Low-dose radiation therapy mobilizes antitumor immunity: New findings and future perspectives.

Radiotherapy has unique immunostimulatory and immunosuppressive effects. Although high-dose radiotherapy has been found to have systemic antitumor effects, clinically significant abscopal effects were uncommon on the basis of irradiating single lesion. Low-dose radiation therapy (LDRT) emerges as a novel approach to enhance the antitumor immune response due to its role as a leverage to reshape the tumor immune microenvironment (TIME). In this article, from bench to bedside, we reviewed the possible immunomodulatory role of LDRT on TIME and systemic tumor immune environment, and outlined preclinical evidence and clinical application. We also discussed the current challenges when LDRT is used as a combination therapy, including the optimal dose, fraction, frequency, and combination of drugs. The advantage of low toxicity makes LDRT potential to be applied in multiple lesions to amplify antitumor immune response in polymetastatic disease, and its intersection with other disciplines might also make it a direction for radiotherapy-combined modalities.

Application of Linear Regression Model of Gpnmb Gene in Rat Injury Time Estimation.

OBJECTIVES: To investigate the effects of injury time, postmortem interval (PMI) and postmortem storage temperature on mRNA expression of glycoprotein non-metastatic melanoma protein B (Gpnmb), and to establish a linear regression model between Gpnmb mRNA expression and injury time, to provide aimed at providing potential indexes for injury time estimation. METHODS: Test group SD rats were anesthetized and subjected to blunt contusion and randomly divided into 0 h, 4 h, 8 h, 12 h, 16 h, 20 h and 24 h groups after injury, with 18 rats in each group. After cervical dislocation, 6 rats in each group were collected and stored at 0 ℃, 16 ℃ and 26 ℃, respectively. The muscle tissue samples of quadriceps femoris injury were collected at 0 h, 12 h and 24 h postmortem at the same temperature. The grouping method and treatment method of the rats in the validation group were the same as above. The expression of Gpnmb mRNA in rat skeletal muscle was detected by RT-qPCR. The Pearson correlation coefficient was used to evaluate the correlation between Gpnmb mRNA expression and injury time, PMI, and postmortem storage temperature. SPSS 25.0 software was used to construct a linear regression model, and the validation group data was used for the back-substitution test. RESULTS: The expression of Gpnmb mRNA continued to increase with the prolongation of injury time, and the expression level was highly correlated with injury time (P<0.05), but had little correlation with PMI and postmortem storage temperature (P>0.05). The linear regression equation between injury time (y) and Gpnmb mRNA relative expression (x) was y=0.611 x+4.489. The back-substitution test proved that the prediction of the model was accurate. CONCLUSIONS: The expression of Gpnmb mRNA is almost not affected by the PMI and postmortem storage temperature, but is mainly related to the time of injury. Therefore, a linear regression model can be established to infer the time of injury.

Efficient multivariate analysis algorithms for longitudinal genome-wide association studies.

MOTIVATION: Current dynamic phenotyping system introduces time as an extra dimension to genome-wide association studies (GWAS), which helps to explore the mechanism of dynamical genetic control for complex longitudinal traits. However, existing methods for longitudinal GWAS either ignore the covariance among observations of different time points or encounter computational efficiency issues. RESULTS: We herein developed efficient genome-wide multivariate association algorithms for longitudinal data. In contrast to existing univariate linear mixed model analyses, the proposed method has improved statistic power for association detection and computational speed. In addition, the new method can analyze unbalanced longitudinal data with thousands of individuals and more than ten thousand records within a few hours. The corresponding time for balanced longitudinal data is just a few minutes. AVAILABILITY AND IMPLEMENTATION: A software package to implement the efficient algorithm named GMA (https://github.com/chaoning/GMA) is available freely for interested users in relevant fields. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Daphnetin inhibits RANKL-induced osteoclastogenesis in vitro.

