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Abstract Clear cell renal cell carcinoma (ccRCC) demonstrates enhanced glycolysis, critically contributing to tumor development. Programmed death-ligand 1 (PD-L1) aids tumor cells in evading T-cell-mediated immune surveillance. Yet, the specific mechanism by which glycolysis influences PD-L1 expression in ccRCC is not fully understood. Our research identified that the glycolysis-related gene (GRG) HK3 has a unique correlation with PD-L1 expression. HK3 has been identified as a key regulator of O-GlcNAcylation in ccRCC. O-GlcNAcylation exists on the serine 900 (Ser900) site of EP300 and can enhance its stability and oncogenic activity by preventing ubiquitination. Stably expressed EP300 works together with TFAP2A as a co-transcription factor to promote PD-L1 transcription and as an acetyltransferase to stabilize PD-L1 protein. Furthermore, ccRCC exhibits interactive dynamics with tumor-associated macrophages (TAMs). The uridine 5′-diphospho-N-acetylglucosamine (UDP-GlcNAc), which serves as a critical substrate for the O-GlcNAcylation process, facilitates TAMs polarization. In ccRCC cells, HK3 expression is influenced by IL-10 secreted by M2 TAMs. Our study elucidates that HK3-mediated O-GlcNAcylation of EP300 is involved in tumor immune evasion. This finding suggests potential strategies to enhance the efficacy of immune checkpoint blockade therapy.

PurposeThe aim of this study is to compare mean platelet volume/platelet count ratio (PVPR) and other indicators’ predictive abilities. Simultaneously, a new nomogram for predicting recurrence-free survival (RFS) after gastrointestinal stromal tumors (GISTs) R0 resection was developed.MethodsFrom January 2010 to July 2019, 295 patients with GIST who were operated on at Harbin Medical University Cancer Hospital were retrospectively reviewed. With a 4-year RFS as the end point, using the Kaplan–Meier methods and log rank test, and then conducting Cox regression analysis, we compared and identified meaningful indicators for predicting prognosis. Finally, a nomogram was developed and validated using calibration curves.ResultsThe receiver operating characteristic curve indicated that a cutoff point of 0.044 was the ideal threshold for PVPR, and patients were divided into a high-PVPR group (≤0.044) and a low-PVPR group (>0.044). Kaplan–Meier curves suggested that PVPR>0.044 had obvious associations with better RFS (p < 0.001). In accordance with multivariate analysis, PVPR (>0.044 vs. ≤0.044) (p = 0.005), National Institutes of Health (NIH) risk category (p < 0.001), and Ki-67 (p = 0.005) were the independent prognostic indicators of RFS. Tumor size, gastrointestinal bleeding, mitotic index, NIH risk category, CD34, and Ki-67 all exhibited an obvious correlation with PVPR (all p < 0.05). The nomogram’s probability of concordance was 0.823, indicating that the nomogram predictions were well calibrated.ConclusionIn GISTs, RFS can be independently predicted by PVPR. Patients with higher PVPR have better RFS. The nomogram including PVPR could be used to assist clinical treatment decision-making.

Abstract Objective The purpose of the study is to construct meaningful nomogram models according to the independent prognostic factor for metastatic pancreatic cancer receiving chemotherapy. Methods This study is retrospective and consecutively included 143 patients from January 2013 to June 2021. The receiver operating characteristic (ROC) curve with the area under the curve (AUC) is utilized to determine the optimal cut‐off value. The Kaplan–Meier survival analysis, univariate and multivariable Cox regression analysis are exploited to identify the correlation of inflammatory biomarkers and clinicopathological features with survival. R software are run to construct nomograms based on independent risk factors to visualize survival. Nomogram model is examined using calibration curve and decision curve analysis (DCA). Results The best cut‐off values of 966.71, 0.257, and 2.54 for the systemic immunological inflammation index (SII), monocyte‐to‐lymphocyte ratio (MLR), and neutrophil‐to‐lymphocyte ratio (NLR) were obtained by ROC analysis. Cox proportional‐hazards model revealed that baseline SII, history of drinking and metastasis sites were independent prognostic indices for survival. We established prognostic nomograms for primary endpoints of this study. The nomograms' predictive potential and clinical efficacy have been evaluated by calibration curves and DCA. Conclusion We constructed nomograms based on independent prognostic factors, these models have promising applications in clinical practice to assist clinicians in personalizing the management of patients.

PurposeThe retrospective study reviewed the clinical and radiological outcomes of patients treated with radiocapitellar joint plasty.Methods10 children with missed Monteggia fracture (MMF) were reviewed. The average time from injury to operation was 20 months. The average age of children who underwent the operation was 10.5 years. 6 flat and 4 domed radial heads were included. 7 type I and 3 type III MMF were identified based on the Bado classification. All children with MMF were treated by open radial head reduction with radiocapitellar joint plasty and ulnar osteotomy (UO).ResultsThe average union time was 4.9 ± 2.6 months. The average osteotomy angle to reduce the radial head was 15.7 ± 3.5°, and the average lengthening of the ulna was 8.2 ± 3.2 mm. The average preoperative flexion range of motion was 110.5 ± 9.1°, and the postoperative flexion range of motion was 138.8 ± 15.1° (p 0.05). The average preoperative supination range of motion was 68.3 ± 9.7°, and the postoperative supination range of motion was 80.1 ± 7.8° (p

The improvement of information sciences promotes the utilization of data for process monitoring. As the core of modern automation, time-stamped signals are used to estimate the system state and construct the data-driven model. Many recent studies claimed that the effectiveness of data-driven methods relies greatly on data quality. Considering the complexity of the operating environment, process data will inevitably be affected. This poses big challenges to estimating faults from data and delivers feasible strategies for electrical systems of industry. This paper addresses the missing data problem commonly in traction systems by designing a martingale posterior-based data generation method for the state-space model. Then, a data-driven approach is proposed for fault detection and estimation via the subspace identification technique. It is a general scheme using the Bayesian framework, in which the Dirichlet process plays a crucial role. The data-driven method is applied to a pilot-scale traction motor platform. Experimental results show that the method has good estimation performance.

Abstract Background and purpose As a crucial diagnostic and prognostic biomarker, telomerase reverse transcriptase (TERT) promoter mutation holds immense significance for personalized treatment of patients with glioblastoma (GBM). In this study, we developed a radiomics nomogram to determine the TERT promoter mutation status and assessed its prognostic efficacy in GBM patients. Methods The study retrospectively included 145 GBM patients. A comprehensive set of 3736 radiomics features was extracted from preoperative magnetic resonance imaging, including T2‐weighted imaging, T1‐weighted imaging (T1WI), contrast‐enhanced T1WI, and fluid‐attenuated inversion recovery. The construction of the radiomics model was based on integrating the radiomics signature (rad‐score)with clinical features. Receiver‐operating characteristic curve analysis was employed to evaluate the discriminative ability of the prediction model, and the risk score was used to stratify patient outcomes. Results The least absolute shrinkage and selection operator classifier identified 10 robust features for constructing the prediction model, and the radiomics nomogram exhibited excellent performance in predicting TERT promoter mutation status, with area under the curve values of.906 (95% confidence interval [CI]:.850–.963) and.899 (95% CI:.708–.966) in the training and validation sets, respectively. The clinical utility of the radiomics nomogram is further supported by calibration curve and decision curve analyses. Additionally, the radiomics nomogram effectively stratified GBM patients with significantly different prognoses (HR = 1.767, p = .019). Conclusion The radiomics nomogram holds promise as a modality for evaluating TERT promoter mutations and prognostic outcomes in patients with GBM.

