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Abstract During the train meeting events, train equipment compartments are exposed to the worst pressure changes, potentially affecting the ventilation performance of equipment, particularly for electrical facilities equipped with independent air ducts. In this paper, a two-step method is used for numerical computation: (1) obtaining the temporal and spatial transient node data of the flow field sections during the train-passing simulation and (2) using the data as the input data for the equipment compartment simulation. In addition, this paper also compares the difference in equipment ventilation between the single-train and train-passing scenarios in real vehicle tests. The results indicate that the primary factors influencing ventilation effectiveness are the aerodynamic compression and deceleration of airflow induced by the other train’s nose, as well as the instability of the external flow field in the wake of the other train. During train crossing, the air is forced into the air duct, with a maximum ratio of the airflow in-duct to the airflow out-duct reaching 3.2. The average mass flow falls below the rated mass flow for the converter. Compared to the rated air volume of converter, the maximum suppression rates obtained from testing and simulation are – 24.5% and – 16.8%, respectively. Compared to the single-train operation, the maximum suppression rates obtained from testing and simulation are – 15% and – 18%, respectively. These findings provide valuable insights into the design and operation of high-speed trains.

Tetrastigma hemsleyanum (TH) has attracted much attention for its heat clearing and detoxification effects, but whether it can become an effective feed supplement in chickens remains unclear. Herein, a total of 120 male Jinhua yellow chickens (two-mth-old) were randomly divided into into four groups (CON, TH-L, TH-M, and TH-H) for a 56-day feeding trial to explore its effects on growth performance and underlying mechanism. Results revealed that dietary TH notably increased the average daily growth (ADG), and decreased the average daily feed intake (ADFI) and feed conversion ratio (FCR) in TH-H group during 29-56 days. Meanwhile, dietary TH improved the development of duodenum and notably increased the contents of essential amino acids and flavor amino acids, while the serum oxidation stress index as well as abdominal fat deposition were not affected in Jinhua yellow chickens. Additionally, TH supplementation notably increased gut microbiota richness, then selectively increased the colonization of potential probiotics and the microbial abundance associated to amino acid synthesis and metabolic pathways in duodenum. Furthermore, qPCR analysis results preliminarily verified that dietary TH not only enhanced intestinal amino acids (rBAT and EAAT3) and peptides (PepT1 and APN) transport but also alleviated the inflammation (IL-1β, IL-6 and IFN-γ), thus thereby improved intestinal development and growth performance in Jinhua yellow chickens. These findings demonstrated that TH is a feed additive that can improve growth performance, muscle amino acids composition and intestinal development.

Abstract Background Studies have indicated a close association between genes linked to liquid–liquid phase separation (LLPS) and the progression of prostate cancer (PCa). However, the interplay among long non-coding RNAs (lncRNAs) linked to LLPS in PCa remains elusive. Therefore, we constructed a prediction model based on LLPS-related LncRNA in PCa to explore its relationship with the prognosis and drug treatment of PCa. Methods We obtained clinical and sequencing data from TCGA and LLPS genes from the Phase Separation Protein Database. By analyzing the differential expression of LLPS-related genes and lncRNAs in prostate cancer, and using Poisson correlation, we identified LLPS-related lncRNAs. Prognostic LLPS-lncRNAs were found through prognostic correlation analysis and included in a Cox model to compute regression coefficients. Patients were scored and divided into high- and low-risk groups. Independent prognostic factors were integrated into a prognostic nomogram with risk and Gleason scores. We also conducted drug sensitivity analyses, GSEA, and validated the impact of key lncRNAs through functional experiments. Results Our study identified five LLPS-associated lncRNAs that are of prognostic importance. And found notable disparities in biochemical recurrence rates and survival outcomes between these risk groups, with the low-risk cohort exhibiting superior prognostic indicators. Moreover, our prediction nomogram demonstrated robust predictive accuracy and significant clinical utility. Furthermore, our model exhibited promising capabilities in forecasting patient sensitivity to various conventional therapeutic drugs, thereby highlighting its potential in personalized treatment strategies. GSEA showed that these lncRNAs may influence PCa prognosis and sensitivity to therapeutic agents by affecting pathways such as cell cycle. Knockdown of AC009812.4 could inhibit the ability of PCa cells to proliferate, migrate and invade, and compare to paracancerous tissue, AC009812.4 in PCa tissue has significantly higher expression. Conclusion Our research uncovers the prognostic significance of lncRNAs associated with LLPS in PCa and established a model exhibiting excellent predictive accuracy for prognosis. Those lncRNAs may influence progress of PCa as well as sensitivity to therapy drugs through pathways such as cell cycle.

