ATS) has achieved impressive performance thanks to recent advances in deep learning (DL) and the availability of large-scale corpora. The key points in ATS are to estimate the salience of information and to generate coherent results. Recently, a variety of DL-based approaches have been developed for better considering these two aspects. However, there is still a lack of comprehensive literature review for DL-based ATS approaches. The aim of this paper is to comprehensively review significant DL-based approaches that have been proposed in the literature with respect to the notion of generic ATS tasks and provide a walk-through of their evolution. We first give an overview of ATS and DL. The comparisons of the datasets are also given, which are commonly used for model training, validation, and evaluation. Then we summarize single-document summarization approaches. After that, an overview of multi-document summarization approaches is given. We further analyze the performance of the popular ATS models on common datasets. Various popular approaches can be employed for different ATS tasks. Finally, we propose potential research directions in this fast-growing field. We hope this exploration can provide new insights into future research of DL-based ATS.

Background The paucity of accurate quantitative standards for determining the quantity of red blood cells (RBCs) needed for perioperative patients and the predominant application of the "preoperative hemoglobin + surgery type" empirical decision-making model have led to widespread RBC application problems. Objective The mathematical model of preoperative variables constructed by machine learning (ML) methods can help doctors decide preoperative RBC applications. Methods We retrospectively analysed 130 996 records of patients who received surgery in our hospital from January 2011 to June 2017. Through the analysis of multiple preoperative parameters that may affect the RBC transfusion volume, we used ML algorithms to build up the artificial intelligence (AI) model to predict the accurate RBC demand quantity and compared each result with those predicted by clinicians. Results Among the seven ML algorithms, the light gradient boosting machine (Lightgbm) algorithm was the best. The AI model predicted whether the patients needed RBC transfusion, and the area under curve (AUC) was 0.908 (95% CI 0.907-0.913). The AI model was more accurate than doctors in predicting RBC of 0, 2, and 4 units (85% data), with RMSEs of 1.61 vs. 2.15, 1.06 vs. 1.21, and 1.46 vs. 1.68, respectively. However, the AI model was not better than doctors in 1, 3, 5-6, 7-8, and 9-10 units (15% data), with RMSEs of 0.92 vs. 0.89, 0.92 vs. 0.89, 2.73 vs. 1.94, 4.53 vs. 3.92, and 6.26 vs. 5.08, respectively. Conclusion Through the comparison of seven ML methods, the Lightgbm algorithm-based model is more accurate than clinician experience-based in predicting preoperative RBC transfusion, which reduces the risk of untimely blood supply caused by insufficient preoperative blood preparation, and reduces the unnecessary cost of blood compatibility testing caused by excessive preoperative blood preparation.

Tumor-infiltrating CD8 cells and expression of programmed cell death ligand 1 (PD-L1) are immune checkpoint markers in patients with hepatocellular carcinoma (HCC). We aimed to determine the ability of preoperative gadoxetic acid-enhanced magnetic resonance imaging (MRI) findings to predict CD8 cell density and PD-L1 expression in HCC. A total of 120 patients with HCC who underwent 3.0-T gadoxetic acid-enhanced MRI before curative resection from January 2016 to June 2020 were enrolled and divided into a training set (n = 84) and a testing set (n = 36). Thirty-four patients with advanced stage HCC who received anti-PD-1 inhibitor between January 2017 and April 2020 and underwent pretreated gadoxetic acid-enhanced MRI scans were enrolled in an independent validation set. PD-L1 expression and CD8 cell infiltration were assessed with immunohistochemical staining, respectively. Two radiologists blinded to pathology results evaluated the pretreated MR features in consensus. Logistic regression and the receiver operating characteristic curve (ROC) analyses were used to determine the value of image features to predict high CD8 cell density, PD-L1 positivity and the combination of high CD8 cell density and PD-L1 positivity in HCC in the training set and validated the findings in the testing set. The associations of MRI predictors with the objective response to immunotherapy were assessed in the independent validation. In the training set, the independent MRI predictors were irregular tumor margin (ITM, P = 0.008) and peritumoral low signal intensity (PLSI) on hepatobiliary phase (HBP) images (P