Multilineage-differentiating stress-enduring (Muse) cells are a type of pluripotent cell with unique characteristics such as non-tumorigenic and pluripotent differentiation ability. After homing, Muse cells spontaneously differentiate into tissue component cells and supplement damaged/lost cells to participate in tissue repair. Importantly, Muse cells can survive in injured tissue for an extended period, stabilizing and promoting tissue repair. In addition, it has been confirmed that injection of exogenous Muse cells exerts anti-inflammatory, anti-apoptosis, anti-fibrosis, immunomodulatory, and paracrine protective effects in vivo. The discovery of Muse cells is an important breakthrough in the field of regenerative medicine. The article provides a comprehensive review of the characteristics, sources, and potential mechanisms of Muse cells for tissue repair and regeneration. This review serves as a foundation for the further utilization of Muse cells as a key clinical tool in regenerative medicine.

Before the construction of a bridge begins, workers arrange the necessary parts and then cut and process them. The quality of the cutting layout directly affects the material utilization rate and the efficiency of the subsequent processes. During bridge construction, an intelligent part layout can improve work efficiency, save time, and reduce the labor intensity and production costs for the company. In this study, we studied a layout optimization algorithm, focusing on rectangular parts in the material preparation process. A mathematical model for the rectangular layout problem was constructed, and a hybrid genetic whale optimization algorithm is proposed that is a combination of the whale optimization algorithm and the genetic algorithm. Based on the “one size fits all” layout strategy, the materials are divided into strips, which are further divided into stacks, serving as the positioning strategy to determine the positional relationships of the parts. Test cases and actual engineering data were used to compare the layouts generated using different algorithms. The results show that the genetic whale algorithm proposed in this paper results in a high utilization rate and is highly effective.

Abstract Background Cuproptosis is a regulated cell death form associated with tumor progression, clinical outcomes, and immune response. However, the role of cuproptosis in pancreatic adenocarcinoma (PAAD) remains unclear. This study aims to investigate the implications of cuproptosis-related genes (CRGs) in PAAD by integrated bioinformatic methods and clinical validation. Methods Gene expression data and clinical information were downloaded from UCSC Xena platform. We analyzed the expression, mutation, methylation, and correlations of CRGs in PAAD. Then, based on the expression profiles of CRGs, patients were divided into 3 groups by consensus clustering algorithm. Dihydrolipoamide acetyltransferase (DLAT) was chosen for further exploration, including prognostic analysis, co-expression analysis, functional enrichment analysis, and immune landscape analysis. The DLAT-based risk model was established by Cox and LASSO regression analysis in the training cohort, and then verified in the validation cohort. Quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) assays were performed to examine the expression levels of DLAT in vitro and in vivo, respectively. Results Most CRGs were highly expressed in PAAD. Among these genes, increased DLAT could serve as an independent risk factor for survival. Co-expression network and functional enrichment analysis indicated that DLAT was engaged in multiple tumor-related pathways. Moreover, DLAT expression was positively correlated with diverse immunological characteristics, such as immune cell infiltration, cancer-immunity cycle, immunotherapy-predicted pathways, and inhibitory immune checkpoints. Submap analysis demonstrated that DLAT-high patients were more responsive to immunotherapeutic agents. Notably, the DLAT-based risk score model possessed high accuracy in predicting prognosis. Finally, the upregulated expression of DLAT was verified by RT-qPCR and IHC assays. Conclusions We developed a DLAT-based model to predict patients’ clinical outcomes and demonstrated that DLAT was a promising prognostic and immunological biomarker in PAAD, thereby providing a new possibility for tumor therapy.

Background: Clear cell renal cell carcinoma (ccRCC) stands as the prevailing variant kidney cancer in humans. Unfortunately, patients with disseminated RCC at diagnosis often have a diminished prognosis. Rapid tumor growth necessitates efficient blood supply for oxygen and nutrients, involving the circulation of blood from vessels to tumor tissues, facilitating tumor cell entry into the extracellular matrix. Vasculogenic mimicry (VM) significantly contributes to tumor growth and metastasis. Within this investigation, we identified vasculogenic mimicry-related genes (VMRGs) by analyzing data from 607 cases of kidney renal clear cell carcinoma (KIRC) in The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/). These findings offer insights into ccRCC progression and metastasis.Method: We identified VMRGs-related subtypes using consistent clustering methods. The signature of the VMRGs was created using univariate Cox regression and LASSO Cox regression analyses. To evaluate differences in immune cell infiltration, we employed ssGSEA. Afterwards, we created an innovative risk assessment model, known as the VM index, along with a nomogram to forecast the prognosis of ccRCC. Additionally, we verified the expression of an important gene related to VM, peroxiredoxin 2 (PRDX2), in tissue samples. Furthermore, we assessed the sensitivity to drugs in various groups by utilizing the pRRophetic R package.Results: Significant predictors of survival rates in both high- and low-risk groups of KIRC patients were identified as VMRGs. The independent prognostic factors for RCC were confirmed by both univariate and multivariate Cox regression analyses, validating VMRG risk signatures. Differences were observed in drug sensitivity, immune checkpoint expression, and responses to immune therapy between patients classified into high- and low-VMRG-risk groups. Our nomograms consistently demonstrated precise predictive capabilities. Finally, we experimentally verified PRDX2 expression levels and their impact on prognosis.Conclusion: The signature predicts patient prognosis and therapy response, laying the groundwork for future clinical strategies in treating ccRCC patients.

Abstract The lack of efficacious treatments for clear cell renal cell carcinoma (ccRCC) has led to a poor 5-year survival rate. Here, we found that the expression of ADAM metallopeptidase with thrombospondin type 1 motif 9 (ADAMTS9) antisense RNA 1 (ADAMTS9-AS1) is commonly decreased in ccRCC tissues. Decreased ADAMTS9-AS1 is associated with advanced stages and poor prognosis in ccRCC patients. Additionally, we found that promoter hypermethylation contributes to the suppression of ADAMTS9-AS1 expression in ccRCC that contained relatively low levels of ADAMTS9-AS1. Further functional studies demonstrated that ADAMTS9-AS1 inhibits cell growth and drug resistance through enhancing mRNA stability of ADAMTS9 in ccRCC. Mechanistically, ADAMTS9-AS1 directly bound to Human Antigen R (HuR). Then, the ADAMTS9-AS1-HuR complex was guided to the ADAMTS9 3’UTR through specific RNA–RNA interaction. Moreover, ADAMTS9-AS1 expression is positively correlated with ADAMTS9 expression in ccRCC tissues. In summary, our data not only highlight the important role of ADAMTS9-AS1 in ccRCC progression, but also reveal new regulatory mechanisms of ADAMTS9, which provides important insights into novel treatment strategies targeting ADAMTS9-AS1-HuR- ADAMTS9 axis in ccRCC.

Extravehicular activity (EVA) is a key point and a difficult point for manned spaceflight tasks, as well as an inevitable trend in the development of the manned spaceflight industry. Equipment maintenance, load installation, and extravehicular routing inspection via EVA on the track are necessary to guarantee the safety and reliability of the long-term in-orbit operation of the China Space Station. In this paper, a comprehensive analysis was conducted on the features of multiple tasks, diverse working modes, and strong systematic coupling during the EVA of the China Space Station (CSS). On this basis, the design, implementation technologies’ development, and in-orbit performance evaluation during EVA were expounded. In the space station system, an extravehicular reliability verification and evaluation system suitable for the requirement for EVA under the conditions of China’s multi-mission, multi-module combination, and repairable spacecraft was constructed. Finally, the in-orbit EVA implementation of the China Space Station since the launch of the core module to the present was summarized, and the subsequent application of the extravehicular technologies in manned lunar landing projects and optical modules was anticipated.