Osteoporosis is a common orthopedic disease which is associated with hyper-activated osteoclastogenesis. Daphnetin is a natural coumarin derivative isolated from Genus Daphne, which possesses antiarthritis effect. However, the role of daphnetin in osteoclastogenesis has not been illustrated. This study aimed to investigate the effects of daphnetin on receptor activator of NF-κB ligand (RANKL)-induced osteoclastogenesis in vitro. Our results showed that the osteoclast formation was significantly suppressed by daphnetin treatment in bone marrow-derived macrophages (BMMs), which was illustrated by reduced number of tartrate-resistant acid phosphatase positive multinucleated osteoclasts and decreased expression levels of tumor necrosis factor receptor-associated factors (TRAF6), c-Fos, nuclear factor of activated T cells c1, and cathepsin K. RANKL caused significant induction effects in reactive oxygen species (ROS) generation and nicotinamide adenine dinucleotide phosphate oxidase activity, whereas the induction was dramatically reduced after pretreatment with daphnetin. In addition, daphnetin prevented the RANKL-induced activation of NF-κB and Akt/GSK-3ß pathways in BMMs. These findings indicated that daphnetin exhibited an inhibitory effect on RANKL-induced osteoclastogenesis in vitro. The effect of daphnetin might be mediated by inhibiting ROS signal transduction, as well as preventing the activation of NF-κB and Akt/GSK-3ß signaling pathways. These findings indicated that daphnetin might be considered as a new therapeutic approach for the osteoporosis treatment.

Promoter engineering enables overproduction of foreign proteins from a single copy expression cassette in Bacillus subtilis.

BACKGROUND: Bacillus subtilis is developed to be an attractive expression host to produce both secreted and cytoplasmic proteins owing to its prominent biological characteristics. Chromosomal integration is a stable expression strategy while the expression level is not ideal compared with plasmid expression. Thus, to meet the requirement of protein overexpression, promoter, as one of the key elements, is important. It is necessary to obtain an ideal promoter for overproduction of foreign proteins from a single copy expression cassette. RESULTS: The activity of promoter Pylb was further enhanced by optimizing the - 35, - 10 core region and upstream sequence (UP) by substituting both sequences with consensus sequences. The final engineered promoter exhibited almost 26-fold in ß-galactosidase (BgaB) activity and 195-fold in super-folded green fluorescent protein (sfGFP) intensity than that of WT. The two proteins account for 43% and 30% of intracellular proteins, respectively. The promoter was eventually tested by successful extracellular overproduction of Methyl Parathion Hydrolase (MPH) and Chlorothalonil hydrolytic dehalogenase (Chd) to a level of 0.3 g/L (144 U/mL) and 0.27 g/L (4.4 U/mL) on shake-flask culture condition. CONCLUSIONS: A strong promoter was engineered for efficient chromosomally integrated expression of heterologous proteins.

The substrate specificity of aniline dioxygenase is mainly determined by two of its components: glutamine synthetase-like enzyme and oxygenase.

The residues of aniline and its derivatives are serious environment pollutants. Aniline dioxygenase (AD) derived from aerobic bacteria catalyzes the conversion of aniline to catechol, which has potential use in the bioremediation of aromatic amines and biorefining process. AD contains four components: a glutamine synthetase (GS)-like enzyme, a glutamine amidotransferase (GAT)-like enzyme, oxygenase, and reductase. ADs from diverse hosts exhibit different substrate specificities against aniline derivatives. However, what component of AD determines AD's substrate specificity is still unknown which limits the effects of extending AD's substrate spectrum through mutagenesis. Here, each component of two ADs (AtdA1A2A3A4A5 and AdoQTA1A2B) which have different substrate ranges was heterologously expressed and purified. The activity of both ADs was successfully constructed in vitro using the purified components. To identify the component that affects the substrate specificity of the ADs, the substrate specificity of each component was studied. The inability of AtdA1A2A3A4A5 to catalyze 4-methylaniline was determined with GS-like enzyme AtdA1; its inability to convert 2-isopropylaniline was caused by the oxygenase component, and its inability to convert 4-isopropylaniline was caused by both GS-like enzyme AtdA1 and oxygenase components. The inability of AdoQTA1A2B to catalyze 2-methylaniline was determined by GS-like enzyme AdoQ; its inability to convert 2-isopropylaniline was caused by both GS-like enzyme AdoQ and oxygenase components. Together, these results show that GS-like enzyme and oxygenase but not GAT-like enzyme or reductase play dominant roles in the substrate specificity of AD, and this finding will facilitate the engineering of AD to expand its substrate range.

