Search

Chuan-Hua Zhan,1 Guo-Jun Liu2 1Department of Clinical Laboratory, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Huangshi, People’s Republic of China; 2Department of Breast Cancer Surgery, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Huangshi, People’s Republic of ChinaCorrespondence: Guo-Jun Liu, Department of Breast Cancer Surgery, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, No. 141, Tianjin Road, Huangshi, Hubei, 435000, People’s Republic of China, Tel +86 714 6323922, Email guojunliu1845@163.comObjective: To investigate the diagnostic value of the combined detection of α-hydroxybutyrate dehydrogenase (α-HBDH), carcinoembryonic antigen (CEA) and cancer antigen 125 (CA125) in early-stage breast cancer (ESBC).Methods: This was a retrospective analysis of 169 patients with ESBC, 138 patients with benign breast disease (BBD) and 200 normal healthy controls (NHCs). The levels of serum α-HBDH, CEA and CA125 in the two groups were detected. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to analyse the diagnostic value of the above indicators alone and in combination for ESBC.Results: The levels of α-HBDH, CEA and CA125 in the ESBC group were significantly higher than those in the BBD and NHC groups ([118.18 ± 11.19 vs 91.24 ± 9.17 vs 89.38 ± 9.01, F = 6.189, p = 0.004], [2.39 ± 1.12 vs 1.48 ± 0.76 vs 1.58 ± 0.58, F = 5.362, p = 0.017] and [14.44 ± 6.78 vs 11.19 ± 3.17 vs 7.18 ± 4.71, F = 8.912, p = 0.001], respectively). In the ESBC group, the positive rate of combined detection was higher than that of single detection (96.12% vs 72.64% vs 53.67% vs 42.41%, X2 = 27.174, p < 0.05). ROC curve analysis showed that serum α-HBDH, CEA, CA125 alone and combined detection in the diagnosis of ESBC. The sensitivity was 48.1%, 63.6%, 44.2% and 54.5%, the specificity was 75.4%, 75.4%, 86.0% and 91.2% and the AUC was 0.654, 0.715, 0.636 and 0.772, respectively. The diagnostic value of combined detection was the highest.Conclusion: The levels of serum α-HBDH, CEA and CA125 in ESBC are high, and the combined detection of the three has a high diagnostic value for ESBC.Keywords: breast cancer, α-hydroxybutyrate dehydrogenase, CA125, carcinoembryonic antigen, diagnosis

Semantic segmentation of aerial images is crucial yet resource-intensive. Inspired by human ability to learn rapidly, few-shot semantic segmentation offers a promising solution by utilizing limited labeled data for efficient model training and generalization. However, the intrinsic complexities of aerial images, compounded by scarce samples, often result in inadequate feature representation and semantic ambiguity, detracting from the model's performance. In this article, we propose to tackle these challenging problems via dual semantic metric learning and multisemantic features fusion and introduce a novel few-shot segmentation Network (DSMF-Net). On the one hand, we consider the inherent semantic gap between the feature of graph and grid structures and metric learning of few-shot segmentation. To exploit multiscale global semantic context, we construct scale-aware graph prototypes from different stages of the feature layers based on graph convolutional networks (GCNs), while also incorporating prior-guided metric learning to further enhance context at the high-level convolution features. On the other hand, we design a pyramid-based fusion and condensation mechanism to adaptively merge and couple the multisemantic information from support and query images. The indication and fusion of different semantic features can effectively emphasize the representation and coupling abilities of the network. We have conducted extensive experiments over the challenging iSAID-5$^{i}$ and DLRSD benchmarks. The experiments have demonstrated our network's effectiveness and efficiency, yielding on-par performance with the state-of-the-art methods.

Abstract Objective The CHOP combined chemotherapy regimen (cyclophosphamide, doxorubicin, vincristine, and prednisone) is commonly used to treat non-Hodgkin Lymphoma (NHL). While these drugs are effective for cancer treatment, they may have side effects on the reproductive system that are poorly studied. This study used a mouse model to investigate the mechanisms of reproductive function impairment induced by the CHOP regimen and developed a predictive model for assessing reproductive damage with a non-invasive procedure. Methods From 2022 to 2023, we statistically analyzed the changes of reproductive function of NHL patients before and after receiving CHOP regimen in the First Affiliated Hospital of Xiamen University. The NHL mouse model was established and divided into CHOP treatment group and control group. The weight of testis and epididymis, sperm quality and motility were compared between the two groups. Histopathological examination of testicular tissue was performed to determine pathological changes. ELISA was used to measure the expression of cytokines and cytokine pathways in serum, protein expression was analyzed by immunohistochemistry, and protein and mRNA levels of cytokines and pathways were evaluated by Western blotting and qPCR. Using stepwise regression method to select important factors, a prediction model of reproductive system damage was constructed. Results Fifty-two NHL patients included in the questionnaire showed significant reproductive system damage after CHOP regimen treatment. The weight of testis and epididymis, as well as the number and vitality of sperm in the mouse model treatment group were significantly lower than those in the control group. Serum LH, FSH, estradiol and progesterone levels decreased significantly, while inhibin B levels increased significantly. There was no significant change in testosterone or prolactin levels. Inflammatory markers such as CSF-1, IL-1, IL-6, TGF-β1 and GDNF increased significantly, while the level of SOD1 decreased significantly. Immunohistochemical staining analysis showed that CAMP, Caspase3, CSF-1, GDNF, IL-1, IL-6, PRKACB, TGF-β1 and TXNDC5 were all expressed in spermatocytes, and the expression of therapeutic histones was significantly higher than that of the control group. Western blot analysis further detected the protein expression, and QPCR detected the mRNA content. The results showed that the expression of histone and mRNA in the treatment group was significantly higher than that in the control group. Stepwise regression method determined that estradiol (E2) was the most important variable in the prediction model, and the AUC for predicting reproductive damage was 1. Conclusions The CHOP regimen induces male reproductive toxicity, potentially mediated through alterations in hormone levels and increased expression of inflammatory cytokines and oxidative stress. Using E2 as the sole predictor in the model accurately predicts the extent of reproductive damage, offering a non-invasive method for detecting reproductive system damage.

In the fields of wind power, and other industries, the Al2O3/TiO2 coating is prepared and ground on the bearing ring, in order to obtain the insulation resisting the electrical erosion for the motors at high voltage. A novel wet chemical mechanical grinding (WCMG) method is proposed to finish this hard-brittle composite material, utilizing the structured diamond abrasives pad and the NaOH solution. The softened workpiece's surface under the chemical reaction was demonstrated by means of Raman spectrum, indentation and scratching tests. The analytical model of surface roughness and fracture cracks is established based on the synthesis of geometry and kinematics, contact mechanics, material removal and indentation fracture mechanics. The surface roughness of coating was reduced from initial Sa 3.293 μm down to final Sa 0.049 μm in the WCMG process with grain size 3 μm and pH 12.01, mostly attributed to the ductile removal of chemically softened coating surface.

Abstract Frictional vibration often occurs during sliding, commonly referred to as the stick-slip phenomenon. It is more likely to occur in the range of the Stribeck curve, where friction and velocity have negative gradient characteristics. In this study, ultrasonic vibration is applied to the metal/metal sliding friction pair which reduce both static and kinetic friction forces. The inhibition mechanism of ultrasonic vibration on the stick-slip phenomenon is investigated for a sliding pair moving at low velocities (0.05–1.0 mm/s) under the condition of dry friction and oil lubrication. Under the condition of dry friction, ultrasonic vibration reduces the slider’s friction force by up to 89%, and the displacement fluctuation by up to 61%, effectively inhibiting the stick-slip phenomenon. Under the condition of oil lubrication, the friction force fluctuates when driving at a constant velocity, and the displacement fluctuation also fluctuates with the change of driving velocities. After ultrasonic vibration is applied, the friction reduction of the slider changes greatly with the driving velocity, so that the inhibition effect of ultrasonic vibration on stick-slip phenomenon under oil lubrication condition is unstable.