Abstract Purpose Prostate cancer (PCa) is a common malignancy in men, with an escalating mortality rate attributed to Recurrence and metastasis. Recent studies have illuminated collagen’s critical regulatory role within the tumor microenvironment, significantly influencing tumor progression. Accordingly, this investigation is dedicated to examining the relationship between genes linked to collagen and the prognosis of PCa, with the objective of uncovering any possible associations between them. Methods Gene expression data for individuals with prostate cancer were obtained from the TCGA repository. Collagen-related genes were identified, leading to the development of a risk score model associated with biochemical recurrence-free survival (BRFS). A prognostic nomogram integrating the risk score with essential clinical factors was crafted and evaluated for efficacy. The influence of key collagen-related genes on cellular behavior was confirmed through various assays, including CCK8, invasion, migration, cell cloning, and wound healing. Immunohistochemical detection was used to evaluate PLOD3 expression in prostate cancer tissue samples. Results Our study identified four key collagen-associated genes (PLOD3, COL1A1, MMP11, FMOD) as significant. Survival analysis revealed that low-risk groups, based on the risk scoring model, had significantly improved prognoses. The risk score was strongly associated with prostate cancer prognosis. Researchers then created a nomogram, which demonstrated robust predictive efficacy and substantial clinical applicability.Remarkably, the suppression of PLOD3 expression notably impeded the proliferation, invasion, migration, and colony formation capabilities of PCa cells. Conclusion The risk score, derived from four collagen-associated genes, could potentially act as a precise prognostic indicator for BRFS of patients. Simultaneously, our research has identified potential therapeutic targets related to collagen. Notably, PLOD3 was differentially expressed in cancer and para-cancer tissues in clinical specimens and it also was validated through in vitro studies and shown to suppress PCa tumorigenesis following its silencing.

ABSTRACT Background Early detection of bladder cancer (BCa) can have a positive impact on patients' prognosis. However, there is currently no widely accepted method for early screening of BCa. We aimed to develop an efficient, clinically applicable, and noninvasive method for the early screening of BCa by detecting specific serum miRNA levels. Methods A mixed‐cohort (including BCa, 12 different other cancers, benign disease patients, and health population) study was conducted using a sample size of 16,189. Five machine learning algorithms were utilized to develop screening models for BCa using the training dataset. The performance of the model was evaluated using receiver operating characteristic curve and decision curve analysis on the testing dataset, and subsequently, the model with the best predictive power was selected. Furthermore, the selected model's screening performance was evaluated using both the validation set and external set. Results The BCaS3miR model, utilizing only three serum miRNAs (miR‐6087, miR‐1343‐3p, and miR‐5100) and based on the KNN algorithm, is the superior screening model chosen for BCa. BCaS3miR consistently performed well in both the testing, validation, and external sets, exceeding 90% sensitivity and specificity levels. The area under the curve was 0.990 (95% CI: 0.984–0.991), 0.964 (95% CI: 0.936–0.984), and 0.917 (95% CI: 0.836–0.953) in the testing, validation, and external set. The subgroup analysis revealed that the BCaS3miR model demonstrated outstanding screening accuracy in various clinical subgroups of BCa. In addition, we developed a BCa screening scoring model (BCaSS) based on the levels of miR‐1343‐3p/miR‐6087 and miR‐5100/miR‐6087. The screening effect of BCaSS is investigated and the findings indicate that it has predictability and distinct advantages. Conclusions Using a mixed cohort with the largest known sample size to date, we have developed effective screening models for BCa, namely BCaS3miR and BCaSS. The models demonstrated remarkable screening accuracy, indicating potential for the early detection of BCa.