The effects of local factors on activation of immune cells infiltrating the central nervous system (CNS) in a rat model of traumatic brain injury (TBI) remain elusive. The cytokine, interleukin (IL)-15, is crucial for development and activation of CD8 T lymphocytes, a prominent lymphocytic population present in TBI lesions. We investigated whether IL-15 originates from astrocytes and whether IL-15 can evoke the CD8 T-lymphocyte response in TBI. We observed that astrocytes were activated in a rat model of TBI and that IL-15 was overexpressed on the surface of astrocytes. Further, CD8 T lymphocytes infiltrating TBI lesions colocalized with IL-15-expressing astrocytes. Activated CD8 T lymphocytes released granzyme B (Gra-b), which, in turn, activated caspase-3-induced poly(ADP-ribose) polymerase cleavage and, ultimately, neuronal apoptosis. Conversely, inhibition of astrocyte activation by pre-treatment with the specific inhibitor, fluorocitrate (FC), that reduces carbon flux through the Krebs cycle in astrocytes resulted in improved neurological function and memory. FC pre-treatment was also associated with downregulated IL-15 expression and CD8 T-cell activation as well as decreased levels of neuronal apoptosis, suggesting that IL-15 initiated a domino effect toward apoptosis. In contrast, rats pre-treated with recombinant rat IL-15 showed upregulated CD8 T-cell numbers and Gra-b levels, in addition to induction of neuronal apoptosis. Together, our results indicated that IL-15 could induce neuronal apoptosis by enhancing CD8 T-cell function in a rat model of TBI.

Background Post-traumatic stress disorder (PTSD) is a debilitating mental disease with high morbidity and major social and economic relevance. No efficient treatment for PTSD has thus far been identified. Clinical research has shown that ketamine can rapidly alleviate symptoms in patients with chronic PTSD; however, its pharmacological mechanism has yet to be determined. Methods This study aimed to identify a model of single prolonged stress (SPS), which induced PTSD-like features in adult mice. Once the model was established, stress-related behavioral changes in the mouse model were evaluated after intraperitoneal injection of ketamine (10 mg/kg). Alterations in certain proteins (HCN1, BDNF, and PSD95) and synaptic ultrastructure in the prefrontal cortex (PFC) and hippocampus (HIP) were measured. Results The mice under the SPS model exhibited anxiety- and depression-like behaviors and induced spatial cognitive deficits, accompanied by elevated HCN1 protein expression in the PFC and HIP, reduced brain-derived neurotrophic factor (BDNF) and PSD95 proteins, and alterations in synaptic morphology. After ketamine administration, the SPS-treated mice restored their protein levels and synaptic ultrastructure in the PFC, and their PTSD-like behaviors improved. However, learning and memory in the SPS-treated mice did not improve in the water maze test, and no significant changes in protein level and synaptic ultrastructure in the HIP were shown. Limitations The electrophysiological mechanism of the HCN1 ion channel after ketamine administration was not explored. Conclusion Ketamine could generally improve SPS-induced mood dysfunction in mice but exerted no effect on the spatial cognitive function, which could be related to the alterations in synaptic morphology and function mediated by HCN1-related BDNF signaling in the PFC and HIP.

Diabetic nephropathy (DN) is a common microvascular complication of diabetes and one of the leading causes of end-stage renal disease. Tubular damage is an early change and characteristic of DN, and mitochondrial dysfunction plays an important role in the development of DN. Therefore, the timely removal of damaged mitochondria in tubular cells is an effective treatment strategy for DN. Mitophagy is a type of selective autophagy that ensures the timely elimination of damaged mitochondria to protect cells from oxidative stress. In this review, we summarize our understanding of mitochondrial dysfunction and dynamic disorders in tubular cells in DN and the molecular mechanism of mitophagy. Finally, the role of mitophagy in DN and its feasibility as a therapeutic target for DN are discussed.