Abstract Purpose One of the most frequent side effects of radical prostatectomy (RP) is urinary incontinence. The primary cause of urine incontinence is usually thought to be impaired urethral sphincter function; nevertheless, the pathophysiology and recovery process of urine incontinence remains unclear. This study aimed to identify potential risk variables, build a risk prediction tool that considers preoperative urodynamic findings, and direct doctors to take necessary action to reduce the likelihood of developing early urinary incontinence. Methods We retrospectively screened patients who underwent radical prostatectomy between January 1, 2020 and December 31, 2023 at the First People ‘s Hospital of Nantong, China. According to nomogram results, patients who developed incontinence within three months were classified as having early incontinence. The training group’s general characteristics were first screened using univariate logistic analysis, and the LASSO method was applied for the best prediction. Multivariate logistic regression analysis was carried out to determine independent risk factors for early postoperative urine incontinence in the training group and to create nomograms that predict the likelihood of developing early urinary incontinence. The model was internally validated by computing the performance of the validation cohort. The nomogram discrimination, correction, and clinical usefulness were assessed using the c-index, receiver operating characteristic curve, correction plot, and clinical decision curve. Results The study involved 142 patients in all. Multivariate logistic regression analysis following RP found seven independent risk variables for early urinary incontinence. A nomogram was constructed based on these independent risk factors. The training and validation groups’ c-indices showed that the model had high accuracy and stability. The calibration curve demonstrates that the corrective effect of the training and verification groups is perfect, and the area under the receiver operating characteristic curve indicates great identification capacity. Using a nomogram, the clinical net benefit was maximised within a probability threshold of 0.01–1, according to decision curve analysis (DCA). Conclusion The nomogram model created in this study can offer a clear, personalised analysis of the risk of early urine incontinence following RP. It is highly discriminatory and accurate, and it can help create efficient preventative measures and identify high-risk populations.

ObjectiveThe prognostic value of the systemic immune-inflammation index (SII) for prostate cancer (PCa) patients receiving different treatments remains unclear. This research examined the relevance of SII in individuals undergoing radical prostatectomy (RP).MethodsPubMed, Embase, Web of Science, Cochrane, Wanfang, and China National Knowledge Infrastructure (CNKI) dat3 abases were used to search literature up to May 2024. The quality was evaluated with Newcastle-Ottawa Scale. Outcomes examined were associations between SII and overall survival (OS), biochemical recurrence-free survival (BFS), and cancer-specific survival (CSS). Pooled analysis, Egger’s test, and sensitivity analysis were conducted using Review Manager 5.4.1 and Stata 15.1. The GRADE system was employed to evaluate and grade the evidence for each outcome. Subgroup analyses were performed for outcomes with significant heterogeneity to evaluate the possible confounders, if data were sufficient.ResultsOut of 101 identified studies, eight studies involving 8,267 individuals were included. Patients with higher SII had shorter overall survival (HR: 1.89; 95% CI: 1.31-2.71; P = 0.0006), biochemical recurrence-free survival (HR: 1.55; 95% CI: 1.08-2.22; P = 0.02), and cancer-specific survival (HR: 3.63; 95% CI: 1.66-7.94; P = 0.001). The evidence for OS and CSS was rated very low-quality due to serious heterogeneity and/or imprecision. The prognostic value of SII for BFS was rated as low-quality evidence, given no serious risk observed. Subgroup analysis showed that, except for the subgroup aged >65 years (HR: 3.70; 95%CI: 0.91, 15.06, P=0.07), the prognostic value of SII for OS was not significant, but the prognostic value of SII for OS in other subgroups was still significant.ConclusionsHigh SII was linked to shorter OS, BFS, and CSS in patients undergoing RP. However, the quality of the evidence provided by this study was low.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024558431.

Effective keywords are extracted from the massive milk product user review data to construct thematic terms and explore the elemental influence relationships to assist manufacturers, and e-commerce platforms in understanding user behaviour and preferences and further optimise product design and marketing strategies. By fusing two different text mining methods, term frequency-inverse document frequency (TF-IDF) and Word2vec, we explore the semantic relationships, then visualise the relevance of user reviews by drawing knowledge graphs with Neo4j, and finally, be able to explore the relationship between the themes of the mined reviews, interpretative structural model (ISM) was used for a comprehensive evaluation, and the effectiveness of the method was verified on the Suning.com website dataset. The fusion of text mining and systematic analysis helps users to locate products quickly and precisely from the huge review information. The six elements of user reviews were categorized as freshness of taste, discounted prices, logistics, customer repurchase, product packaging, nutritional composition, and their element levels were divided into three layers. the first layer was discounted prices, customer repurchase, and logistics; the second layer was product packaging and nutritional composition; and the third layer was taste freshness.

ObjectivesThis study evaluated the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) for survival outcomes in bladder cancer patients treated with radical cystectomy.MethodsStudies assessing NLR’s prognostic significance for bladder cancer after radical cystectomy were identified from PubMed, Embase, Web of Science, and Cochrane databases until April 2024. Survival outcomes analyzed included overall survival (OS), disease-free survival (DFS), relapse-free survival (RFS), cancer-specific survival (CSS), and progression-free survival (PFS).ResultsThe meta-analysis comprised 15 cohort studies with 8,448 patients. Multivariate analysis showed significantly shorter OS, CSS, DFS, and RFS in the high NLR group compared to the low NLR group. However, no significant difference in PFS was observed between the groups.ConclusionsNLR serves as an independent prognostic indicator for bladder cancer patients undergoing radical cystectomy, with elevated NLR associated with poorer survival. Further large-scale, prospective studies are warranted to validate the relationship between NLR and prognosis in bladder cancer.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024549573.

Abstract Background Dysbacteriosis of intestinal tract may cause systemic inflammation, making distant anatomical locations more susceptible to illness. Recent research has demonstrated that the microbiome can affect both prostatitis and the inflammation of the prostate that is linked to prostate cancer. It is still unclear, though, whether this relationship indicates causation. We conducted a Mendelian randomization investigation on two samples to fully uncover gut microbiota’s potential genetic causal role in prostatitis. Method Prostatitis (1859 prostatitis cases and 72,799 controls) was utilized as the outcome, while SNPs highly linked with 196 microbial taxa (18 340 people) were chosen as instrumental factors. Random effects, inverse variance weighting, weighted medians, and MR-Egger were used to analyze causal effects. The Cochran’s Q test, funnel plot, leave-one-out analysis, and MR-Egger intercept test were all used in the sensitivity analysis. Results A causal effect in lowering the incidence of prostatitis is anticipated for five gut microorganisms (Methanobacteria, Methanobacteriaceae, Erysipelatoclostridium, Parasutterella, and Slackia; P

Abstract Audio‐visual wake word spotting is a challenging multi‐modal task that exploits visual information of lip motion patterns to supplement acoustic speech to improve overall detection performance. However, most audio‐visual wake word spotting models are only suitable for simple single‐speaker scenarios and require high computational complexity. Further development is hindered by complex multi‐person scenarios and computational limitations in mobile environments. In this paper, a novel audio‐visual model is proposed for on‐device multi‐person wake word spotting. Firstly, an attention‐based audio‐visual voice activity detection module is presented, which generates an attention score matrix of audio and visual representations to derive active speaker representation. Secondly, the knowledge distillation method is introduced to transfer knowledge from the large model to the on‐device model to control the size of our model. Moreover, a new audio‐visual dataset, PKU‐KWS, is collected for sentence‐level multi‐person wake word spotting. Experimental results on the PKU‐KWS dataset show that this approach outperforms the previous state‐of‐the‐art methods.