Abstract Aims Previous prediction studies for 30 day readmission in patients with heart failure were built mainly based on electronic medical records and rarely involved patient‐reported outcomes. This study aims to develop and validate a nomogram including patient‐reported outcomes to predict the possibility of 30 day all‐cause readmission in older patients with heart failure and to explore the value of patient‐reported outcomes in prediction model. Methods and results This was a prospective cohort study. The nomogram was developed and internally validated by Logistic regression analysis based on 381 patients in training group from March to December 2019. The nomogram was externally validated based on 170 patients from July to October 2020. Receiver operating characteristic curves, calibration plots and decision‐curve analysis were used to evaluate the performance of the nomogram. A total of 381 patients' complete data were analysed in the training group and 170 patients were enrolled in the external validation group. In the training group, 14.4% (n = 55) patients were readmitted to hospitals within 30 days of discharge and 15.9% (n = 27) patients were readmitted in the external validation group. The nomogram included six factors: history of surgery, changing the type of medicine by oneself, information acquisition ability, subjective support, depression level, quality of life, all of which were significantly associated with 30 day readmission in older patients with heart failure. The areas under the receiver operating characteristic curves of nomogram were 0.949 (95% CI: 0.925, 0.973, sensitivity: 0.873, specificity: 0.883) and 0.804 (95% CI: 0.691, 0.917, sensitivity: 0.778, specificity: 0.832) respectively in the training and external validation groups, which indicated that the nomogram had better discrimination ability. The calibration plots demonstrated favourable coordination between predictive probability of 30 day readmission and observed probability. Decision‐curve analysis showed that the net benefit of the nomogram was better between threshold probabilities of 0–85%. Conclusions A novel and easy‐to‐use nomogram is constructed and demonstrated which emphasizes the important role of patient‐reported outcomes in predicting studies. The performance of the nomogram drops in the external validation cohort and the nomogram must be validated in a wide prospective cohort of HF patients before its clinical relevance can be demonstrated. All these findings in this study can assist professionals in identifying the needs of HF patients so as to reduce 30 day readmission.

Background: The delivery channels and approaches related to cardiac rehabilitation (CR), such as eHealth, mHealth, and telehealth, are evolving. Several studies have identified their effects on patients with coronary heart disease, although no studies have focused on all the approaches collectively. Methods: Randomized controlled trials have investigated lipid profiles, through systolic blood pressure (SBP), diastolic blood pressure (DBP), and body mass index (BMI). Stata software was used for analysis, while Egger’s linear regression test and Begg’s funnel plot were also applied. Results: Technology-based home CR revealed significantly lower total cholesterol (TC) levels (standardized mean difference (SMD) = –0.19; 95% confidence interval [CI]: [–0.27, –0.11]); triglyceride (TG) levels (SMD = –0.26; 95% CI: [–0.35, 0.17]); low-density lipoprotein (LDL) levels (SMD = –0.18; 95% CI: [ –0.25, –0.11]); SBP (SMD = –0.26; 95% CI: [–0.33, –0.19]); DBP (SMD = –0.24; 95% CI: [–0.32, –0.16]); BMI (SMD = –0.12; 95% CI: [–0.18, –0.05]), and improved high-density lipoprotein (HDL) levels (SMD = 0.22; 95% CI: [0.14, 0.31]). Conclusions: Technology-based home CR can be used to lower TC, TG, and LDL levels, alongside the BMI, SBP, and DBP indexes, while also raising HDL levels; thus, its use should be widely promoted.

Abstract Background Online health care consultation has been widely adopted to supplement traditional face-to-face patient-doctor interactions. Patients benefit from this new modality of consultation because it allows for time flexibility by eliminating the distance barrier. However, unlike the traditional face-to-face approach, the success of online consultation heavily relies on the accuracy of patient-reported conditions and symptoms. The asynchronous interaction pattern further requires clear and effective patient self-description to avoid lengthy conversation, facilitating timely support for patients. Method Inspired by the observation that doctors talk to patients with the goal of eliciting information to reduce uncertainty about patients' conditions, we proposed and evaluated a machine learning-based computational model towards this goal. Key components of the model include (1) how a doctor diagnoses (predicts) a disease given natural language description of a patient's conditions, (2) how to measure if the patient's description is incomplete or more information is needed from the patient; and (3) given the patient's current description, what further information is needed to help a doctor reach a diagnosis decision. This model makes it possible for an online consultation system to immediately prompt a patient to provide more information if it senses that the current description is insufficient. Results We evaluated the proposed method by using classification-based metrics (accuracy, macro-averaged F-score, area under the receiver operating characteristics curve, and Matthews correlation coefficient) and an uncertainty-based metric (entropy) on three Chinese online consultation corpora. When there was one consultation round, our method delivered better disease prediction performance than the baseline method (No Prompts) and two heuristic methods (Uncertainty-based Prompts and Certainty-based Prompts). Conclusion The disease prediction performance correlated with uncertainty of patients’ self-described symptoms and conditions. However, heuristic solutions ignored the context to decrease large amounts of uncertainty, which did not improve the prediction performance. By elaborate design, a machine-learning algorithm can learn the inner connection between a patient’s self-description and the specific information doctors need from doctor-patient conversations to provide prompts, which can enrich the information in patient self-description for a better performance in disease prediction, thereby achieving online consultation with fewer rounds of doctor-patient conversation.

Abstract Previous studies have investigated whether tumor-associated macrophages (TAMs) play tumorigenic and immunosuppressive roles to encourage cancer development, but the role of TAMs in regulating vasculogenic mimicry (VM) in clear-cell renal cell carcinoma (ccRCC) cells has not been completely clarified. We conducted immunostaining of the tumor-associated macrophage biomarkers CD68/CD163 and double staining for PAS/CD31 in ccRCC human specimens to find that higher TAM infiltration was positively correlated with VM formation. Then we demonstrated that TAM-derived exosomes downregulate TIMP2 expression in RCC cells to promote VM and invasion by shuttling miR-193a-5p. Mechanistic analysis indicated that HIF-1α upregulation in macrophages could transcriptionally increase miR-193a-5p expression. Exosome-shuttled miR-193a-5p then targeted the 3′ untranslated region (UTR) of TIMP2 mRNA to suppress its translation. A preclinical study using an in vivo orthotopic xenograft model of ccRCC in mice substantiated that TAM-derived exosomes enhance VM and enable tumor progression, which confirmed our in vitro data. Suppressing TAM-derived exosomal miR-193a-5p successfully inhibited tumor progression and metastasis. Overall, miR-193a-5p from TAM-derived exosomes downregulates the TIMP2 gene to facilitate the development of RCC, which provides a novel perspective for developing therapeutic strategies for RCC.