In light of continuous advancements in science and technology, the global economy is experiencing rapid growth. However, this growth has been accompanied by significant depletion of natural resources and environmental degradation. Consequently, there is a burgeoning global emphasis on energy conservation, emissions reduction, and sustainable development. In this study, based on the Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) databases from 1990 to 2022, a statistical analysis of energy conservation and emission reduction in alignment with Sustainable Development Goals (SDGs)-related publications was undertaken using biblimometric methods. The findings reveal that (1) In recent years, there has been a discernible increase in global research on this subject, especially since 2009, with a sustained trend of exceeding 100 publications per annum. China prominently contributing to this domain, the proportion reached 34.2%, reflecting a growing emphasis on eco-friendly development trends. (2) Due to the burgeoning significance of energy conservation and emission reduction, there has been a notable escalation in research efforts pertaining to “Energy and Fuels,” “Environmental Science” and “Green and Sustainable Science and Technology” and other related subjects. (3) Regarding the keyword analysis, “renewable energy” as the most frequently encountered term, often paired with “CO2 emissions.” This association underscores the pivotal role of renewable energy technologies in advancing green development initiatives and mitigating emissions. (4) China, United States and United Kingdom occupy central positions in terms of both paper publication volume and collaborative networks, collectively accounting for about 54.7%, and these countries are pivotal contributors to the scholarly discourse on sustainable development and environmental conservation. (5) From 1990 to 2022, the top 20 cited articles predominantly address diverse sub-goals of Sustainable Development Goal 7, with a common emphasis on enhancing energy efficiency, sustainability and renewable energy. These findings furnish valuable analytical insights for subsequent researchers investigating energy conservation and emission reduction as well as sustainable development endeavors.

Abstract Purpose Prostate cancer (PCa) is one of the major tumor diseases that threaten men’s health globally, and biochemical recurrence significantly impacts its prognosis. Disulfidptosis, a recently discovered cell death mechanism triggered by intracellular disulfide accumulation leading to membrane rupture, is a new area of research in the context of PCa. Currently, its impact on PCa remains largely unexplored. This study aims to investigate the correlation between long non-coding RNAs (lncRNAs) associated with disulfidptosis and the prognosis of PCa, seeking potential connections between the two. Methods Transcriptomic data for a PCa cohort were obtained from the Cancer Genome Atlas database. Disulfidptosis-related lncRNAs (DDRLs) were identified through differential expression and Pearson correlation analysis. DDRLs associated with biochemical recurrence-free survival (BRFS) were precisely identified using univariate Cox and LASSO regression, resulting in the development of a risk score model. Clinical factors linked to BRFS were determined through both univariate and multivariate Cox analyses. A prognostic nomogram combined the risk score with key clinical variables. Model performance was assessed using Receiver Operating Characteristic (ROC) curves, Decision Curve Analysis (DCA), and calibration curves. The functional impact of a critical DDRL was substantiated through assays involving CCK8, invasion, migration, and cell cloning. Additionally, immunohistochemical (IHC) staining for the disulfidptosis-related protein SLC7A11 was conducted. Results The prognostic signature included AC026401.3, SNHG4, SNHG25, and U73166.1 as key components. The derived risk score from these signatures stood as one of the independent prognostic factor for PCa patients, correlating with poorer BRFS in the high-risk group. By combining the risk score with clinical variables, a practical nomogram was created, accurately predicting BRFS of PCa patients. Notably, silencing AC026401.3 significantly hindered PCa cell proliferation, invasion, migration, and colony formation. IHC staining revealed elevated expression of the dithiosulfatide-related protein SLC7A11 in tumor tissue. Conclusions A novel prognostic signature for PCa DDRLs, possessing commendable predictive power, has been constructed, simultaneously providing potential therapeutic targets associated with disulfidptosis, among which AC026401.3 has been validated in vitro and demonstrated inhibition of PCa tumorigenesis after its silencing.