Background: Long-term morphine use is associated with serious side effects, such as morphine-induced hyperalgesia and analgesic tolerance. Previous investigations have documented the association between dopamine (DA) neurons in the ventral tegmental area (VTA) and pain. However, whether VTA DA neurons are implicated in morphine-induced hyperalgesia and analgesic tolerance remains elusive. Methods: Initially, we observed behavioural effects of lidocaine administration into VTA or ablation of VTA DA neurons on morphine-induced hyperalgesia and anti-nociceptive tolerance. Subsequently, c-Fos expression in nucleus accumbens (NAc) shell-projecting and medial prefrontal cortex (mPFC)-projecting VTA DA neurons after chronic morphine treatment was respectively investigated. Afterwards, the effects of chemogenetic manipulation of NAc shell-projecting or mPFC-projecting DA neurons on morphine-induced hyperalgesia and anti-nociceptive tolerance were observed. Additionally, effects of chemogenetic manipulation of VTA GABA neurons on c-Fos expression in VTA DA neurons were investigated. Results: Lidocaine injection into VTA relieved established hyperalgesia and anti-nociceptive tolerance whereas ablation of VTA DA neurons prevented the development of morphine-induced hyperalgesia and anti-nociceptive tolerance. Chronic morphine treatment increased c-Fos expression in NAc shell-projecting DA neurons, rather than in mPFC-projecting DA neurons. Chemogenetic manipulation of NAc shell-projecting DA neurons had influence on morphine-induced hyperalgesia and tolerance. However, chemogenetic manipulation of mPFC-projecting DA neurons had no significant effects on morphine-induced hyperalgesia and anti-nociceptive tolerance. Chemogenetic manipulation of VTA GABA neurons affected the c-Fos expression in VTA DA neurons. Conclusions: These findings revealed the involvement of NAc shell-projecting VTA DA neurons in morphine-induced hyperalgesia and anti-nociceptive tolerance, and may shed new light on the clinical management of morphine-induced hyperalgesia and analgesic tolerance. Perspective: This study demonstrated that NAc shell-projecting DA neurons rather than mPFC-projecting DA neurons in the VTA were implicated in morphine-induced hyperalgesia and anti-nociceptive tolerance. Our findings may pave the way for the discovery of novel therapies for morphine-induced hyperalgesia and analgesic tolerance.

Due to the advancement of cloud computing, public key encryption with equality test has become a hot topic in the cryptography community. The notion was extended to the identity-based setting to obtain a new primitive, called identity-based encryption with equality test (IBEET). To the best of our knowledge, there are two categories of authorization mechanisms for IBEET: ciphertext-specified authorization and user-specified authorization. However, these authorizations are not applicable for some scenarios. Motivated by this, we propose in this paper a new primitive, called identity-based encryption with equality test and datestamp-based authorization mechanism (IBEET-DBA). In the primitive, the data owner can control the validity of trapdoor by embedding datestamp into it. The cloud server can only obtain the correct equivalence results on the ciphertexts which are generated within the valid period of trapdoor. In this paper, we formally define this primitive and its security notion. Moreover, we propose the first IBEET-DBA scheme and prove its security.

Public key encryption with equality test (PKEET) is an important cryptographic primitive for protecting users’ outsourced data in the cloud-based email systems. Due to the fact that it is required to deploy different authorization policies for the demand of dynamic privacy protection in the cloud-based email systems, Ma et al. recently presented a new related primitive, called public key encryption with equality test supporting flexible authorization (PKEET-FA). In their proposal, four types of authorization were considered to support different authorization policies. Their proposal is based on the bilinear pairings. However, as the basic operation of equality test, bilinear pairings are expensive operations compared with modular multiplications and modular inverses. Hence, it is desired to propose a new method for constructing efficient equality test with modular multiplications and modular inverses. In this paper, we present such a PKEET-FA scheme. Compared with Ma et al.’s, our proposal is (surprisingly) more efficient, especially in terms of equality test. Moreover, our proposal supports an additional type of authorization, called user-specific ciphertext-to-user (or user-specific user-to-ciphertext) level authorization. Hence, ours is more flexible than Ma et al.’s.