Abstract Background Natural language processing (NLP) tasks in the health domain often deal with limited amount of labeled data due to high annotation costs and naturally rare observations. To compensate for the lack of training data, health NLP researchers often have to leverage knowledge and resources external to a task at hand. Recently, pretrained large-scale language models such as the Bidirectional Encoder Representations from Transformers (BERT) have been proven to be a powerful way of learning rich linguistic knowledge from massive unlabeled text and transferring that knowledge to downstream tasks. However, previous downstream tasks often used training data at such a large scale that is unlikely to obtain in the health domain. In this work, we aim to study whether BERT can still benefit downstream tasks when training data are relatively small in the context of health NLP. Method We conducted a learning curve analysis to study the behavior of BERT and baseline models as training data size increases. We observed the classification performance of these models on two disease diagnosis data sets, where some diseases are naturally rare and have very limited observations (fewer than 2 out of 10,000). The baselines included commonly used text classification models such as sparse and dense bag-of-words models, long short-term memory networks, and their variants that leveraged external knowledge. To obtain learning curves, we incremented the amount of training examples per disease from small to large, and measured the classification performance in macro-averaged $$F_{1}$$ F 1 score. Results On the task of classifying all diseases, the learning curves of BERT were consistently above all baselines, significantly outperforming them across the spectrum of training data sizes. But under extreme situations where only one or two training documents per disease were available, BERT was outperformed by linear classifiers with carefully engineered bag-of-words features. Conclusion As long as the amount of training documents is not extremely few, fine-tuning a pretrained BERT model is a highly effective approach to health NLP tasks like disease classification. However, in extreme cases where each class has only one or two training documents and no more will be available, simple linear models using bag-of-words features shall be considered.

A major complication of a joint replacement is prosthesis loosening caused by inflammatory osteolysis, leading to the revision of the operation. This is due to the abnormal activation of osteoclast differentiation and function caused by periprosthetic infection. Therefore, targeting abnormally activated osteoclasts is still effective for treating osteolytic inflammatory diseases. CDZ173 is a selective PI3K inhibitor widely used in autoimmune-related diseases and inflammatory diseases and is currently under clinical development. However, the role and mechanism of CDZ173 in osteoclast-related bone metabolism remain unclear. The possibility for treating aseptic prosthesis loosening brought on by inflammatory osteolysis illness can be assessed using an LPS-induced mouse cranial calcium osteolysis model. In this study, we report for the first time that CDZ173 has a protective effect on LPS-induced osteolysis. The data show that this protective effect is due to CDZ173 inhibiting the activation of osteoclasts in vivo. Meanwhile, our result demonstrated that CDZ173 had a significant inhibitory effect on RANKL-induced osteoclasts. Furthermore, using the hydroxyapatite resorption pit assay and podosol actin belt staining, respectively, the inhibitory impact of CDZ173 on bone resorption and osteoclast fusion of pre-OC was determined. In addition, staining with alkaline phosphatase (ALP) and alizarin red (AR) revealed that CDZ173 had no effect on osteoblast development in vitro. Lastly, CDZ173 inhibited the differentiation and function of osteoclasts by weakening the signal axis of PI3K-AKT/MAPK-NFATc1 in osteoclasts. In conclusion, our results highlight the potential pharmacological role of CDZ173 in preventing osteoclast-mediated inflammatory osteolysis and its potential clinical application.

Abstract Background To report on the technique and results of parallel endplate osteotomy (PEO) for severe rigid spinal deformity. Methods We retrospectively reviewed the clinical data of 36 patients with severe rigid spinal deformities who underwent PEO between July 2016 and December 2018 and who were followed up for at least 24 months. Results Following PEO, the kyphosis and scoliosis correction rates reached 77.4 ± 14.0% and 72.2 ± 18.2%, respectively. The median intraoperative estimated blood loss was 1500 mL and the median operative time was 6.8 h. The SF-36 scores of physical function, role-physical, bodily pain, general health, vitality, social function, role-emotional and mental health changed from 62 ± 28, 51 ± 26, 49 ± 29, 35 ± 30, 53 ± 28, 45 ± 30, 32 ± 34 and 54 ± 18 at baseline to 81 ± 16, 66 ± 41, 72 ± 40, 64 ± 44, 75 ± 25, 71 ± 46, 66 ± 34 and 76 ± 28 at 12 months postoperatively, 82 ± 32, 67 ± 42, 81 ± 30, 71 ± 41, 80 ± 30, 74 ± 36, 68 ± 35 and 85 ± 33 at 18 months postoperatively, and 86 ± 21, 83 ± 33, 88 ± 26, 79 ± 39, 86 ± 36, 86 ± 48, 80 ± 47 and 91 ± 39 at 24 months postoperatively, respectively. Conclusions PEO is an effective technique for successful correction of spinal deformities. At the two-year follow-up visit, all patients achieved better clinical results based on the SF-36 scores.

Background: Cardiac rehabilitation (CR) is a multidisciplinary medical program. Most studies have emphasized the effect of exercise-based CR in lowering lipid levels; however, the effect of CR as a comprehensive program on lipid levels remains unclear. Methods: Electronic database were searched up to 2022. Randomized controlled trials with lipid profile indicators were included. Standardized mean differences (SMDs) and 95% CIs were used to evaluate the effect size. Begg’s funnel plot and Egger’s linear regression test were used to assess publication bias. Results: CR remarkably reduced low-density lipoprotein cholesterol (LDL-C) levels (SMD = –0.23; 95%CI: [–0.38, –0.08]; P < 0.001), triglyceride (TG) levels (SMD = –0.17; 95%CI: [–0.28, –0.06]; P < 0.001), and total cholesterol (TC) levels (SMD = –0.30; 95%CI: [–0.43, –0.16]; P < 0.001) and increased high-density lipoprotein cholesterol (HDL-C) levels (SMD = 0.19; 95%CI: [0.10, 0.29]; P < 0.001). Conclusions: CR reduce TC, TG, and LDL-C levels while improving HDL-C levels. CR should be promoted and more trials should be conducted for long-term CR.

This paper uses the EBM model to measure the carbon emission efficiency of the logistics industry in 30 provinces in China from 2010 to 2019 and analyzes its spatial and temporal evolution characteristics using ARCGIS visualization. On this basis, the structural characteristics of the spatial correlation network of carbon emission efficiency of the logistics industry in China and its influencing factors are explored and analyzed by using the social network analysis method and the quadratic distribution method (QAP). The study shows that: 1) The national average logistics industry carbon emission efficiency increased from 2010 to 2019, and the spatial logistics industry carbon emission efficiency shows the characteristics of East > Central > Northeast > West, and most of the provinces in China are still in the middle and low logistics industry carbon emission efficiency zone. 2) The carbon emission efficiency of logistics industry in 30 provinces in China has formed a stable spatial correlation network, and there is an obvious spatial spillover relationship. However, the structure of the spatial association network is loose, and there are obvious gaps in the status of each province in the spatial association network. The provinces in the eastern region are at the core of the spatial correlation network, while the provinces in the northeast and west are at the periphery of the spatial correlation network. 3) The reduction of geographical distance between provinces, the greater the differences in logistics development level, logistics energy intensity and logistics environmental protection level, and the higher the similarity of logistics informatization level, the more it can promote the formation of spatial correlation network.

Diazinon is one of the most widely used organophosphate insecticides, one that is frequently detected in the environment. In this study, a diazinon-degrading bacterium, DI-6, previously isolated from diazinon-contaminated soil in China has been subsequently identified as Sphingobium sp. on the basis of its physiological and biochemical characteristics, as well as by virtue of a comparative analysis of 16S rRNA gene sequences. This strain is capable of using diazinon as its sole carbon source for growth and was able to degrade 91.8% of 100 mg L–1 diazinon over a 60-h interval. During the degradation of diazinon, the following seven metabolites were captured and identified by gas chromatography/mass spectrometry (GC–MS) analysis: diazoxon, diazinon aldehyde, isopropenyl derivative of diazinon, hydroxyethyl derivative of diazinon, diazinon methyl ketone, O-[2-(1-hydroxyethyl)-6-methylpyrimidin-4-yl] O-methyl O-hydrogen phosphorothioate, and O-(6-methyl pyrimidin-4-yl) O,O-dihydrogen phosphorothioate. Based on these metabolites, a novel microbial biodegradation pathway of diazinon by Sphingobium sp. DI-6 is proposed. This research provides potentially useful information for the application of the DI-6 strain in bioremediation of diazinon-contaminated environments.