The grid-forming （GFM） control technology is instrumental in enabling converters to provide frequency and voltage support response akin to synchronous generators， thus bolstering the stability of the new power system. Nonetheless， a notable challenge lies in delivering grid support during fault current limiting. To this end， a strategy for fault current limiting in GFM converters based on measuring terminal and internal differential voltage orientation is proposed. In this approach， the angles of the positive and negative sequence current commands lag 90° behind the positive and negative sequence voltage differences. Additionally， the maximum magnitude of the synthesized vector of the current commands aligns with the converter’s overcurrent capability， which is equivalent to the generation of positive and negative sequence adaptive virtual inductance by control， respectively. This method obviates the need for direct virtual inductance value calculations and can maximize the maximum support capacity of the converter to realize the fault current characteristics resembling those of synchronous generators. The proposed fault current limiting strategy is validated by a simulation system built through PSCAD/EMTDC. The simulation outcomes affirm the strategy’s efficacy in delivering substantial grid support to the AC system while limiting fault currents.

The growing demand for lightweight materials in the automotive and aerospace industries has driven research on joining dissimilar lightweight alloys, particularly Al and Mg alloys (Al/Mg). Friction stir welding (FSW) is a promising technique for joining Al/Mg alloys, as it works below the base metal's melting temperature, leading to refined microstructures, reduced porosity, and enhanced productivity. The strength of Al/Mg friction stir weldment depends on the evolved interface, which is primarily characterized by micromechanical interlocks, type, and intermetallic compounds (IMCs) distribution. Different interfaces for butt joints have been discussed in the literature. However, the mechanism of interfacial interaction together with the ways to enhance the interface have not been reviewed yet. This review article fills the gap by analyzing the retrospective data for process parameters and mechanical properties. Joining mechanisms and the evolution of different interfaces at the microstructural level have been discussed. Lastly, ways to enhance the interface for improved mechanical properties are explained. By offering essential insights into FSW techniques and Al/Mg weld interfaces, this review article paves the way for developing FSW procedures for Al/Mg butt welds aiming for enhanced strength and performance. This review article is expected to be of interest to researchers and engineers working in the field of FSW, particularly for Al/Mg lightweight applications. It provides an overview of the current state of knowledge and identifies key areas for future research.

ABSTRACT A novel circularly polarised (CP) antenna design, termed differential mode (DM) and common mode (CM) design, is presented with equal‐amplitude in‐phase feed (EAIPF) in this article. At first, the CM and DM of the antenna are excited separately using the dual ports. Then, the CP antenna is obtained with EAIPF by adjusting the radiation amplitude of CM and DM, due to the orthogonality with a 90° phase difference for CM and DM. Finally, the obtained operational bandwidth of the presented antenna is 1.75–2.30 GHz (27.1%), with a reflection coefficient

Abstract Whether the alternated microbiota in the gut contribute to the risk of allograft rejection (AR) and pulmonary infection (PI) in the setting of lung transplant recipients (LTRs) remains unexplored. A prospective multicenter cohort of LTRs was identified in the four lung transplant centers. Paired fecal and serum specimens were collected and divided into AR, PI, and event-free (EF) groups according to the diagnosis at sampling. Fecal samples were determined by metagenomic sequencing. And metabolites and cytokines were detected in the paired serum to analyze the potential effect of the altered microbiota community. In total, we analyzed 146 paired samples (AR = 25, PI = 43, and EF = 78). Notably, we found that the gut microbiome of AR followed a major depletion pattern with decreased 487 species and compositional diversity. Further multi-omics analysis showed depleted serum metabolites and increased inflammatory cytokines in AR and PI. Bacteroides uniformis, which declined in AR (2.4% vs 0.6%) and was negatively associated with serum IL-1β and IL-12, was identified as a driven specie in the network of gut microbiome of EF. Functionally, the EF specimens were abundant in probiotics related to mannose and cationic antimicrobial peptide metabolism. Furthermore, a support-vector machine classifier based on microbiome, metabolome, and clinical parameters highly predicted AR (AUPRC = 0.801) and PI (AUPRC = 0.855), whereby the microbiome dataset showed a particularly high diagnostic power. In conclusion, a disruptive gut microbiota showed a significant association with allograft rejection and infection and with systemic cytokines and metabolites in LTRs.

Objective To evaluate the feasibility, safety and efficacy of three-port laparoscopic sleeve gastrectomy(LSG). Methods Clinical data of 130 patients with obesity who underwent LSG from April 2020 to January 2021 and completed follow-up in time were analyzed retrospectively. All patients were divided into two groups as surgical method, there were 52 cases in three-port group and 78 cases in four-port group. Perioperative indicators and improvement of obesity in two groups were compared. Results All procedures were performed via LSG. Compared with four-port group, the mean operative time of three-port group was shorter [(88.35±22.64) min vs. (98.29±26.25) min, P=0.027]. There were no significant differences in amount of bleeding intraoperative, postoperative pain, postoperative drainage, hospital stay after operation, postoperative complication rate and weight loss 6 months and 2 years after surgery (P>0.05). Conclusions Under the premise of no increase in surgical complications and operative time, three-port LSG can reduce the number and size of surgical scars, which is conducive to skin beauty, and obtain the same weight loss effect as four-port LSG, and can be used as a routine operation for sleeve gastrectomy.

Human echinococcosis is a parasitic disease caused by tapeworms of the genus Echinococcus. The two most important forms of the disease in humans are cystic echinococcosis (hydatidosis) and alveolar echinococcosis. Humans are infected through ingestion of parasite eggs in contaminated food, water, or soil, or through direct contact with animal hosts. Although most reported patients with Echinococcosis have cysts in their lungs and livers, more unusual cyst locations were also recorded. Evolution of cysts, irrespective of their localization is associated with many complications including life-threatening. We report unusual localization of parasitic cyst in urinary bladder, diagnostic and therapeutic problems.

Abstract：: Background: One of the most fatal forms of cancer of the urinary system, renal cell carcinoma (RCC), significantly negatively impacts human health. Recent research reveals that abnormal glycosylation contributes to the growth and spread of tumors. However, there is no information on the function of genes related to glycosylation in RCC. Methods: In this study, we created a technique that can be used to guide the choice of immunotherapy and chemotherapy regimens for RCC patients while predicting their survival prognosis. The Cancer Genome Atlas (TCGA) provided us with patient information, while the GeneCards database allowed us to collect genes involved in glycosylation. GSE29609 was used as external validation to assess the accuracy of prognostic models. The “ConsensusClusterPlus” program created molecular subtypes based on genes relevant to glycosylation discovered using differential expression analysis and univariate Cox analysis. We examined immune cell infiltration as measured by estimate, CIBERSORT, TIMER, and ssGSEA algorithms, Tumor Immune Dysfunction and Exclusion (TIDE) and exclusion of tumour stemness indices (TSIs) based on glycosylation-related molecular subtypes and risk profiles. Stratification, somatic mutation, nomogram creation, and chemotherapy response prediction were carried out based on risk factors. Results: We built and verified 16 gene signatures associated with the prognosis of ccRCC patients, which are independent prognostic variables, and identified glycosylation-related genes by bioinformatics research. Cluster 2 is associated with lower human leukocyte antigen expression, worse overall survival, higher immunological checkpoints, and higher immune escape scores. In addition, cluster 2 had significantly better angiogenic activity, mesenchymal EMT, and stem ability scores. Higher immune checkpoint genes and human leukocyte antigens are associated with lower overall survival and a higher risk score. Higher estimated and immune scores, lesser tumor purity, lower mesenchymal EMT, and higher stem scores were all characteristics of the high-risk group. High amounts of tumor-infiltrating lymphocytes, a high mutation load, and a high copy number alteration frequency were present in the high-risk group.Discussion.According to our research, the 16-gene prognostic signature may be helpful in predicting prognosis and developing individualized treatments for patients with renal clear cell carcinoma, which may result in new personalized management options for these patients.