Aims/Introduction The aim of this study was to determine whether distinct subphenotypes of patients with type 2 diabetes in the European classification exist in Chinese populations, and to further establish novel subphenotypes more suitable for Chinese populations. Material and Methods The research retrospectively analyzed 5414 patients with type 2 diabetes from the National Clinical Research Center for Metabolic Diseases Diabetes Center in China, and a two‐step cluster analysis was carried out. First, we confirmed the European classification in Chinese populations by six parameters, including age at disease onset, body mass index, glycosylated hemoglobin, homeostatic model assessment 2 to estimate β‐cell function and insulin resistance, and glutamate decarboxylase antibodies. Furthermore, triglycerides and uric acid were added to refine the cluster analysis, and Cox regression was used to evaluate the risk of diabetic complications. Results Just three clusters were replicated in our cohort according to Emma Ahlqvist's European classification. When other variables were added to the cluster analysis, seven subgroups were identified, including five clusters of the European classification and two novel subgroups, namely, uric acid‐related diabetes and inheritance‐related diabetes. Compared with patients with inheritance‐related diabetes, patients with severe insulin‐resistant diabetes showed a higher risk of diabetic peripheral neuropathy, hypertension and chronic kidney disease, and the uric acid‐related diabetes subgroup showed a higher risk of coronary heart disease, cerebral vascular disease and end‐stage renal disease. Patients with severe insulin‐deficient diabetes showed a higher risk of diabetic retinopathy and diabetic foot than those with inheritance‐related diabetes. Furthermore, there were sex‐specific associations between subgroups and clinical outcomes. No significant difference was observed in the prevalence of cancer in each subgroup. Conclusions Seven subgroups of type 2 diabetes were identified in Chinese populations, with distinct characteristics and disparate clinical outcomes. This etiology‐based stratification might contribute to the diagnosis and management of type 2 diabetes., Seven subgroups of type 2 diabetes were identified in Chinese populations, with distinct characteristics and disparate clinical outcomes. This etiology‐based stratification may contribute to the diagnosis and management of type 2 diabetes.

Diabetic nephropathy (DN) is one of the most common and important microvascular complications of diabetes mellitus (DM). The main clinical features of DN are proteinuria and a progressive decline in renal function, which are associated with structural and functional changes in the kidney. The pathogenesis of DN is multifactorial, including genetic, metabolic, and haemodynamic factors, which can trigger a sequence of events. Controlling metabolic risks such as hyperglycaemia, hypertension, and dyslipidaemia is not enough to slow the progression of DN. Recent studies emphasized immunoinflammation as a critical pathogenic factor in the progression of DN. Therefore, targeting inflammation is considered a potential and novel treatment strategy for DN. In this review, we will briefly introduce the inflammatory process of DN and discuss the anti-inflammatory effects of antidiabetic drugs when treating DN.

Summary Perovskite solar cells (PSCs) suffer from significant nonradiative recombination, limiting their power conversion efficiencies. Here, for the first time, we directly observe a complete transformation of perovskite MAPbI3 surface region energetics from p- to n-type during defect passivation caused by natural additive capsaicin, attributed to the spontaneous formation of a p-n homojunction in perovskite active layer. We demonstrate that the p-n homojunction locates at ∼100 nm below perovskite surface. The energetics transformation and defect passivation promote charge transport in bulk perovskite layer and at perovskite/PCBM interface, suppressing both defect-assisted recombination and interface carrier recombination. As a result, an efficiency of 21.88% and a fill factor of 83.81% with excellent device stability are achieved, both values are the highest records for polycrystalline MAPbI3 based p-i-n PSCs reported to date. The proposed new concept of synergetic defect passivation and energetic modification via additive provides a huge potential for further improvement of PSC performance.