C-reactive protein inhibits high-molecular-weight adiponectin expression in 3T3-L1 adipocytes via PI3K/Akt pathway.

Adiponectin, an adipose-specific protein hormone, is secreted from white adipose tissue and involved in glucose and lipid metabolism. It is assembled into low-molecular-weight trimer (LMW), middle-molecular-weight hexameric (MMW) and high-molecular-weight (HMW), among which HMW exhibits higher activity. In this study, we proved that C-reactive protein (CRP), an inflammatory marker, inhibited adiponectin expression, especially HMW in time-and dose-dependent manners. Furthermore, CRP decreased the HMW/total adiponectin ration and reduced adiponectin assembly by increasing ERp44, and decreasing Ero1-α and DsbA-L. CRP activated pAkt, the downstream of PI3K. Inhibition of PI3K or pAkt abolished the effect of CRP. Our study suggested that CRP decreased adiponectin expression and multimerization, while CRP-induced decline in adiponectin might be mediated through the PI3K/Akt pathway.

Reduced circulating oxytocin and High-Molecular-Weight adiponectin are risk factors for metabolic syndrome.

The neurohypophysial hormone, oxytocin, is involved in the regulation of energy metabolism. Adiponectin (APN) is an adipose tissue-specific serum protein that inversely associates with metabolic syndrome (MetS). High-molecular-weight adiponectin (HMW APN) is considered the active form. In the present study, we aimed to determine the relationships of oxytocin and HMW APN to MetS and investigate whether or not the combination of oxytocin and HMW APN is associated with further metabolic abnormalities compared to each of them alone. A total of 170 subjects (75 with MetS and 95 non-MetS) were enrolled. Anthropometric parameters, oral glucose tolerance test (OGTT), blood lipids, hs-CRP, oxytocin and HMW APN levels were measured. Compared with non-MetS subjects, serum oxytocin and HMW APN levels were significantly lower in subjects with MetS (P<0.01). We then classified the subjects into three groups: high oxytocin and high HMW APN levels (high score group), low oxytocin and low HMW APN levels (low score group) and others. Participants in low score group showed the worst metabolic profiles and were more likely to have MetS compared to the other two group. In Spearman rank correlation coefficient, the classification by the combination of oxytocin and HMW APN was significantly correlated with a larger number of metabolic risk factors compared with classification by each of them alone. Individuals with low circulating oxytocin levels coupled with low HMW APN levels were at significantly increased risk of MetS. The combination of both markers would be useful for identifying MetS high risk patients.

Fibroblast growth factor 1 levels are elevated in newly diagnosed type 2 diabetes compared to normal glucose tolerance controls.

Fibroblast growth factor 1 (FGF1) has been recently characterized as a potent insulin sensitizer that regulates adipose tissue remodeling, but the physiological role of FGF1 remains unclear. This study measured serum FGF1 levels for the first time in patients with newly diagnosed type 2 diabetes mellitus (T2DM), and further explored the correlations between FGF1 levels and various metabolic parameters in T2DM. Serum FGF1 levels were determined using ELISA in age-, sex- and BMI- matched subjects with normal glucose tolerance (NGT) (n=80) and newly diagnosed T2DM (n=80). Oral glucose tolerance test (OGTT), glycosylated hemoglobin (HbA1C), blood lipids, and insulin secretion were also measured. Insulin resistance and pancreatic ß-cell function were assessed by homeostasis model assessment of insulin resistance (HOMA-IR) and homeostasis model assessment of beta cell function (HOMA-ß), respectively. Serum FGF1 levels were significantly higher in T2DM patients than in normal glucose tolerance subjects (74.52 [55.91∼101.34] vs. 60.31 [48.99∼83.91] pg/mL; P<0.05). In addition, serum FGF1 level positively correlated with body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR), fasting plasma glucose (FPG), 2-h post-OGTT glucose (2h PG), and HbA1C (all P values <0.05) in T2DM subjects. Multivariate regression analyses showed that BMI and HbA1C were the independent factors influencing serum FGF1 levels. Logistic regression analyses demonstrated that serum FGF1 was significantly associated with type 2 diabetes (P<0.01). Circulating concentrations of FGF1 are significantly increased in T2DM patients. Our results suggest that FGF1 may play a role in the pathogenesis of T2DM.