Abstract Small-scale distributed water treatment equipment such as sequencing batch reactor (SBR) is widely used in the field of rural domestic sewage treatment because of its advantages of rapid installation and construction, low operation cost and strong adaptability. However, due to the characteristics of non-linearity and hysteresis in SBR process, it is difficult to construct the simulation model of wastewater treatment. In this study, a methodology was developed using artificial intelligence and automatic control system that can save energy corresponding to reduce carbon emissions. The methodology leverages random forest model to determine a suitable soft sensor for the prediction of COD trends. This study uses pH and temperature sensors as premises for COD sensors. In the proposed method, data were pre-processed into 12 input variables and top 7 variables were selected as the variables of the optimized model. Cycle ended by the artificial intelligence and automatic control system instead of by fixed time control that was an uncontrolled scenario. In 12 test cases, percentage of COD removal is about 91. 075% while 24. 25% time or energy was saved from an average perspective. This proposed soft sensor selection methodology can be applied in field of rural domestic sewage treatment with advantages of time and energy saving. Time-saving results in increasing treatment capacity and energy-saving represents low carbon technology. The proposed methodology provides a framework for investigating ways to reduce costs associated with data collection by replacing costly and unreliable sensors with affordable and reliable alternatives. By adopting this approach, energy conservation can be maintained while meeting emission standards.

Anomaly detection has wide applications to help people recognize false, intrusion, flaw, equipment failure, etc. In most practical scenarios, the amount of the annotated data and the trusted labels is low, resulting in poor performance of the detection. In this paper, we focus on the anomaly detection for the text type data and propose a detection network based on biological immunity for few-shot detection, by imitating the working mechanism of the immune system of biological organisms. This network enabling the protected system to distinguish the aggressive behavior of “nonself” from the legitimate behavior of “self” by embedding characters. First, it constructs episodic task sets and extracts data representations at the character level. Then, in the pretraining phase, Word2Vec is used to embed the representations. In the meta-learning phase, a dynamic prototype containing encoder, routing, and relation is designed to identify the data traffic. Compare to the mean-based prototype, the proposed prototype applies a dynamic routing algorithm that assigns different weights to samples in the support set through multiple iterations to obtain a prototype that combines the distribution of samples. The proposed method is validated on 2 real traffic datasets. The experimental results indicate that (a) the proposed anomaly detection prototype outperforms state-of-the-art few-shot techniques with 1.3% to 4.48% accuracy and 0.18% to 4.55% recall; (b) under the premise of ensuring the accuracy and recall, the number of training samples is reduced to 5 or 10; (c) ablation experiments are designed for each module, and the results show that more accurate prototypes can be obtained by using the dynamic routing algorithm.

In this paper, the classical online multi-target tracking algorithms SORT and DeepSORT are improved. Firstly, we reduce the frequency of ID-Switch occurrence by integrating representational information, on which we complete the improvement of SORT to obtain the DeepSORT algorithm. Then, an MF-SORT multi-target tracking algorithm is proposed by using the squared Martens distance instead of the cosine distance of the high-dimensional representational features in DeepSORT to track the similarity between the frame and the detection frame. Subsequently, the algorithm is applied to analyze soccer training videos, and in this way, a soccer teaching and training method is proposed. The results of the teaching experiment show that the average score of the players who receive this method is 2.7 points ahead of the players who receive the traditional method on average. The post-test score of the experimental group is 2.6 points higher than the pre-test score. The players who received the training method were 10.2% more satisfied with their training than the players who did not receive it. It shows that the video analysis method for ball training has good results both in soccer training performance and satisfaction with training.

Abstract Clear cell renal cell carcinoma (ccRCC) is a main subtype of renal cancer, and advanced ccRCC frequently has poor prognosis. Many studies have found that lipid metabolism influences tumor development and treatment. This study was to examine the prognostic and functional significance of genes associated with lipid metabolism in individuals with ccRCC. Using the database TCGA, differentially expressed genes (DEGs) associated with fatty acid metabolism (FAM) were identified. Prognostic risk score models for genes related to FAM were created using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses. Our findings demonstrate that the prognosis of patients with ccRCC correlate highly with the profiles of FAM-related lncRNAs (AC009166.1, LINC00605, LINC01615, HOXA-AS2, AC103706.1, AC009686.2, AL590094.1, AC093278.2). The prognostic signature can serve as an independent predictive predictor for patients with ccRCC. The predictive signature's diagnostic effectiveness was superior to individual clinicopathological factors. Between the low- and high-risk groups, immunity research revealed a startling difference in terms of cells, function, and checkpoint scores. Chemotherapeutic medications such lapatinib, AZD8055, and WIKI4 had better outcomes for patients in the high-risk group. Overall, the predictive signature can help with clinical selection of immunotherapeutic regimens and chemotherapeutic drugs, improving prognosis prediction for ccRCC patients.

The safety of people and property in mountainous regions can be affected by landslides, and measurement of vertical ground formation is a vital component of landslide monitoring and forecasting. Over the past few years, UAV images have gained increasing popularity in the landslide monitoring; however, studies on the measurement accuracy of UAV image-based landslide surface deformation monitoring are relatively limited. In this study, a series of outdoor model tests are conducted to investigate the measurement accuracy of the digital difference-based software of CloudCompare, Global Mapper, and PolyWorks in UAV image-based vertical ground deformation measurement. The results indicate that when the resolution of the input UAV image is better than 3.0 cm/pixel, all the selected software can recognize the ground deformation zones with vertical ground deformation larger than 5.0 cm; under different vertical ground deformation scenarios, the vertical ground deformation measurement obtained with Global Mapper tends to be more accurate, and the medium error of the measurement ranges from 1.5 cm to 4.0 cm. Neither the medium error of measurement nor the standard deviation of measurement error is greatly affected by the magnitude of vertical ground deformation. The statistical analysis of measurement error suggests that the measurement errors of the selected software all follow normal distributions; then, based on the statistics of the measurement errors, the 95% confidence intervals of the vertical ground deformations obtained from the selected software could be obtained. Furthermore, Global Mapper software is applied to identify and measure the vertical deformation of the Dangchuan landslides in Heifangtai, and the results indicate that this software can accurately identify the landslide deformation area and locate the related ranges.

BackgroundThe safety of mastectomy (MT) with immediate reconstruction (IR) in breast cancer patients who have completed neoadjuvant chemotherapy (NAC) is not apparent. This meta-analysis aims to systematically evaluate the differences in surgical complications and postoperative survival rates between MT with IR (MT+IR) and MT alone in post-NAC breast cancer patients.MethodsThe PubMed, Embase, Cochrane Library, WanFang Data, and CNKI databases were systematically searched, and cohort studies of post-NAC breast cancer patients with MT+IR or MT surgery were collected from databases inception to May 25, 2023. Two researchers independently executed literature screening, data extraction, and bias risk assessment, and meta-analysis was performed using Revman 5.3 software.ResultsA total of 12 studies involving 7378 cases who have accepted NAC were collected for this study. The results showed that compared with the MT group, the relative risk of surgical complications in the MT+IR group was increased by 44%, with no statistical significant [RR=1.44, 95% CI (0.99, 2.09), P=0.06]. While among study subgroups with a median follow-up of less than one year, more surgical complications occurred in the MT+IR group by 23% [RR=1.23, 95% CI (1.00, 1.52), P=0.05]. There was no significant differences in overall survival, disease-free survival, local relapse-free survival, and distant metastasis-free survival between the two groups.ConclusionsCompared with the MT, MT+IR does not affect the postoperative survival rate in post-NAC breast cancer patients, accompanied by a mild increase in short-term surgical complications, but no significant difference in long-term complications.Systematic review registrationhttps://www.crd.york.ac.uk/prospero, identifier CRD42023421150.