Background: TAR DNA-binding protein-43 (TDP-43) and neurofilament light chain (NfL) are promising fluid biomarkers of disease progression for various dementia. Objective: We would explore whether blood levels of NfL and TDP-43 could predict the long-term progression to dementia, and the relationship of TDP-43 levels between cerebrospinal fluid (CSF) and blood. Methods: A total of 86 non-dementia elderly received 7-year follow-up, and were divided into 49 stable normal control (NC)/mild cognitive impairment (MCI) subjects, 19 subjects progressing from NC to MCI, and 18 subjects progressing from NC/MCI to dementia. Blood TDP-43 and NfL levels, and cognitive functions were measured in all subjects. Furthermore, another cohort of 23 dementia patients, including 13 AD and 10 non-AD patients received blood and CSF measurements of TDP-43. Results: In cohort 1, compared to stable NC/MCI group, there were higher levels of blood TDP-43 at baseline in subjects progressing from NC/MCI to dementia. The combination of baseline blood TDP-43 levels with demographics including age, education, and diabetes had the detection for dementia occurrence. Baseline blood levels of NfL are negatively associated with cognitive function at 7-year follow-up. In cohort 2, we found there were no relationship between CSF and blood levels of TDP-43. Moreover, the levels of TDP-43 in CSF was positively associated with the age of patients, especially in AD group. Conclusion: Single blood TDP-43 could not estimate dementia occurrence; however, TDP-43 combined with demographics has the predictive effect for dementia occurrence and NfL level is associated with a decrease of cognitive function.

Digitally aligned long continuous ZnO NWs with distinct widths and microstructures are prepared and used for tuning the plasticity of synaptic transistors (STs) for the first time. Intrinsically controlled synaptic plasticity, i.e. short-term plasticity (STP) and long-term plasticity (LTP), was achieved using the same source material and post-fabrication condition for the first time, which is essential for simple and low-cost fabrication. Moreover, these versatile properties of ZnO STs enable the integration of STP and LTP as realized by multiplexed neurotransmission of different neurotransmitters: dopamine and acetylcholine, which promote learning and memory in organisms, so the device may utilize these processes in neuroelectronic devices. Devices with well-controlled synaptic plasticity can simulate the "learning-forgetting-erase" and "instant display" processes. ZnO NWs may enable the development of neuromorphic computers that can use the same material to achieve both short-term computation and long-term memory.

Dietary factors can reshape the gut microbiota and consequently affect disease progression. We previously reported that tetrahydrocurcumin (THC), the major active metabolite of curcumin (Cur), could ameliorate allergic inflammation in asthmatic mice. Herein, we aimed to investigate whether THC or Cur exerts anti-inflammatory effects on allergic asthma via modulating gut microbiota. Ovalbumin (OVA)-induced asthmatic mice were treated with Cur or THC, and the gut microbiota profiles were analyzed by 16S rRNA sequencing. Fecal microbiota transplantation (FMT) from Cur- or THC-fed donor mice was administered to OVA-induced asthmatic mice. Nasal symptoms and inflammation patterns of lungs and colons were evaluated in control, OVA-induced and Cur-or THC-treated mice. Both Cur and THC treatment could alter the compositions of the gut microbiota in asthmatic mice, characterized by a significant decrease in the ratio of Firmicutes to Bacteroidetes; Cur or THC supplementation also reduced the relative abundances of pro-inflammatory bacteria, e.g., Proteobacteria, Intestinimonas, Unidentified-Ruminococcaceae, and Lachnospiraceae, in OVA-induced mice. The relative abundances of Unidentified-Ruminococcaceae, Romboutsia, Intestinimonas, Akkermansia, and Mucispirillum were positively associated with the levels of Th2-related factors in asthmatic mice upon Cur or THC treatment. Moreover, THC-FMT showed better preventive effects than Cur-FMT on the development of allergic inflammation in OVA-induced mice, resulting in a reduction in symptoms and Th2-mediated inflammation in both lung and colon tissues. The results reveal that Cur- or THC-mediated alleviation of airway allergic inflammation is dependent on gut microbiota modulation. THC-induced gut microbiota may have therapeutic potential for asthma treatment.