Abstract An efficient one-pot strategy for the facile synthesis of double boron–oxygen-fused polycyclic aromatic hydrocarbons (dBO-PAHs) with high regioselectivity and efficient skeletal editing is developed. The boron–oxygen-fused rings exhibit low aromaticity, endowing the polycyclic aromatic hydrocarbons with high chemical and thermal stabilities. The incorporation of the boron–oxygen units enables the polycyclic aromatic hydrocarbons to show single-component, low-temperature ultralong afterglow of up to 20 s. Moreover, the boron–oxygen-fused polycyclic aromatic hydrocarbons can also serve as ideal n-type host materials for high-brightness and high-efficiency deep-blue OLEDs; compared to single host, devices using boron–oxygen-fused polycyclic aromatic hydrocarbons-based co-hosts exhibit dramatically brightness and efficiency enhancements with significantly reduced efficiency roll-offs; device 9 demonstrates a high color-purity (Commission International de l’Eclairage CIEy = 0.104), and also achieves a record-high external quantum efficiency (28.0%) among Pt(II)-based deep-blue OLEDs with Commission International de l’Eclairage CIEy

Abstract Objective The primary aim of this study was to create a nomogram for predicting survival outcomes in penile cancer patients, utilizing data from the Surveillance, Epidemiology, and End Results (SEER) and a Chinese organization. Methods Our study involved a cohort of 5744 patients diagnosed with penile cancer from the SEER database, spanning from 2004 to 2019. In addition, 103 patients with penile cancer from Sun Yat‐sen Memorial Hospital of Sun Yat‐sen University were included during the same period. Based on the results of regression analysis, a nomogram is constructed and validated internally and externally. The predictive performance of the model was evaluated by concordance index (c‐index), area under the curve, decision curve analysis, and calibration curve, in internal and external datasets. Finally, the prediction efficiency is compared with the TNM staging model. Results A total of 3154 penile patients were randomly divided into the training group and the internal validation group at a ratio of 2:1. Nine independent risk factors were identified, including age, race, marital status, tumor grade, histology, TNM stage, and the surgical approach. Based on these factors, a nomogram was constructed to predict OS. The nomogram demonstrated relatively better consistency, predictive accuracy, and clinical relevance, with a c‐index over 0.73 (in the training cohort, the validation cohort, and externally validation cohort.) These evaluation indexes are far better than the TNM staging system. Conclusion Penile cancer, often overlooked in research, has lacked detailed investigative focus and guidelines. This study stands as the first to validate penile cancer prognosis using extensive data from the SEER database, supplemented by data from our own institution. Our findings equip surgeons with an essential tool to predict the prognosis of penile cancer better suited than TNM, thereby enhancing clinical decision‐making processes.

Abstract Background SPOCK3 is a secreted extracellular matrix proteoglycan. This study aimed to investigate the effect of SPOCK3 on the malignant progression of prostate cancer and to construct a prognostic model to predict DFS of patients with prostate cancer. Methods Clinical and transcriptome sequencing data for prostate cancer were download from the TCGA and GEO databases. The survival curve showed that SPOCK3 has prognostic significance. GO, KEGG, and GSEA enrichment analysis were used to investigate how SPOCK3 affects the malignant progression of prostate cancer. Based on ESTIMATE and ssGSEA, the relationship between SPOCK3 and immune cell infiltration in prostate cancer tissue was clarified. Univariate and multivariate COX regression analysis was used to identify the independent prognostic factors of prostate cancer OS and to construct a nomogram. The calibration curve and ROC curves were drawn to assess the nomogram's predictive power. Results The survival curve revealed that patients in the low-expression group of SPOCK3 had a poor prognosis. According to enrichment analysis, SOPCK3-related genes were enriched in collagen-containing extracellular matrix, PI3K-Akt, and MAPK signaling pathway. ESTIMATE analysis revealed that SPOCK3 expression was positively correlated with the interstitial score, immune score, and ESTIMATE score. The results of ssGSEA analysis revealed that the infiltration levels of Mast cells, NK cells, and B cells were higher in the SPOCK3 high expression group. Cox regression analysis showed that SPOCK3 expression level, T and Gleason score were independent risk factors of patient prognosis, and a nomogram was constructed. The ROC curve showed the AUCs of DFS at 2, 3, and 5 years. Conclusion SPOCK3 is a protective factor for DFS in prostate cancer patients. SPOCK3 is significantly associated with immune cell infiltration. The prognostic model constructed based on SPOCK3 has excellent predictive performance.