The various applications of bearing-only sensor networks for detection and localization are becoming increasingly widespread and important. The array layout of the bearing-only sensor network seriously impacts the detection performance. This paper proposes a multi-strategy fusion improved adaptive mayfly algorithm (MIAMA) in a bearing-only sensor network to perform layout planning on the geometric configuration of the optimal detection. Firstly, the system model of a bearing-only sensor network was constructed, and the observability of the system was analyzed based on the Cramer–Rao Lower Bound and Fisher Information Matrix. Then, in view of the limitations of the traditional mayfly algorithm, which has a single initial population and no adaptability and poor global search capabilities, multi-strategy fusion improvements were carried out by introducing Tent chaos mapping, the adaptive inertia weight factor, and Random Opposition-based Learning. Finally, three simulation experiments were conducted. Through comparison with the Particle Swarm Optimization (PSO) algorithm, Mayfly Algorithm (MA), and Genetic Algorithm (GA), the effectiveness and superiority of the proposed MIAMA were validated.

The problem of state estimation based on bearing-only sensors is increasingly important while existing research on distributed filtering solutions is rather limited. Therefore, this paper proposed the novel distributed cubature information filtering (DCIF) method for addressing the state estimation challenge in bearing-only sensor networks. Firstly, the system model of the bearing-only sensor network was constructed, and the observability of the system was analyzed. The sensor nodes are paired to measure relative angle information. Subsequently, the coordinated consistency theory is employed to achieve a unified state estimation of the maneuvering target. The DCIF method enhances the observability of the system, addressing the issues of large accuracy errors and divergence in traditional nonlinear filtering algorithms. Building upon the theoretical proof of consistency convergence in DCIF, four simulation experiments were conducted for comparison. These experiments validate the effectiveness and superiority of the DCIF method in bearing-only sensor networks.

[Objective] The net primary productivity (NPP), carbon fixation, and oxygen release in a wetland of Ezhou City, Hubei Province were estimated, and a method for estimating wetland NPP on small and medium-scale wetlands involving large areas of water was established in order to provide accurate data support for related policies. [Methods] A wetland classification model was constructed to divide Ezhou wetlands into surface wetlands and water wetlands. Remote sensing data and a light energy utilization model were used to estimate NPP for surface wetlands. For water wetlands, chlorophyll a and biomass were introduced as indicators to build a regression model to estimate NPP. The annual total NPP in 2020 was obtained by summarizing the results for both surface wetlands and water wetlands at the same time, and the spatial distribution of NPP, carbon fixation, and oxygen release were obtained. [Results] The annual total NPP was 2.99×105 tons of carbon, the fixation of CO2 was 4.87×105 tons, and the release of O2 was 3.59×105 tons. The overall spatial distribution pattern indicated that NPP was high in southern part of the study region and low in the northern part. [Conclusion] A wetland classification model was used to estimate the NPP of water wetlands separately from the NPP of surface wetlands. This method made up for the deficiencies arising from estimating NPP only with a light energy utilization model, and provided estimation results that were closer to observed values for wetlands. This model and method is applicable to similar wetland NPP estimation research involving water bodies.

The focus in this paper is on coverage energy-efficient of WSN (wireless sensor networks). Communication path lengths of a randomly distributed BSs and sensor nodes field are characterized by distance distributions. For sensor nodes, this paper will use theory of Poisson point process (PPP) and Boolean Model (BM) to purpose a power allocation scheme results in green communication of sensor nodes. The energy allocation scheme of wireless sensor networks can help to prolong the life of the whole network. In this paper, we prove that the scheduling and allocation scheme can achieve energy saving, so as to prolong the life cycle of the whole wireless sensor networks. In the uniform placement migration case, we simulation 1000 times. In Boolean Model, There is 71.3% for power scheduling and allocation schemes and 28.7% is not. From these results, we see that, in wireless sensor networks, 20%–30% of total energy, which was being consumed from the part of power scheduling and allocation. The scheduling scheme improves response time, throughput and overall energy consumption over base case. Compared with other allocation schemes, the advantage of the scheme proposed in this paper is that the less sensors selected can still provide more than 95% detection area coverage. It will enable robust communication against cross-tier interference and co-layer interference thereby obtaining a substantial improvement in link quality.

This article examines the overall characteristics of historical medical exchanges between China and foreign countries, analyzing their contribution to the development of medicines in the world. It presents a summary of historical experiences of the development of medicines through mutual exchanges. It also provides an objective analysis of the effects of the eastward dissemination of Western medicine on traditional Chinese medicine. The history of their exchanges can be used as a mirror for each to learn from the other’s strengths to offset their own weakness, and achieve the coordinated and balanced development of both traditional Chinese medicine and Western medicine. Such balanced development would enable the world’s medicinal systems to thrive and protect the health of people worldwide.

In view of the problem that B element is easy to cause more hard and brittle phases in brazed diamond joints, a new type of Ni–Cr–Si–Cu–Sn boron free active solder was prepared, and the effects of Cr element on the microstructure of solder and the properties of brazed diamond were analyzed. The results show that Cr element can refine the solder grain and regulate the distribution of elements in the solder, which can improve the microhardness of the solder alloy. Excessive Cr addition will cause the melting point of the solder to increase and the wettability of the solder to decrease. In general, the boron free solder containing 15% Cr has the best performance, the grinding performance of brazed diamond is better, and Cr7C3 phases of various shapes appear at the joint, realizing the high-strength connection of the solder to the diamond.

Height estimation has long been a pivotal topic within measurement and remote sensing disciplines, with monocular height estimation offering wide-ranging data sources and convenient deployment. This paper addresses the existing challenges in monocular height estimation methods, namely the difficulty in simultaneously achieving high-quality instance-level height and edge reconstruction, along with high computational complexity. This paper presents a comprehensive solution for monocular height estimation in remote sensing, termed HeightFormer, combining multilevel interactions and image-adaptive classification–regression. It features the Multilevel Interaction Backbone (MIB) and Image-adaptive Classification–regression Height Generator (ICG). MIB supplements the fixed sample grid in the CNN of the conventional backbone network with tokens of different interaction ranges. It is complemented by a pixel-, patch-, and feature map-level hierarchical interaction mechanism, designed to relay spatial geometry information across different scales and introducing a global receptive field to enhance the quality of instance-level height estimation. The ICG dynamically generates height partition for each image and reframes the traditional regression task, using a refinement from coarse to fine classification–regression that significantly mitigates the innate ill-posedness issue and drastically improves edge sharpness. Finally, the study conducts experimental validations on the Vaihingen and Potsdam datasets, with results demonstrating that our proposed method surpasses existing techniques.