Introduction Living with heart failure (HF), is a shared journey and arduous work for patients and their informal family caregivers. Given the key role and limited evidence of dyad illness management in improving dyad health in the context of HF, we developed a customisable, relationship focused, family online dynamic disease management programme—FOCUS programme—to improve dyad health for HF patients and their informal caregivers in China.Methods and analysis Based on the Theory of Dyadic Illness Management and the Systemic Transactional Model of Stress and Coping, the family customised online FOCUS programme has five modules: (1) family participatory; (2) open communication; (3) coping effectiveness; (4) uncertainty reduction and 5) shared dyad life stories. HF family dyads will be recruited in the cardiology wards of four university-affiliated hospitals in China. The dyads (N=142) will be randomly allocated to the intervention group that will receive the family customised online FOCUS programme, and the attention control group that will not receive elements of the FOCUS programme. Dyadic coping, HF somatic perception, self-care, anxiety and depression for patients and family caregivers and all-cause mortality and hospital admission for patients will be measured at baseline, 4 weeks (after the discharge, T1), 12 weeks (after the discharge, T2) and 24 weeks (after the discharge, T3). Statistical analysis will be performed using SPSS V. 22.0 software.Ethics and dissemination The study protocol was approved by the ethics committees of Tianjin Medical University (Reference number TMUHEC2019002) that covers all the centres enrolled in this study. The findings of this study will be published in scientific journals and will be presented at scientific conferences.Trial registration number ChiCTR2100053168.

BackgroundPoor prognosis of kidney renal clear cell carcinoma (KIRC) is often related to angiogenesis. The lncRNAs that regulate angiogenesis could also affect the prognosis of KIRC. It is meaningful for us to use lncRNAs related to angiogenesis to construct a generic, individualized prognostic signature for patients with KIRC.MethodsWe identified eight angiogenesis-associated genes (AAGs) by differential expression analysis and univariate Cox regression from The Cancer Genome Atlas dataset, including 537 KIRC samples and 72 normal samples. In total, 23 prognostic lncRNAs were screened out after Pearson correlation analysis and univariate Cox regression analysis. Then, we performed least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression to establish a four-AAG-related lncRNA prognostic signature.ResultsThe risk score was calculated for each KIRC patients by using a four-AAG-related lncRNA prognostic signature. We divided the KIRC patients into high- and low-risk groups by the median of the risk score. It was confirmed that the AAG-related lncRNA prognostic signature has good prognostic value for KIRC patients by time-dependent receiver operating characteristic and Kaplan–Meier survival analysis. We identified 3,399 differentially expressed genes between the high- and low-risk groups and performed their functional enrichment analyses. The AAG-related lncRNA prognostic signature was an independent prognostic predictor for KIRC patients and was used to perform a combined nomogram. We reevaluated them in terms of survival, clinic characteristics, tumor-infiltrating immune cells and tumor mutation burden.ConclusionOur research indicates that the AAG-related lncRNA prognostic signature is a promising and potential independent prognostic indicator for KIRC patients. Then, it could offer new insights into the prognosis assessment and potential treatment strategies of KIRC patients.

Abstract Cataract surgery is the most common intraocular procedure. To decrease postsurgical inflammation, prevent infection and reduce the incidence of secondary cataract, we built a temperature-sensitive drug delivery system carrying dexamethasone, moxifloxacin and genistein nanostructured lipid carrier (GenNLC) modified by mPEG-PLA based on F127/F68 as hydrogel. Characterizations and release profiles of the drug delivery system were studied. In vitro functions were detected by CCK-8 test, immunofluorescence, wound-healing assay, real time-PCR and western blotting. The size of GenNLCs was 39.47 ± 0.69 nm in average with surface charges of − 4.32 ± 0.84 mV. The hydrogel gelation temperature and time were 32 °C, 20 s with a viscosity, hardness, adhesiveness and stringiness of 6.135 Pa.s, 54.0 g, 22.0 g, and 3.24 mm, respectively. Transmittance of the gel-release medium was above 90% (93.44 ± 0.33% to 100%) at range of 430 nm to 800 nm. Moxifloxacin released completely within 10 days. Fifty percent of dexamethasone released at a constant rate in the first week, and then released sustainably with a tapering down rate until day 30. Genistein released slowly but persistently with a cumulative release of 63% at day 40. The thermoresponsive hydrogel inhibited the proliferation, migration and epithelial-mesenchymal transition of SRA 01/04 cells, which were confirmed by testing CCK-8, wound-healing assay, western blot, real time-PCR (RT-PCR) and immunofluorescence. These results support this intracameral thermoresponsive in situ multi-drug delivery system with programmed release amounts and release profiles to cut down the need of eye drops for preventing inflammation or infection and to reduce posterior capsular opacification following cataract surgery.

Motivation: Kidney renal clear cell carcinoma, which is a common type and accounts for 70–80% of renal cell carcinoma, can easily lead to metastasis and even death. A reliable signature for diagnosis of this cancer is in need. Hence, we seek to select miRNAs for identifying kidney renal clear cell carcinoma.Method: A feature selection strategy is used and improved to identify microRNAs for diagnosis of kidney renal clear cell carcinoma. Samples representing kidney renal clear cell carcinoma and normal tissues are split into training and testing groups. Accumulated scores representing the variable importance of each miRNA are derived from an iteration of resampling, training, and scoring. Those miRNAs with higher scores are selected based on the Gaussian mixture model. The sample split is repeated ten times to get more central miRNAs.Results: A total of 611 samples are downloaded from TCGA, each of which contains 1,343 miRNAs. The improved feature selection method is implemented, and five miRNAs are identified as a biomarker for diagnosis of kidney renal clear cell carcinoma. GSE151419 and GSE151423 are selected as the independent testing sets. Experimental results indicate the effectiveness of the selected signature. Both data-driven measurements and knowledge-driven evidence are given to show the effectiveness of our selection results.

Accumulating evidence suggests that DNA methylation has essential roles in the development of renal cell carcinoma (RCC). Aberrant DNA methylation acts as a vital role in RCC progression through regulating the gene expression, yet little is known about the role of methylation and its association with prognosis in RCC. The purpose of this study is to explore the DNA methylation-driven genes for establishing prognostic-related molecular clusters and providing a basis for survival prediction. In this study, 5,198 differentially expressed genes (DEGs) and 270 DNA methylation-driven genes were selected to obtain 146 differentially expressed DNA methylation-driven genes (DEMDGs). Two clusters were distinguished by consensus clustering using 146 DEMDGs. We further evaluated the immune status of two clusters and selected 106 DEGs in cluster 1. Cluster-based immune status analysis and functional enrichment analysis of 106 DEGs provide new insights for the development of RCC. To predict the prognosis of patients with RCC, a prognostic model based on eight DEMDGs was constructed. The patients were divided into high-risk groups and low-risk groups based on their risk scores. The predictive nomogram and the web-based survival rate calculator (http://127.0.0.1:3496) were built to validate the predictive accuracy of the prognostic model. Gene set enrichment analysis was performed to annotate the signaling pathways in which the genes are enriched. The correlation of the risk score with clinical features, immune status, and drug susceptibility was also evaluated. These results suggested that the prognostic model might be a promising prognostic tool for RCC and might facilitate the management of patients with RCC.