Assessing the effects of future urban expansion on ecosystem services (ESs) is essential for the sustainability of cities worldwide. Nonetheless, evaluating these effects of future urban expansion on ESs remains challenging due to the uncertainties associated with socioeconomic development and the intricate nature of urban expansion. In this research, we initially integrated the localized Shared Socioeconomic Pathways (SSPs) and the Land Use Scenario Dynamics-urban (LUSD-urban) model to project the urban expansion of the Yangtze River Delta urban agglomeration (YRDUA). Subsequently, we quantified the impacts of urban expansion on ESs utilizing the Integrated Valuation of ESs and Tradeoffs (InVEST) model. The outcomes indicate that the urban land in the YRDUA is projected to expand by 1,020.19–12,282.04 km2 at a growth rate of 3.71–44.67% from 2022 to 2050. Simultaneously, habitat quality (HQ), carbon storage (CS), water retention (WR), and air purification (AP) are expected to decline by 0.34–4.24%, 0.48–5.82%, 0.39–4.75% and 0.20–2.45%, correspondingly. Most importantly, the primary cause of ES losses is the conversion of cropland to urban land, accounting for more than 90% of the total ES losses. The results offer crucial contextual insights to support future synergistic development policies for urbanization and ecological conservation in the YRDUA under increased climate change.

Abstract Tea polyphenols (TP) are the most biologically active components in tea, with antioxidant, antiobesity, and antitumor properties, as well as the ability to modulate the composition and function of intestinal microbiota. This experimental study evaluated the chemical constituents of polyphenols in Pu-erh (PTP) and Dian Hong tea (DHTP). It also investigated the co-regulatory effects of PTP and DHTP on intestinal flora and liver tissues in mice using 16 S rRNA gene and transcriptome sequencing. The results revealed that DHT had higher concentrations of EGC (epigallocatechin), C (catechin), EC (epicatechin), and EGCG (epigallocatechin gallate). In contrast, PT had higher concentrations of GA (gallic acid), ECG (epicatechin-3-gallate), TF (theaflavin), and TB (theabrownin). PTP and DHTP consumption significantly reduced the rates of weight gain in mice. Microbial community diversity was significantly higher in PTP and DHTP-treated mice than in the control group. Notably, beneficial microbes such as Lactobacillus increased significantly in PTP-treated mice, whereas Lachnospiraceae increased significantly in DHTP-treated mice. Both PTP and DHTP improved the activity of the antioxidant enzymes (SOD) and total antioxidant capacity (T-AOC) in the liver. The transcriptome analysis revealed that the beneficial effects of PTP and DHTP were due to changes in various metabolic pathways, the majority of which were related to antioxidant and lipid metabolism. This study discovered that PTP and DHTP had beneficial effects in mice via the gut-liver axis.