Abstract Background Anthracnose of Camellia oleifera is a very destructive disease that commonly occurs in the Camellia oleifera industry, which severely restricts the development of the Camellia oleifera industry. In the early stage of the Camellia oleifera suffering from anthracnose, only the diseased parts of the tree need to be repaired in time. With the aggravation of the disease, the diseased branches need to be eradicated, and severely diseased plants should be cut down in time. At present, aiming at the problems of complex experiments and low accuracy in detecting the degree of anthracnose of Camellia oleifera, a method is proposed to detect the degree of anthracnose of Camellia oleifera leaves by using terahertz spectroscopy (THz) combined with laser-induced breakdown spectroscopy (LIBS), so as to realize the rapid, efficient, non-destructive and high-precision determination of the degree of anthracnose of Camellia oleifera. Results Mn, Ca, Ca II, Fe and other elements in the LIBS spectrum of healthy and infected Camellia oleifera leaves with different degrees of anthracnose are significantly different, and the Terahertz absorption spectra of healthy Camellia oleifera leaves, and Camellia oleifera leaves with different degrees of anthracnose there are also significant differences. Partial least squares discriminant analysis (PLS-DA), support vector machine (SVM), and linear discriminant analysis (LDA) are used to establish the fusion spectrum anthracnose classification model of Camellia oleifera. Among them, the Root mean square error of prediction (RMSEP) and the prediction determination coefficient R2p of THz-LIBS-CARS-PLS-DA of prediction set are 0.110 and 0.995 respectively, and the misjudgment rate is 1.03%; The accuracy of the modeling set of THz (CARS)-LIBS (CARS)-SVM is 100%, and the accuracy of prediction set is 100%, after preprocessing of the multivariate scattering correction (MSC), the accuracy of the THz-LIBS-MSC-CARS modeling set is 100%, and the accuracy of prediction set is 100%; The accuracy rate of THz-LIBS-MSC-CARS-LDA of modeling set is 98.98%, and the accuracy rate of the prediction set is 96.87%. Conclusion The experimental results show that: the SVM model has higher qualitative analysis accuracy and is more stable than the PLS-DA and LDA models. The results showed that: the THz spectrum combined with the LIBS spectrum could be used to separate healthy Camellia oleifera leaves from various grades of anthracnose Camellia oleifera leaves non-destructively, quickly and accurately.

Drought is a severe environmental condition that restricts the vegetative growth and reduces the yield of grapevine (Vitis vinifera L.). However, the mechanisms underlying grapevine response and adaptation to drought stress remain unclear. In the present study, we characterized an ANNEXIN gene, VvANN1, which plays a positive role in the drought stress response. The results indicated that VvANN1 was significantly induced by osmotic stress. Expression of VvANN1 in Arabidopsis thaliana enhanced osmotic and drought tolerance through modulating the level of MDA, H2O2, and O2·- at the seedling stage, implying that VvANN1 might be involved in the process of ROS homeostasis under drought or osmotic stress conditions. Moreover, we used yeast one-hybridization and chromatin immunoprecipitation assays to show that VvbZIP45 could regulate VvANN1 expression by directly binding to the promoter region of VvANN1 in response to drought stress. We also generated transgenic Arabidopsis that constitutively expressed the VvbZIP45 gene (35S::VvbZIP45) and further produced VvANN1Pro::GUS/35S::VvbZIP45 Arabidopsis plants via crossing. The genetic analysis results subsequently indicated that VvbZIP45 could enhance GUS expression in vivo under drought stress. Our findings suggest that VvbZIP45 may modulate VvANN1 expression in response to drought stress and reduce the impact of drought on fruit quality and yield.

Accurate identification of road objects is crucial for achieving intelligent traffic systems. However, developing efficient and accurate road object detection methods in complex traffic scenarios has always been a challenging task. The objective of this study was to improve the target detection algorithm for road object detection by enhancing the algorithm’s capability to fuse features of different scales and levels, thereby improving the accurate identification of objects in complex road scenes. We propose an improved method called the Enhanced YOLOv5 algorithm for road object detection. By introducing the Bidirectional Feature Pyramid Network (BiFPN) into the YOLOv5 algorithm, we address the challenges of multi-scale and multi-level feature fusion and enhance the detection capability for objects of different sizes. Additionally, we integrate the Convolutional Block Attention Module (CBAM) into the existing YOLOv5 model to enhance its feature representation capability. Furthermore, we employ a new non-maximum suppression technique called Distance Intersection Over Union (DIOU) to effectively address issues such as misjudgment and duplicate detection when significant overlap occurs between bounding boxes. We use mean Average Precision (mAP) and Precision (P) as evaluation metrics. Finally, experimental results on the BDD100K dataset demonstrate that the improved YOLOv5 algorithm achieves a 1.6% increase in object detection mAP, while the P value increases by 5.3%, effectively improving the accuracy and robustness of road object recognition.

Clear‐cell renal cell carcinoma (ccRCC) is the most prevalent renal malignancy. The pathogenesis of the disease is currently poorly understood, and the prognosis is poor. Therefore, in this study, we focused on exploring and identifying genes and signal transduction pathways that are closely related to ccRCC. Differentially expressed genes (DEGs) were analyzed using the renal cell oncogene expression profiles GSE100666 and GSE68417. DAVID evaluation of gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses was used. We constructed a protein–protein interaction (PPI) network of DEGS using Cytoscape software and analyzed the submodules with the CytoHubba plugin. Finally, we performed western blot, immunohistochemistry, and PCR validation by collecting tissues, and also utilized cells for in vitro functional analysis of ceruloplasmin (CP). In total, 202 DEGs (52 upregulated and 150 downregulated genes) were identified. Upregulated DEGs are significantly rich in angiogenesis, cell adhesion, and response to hypoxia, whereas downregulated DEGs are involved in intracellular pH regulation, excretion, coagulation, and chloride transmembrane transport. We selected the interactions of the top 20 hub genes provided by the PPI network, all of which are involved in important physiological pathways in vivo, such as complement and coagulation cascades. Tissue protein assays demonstrated that renal cancer highly expressed CP, while in vitro experiments showed that CP could promote the invasion of renal cancer cells. Our study suggests that ALB, C3, LOX, HRG, CXCR4, GPC3, SLC12A3, CP, and CASR may be involved in the development of ccRCC, and is expected to provide theoretical support for future studies on the diagnosis and targeted therapy of ccRCC.

Background The influencing factors of diabetic kidney disease (DKD) in Chinese patients with type 2 diabetes mellitus (T2DM) were explored to develop and validate a DKD diagnostic tool based on nomogram approach for patients with T2DM. Methods A total of 2,163 in-hospital patients with diabetes diagnosed from March 2015 to March 2017 were enrolled. Specified logistic regression models were used to screen the factors and establish four different diagnostic tools based on nomogram according to the final included variables. Discrimination and calibration were used to assess the performance of screening tools. Results Among the 2,163 participants with diabetes (1,227 men and 949 women), 313 patients (194 men and 120 women) were diagnosed with DKD. Four different screening equations (full model, laboratory-based model 1 [LBM1], laboratory-based model 2 [LBM2], and simplified model) showed good discriminations and calibrations. The C-indexes were 0.8450 (95% confidence interval [CI], 0.8202 to 0.8690) for full model, 0.8149 (95% CI, 0.7892 to 0.8405) for LBM1, 0.8171 (95% CI, 0.7912 to 0.8430) for LBM2, and 0.8083 (95% CI, 0.7824 to 0.8342) for simplified model. According to Hosmer-Lemeshow goodness-of-fit test, good agreement between the predicted and observed DKD events in patients with diabetes was observed for full model (χ2=3.2756, P=0.9159), LBM1 (χ2=7.749, P=0.4584), LBM2 (χ2=10.023, P=0.2634), and simplified model (χ2=12.294, P=0.1387). Conclusion LBM1, LBM2, and simplified model exhibited excellent predictive performance and availability and could be recommended for screening DKD cases among Chinese patients with diabetes.