Abstract Background This is a retrospective study of the use of parallel endplate osteotomy (PEO) for correction of severe rigid thoracolumbar spine deformity. Methods From July 2016 to January 2019, 12 patients with severe rigid thoracolumbar spine deformity underwent PEO on T12 or L1 vertebrae were studied. Results Following PEO at T12 or L1, the mean kyphosis and scoliosis correction rates reached 77.0 ± 8.9% and 75.5 ± 8.0%, respectively and the intraoperative estimated blood loss was 1950 ± 1050 mL, and the mean operative time was 6.98 ± 4.02 h. The SF-36 scores of physical function, role-physical, bodily pain, general health, vitality, social function, role-emotional and mental health changed from 63 ± 28, 50 ± 25, 50 ± 30, 34 ± 19, 53 ± 28, 45 ± 30, 30 ± 36 and 54 ± 18 at baseline to 83 ± 18, 69 ± 19, 72 ± 12, 66 ± 21, 75 ± 15, 72 ± 22, 66 ± 34 and 76 ± 12 at 1 year postoperatively, 83 ± 8, 68 ± 32, 83 ± 17, 73 ± 17, 82 ± 18, 76 ± 26, 70 ± 37 and 88 ± 12 at 18 months postoperatively, 86 ± 6, 83 ± 33, 90 ± 16, 81 ± 16, 89 ± 14, 88 ± 25, 83 ± 17 and 94 ± 10 at 24 months postoperatively, respectively (P

In order to realize low-carbon and high-quality development, this study took the carbon emissions of each district and county in the Chengdu–Chongqing region from 2005 to 2017 as the research object and used the spatial autocorrelation model to analyze the spatial and temporal evolution characteristics of carbon emissions in the counties of the Chengdu–Chongqing region, so as to fill in the research blank of carbon emissions in the counties of the Chengdu–Chongqing region. Then, the geographical detector model is used to explore the interaction among influencing factors of carbon emissions and reveal the time changes and regional differences of influencing factors, so as to improve the lack of spatial and temporal heterogeneity of influencing factors of carbon emissions by geographical detector. The results show the following: (i) The overall carbon emissions of counties show a year-on-year growth trend with the main urban areas of Chengdu and Chongqing as the core, but the growth rate slows down after 2010. (ii) The carbon emissions showed a significant positive spatial autocorrelation, and the neighboring counties showed a spatial clustering characteristic of “high-high” or “low-low”, and the clustering status tended to be enhanced. (iii) The carbon emissions are strongly influenced by industrial structure, economic development, investment level, financial situation, urbanization rate and social consumption, and their interactions are all enhanced, but the influence mostly tends to rise first and then fall. (iv) County carbon emissions can be divided into four types of geographical types, such as population size influencing type, urbanization rate influencing type, economic development influencing type and industrial structure influencing type. Therefore, a variety of factors need to be considered comprehensively, a multi-pronged approach, and a comprehensive policy to realize low-carbon transformation in the Chengdu–Chongqing region.

Abstract Background Accurately recognizing rare diseases based on symptom description is an important task in patient triage, early risk stratification, and target therapies. However, due to the very nature of rare diseases, the lack of historical data poses a great challenge to machine learning-based approaches. On the other hand, medical knowledge in automatically constructed knowledge graphs (KGs) has the potential to compensate the lack of labeled training examples. This work aims to develop a rare disease classification algorithm that makes effective use of a knowledge graph, even when the graph is imperfect. Method We develop a text classification algorithm that represents a document as a combination of a “bag of words” and a “bag of knowledge terms,” where a “knowledge term” is a term shared between the document and the subgraph of KG relevant to the disease classification task. We use two Chinese disease diagnosis corpora to evaluate the algorithm. The first one, HaoDaiFu, contains 51,374 chief complaints categorized into 805 diseases. The second data set, ChinaRe, contains 86,663 patient descriptions categorized into 44 disease categories. Results On the two evaluation data sets, the proposed algorithm delivers robust performance and outperforms a wide range of baselines, including resampling, deep learning, and feature selection approaches. Both classification-based metric (macro-averaged F 1 score) and ranking-based metric (mean reciprocal rank) are used in evaluation. Conclusion Medical knowledge in large-scale knowledge graphs can be effectively leveraged to improve rare diseases classification models, even when the knowledge graph is incomplete.

Gastrodin (GAS) is the main bioactive ingredient of Gastrodia, a famous Chinese herbal medicine widely used as an analgesic, but the underlying analgesic mechanism is still unclear. In this study, we first observed the effects of GAS on the vincristine-induced peripheral neuropathic pain by alleviating the mechanical and thermal hyperalgesia. Further studies showed that GAS could inhibit the current density of NaV1.7 and NaV1.8 channels and accelerate the inactivation process of NaV1.7 and NaV1.8 channel, thereby inhibiting the hyperexcitability of neurons. Additionally, GAS could significantly reduce the over-expression of NaV1.7 and NaV1.8 on DRG neurons from vincristine-treated rats according to the analysis of Western blot and immunofluorescence results. Moreover, based on the molecular docking and molecular dynamic simulation, the binding free energies of the constructed systems were calculated, and the binding sites of GAS on the sodium channels (NaV1.7 and NaV1.8) were preliminarily determined. This study has shown that modulation of NaV1.7 and NaV1.8 sodium channels by GAS contributing to the alleviation of vincristine-induced peripheral neuropathic pain, thus expanding the understanding of complex action of GAS as a neuromodulator.

Background: Several paclitaxel-coated balloons have been proved to provide better efficacy results than uncoated balloons in femoropopliteal lesions. But the efficacy and safety of FREEWAY balloons have not been investigated in Chinese patients. This study aimed to evaluate the efficacy and safety performance of FREEWAY paclitaxel-coated balloons vs. uncoated balloons in Chinese femoropopliteal artery lesions.Methods: In this prospective multi-center randomized controlled FREEWAY-CHINA study, 311 patients with symptomatic lower limb ischemia (Rutherford category 2–5) and femoropopliteal lesions of 14 Chinese centers were randomly assigned in a 1:1 ratio to endovascular treatment with either FREEWAY paclitaxel-coated balloons or uncoated balloons (control). The primary endpoint was the 6-month clinically-driven target lesion revascularization (CD-TLR) rate. Secondary endpoints included the device and technical success rate, the ankle-brachial indexes (ABIs), Rutherford category change, the 6-month primary and secondary patency rates, severe adverse effects, and the 12-month CD-TLR rate.Results: The two groups were comparable in terms of their demographic and lesion characteristics. Patients' mean age was 70 years, and 70% were men. The mean lesion length was 71 mm. The 6-month CD-TLR rate was 2.6% in the FREEWAY group and 11.7% in the control group (P = 0.001). The 12-month CD-TLR rate was 2.7% in the FREEWAY group and 13.2% in the control group (P = 0.0005). Other endpoints, including patency rates, major adverse events, and ABI or Rutherford change, did not differ between the two groups.Conclusion: The FREEWAY balloon resulted in an effective decrease in CD-TLR rates and had similar safety results compared to the uncoated balloon in Chinese femoropopliteal artery patients at the 12-month follow-up appointment.