Abstract Although dysregulated HMMR is linked to prostate cancer (PCa) prognosis, the precise mechanisms remain unclear. Here, we sought to elucidate the role of HMMR in PCa progression as well as underlying mechanism. Herein, we found that upregulation of HMMR frequently observed in PCa samples and was associated with poor prognosis. Additionally, HMMR significantly promoted PCa proliferation and metastasis through gain- and loss-of function approaches in vitro and in vivo. Mechanistically, HMMR may interact with AURKA and elevated AURKA protein level through inhibiting ubiquitination-mediated degradation, which subsequently activated mTORC2/AKT pathway to ensure the reinforcement of PCa progression. Moreover, upregulated E2F1 caused from sustained activation of mTORC2/AKT pathway in turn function as transcription factor to promote HMMR transcription, thereby forming a positive feedback loop to trigger PCa progression. Importantly, administration of the mTOR inhibitor partially antagonised HMMR-mediated PCa progression in vivo. In summary, we not only reveal a novel possible post-translation mechanism mediated by HMMR involved in AURKA regulation, but also describe a positive feedback loop that contributes to PCa deterioration, suggesting HMMR may serve as a potential promising therapeutic target in PCa.

Abstract Background Migration can be linked to the transmission of COVID-19. COVID-19 vaccine uptake and hesitancy among rural-to-urban migrant workers in China, the largest group of internal migrants in the world, has not been characterized. Objective To investigate COVID-19 vaccine uptake and identify vaccine hesitancy-associated factors among rural-to-urban migrant workers in the first round of COVID-19 vaccination in China. Methods A cross-sectional questionnaire-based survey was conducted, including 14,917 participants. Socio-demographics, COVID-19 vaccine uptake, vaccine hesitancy and its associated factors based on Vaccine Hesitancy Determinants Matrix (VHDM) were applied for the survey. Data were principally analyzed by logistic regression analysis. Results The COVID-19 vaccine uptake and vaccine hesitancy rates were 7.1% and 57.7%, respectively. Vaccine hesitancy was strongly associated with VHDM, including individual factors (female, higher annual income and fewer medical knowledge), group factors (less family support, friend support and public opinion support), COVID-19 epidemic factors (lower fatality, infection and emotional distress) and vaccine factors (less vaccine necessity, vaccine safety, vaccine efficacy, vaccine importance and vaccine reliability). Conclusion The VHDM model has the potential utility in efforts to reduce COVID-19 vaccine hesitancy. Greater efforts should be put into addressing positive predictors associated with vaccine hesitancy.

Due to Butylparaben (BuP) widespread application in cosmetics, food, pharmaceuticals, and its presence as an environmental residue, human and animal exposure to BuP is common, potentially posing hazards to both human and animal health. Congenital heart disease is already a serious problem. However, the effects of BuP on the developing heart and its underlying mechanisms remain unclear. Here, zebrafish embryos were exposed to environmentally and human-relevant concentrations of BuP (0.6 mg/L, 1.2 mg/L, and 1.8 mg/L, calculated but not measured) at 6 h post-fertilization (hpf) and were treated until 72 hpf. Exposure to BuP led to cardiac morphological defects and cardiac dysfunction in zebrafish embryos, manifesting symptoms similar to systolic heart failure. The etiology of BuP-induced systolic heart failure in zebrafish embryos is multifactorial, including cardiomyocyte apoptosis, endocardial and atrioventricular valve damage, insufficient myocardial energy, impaired Ca2+ homeostasis, depletion of cardiac-resident macrophages, cardiac immune non-responsiveness, and cardiac oxidative stress. However, excessive accumulation of reactive oxygen species (ROS) in the cardiac region and cardiac immunosuppression (depletion of cardiac-resident macrophages and cardiac immune non-responsiveness) may be the predominant factors. In conclusion, this study indicates that BuP is a potential hazardous substance that can cause adverse effects on the developing heart and provides evidence and insights into the pathological mechanisms by which BuP leads to cardiac dysfunction. It may help to prevent the BuP-based congenital heart disease heart failure in human through ameliorating strategies and BuP discharge policies, while raising awareness to prevent the misuse of preservatives.