The analysis of aerobics intelligent fitness system for neurorobotics based on big data and machine learning.

In modern society, people's pace of life is fast, and the pressure is enormous, leading to increasingly prominent issues such as obesity and sub-health. Traditional fitness methods cannot meet people's needs to a certain extent. Therefore, this work aims to use technology to change people's lifestyles and compensate for traditional fitness methods' shortcomings. Firstly, this work overviews neurorobotics, providing neural perception and control functions for aerobics intelligent fitness system. Secondly, the connection between big data and machine learning (ML), big data technology products, and the ML process are discussed. The Spark big data platform builds node data for calculation, and the decision tree algorithm is used for data preprocessing. These are important for future intelligent fitness analysis. This work proposes an aerobics intelligent fitness system based on neurorobotics technology and big data analysis and develops a recommendation system for the best fitness exercise. This system utilizes neural perception and control functions, combined with big data and ML technology, to solve the obesity and sub-health problems faced by people in fast-paced and high-pressure lifestyles. By harnessing the computational capabilities of the Spark big data platform and applying the decision tree algorithm for data preprocessing, the system can furnish users with personalized fitness plans and optimization recommendations. This work conducts a model performance study on 35 % aerobic fitness data on intelligent fitness Android v1.0.8 to evaluate the system's data processing ability and training effectiveness. Moreover, the aerobics intelligent fitness system models based on neurorobotics, big data, and ML are evaluated. The results indicate that normalizing the data using the Min-Max method leads to a decrease in the F1 value and a reduction in data set errors. Consequently, the dataset studied by the system model is beneficial to improving the work efficiency of the aerobics intelligent fitness system. After the comprehensive human quality of the system model is evaluated, the actual average score of the comprehensive human quality of the 13 users tested before the aerobics intelligent fitness system test is 91.44, and the average prediction score is 90.88. The results of the two tests are similar. Thus, using the intelligent fitness system can enable the user to obtain system feedback according to the actual training effect, thereby playing a guiding role in the intelligent fitness of aerobics for the user. This work designs and implements the aerobics intelligent fitness system close to the human body's training effect, further enhancing the specialization and individualization of sports and fitness.

FLASH radiotherapy: A new milestone in the field of cancer radiotherapy.

Radiotherapy plays a pivotal role in the control and eradication of tumors, but it can also induce radiation injury to surrounding normal tissues while targeting tumor cells. In recent years, FLASH-Radiotherapy (FLASH-RT) has emerged as a cutting-edge research focus in the field of radiation therapy. By delivering high radiation doses to the treatment target in an ultra-short time, FLASH-RT produces the FLASH effect, which reduces the toxicity to normal tissues while achieving comparable tumor control efficacy to conventional radiotherapy. This review provides a brief overview of the development history of FLASH-RT and its impact on tumor control. Additionally, it focuses on introducing the protective effects and molecular mechanisms of this technology on various normal tissues, as well as exploring its synergistic effects when combined with other tumor therapies. Importantly, this review discusses the challenges faced in translating FLASH-RT into clinical practice and outlines its promising future applications.

MPTN: A message-passing transformer network for drug repurposing from knowledge graph.