This article was submitted to Experimental Pharmacology and Drug Discovery, a section of the journal Frontiers in Pharmacology. Postmenopausal osteoporosis (PMOP), which increases the risk of fracture, is the most common bone disease in women. PMOP not only increases the risk of death but also imposes a financial burden on countless families. At present, most of the drugs used to treat osteoporosis have significant side effects, so it is important to find effective anti-osteoporosis medications without major side effects. Sesamolin (Ses) is a kind of natural lignan extracted from sesame oil. Many researches have shown that Ses has anti-inflammatory, antioxidative, and anticancer effects, however it is still unknown whether it has any effect on osteoporosis. In this research, we explored the therapeutic effect of Ses in the process of osteoclast formation and bone resorption and found that Ses effectively inhibited osteoclast formation in vitro through TRAcP staining and hydroxyapatite resorption assays. Through Western blot analysis of the NF-κB pathway, MAPK pathway, c-Fos and NFATc1, it was found that Ses not only effectively inhibited the activation of NF-κB and MAPK signaling pathways induced by RANKL but also significantly reduced the protein expression of c-Fos and NFATc1. Several genes specifically expressed in osteoclasts were determined by qPCR, and Ses was also found to play a significant inhibitory role on the expression of these genes. Besides, an osteoporosis model induced in ovariectomized (OVX) mice was employed to verify that Ses could effectively reduce bone loss caused by estrogen deficiency in vivo. In conclusion, Ses showed promise as a new treatment for postmenopausal osteoporosis.

Abstract Background Kidney renal clear cell carcinoma (KIRC) is the most common type of kidney cancer in adults, and it is responsible for approximately 90–95% of cases. Although extensive evidence has suggested that many immune- and inflammation-related genes could serve as effective biomarkers in KIRC, the potential associations among immune-, inflammation- and KIRC-related genes has not been sufficiently understood. Methods Here, we integrated multiple levels of data to construct an immune-, inflammation- or KIRC-directed neighbour network (IIKDN network) and a KIRC-related gene-directed network (KIRCD network). Results Our analysis suggested that immune- and inflammation-related genes in the network have special topological characteristics and expression patterns related to KIRC. We further identified five core clusters that showed a tighter network structure and stronger correlation of expression from the KIRCD network. Specifically, multiple-level molecular characteristics were systematically portrayed, including somatic mutation, copy-number variant and DNA methylation for the genes in five core clusters. We discovered that the genes showed strong correlation with respect to the expression and methylation levels in these five core clusters. These five core clusters could become special prognostic biomarkers for KIRC, and functional analysis showed that they were associated with activation of the immune and inflammation systems and cancer progression. Conclusions Our findings highlighted the novel role of the immune and inflammation genes in KIRC.

Fascaplysin is a natural marine product originating from sponges, attracting widespread attention due to its potential inhibitory activities against CDK4. However, its clinical application has been largely limited because of serious adverse effects caused by planar skeleton. To reduce the serious adverse effects, 18 tetrahydro-β-carboline analogs (compounds 6a-i and 7a-i) were designed and synthesized via breaking the planarity of fascaplysin, and the biological activities of the synthesized compounds were evaluated by MTT assay and CDK4/CycD3 enzyme inhibition assay. The title compounds showed varying degrees of inhibitory activities, especially the cytotoxicity of compound 6c against HeLa cells (IC50 = 1.03 ± 0.19 μM) with quite weak cytotoxicity toward the normal cells WI-38 (IC50 = 311.51 ± 56.06 μM), and the kinase inhibition test indicated that compound 6c was a potential CDK4 inhibitor. In order to further compare the action mechanisms of planar and nonplanar molecules on CDK4, the studied complexes of CDK4 bound with fascaplysin and three representative compounds (compound 6a-c) with bioactivities gradient were constructed by molecular docking and further verified through molecular dynamic simulation, which identified the key residues contributing to the ligands’ binding. By comparing the binding modes of the constructed systems, it could be found that the residues contributing significantly to compound 6c′s binding were highly consistent with those contributing significantly to fascaplysin’s binding. Through the design, synthesis of the nonplanar fascaplysin derivatives, and binding mechanism analysis, some valuable hints for the discovery of antitumor drug candidates could be provided.

The present work systematically investigated the initiation mechanism of localized corrosion induced by Al2O3-MnS composite inclusion in E690 steel under a simulated marine environment. The results showed that a micro-gap exists between the Al2O3-MnS inclusion and the matrix, and electron backscattered diffraction (EBSD) analysis revealed significant lattice dislocation zones around the Al2O3-MnS composite inclusion. The presence of the micro-gap and the lattice dislocation both promoted the localized corrosion initiation. The Volta potential of Al2O3 detected by scanning Kelvin probe force microscopy (SKPFM) was approximately 149.33 mV higher than that of the steel matrix, and the Volta potential of MnS was 10 mV lower than that of the steel matrix. The current-sensing atomic force microscopy (CSAFM) results showed that the Al2O3 was not conductive, while the MnS had good conductive properties. Therefore, it was not possible for a galvanic couple to be formed between Al2O3 and the adjacent steel matrix. A galvanic couple effect between the MnS and the adjacent steel matrix was directly demonstrated for the first time. The MnS acted as the anode phase for preferential dissolution in the corrosion process. The in situ immersion experiments and the Pourbaix diagram results confirmed that the dissolution of MnS was an electrochemical reaction process and the dissolution of Al2O3 was a chemical reaction.

Purpose: Venous anastomosis is the key procedure for Ishikawa zone Ⅱ fingertip replantation. Both palmar and lateral veins provide efficient venous drainage. This study compared the clinical effects between these venous anastomoses for fingertip replantation. Methods: In 2016–2018, 61 patients underwent Ishikawa zone Ⅱ fingertip replantation with venous anastomosis (28 and 33 cases with palmar and lateral anastomoses, respectively). Retrospective comparative analyses evaluated surgical technique and function, including operative time; rates of finger survival, venous congestion, and infection; sensation; joint motion; cold intolerance symptom severity (CISS), Disabilities of the Arm, Shoulder, and Hand (DASH), and Vancouver scar scores; and chronic regional pain syndrome (CRPS) rates. Results: There were 33 patients with lateral vein anastomosis and 28 patients with palmar vein anastomosis. The average patient follow-up was 18.2 months. The survival rates did not differ significantly between groups (87.8% (29/33) vs. 85.7% (24/28), p > 0.05); however, the operative time was shorter in the lateral vein group than in the palmar vein group (78.57 ± 7.08 min vs. 67.88 ± 5.77 min, p < 0.05). Venous congestion and infection rates did not differ significantly between groups ( p > 0.05). The replanted finger function, including joint motion, sensation, DASH scores, Vancouver scar scores, and CRPS rates, did not differ significantly between groups ( p > 0.05). However, the CISS score was higher in the palmar vein group than in the lateral vein group (44.39 ± 5.16 vs. 38.09 ± 4.49, p < 0.05). Conclusions: Venous anastomosis with either palmar or lateral veins showed high survival rates and good function in fingertip replantation. The lateral vein had a shorter operative time and benefit to arterial revision and was especially suitable for patients with finger pulp damage.

The research on the deformation of soil mass and ground connection walls is not sufficiently thorough due to the huge risk of deep excavation in soft soil areas. In this paper, finite element software is used to numerically simulate a symmetrical foundation pit in Suzhou, and the reliability is verified by on-site measured data. The purpose of this study is to investigate the deformation mechanism of the enclosure structure and surrounding soil during the excavation of soft soil foundation pits, and to carry out sensitivity analysis. The results show that the maximum subsidence of the surface is 21.25 mm, the maximum horizontal displacement of the underground diaphragm wall is 9.45 mm, and the maximum uplift of the pit bottom is 21.46 mm. By changing the soil layer properties (the elastic modulus, cohesion, and internal friction angle) and the insertion ratio of the diaphragm wall, the maximum horizontal displacement of the diaphragm wall is more easily affected than the maximum settlement of the surface. Based on different research results, the maximum land subsidence and maximum horizontal displacement of the support structure are 0.313–0.060% and 0.070–0.250% of the maximum excavation depth, respectively. Finally, the simulation may have some applicability to other foundation pit excavations.