Background: Clear cell renal cell carcinoma (ccRCC) is the main component of renal cell carcinoma (RCC), and advanced ccRCC frequently indicates a poor prognosis. The significance of the CCCH-type zinc finger (CTZF) gene in cancer has been increasingly demonstrated during the past few years. According to studies, targeted radical therapy for cancer treatment may be a revolutionary therapeutic approach. Both lncRNAs and CCCH-type zinc finger genes are essential in ccRCC. However, the predictive role of long non-coding RNA (lncRNA) associated with the CCCH-type zinc finger gene in ccRCC needs further elucidation. This study aims to predict patient prognosis and investigate the immunological profile of ccRCC patients using CCCH-type zinc finger-associated lncRNAs (CTZFLs).Methods: From the Cancer Genome Atlas database, RNA-seq and corresponding clinical and prognostic data of ccRCC patients were downloaded. Univariate and multivariate Cox regression analyses were conducted to acquire CTZFLs for constructing prediction models. The risk model was verified using receiver operating characteristic curve analysis. The Kaplan-Meier method was used to analyze the overall survival (OS) of high-risk and low-risk groups. Multivariate Cox and stratified analyses were used to assess the prognostic value of the predictive feature in the entire cohort and different subgroups. In addition, the relationship between risk scores, immunological status, and treatment response was studied.Results: We constructed a signature consisting of eight CTZFLs (LINC02100, AC002451.1, DBH-AS1, AC105105.3, AL357140.2, LINC00460, DLGAP1-AS2, AL162377.1). The results demonstrated that the prognosis of ccRCC patients was independently predicted by CTZFLs signature and that the prognosis of high-risk groups was poorer than that of the lower group. CTZFLs markers had the highest diagnostic adequacy compared to single clinicopathologic factors, and their AUC (area under the receiver operating characteristic curve) was 0.806. The overall survival of high-risk groups was shorter than that of low-risk groups when patients were divided into groups based on several clinicopathologic factors. There were substantial differences in immunological function, immune cell score, and immune checkpoint expression between high- and low-risk groups. Additionally, Four agents, including ABT737, WIKI4, afuresertib, and GNE 317, were more sensitive in the high-risk group.Conclusion: The Eight-CTZFLs prognostic signature may be a helpful prognostic indicator and may help with medication selection for clear cell renal cell carcinoma.

BACKGROUND The water-soluble fluoride in soil was pretreated by ultrasonic extraction and determined by ion selective electrode. The thermal effect of ultrasonic cavitation can cause the temperature of the extract to rise, and the test result may be unstable, and it cannot truthfully reflect the water-soluble fluorine content in the soil, which causes problems for the monitoring of fluorine in the soil environment. Therefore, how to effectively control the extraction temperature is the focus of this study. OBJECTIVES To select the optimal temperature control method, verify the accuracy of the results, and preliminarily discuss the inevitability of temperature control. METHODS In order to select the optimal temperature control method, the temperature change of the extraction liquid during the extraction using four temperature control methods was recorded: direct ultrasound, adding ice pack, adding ice water and cooling circulating water. In order to verify its reasonableness and validity, the applicable and representative soil active state component analysis standard material was selected as the experimental sample to determine the soil water-soluble fluorine content. To investigate the effect of temperature on the amount of water-soluble fluoride extracted from soil, the pH value of the extracted liquid was determined during the extraction process. RESULTS The results showed that the cooling circulating water temperature control method could effectively control the extraction temperature within 25±2℃. The relative error (8.9%) was significantly less than that of direct ultrasound method (14.1%). The pH value of the extract liquid did not change significantly, and the determination results were stable and reliable. CONCLUSIONS The temperature control method by cooling circulating water has the advantages of low cost, simple operation, accurate and reliable results, suitable for batch sample treatment, and can be widely used in soil environmental fluorine monitoring.

Immune checkpoint inhibitor-associated adverse reactions (irAEs) are a clinical treatment issue that requires additional attention when ICIs have significant survival benefits in patients with advanced hepatocellular carcinoma (HCC). Among them, ICIs-associated myocarditis (ICIAM) is a kind of severe irAE with a high mortality rate (17%–50%). Despite its low incidence (PD1/PD-L1 related: 0.41%–0.8%), ICIAM can significantly disturb the decision making of therapeutic schemes and even the survival outcomes of patients. ICIAM induced by sintilimab has not been reported in any complete clinical studies yet and understanding the clinical characteristics involved may inform better practices for the management. Here, we reported a 78 y/o patient with advanced HCC, who experienced ICIAM induced by sintilimab within a short course from treatment onset and found that adequate baseline examination before the implementation of the therapeutic scheme, regular monitoring of myocardial enzymonram and cardiac imaging were measures for the early detection, while glucocorticoid pulse therapy is still the best choice with timely and sufficient application. Simultaneously, the combination of other immunosuppressants may lead to better results. New-predictive markers and examination methods are still required to facilitate the early detection.

Insect quantity is an important index for determining the degree of damage to plants. The brown planthopper (BPH), Nilaparvata lugens (Stål), is one of the most important rice pests in Asia. Here, we used two genotypes of BPH, a high-fecundity genotype (HFG) and a low-fecundity genotype (LFG), to measure their ecological fitness and to explore possible causes for genotype differentiation by transcriptome sequencing. Our results showed that there were significant differences in body weight, egg hatching rate and honeydew secretion between the HFG and LFG, particularly, the number of eggs laid per female was more significant. Transcriptional analysis showed that a total of 1966 differentially expressed genes (DEGs) were mainly involved in energy metabolism, carbohydrate and lipid synthesis, insect hormone synthesis and fecundity-related pathways. Moreover, we found that the phosphorylation levels of AMPK, AKT and FoxO and the synthesis of ecdysone were different between the two genotypes of BPH. These findings may partially explain the difference in the ecological fitness between HFG and LFG. This study is the first to compare the differences between two genotypes of BPH and to provide transcriptomic evidence to further understand the fecundity of BPH.

Fibrosis in the ventricular system is closely associated with post-hemorrhagic hydrocephalus (PHH). It is characterized by an expansion of the cerebral ventricles due to CSF accumulation following intraventricular hemorrhage (IVH). The activation of transforming growth factor-β1 (TGF-β1) may be involved in thrombin-induced arachnoid fibrosis.

Sarcoplasmic/endoplasmic reticulum calcium ATPase 2 (SERCA2) is a key player in cardiomyocyte calcium handling and also a classic target in the gene therapy for heart failure. SERCA2 expression dramatically increases during cardiomyocyte maturation in the postnatal phase of heart development, which is essential for the heart to acquire its full function in adults. However, whether and how SERCA2 regulates cardiomyocyte maturation remains unclear. Here, we performed Cas9/AAV9-mediated somatic mutagenesis (CASAAV) in mice and achieved cardiomyocyte-specific knockout of Atp2a2, the gene coding SERCA2. Through a cardiac genetic mosaic analysis, we demonstrated the cell-autonomous role of SERCA2 in building key ultrastructures of mature ventricular cardiomyocytes, including transverse-tubules and sarcomeres. SERCA2 also exerts a profound impact on oxidative respiration gene expression and sarcomere isoform switching from Myh7/Tnni1 to Myh6/Tnni3, which are transcriptional hallmarks of cardiomyocyte maturation. Together, this study uncovered a pivotal role of SERCA2 in heart development and provided new insights about SERCA2-based cardiac gene therapy.