Drug repurposing (DR) based on knowledge graphs (KGs) is challenging, which uses knowledge graph reasoning models to predict new therapeutic pathways for existing drugs. With the rapid development of computing technology and the growing availability of validated biomedical data, various knowledge graph-based methods have been widely used to analyze and process complex and novel data to discover new indications for given drugs. However, existing methods need to be improved in extracting semantic information from contextual triples of biomedical entities. In this study, we propose a message-passing transformer network named MPTN based on knowledge graph for drug repurposing. Firstly, CompGCN is used as precoder to jointly aggregate entity and relation embeddings. Then, to fully capture the semantic information of entity context triples, the message propagating transformer module is designed. The module integrates the transformer into the message passing mechanism and incorporates the attention weight information of computing entity context triples into the entity embedding to update the entity embedding. Next, the residual connection is introduced to retain information as much as possible and improve prediction accuracy. Finally, MPTN utilizes the InteractE module as the decoder to obtain heterogeneous feature interactions in entity and relation representations and predict new pathways for drug treatment. Experiments on two datasets show that the model is superior to the existing knowledge graph embedding (KGE) learning methods.

Ferroptosis and inflammation are modulated by the NFIL3-ACSL4 axis in sepsis associated-acute kidney injury.

Sepsis-associated acute kidney injury (SA-AKI) increases the risk of death in patients with sepsis, and its major pathological change is the death of renal tubular cells. However, the mechanism of its occurrence remains unclear. Sepsis can lead to circadian dysregulation, and the rhythm gene NFIL3 has been reported to regulate lipid metabolism. There is compelling evidence that has demonstrated that lipid peroxidation can cause cellular ferroptosis. In this study, we established the in vitro and in vivo models of SA-AKI and confirmed the presence of ferroptosis of the renal tubular epithelial cells in SA-AKI. In addition, analysis of the GEO database showed that NFIL3 was highly expressed in sepsis patients and was highly correlated with the key molecule of ferroptosis, ACSL4. The in vitro and in vivo data suggested that NFIL3 was involved in ferroptosis and inflammation in SA-AKI. Subsequently, loss-of-function experiments revealed that NFIL3 knockdown attenuated ferroptosis and inflammation in renal tubular epithelial cells by downregulating ACSL4 expression, thus protecting SA-AKI. In conclusion, this study is the first to illustrate the involvement of the rhythm gene NFIL3 in SA-AKI, providing new insights and potential therapeutic targets for SA-AKI.

The utilization of single-cell sequencing technology in investigating the immune microenvironment of ccRCC.

The growth and advancement of ccRCC are strongly associated with the presence of immune infiltration and the tumor microenvironment, comprising tumor cells, immune cells, stromal cells, vascular cells, myeloid-derived cells, and extracellular matrix (ECM). Nevertheless, as a result of the diverse and constantly evolving characteristics of the tumor microenvironment, prior advanced sequencing methods have frequently disregarded specific less prevalent cellular traits at varying intervals, thereby concealing their significance. The advancement and widespread use of single-cell sequencing technology enable us to comprehend the source of individual tumor cells and the characteristics of a greater number of individual cells. This, in turn, minimizes the impact of intercellular heterogeneity and temporal heterogeneity of the same cell on experimental outcomes. This review examines the attributes of the tumor microenvironment in ccRCC and provides an overview of the progress made in single-cell sequencing technology and its particular uses in the current focus of immune infiltration in ccRCC.

The Influence Mechanism of Owners' Safety Management Behavior on Construction Workers' Safety Citizenship Behavior.

The safety citizenship behavior (SCB) of construction workers can improve project safety performance. This study explored how construction company owners' safety management behavior contributes to the development and encouragement of SCB. It combined the Job Demands-Resources (JD-R) and Stimulus-Organism-Response (SOR) theories to propose relevant hypotheses and develop a theoretical model to examine the effect of owners' safety management behavior on construction workers' SCB. Data from 534 construction workers were collected through questionnaires. Confirmatory Factor Analysis (CFA) and the Structural Equation Model (SEM) were used for empirical analysis. It was found that the owner's safety management behavior positively affected the construction workers' SCB. In particular, work engagement played an intermediary role, while power distance exhibited a moderating effect. A few noteworthy findings are that proactive safety behavior is significantly positively influenced by organization and coordination, prosocial safety behavior is significantly positively influenced by safety funding investment, and high power distance is not always bad for construction workers' safety citizenship behavior. By determining the connection between owners' safety management behavior and construction workers' SCB, this study offered a fresh perspective on promoting construction workers' proactive behavior and put forward suggestions for owners to improve project safety management.