Graphene is considered to be a valuable material in the field of photodetection due to its ultra-high electron mobility. However, its weak light absorption, short carrier lifetime and lack of gain mechanism limit the light responsivity of graphene at the magnitude of mA W−1. Herein, based on the oxidation characteristics of eutectic gallium–indium (EGaIn) alloy and the adoption of low-cost physical vapor deposition methods, we develop nanoparticles with gradient changes in elements to solve the drawback of common quantum dots of a narrow response band, fabricating a composite nanostructure of suspended graphene and oxidized EGaIn nanoparticles. The photodetector achieves wide-spectrum and high-performance detection from ultraviolet to near-infrared, with a responsivity enhancement of three order magnitude compared to that of pristine graphene. Then, the enhancement mechanism is analysed through structural characterization and control experiments, proving the dominant effect of oxidized nanoparticles on improving the responsivity and response band. This paper expands the application of EGaIn in the field of photoelectric detection and offers new idea for constructing high-performance quantun-dot based photodetectors.

The ultraviolet to terahertz band forms the main focus of optoelectronics research, while light detection in different bands generally requires the use of different materials and processing methods. However, researchers are aiming to realize multi-band detection simultaneously in the same device in certain specific application scenarios and ultra-wideband photoelectric detectors can also realize multi-function and multi-system integration. Therefore, the research and development work on ultra-wideband photoelectric detectors has important practical application value. Here, we produced self-powered suspended Pd-reduced graphene oxide-Ti (Pd-rGO-Ti) photodetectors. We varied the properties of the rGO films by using different annealing temperatures and achieved p-doping and n-doping of the films by evaporating palladium films and titanium films, respectively, thus enabling preparation of photothermoelectric (PTE) photodetectors based on rGO films. The resulting detectors have excellent photoelectric responses over a wideband illumination wavelength range from 375 nm to 118.8 μm (2.52 THz). At the same time, we determined the best experimental conditions and device structure by varying the channel width, the laser spot irradiation position and the experimental atmospheric pressure. The maximum responsivity obtained from our detectors is 142.08 mV W−1, the response time is approximately 100–200 ms and the devices have high detection sensitivity. Based on this work, we assumed in the subsequent experiments that detectors with higher performance can be obtained by reducing the channel width and atmospheric pressure. With advantages that include simple fabrication, low cost, large-scale production potential and ultra-wideband responses, these Pd-rGO-Ti photodetectors have broad application prospects in high-performance integrated optoelectronics.

Objective: This study aimed to clarify the death characteristics of esophageal cancer in Inner Mongolia and the population distribution with various education levels. Methods: The mortality rate of esophageal cancer was calculated using the monitoring point of Death Registry System in Inner Mongolia from 2009 to 2015. The gender, age, region, ethnicity at two education levels of percentage were calculated and the χ2 test was executed. Result: The mortality rate of esophageal cancer was 10.10/105, China Adjustment Mortality was 10.97/105, World Adjustment Mortality was 9.08/105 in Inner Mongolia. The death of esophageal cancer showed statistical significance at two educational levels (P < 0.05). High school and below accounted for 93.9% at the education level, and above high school accounted for 3.5%. In addition, there were significant differences in the percentage of death by gender, age and region at two educational levels (P < 0.05). Conclusion: Education level has a certain relation with the death of esophageal cancer. To improve the health level, health education plans can be formulated according to esophageal cancer prevention relevant policy with different education levels.

We conducted the present study to assess the correlation of the prostatic anatomical parameters, especially the ratio of peripheral zone thickness and transitional zone thickness, with clinical and uroflowmetry characteristics suggestive of benign prostate hyperplasia (BPH). A total of 468 consecutive patients with a detailed medical history were identified. All patients were evaluated by scoring subjective symptoms with the International Prostate Symptom Score (IPSS) and quality of life (QoL). The prostatic anatomical parameters were measured using transrectal ultrasonography, and postvoid residual urine and maximum flow rate (Qmax) values were also determined. Pearson's correlation analysis revealed that both total prostate volume (TPV; r = 0.160, P < 0.001) and transitional zone volume (TZV; r = 0.104, P = 0.016) increased with patients' age; however, no correlations were observed of TPV, TZV, transitional zone index (TZI), and transitional zone thickness (TZT) with IPSS or QoL (all P > 0.05). Peripheral to transitional zone index (PTI) was found negatively correlated with total IPSS (r = −0.113, P = 0.024), storage IPSS (r = −0.103, P = 0.041), and voiding IPSS (r = −0.123, P = 0.014). As regards the uroflowmetry characteristics, PTI (r = 0.157, P = 0.007) was indicated to be positively correlated with Qmax and negatively correlated with TZI (r = −0.119, P = 0.042) and TZT (r = −0.118, P = 0.045), but not correlated with TPV, TZV, or peripheral zone thickness (PZT) (all P > 0.05). Postvoid residual urine (PVR) had not correlated with all the prostatic anatomical variables (all P > 0.05). This is the first study that formally proposed the concept of PTI, which is an easy-to-measure prostate anatomical parameter which significantly correlates with total IPSS, storage IPSS, voiding IPSS, and Qmax, suggesting that PTI would be useful in evaluating and managing men with lower urinary tract symptoms (LUTS)/BPH. However, well-designed studies are mandatory to verify the clinical utility of PTI.