Background: Clear cell renal cell carcinoma (ccRCC) is the most frequent and lethal type of kidney cancer. Although differential expression of cyclin-dependent kinase-like 2 (CDKL2) has been reported to be associated with tumor progression in other cancers, its prognostic value, and potential mechanism in patients with ccRCC still remain unknown.Methods: Gene expression analysis was conducted using The Cancer Genome Atlas (TCGA), Gene Expression Omnibus, and International Cancer Genome Consortium databases. Further, clinicopathologic analysis; Kaplan–Meier survival analysis; weighted gene co-expression network analysis; gene set enrichment analysis; gene ontology enrichment; methylation; and immune infiltration analyses were performed using TCGA-kidney renal clear cell carcinoma profiles. CDKL2 translational levels were analyzed using The Human Protein Atlas database.Results:CDKL2 expression was decreased in ccRCC samples retrieved from the four databases. Gender, survival status, histologic grade, clinical stage, TNM classification, and tumor status were closely related to CDKL2 expression. In addition, CDKL2 downregulation was an independent prognostic factor for poor prognosis in multivariate analysis. Enrichment analyses using multiple tests revealed that CDKL2 is not just closely related to immune response but this association is highly correlated as well. Further, we found that CDKL2 expression was significantly correlated with the infiltration levels of T cell CD4 memory resting; monocytes; macrophages M0, M1, and M2; dendritic cells resting; mast cells resting; plasma cells; T cell CD8; and T cell regulatory.Conclusion: This is the first report to study the expression of CDKL2 in ccRCC, wherein we suggest that decreased CDKL2 expression is closely correlated with poor prognosis in ccRCC. We consider that CDKL2 is a novel and potential prognostic biomarker associated with immune infiltrates in ccRCC.

To study the axial compression performance of a steel-reinforced ultra-high-performance concrete-filled square stainless-steel tube (SR-UHPCFSSST), eight specimens were designed with different length-to-diameter ratios and skeleton contents, and axial compression tests and numerical simulations were performed. Damage pattern, ultimate load capacity, and load–displacement curve data of the specimens were obtained. Finite element analysis was performed using ABAQUS software for parameter expansion. The damage mechanisms of the specimens and the influences of various parameters, such as the length-to-diameter ratio, skeleton content, diameter-to-thickness ratio, and concrete strength, on the damage processes and ultimate bearing capacities of the specimens were studied. The results showed that among the components of the test piece under the same axial load, the stress of the built-in steel skeleton was the first to approach its yield stress, and the steel pipe was the first to produce a bulging deformation. The ultimate bearing capacities of the specimens increased with the increase in the skeleton content and concrete strength and decreased with the increase in the length-to-diameter and diameter-to-thickness ratios. Based on the test and numerical simulation results, this paper puts forward a calculation formula of the axial compression bearing capacity of a square-stainless-steel-tube ultra-high-performance-concrete middle-length column with a steel skeleton, which provides a reference for engineering design and for compiling relevant codes.

Abstract Background Clear cell renal cell carcinoma (ccRCC) is a malignancy characterized by metabolic reprogramming. ABAT and ALDH6A1 are metabolic enzymes. In this study, we aim to investigate the associations of ABAT and ALDH6A1 with the malignancy of ccRCC cells. Methods The gene expression levels of ABAT and ALDH6A1 in ccRCC were analyzed from gene expression microarray datasets and RNA sequencing data. Clinical information was analyzed from The Cancer Genome Atlas (TCGA) data. The distributions of ABAT and ALDH6A1 in ccRCC clinical tissues were screened by reverse transcription-quantitative polymerase chain reaction (RT-QPCR) and immunohistochemical assays. The effect of overexpression of ABAT or ALDH6A1 was measured by detecting the cell viability, migration ability, and the ratio of lactate and nicotinamide adenine dinucleotide phosphate (NADPH). Chromatin immunoprecipitation (ChIP) and luciferase reporter assays were carried out to investigate the transcript regulation of HNF4A in ABAT and ALDH6A1. Results Remarkable downregulated ABAT and ALDH6A1 expression levels were observed in ccRCC patients and low expression of ABAT and ALDH6A1 was correlated with poor survival. Overexpression of ABAT or ALDH6A1 significantly attenuated cell proliferation and migration, and impaired lactate production. In ABAT increased ccRCC cells, the ratio of NADPH/NADP+ was reduced. Finally, we demonstrated that ABAT and ALDH6A1 were directly regulated by a tumor suppressor, HNF4A. Conclusions These observations identified HNF4A-regulated low-expressed ABAT and ALDH6A1 as promising diagnostic and prognostic biomarkers for ccRCC.

The ocean is a significant strategic resource, and the insufficient development and use of the ocean, as well as the increase in attention to the ocean, have led to the development of underwater robot technology. The need for in-depth marine exploration and the limitations of one underwater robot has sparked research on the underwater multi-robot system. In the underwater environment, weak communication is caused by the shielding effect of the seawater medium, which makes multi-robot systems difficult to form. Hence, we combine the robot’s vision system with the leader-follower structure to form a vision-based underwater formation method, in which the visual solution serves as the control system’s feedback. By using three small underwater robot platforms, the proposed method is proved to be effective and practicable through underwater formation experiments. Furthermore, the coordination period and error of the control system are analyzed.

With the rapid development of the Internet, more and more users expressed their views on the Internet. Therefore, the big data of texts are generated on the Internet. In the era of big data, mining the sentiment tendencies contained in massive texts on the Internet through natural language processing technology has become an important way of public opinion supervision. In this paper, the sensitive information topics-based sentiment analysis method for big data is proposed. This method integrates topic semantic information into text representation through a neural network model. The attention mechanism is introduced into the neural network, and context-aware vector is introduced to calculate the weight of each word. In addition, in order to make the model more adaptable, the method of sentiment dictionary tagging is used to obtain the training data. The experimental results show that the proposed model can effectively improve the accuracy of sentiment analysis results.

With the rapid development of the Internet, the amount of data has grown exponentially. On the one hand, the accumulation of big data provides the basic support for artificial intelligence. On the other hand, in the face of such huge data information, how to extract the knowledge of interest from it has become a matter of general concern. Topic tracking can help people to explore the process of topic development from the huge and complex network texts information. By effectively organizing large-scale news documents, a method for the evolution of news topics over time is proposed in this paper to realize the tracking and evolution of topics in the news text set. First, the LDA (latent Dirichlet allocation) model is used to extract topics from news texts and the Gibbs Sampling method is used to speculate parameters. The topic mining using the K-means method is compared to highlight the advantages of using LDA for topic discovery. Second, the improved single-pass algorithm is used to track news topics. The JS (Jensen-Shannon) divergence is used to measure the topic similarity, and the time decay function is introduced to improve the similarity between topics with the similar time. Finally, the strength of the news topic and the content change of the topic in different time windows are analyzed. The experiments show that the proposed method can effectively detect and track the topic and clearly reflect the trend of topic evolution.

Developing new coating modification technology of aluminum nitride (AlN) powder for higher hydrolysis resistance is the key to prepare high-performance AlN ceramic substrate with water-based wet process in the future. In the this paper, The poly(vinyl pyrrolidone)-b-poly(Styrene/Itaconic anhydride) (PVP-b-P(St/ITA))block copolymer with PVP as the independent chain segment was designed and synthesized through reversible addition fragmentation chain transfer (RAFT) polymerization, which was used for the study on coating modification, hydrolysis resistance, and dispersion performance of AIN powder. The study results show that, when using PVP macromolecular chain transfer agent (PVP-CTA) for the RAFT chain extension and polymerization in St/ITA binary system, the molecular weight increases linearly and the molecular weight distribution tends to decrease with the monomer conversion rate, which is in line with the activity-controlled characteristics of RAFT polymerization. The copolymer PVP-b-P(St/ITA) was used to for surface modification treatment of submicron AlN powder to generate esterification reaction, which was absorbed and bound to the powder surface. Hydrolysis resistance and dispersion experiments were conducted for modified powder, and the crystal phase and micro structure of modified powder were analyzed and observed through XRD, SEM, and TEM. It was found that copolymer modification had no effect on the powder crystal phase. A 8–21 nm passivation layer was coated on the surface, which can exist stably for 10 h in 60 °C water. Zeta potential and laser particle analyzer tests showed that modified powder featured excellent water-based slurry dispersion performance, and certain self-dispersing characteristics. The highest Zeta potential appeared in pH 6~7, and the particle granularity was distributed uniformly with the median particle diameter of 875 nm. The powder hydrolysis resistance and dispersion performance are significantly improved.