Multiple pressures and vegetation conditions shape the spatiotemporal variations of ecosystem services in the Qinghai-Tibet Plateau.

Human activities and environmental change can impact the supply of ecosystem services (ESs) as pressures. Understanding the mechanisms of these impacts is crucial to support ecological conservation and restoration policy and applications. In this study, we highlighted the contribution of vegetation to mitigating these impacts on ESs in the Qinghai-Tibet Plateau (QTP) of China. First, we identified hot and cold spots of pressures from human activities and environmental factors and mapped the cumulative provision of five ESs (i.e., water yield, soil retention, carbon sequestration, habitat quality, and landscape aesthetics). Then, we clustered these ESs into five bundles based on their supply level. Furthermore, structural equation modeling was used to quantify the pathways of multiple pressures on ESs. The results indicated that 1) for 2000, 2010 and 2019, the percentages of hot spots with high pressure were 28.88%, 27.59% and 45.66% respectively, with significant spatial heterogeneity from northwest to southeast; 2) both regions with high and low cumulative ES values experienced increased volatility; and 3) the joint effects of multiple pressures shaped ESs through pressure-ES (direct) and pressure-vegetation-ES (indirect) pathways. Specifically, precipitation had the largest positive effect on regulating services (rα ≥ 0.76), and landscape fragmentation had the largest negative effect on cultural services (-0.10 ≤ rα ≤ -0.07). Vegetation played an important role in modulating multiple pressures on ESs. This study contributes to ecosystem management by effectively coping with anthropogenic and environmental pressures and sustaining the supply of ESs, particularly in alpine and plateau regions.

Landscape pattern and ecosystem services are critical for protected areas' contributions to sustainable development goals at regional scale.

Protected areas are essential for the conservation of biodiversity, natural and cultural resources, and contribute to regional and global sustainable development. However, since authorities and stakeholders concern more on the conservation targets of protected areas, how to better evaluate the protected areas' contributions to sustainable development goals (SDGs) remains generally understudied. To fill this knowledge gap, we chose the Qinghai-Tibet Plateau (QTP) as the study area, mapped the SDGs in 2010, 2015 and 2020, detecting the interactive relationships among SDGs. Then we used the landscape pattern indices and ecosystem service (ES) proxies to describe the characteristics of national nature reserves (NNRs), and explore the contributions of protected areas to SDGs using panel data models. The results showed that from 2010 to 2020, most cities of QTP improved their SDG scores to >60. The three cities with the best SDG performance improved their average scores by nearly 20 %. Among the 69 pairs correlations of SDG indicators, 13 synergies and 6 trade-offs were observed. About 65 % of the SDG indicators were significantly correlated with landscape pattern or ESs of NNRs. Carbon sequestration had a significant positive effect on 30 % of the SDG indicators, while habitat quality had a negative effect on 18 % of the SDG indicators. For the landscape pattern indices, the largest patch index had a significant positive effect on 18 % of the SDG indicators. This study highlighted that the ESs and landscape pattern could well quantify the contribution of protected areas to SDGs, which can provide essential implications for protected area management and regional sustainable development.

Integrative analysis of biodiversity, ecosystem services, and ecological vulnerability can facilitate improved spatial representation of nature reserves.

Understanding how to identify priority conservation areas for biodiversity and ecosystem services (ESs) is crucial for nature reserve (NR) optimization and regional planning. This study reports a regional assessment in Qinghai Province of China, quantifying the biodiversity and the provision of four ESs (carbon sequestration-net primary productivity (NPP), water yield, soil retention, and sandstorm prevention). The representativeness-vulnerability framework was employed to identify priority conservation areas for biodiversity and ESs, and the conservation gaps of existing NRs. The results show that the biodiversity, ES supply, and vulnerability of biodiversity and ESs to human activities present spatial heterogeneity. Except for sandstorm prevention, the high-value areas of ESs are generally in eastern or southern Qinghai. NPP, water yield, soil retention, and biodiversity are positively correlated (p < 0.01). The ten NRs in Qinghai only protected 5.59 %, 5.01 %, 4.29 %, 0.65 %, and 4.49 % of the priority conservation area for biodiversity, NPP, water yield, sandstorm prevention, and soil retention, respectively. Overall, a total of 170,932 km2 of theoretically comprehensive priority conservation areas for both biodiversity and ESs have been identified, which were mostly distributed in eastern, southern, and southeastern Qinghai. The existing NRs has notable conservation gaps (161,956 km2 accounting for 94.75 % of the targeted conservation areas) for both biodiversity and ESs. This study illuminates a strategy for strengthening both biodiversity and ESs through NR optimization, which is also applicable to other regions.