Diabetic nephropathy (DN) is a common complication of diabetes. Tamsulosin is a selective α1-AR antagonist. α1-AR is expressed widely in kidney tissues and has displayed its various physiological functions. However, whether Tamsulosin has affects DN is unknown. To our knowledge, this is the first time it has been examined whether Tamsulosin possesses a beneficial effect in high glucose-challenged glomerular endothelial cells (GECs). Firstly, we found that Tamsulosin reduced high glucose-induced expressions of TNF-α, IL-6, and IL-8. Secondly, Tamsulosin alleviated high glucose-induced expressions of MMP-2 and MMP-9. Thirdly, Tamsulosin inhibited the expressions of VCAM-1 and ICAM-1. Importantly, our results indicate that Tamsulosin inhibited high glucose-induced expressions of fibrosis factors such as Col-1 and TGF-β1. Additionally, we found that Tamsulosin ameliorated oxidative stress via reducing the generation of ROS and preventing the activation of p38. Mechanistically, we found that Tamsulosin attenuated high glucose-induced activation of NF-κB. Based on these findings, we conclude that Tamsulosin could attenuate high glucose-induced injury in GECs through alleviating oxidative stress and inflammatory response., Graphical abstract

Qinshan nuclear power plant is the first large Chinese-designed nuclear power station based on pressurized water reactor, and the second generation main stream active safety injection system is adopted for Qinshan nuclear power plant. In this paper, a novel passive safety injection system (PSIS) has been proposed for ocean-based Qinshan Phase One nuclear power plant to replace the original active one. The PSIS contains high-pressure, medium-pressure, and lower-pressure safety injection systems, and a two-stage automatic depressurization system. To evaluate the system performance, small-break LOCA has been investigated using RELAP5. Various break sizes and locations including 2-inch, 10-inch cold leg break, and double-ended direct vessel injection line break were analyzed. Key safety parameters such as safe injection mass flow rates, coolant level of the core, system pressure, and fuel cladding temperature were monitored during the accident process. The results illustrate that the performance of the safety injection system can guarantee the effective core cooling and submerged under different LOCA even with only half of the safety injection system, which can fulfill the single failure criteria. The thermal-hydraulic analysis for the Qinshan passive safety injection system is significant to master the related technologies for Chinese engineer and develop the Chinese-designed third-generation nuclear power plants, and the PSIS can guarantee the reactor submerged under LOCA even plus the station block out accident.

Small modular reactors (SMRs) are suitable for deployment in isolated underdeveloped areas to support highly localized microgrids. In order to achieve almost autonomous operation for reducing the cost of operating personnel, an autonomous control system with decision-making capability is needed. In this paper, a decision-making method based on Bayesian optimization algorithm (BOA) is proposed to explore the optimal operation scheme under fault conditions. BOA is used to adjust exploration strategy of operation scheme according to observations (operation schemes previously explored). To measure the feasibility of each operation scheme, an objective function that considers security and economy is established. BOA attempts to obtain the optimal operation scheme with maximum of the objective function in as few iterations as possible. To verify the proposed method, all main pump powered off fault is simulated by RELAP5 code. The optimal operation scheme of the fault is applied, the transient result shows that all key parameters are within safe limits and SMR is maintained at relatively high power, which means that BOA has the decision-making capability to get an optimal operation scheme on fault conditions.