Vegetation phenology is a key biological indicator for monitoring terrestrial ecosystems and global change, and regions with the most obvious phenological changes in vegetation are primarily located at high latitudes and altitudes. Over the past three decades, investigations of obvious phenological changes in vegetation at middle and high latitudes in the Northern Hemisphere have provided significant contributions to understanding global climate change. In this study, phenological parameters were extracted from the Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) to analyze the spatial and temporal characteristics of vegetation phenological changes above 40°N in the Northern Hemisphere from 1982–2013. The results showed that the start of season (SOS) was significantly advanced (−2.2 ± 0.6 days·decade−1, p < 0.05) and that the end of season (EOS) was slightly delayed (0.78 ± 0.6 days·decade−1, p = 0.21) over the entire study area in the initial 21 years (1982–2002). When the time scale was extended to 2013, the change rate of the SOS and EOS was significantly reduced; in addition, the SOS was delayed (3.2 ± 1.7 days·decade−1, p < 0.05), and the EOS was advanced (4.5 ± 0.9 days·decade−1, p < 0.05) over the entire study area in the last 11 years (2003–2013). The trends of advanced SOS and delayed EOS over the past three decades were slower than those over the initial two decades on a hemispheric scale. The change trends showed obvious variability with different vegetation types and were greater for woody plants than for herbaceous plants. For broad-leaved forest, the SOS was significantly advanced (2 ± 0.5 days·decade−1, p < 0.05) and the EOS was significantly delayed (2.7 ± 0.6 days·decade−1, p < 0.05) from 1982–2013. The trend of delayed EOS was greater than that of advanced SOS for different vegetation types. With respect to the spatial distribution of phenological trends in the Northern Hemisphere, the trends of advanced SOS and delayed EOS were strongest in Europe followed by North America, and the trends were least significant in Asia. Coniferous forest, shrub forest, grassland, and the entire study area have the same change trends for the two time periods (1982–2002 and 2003–2013), and the increased rate of the phenology parameters has decelerated over the most recent decade. The length of season (LOS) of broad-leaved forest and mixed forest over the past 32 years shows a strong increased trend, and simultaneously, the SOS and EOS show an advanced trend and a delayed trend, respectively

Purpose. The functions of vascular endothelial growth factor (VEGF) in scar formation after trabeculectomy were investigated in a human Tenon fibroblast cell line from glaucoma patients using lentivirus-mediated VEGF shRNA. Methods. Human Tenon fibroblast (HTF) cells were isolated from scar tissue of glaucoma patients during secondary surgery. Lentivirus-VEGF-shRNA was constructed and transfected into HTF cells. Subsequently, VEGF mRNA and protein expression were analyzed using quantitative RT-PCR and western blotting, respectively, and the effects of VEGF knockdown were analyzed. The inhibition of HTF proliferation was monitored according to total cell numbers using ScanArray. Results. Both mRNA and protein levels of VEGF were reduced by lentivirus-mediated VEGF-shRNA, and proliferation of HTF cells was inhibited. Conclusions. Primary cultures of human Tenon fibroblast (HTF) were established, and proliferation was decreased following inhibition of VEGF. VEGF may be a suitable therapeutic target for reducing scar tissue formation in glaucoma patients after filtration surgery.

To circumvent the thermodynamic limitation of the synthesis of oxazolidinones starting from 2-aminoethanols and CO2 and realize incorporation CO2 under atmospheric pressure, a protic ionic liquid-facilitated three-component reaction of propargyl alcohols, CO2 and 2-aminoethanols was developed to produce 2-oxazolidinones along with equal amount of α-hydroxyl ketones. The ionic liquid structure, reaction temperature and reaction time were in detail investigated. And 15 mol% 1,5,7-triazabicylo[4.4.0]dec-5-ene ([TBDH][TFE]) trifluoroethanol was found to be able to synergistically activate the substrate and CO2, thus catalyzing this cascade reaction under atmospheric CO2 pressure. By employing this task-specific ionic liquid as sustainable catalyst, 2-aminoethanols with different substituents were successfully transformed to 2-oxazolidinones with moderate to excellent yield after 12 h at 80 °C.

The increasing frequency of fires inhibits the estimation of carbon reserves in boreal forest ecosystems because fires release significant amounts of carbon into the atmosphere through combustion. However, less is known regarding the effects of vegetation succession processes on ecosystem C-flux that follow fires. This paper describes intra- and inter-annual vegetation restoration trajectories via MODIS time-series and Landsat data. The temporal and spatial characteristics of the natural succession were analyzed from 2000 to 2016. Finally, we regressed post-fire MODIS EVI, LST and LSWI values onto GPP and NPP values to identify the main limiting factors during post-fire carbon exchange. The results show immediate variations after the fire event, with EVI and LSWI decreasing by 0.21 and 0.31, respectively, and the LST increasing to 6.89 °C. After this initial variation, subsequent fire-induced variations were significantly smaller; instead, seasonality began governing the change characteristics. The greatest differences in EVI, LST and LSWI were observed in August and September compared to those in other months (0.29, 6.9 and 0.35, respectively), including July, which was the second month after the fire. We estimated the mean EVI recovery periods under different fire intensities (approximately 10, 12 and 16 years): the LST recovery time is one year earlier than that of the EVI. GPP and NPP decreased after the fire by 22–45 g C·m−2·month−1 (30–80%) and 0.13–0.35 kg C·m−2·year−1 (20–60%), respectively. Excluding the winter period, when no photosynthesis occurred, the correlation between the EVI and GPP was the strongest, and the correlation coefficient varied with the burn intensity. When changes in EVI, LST and LSWI after the fire in the boreal forest were more significant, the severity of the fire determined the magnitude of the changes, and the seasonality aggravated these changes. On the other hand, the seasonality is another important factor that affects vegetation restoration and land-surface energy fluxes in boreal forests. The strong correlations between EVI and GPP/NPP reveal that the C-flux can be simply and directly estimated on a per-pixel basis from EVI data, which can be used to accurately estimate land-surface energy fluxes during vegetation restoration and reduce uncertainties in the estimation of forests’ carbon reserves.

PURPOSE: Several epidemiologic studies have evaluated the association between nonsteroidal anti-inflammatory drugs (NSAIDs) and bladder cancer risk and the results were varied. Thus, we conducted a comprehensive meta-analysis of studies exclusively dedicated to the relationship between the 3 most commonly used analgesics and bladder cancer risk. METHODS: A systematic literature search up to November 2012 was performed in PubMed database for 3 categories of analgesics: acetaminophen, aspirin or non-aspirin NSAIDs. Study-specific risk estimates were pooled using a random-effects model. RESULTS: Seventeen studies (8 cohort and 9 case-control studies), involving a total of 10,618 bladder cancer cases, were contributed to the analysis. We found that acetaminophen (relative risk [RR] 1.01, 95% confidence interval [CI] 0.88-1.17) and aspirin (RR 1.02, 95% CI 0.91-1.14) were not associated with bladder cancer risk. Although non-aspirin NSAIDs was statistically significantly associated with reduced risk of bladder cancer among case-control studies (but not cohort studies), the overall risk was not statistically significant (RR 0.87, 95% CI 0.73-1.05). Furthermore, we also found that non-aspirin NSAIDs use was significantly associated with a 43% reduction in bladder cancer risk among nonsmokers (RR 0.57, 95% CI 0.43-0.76), but not among current smokers. CONCLUSION: The results of our meta-analysis suggest that there is no association between use of acetaminophen, aspirin or non-aspirin NSAIDs and bladder cancer risk. However, non-aspirin NSAIDs use might be associated with a reduction in risk of bladder cancer for nonsmokers.