Potential value of mitochondrial regulatory pathways in the clinical application of clear cell renal cell carcinoma: a machine learning-based study.

BACKGROUND: Renal clear cell carcinoma (RCC) is a common cancer in urinary system with increasing incidence. At present, targeted therapy and immunotherapy are the main therapeutic programs in clinical therapy. To develop novel drugs and provide new ideas for clinical therapy, the identification of potential ccRCC subtypes and potential target genes or pathways has become a current research focus. AIM: The aim of this study was to explore the underlying mechanisms of mitochondrial function in ccRCC. This regulatory pathway is closely related to tumor development and metastasis in ccRCC patients, and their abnormal changes may affect the prognosis of cancer patients. Therefore, we decided to construct a prognostic model of ccRCC patients based on mitochondrial regulatory genes, aiming to provide new methods and ideas for clinical therapy. RESULT: The 5-year survival prediction model based on iterative LASSO reached 0.746, and the cox model based on coxph reached C-index = 0.77, integrated c/D AUC = 0.61, and integrated brier score = 0.14. The rsf model based on randomForestSRC was built with C-index = 0.82, integrated c/D AUC = 0.69, and integrated brier score = 0.11. The results show that mitochondrial regulatory pathway is a potential target pathway for clinical therapy of ccRCC, which can provide guidelines for clinical targeted therapy, immunotherapy and other first-line therapy.

Efficacy of Tai Chi on lower limb function of Parkinson's disease patients: A systematic review and meta-analysis.

Background: At present, the effect of Tai Chi (TC) on lower limb function in patients with Parkinson's disease (PD) is controversial. Therefore, we conducted a meta-analysis on the influence of TC on lower limb function in PD patients. Methods: According to the PRISMA guidelines, seven databases were searched. Randomized controlled trials (RCTS) were selected and screened according to inclusion and exclusion criteria. We assessed the quality of the studies using the Cochrane Risk of Bias tool and then extracted the characteristics of the included studies. The random effect model was adopted, and heterogeneity was measured by I 2 statistic. Results: A total of 441 articles were screened, and 10 high-quality RCTs were with a total of 532 patients with PD met Our inclusion criteria. Meta-analysis showed that compared To control groups TC improved several outcomes. TC significantly improved motor function (SMD = -0.70; 95% CI = -0.95, -0.45; p < 0.001; I 2 = 35%), although The results were not statistically significant for The subgroup analysis of TC duration (SMD = -0.70; 95% CI = -0.95, -0.45; p = 0.88; I 2 = 0%;). TC significantly improved balance function (SMD = 0.89; 95% CI = 0.51, 1.27; p < 0.001; I 2 = 54%), functional walking capacity (SMD = -1.24; 95% CI = -2.40, -0.09; p = 0.04; I 2 = 95%), and gait velocity (SMD = 0.48; 95% CI = -0.02, 0.94; p = 0.04; I 2 = 78%), But Did Not improve endurance (SMD = 0.31; 95% CI = -0.12, 0.75; p = 0.16; I 2 = 0%), step length (SMD = 0.01; 95% CI = -0.34, 0.37; p = 0.94; I 2 = 29%), and cadence (SMD = 0.06; 95% CI = -0.25, 0.36; p = 0.70; I 2 = 0%). Conclusion: TC has beneficial effects on motor function, balance function, functional walking ability, and gait velocity, but does not improve walking endurance, stride length, and cadence.