Utility-scale solar energy (USSE) and rooftop solar PV generate about 70% and 30% of all solar electricity. While the adoption of rooftop solar in the United States (U.S.) has been explored in depth, how USSE is spatially distributed has yet to be discussed. This study examines the spatial distribution of solar power plants of 1 MW and above across regions of different socio-demographic characteristics in the U.S. and the impact of solar policy on the spatial distribution using the Geographical Detector Model (GDM) and Kernel Density analysis. The results show that: 1) the distribution of USSE has significant spatial disparity across different socio-economic communities and is not entirely following solar irradiance abundancy; 2) contrary to rooftop solar, USSE is more distributed in more ethnically diverse regions and regions with higher renter percent, which can mitigate the energy inequity issue in rooftop solar PV's tilt toward white communities and house owners; 3) similar to rooftop solar, USSE is also more adopted by groups of higher income levels; 4) The solar policy is an effective tool in promoting USSE but is also exacerbating the spatial disparity of USSE. The findings of this study help to understand better how to mitigate potential inequity during the energy transition toward a renewable and sustainable future.

The growth of Residential rooftop solar (RRS) in some western countries has predominantly been driven by individual or market behaviour and has been extensively studied. However, the development landscape of RRS in China differs, and its driving mechanisms remain unclear. To address this research gap, we investigate the spatial distribution pattern and driving factors of RRS growth using city-level data on RRS installation. Employing the Geographical Detector Model, we calculate indicators to identify the contributions of various socio-economic factors to RRS growth and the strength of their interactions. Our key findings include: 1) significant spatial heterogeneity in RRS growth across regions with different natural and socio-economic characteristics, which impact RRS growth in two patterns: one-way and inverted U-shaped; 2) although solar radiation abundancy is important, air pollution and certain socio-economic factors appear more influential, be it comparing between the eastern and western China, or north and south; 3) the significance of fiscal subsidies has diminished, but benchmark electricity prices (BEP) could serve as a useful alternative; 4) substantial synergistic effects exist between different factors, with environmental and demographic factors displaying particularly strong synergies with others, suggesting that they are essential considerations for future RRS planning. Our findings contribute to a comprehensive understanding of RRS development in China and hold critical implications for future policy design.

Due to the advantages such as low multi-solution, high signal-to-noise ratio, low environmental impact, high efficiency and low cost, microbial prospection for oil and gas has been accepted for petroleum exploreration. With the rapid development of high-throughput sequencing, molecular biology and bioinformatics, describing the changes of specific oil and gas indicator micro-organisms from the perspective of microbial community as a whole has become an valuable progress of microbial exploration method for the future. In this paper, soil sampling, DNA extraction and analysis, discriminant model development and favorable area prediction are introduced, and soil DNA extraction as well as oil/gas indicator micro-organism detection are emphasized. With the study of industrial-grade DNA extraction technology, Griffth method has been considered as the best effect for the extraction and purification of soil microbial DNA. For projects with a large sample number, high-throughput pipetting workstations and commercial multi-well plate DNA extraction kits can greatly improve working efficiency. Integrated stable isotope probes and the molecular detection of high-throughput sequencing showed that the main hydrocarbon indicator microorganism strains typically imply the expected distribution. High frequency oil indicator bacteria (AMNR) are Arthrobacter, Mycobacterium, Nocardia, and Rhodospirillum, while high frequency gas indicator bacteria include Methylococcus, Methylobacterium, and Methylocystis. The preliminary application in the Hangjinqi area shows that the microbial molecular exploration technology can significantly improve the oil and gas identification accuracy in loess tableland regions, and has a good effect on the evaluation of oil and gas bearing property, which provides a reference for the selection of favorable tight gas regions in the northern part of Ordos Basin.

Methane-oxidizing bacteria (MOB) have long been recognized as an important bioindicator for oil and gas exploration. However, due to their physiological and ecological diversity, the distribution of MOB in different habitats varies widely, making it challenging to authentically reflect the abundance of active MOB in the soil above oil and gas reservoirs using conventional methods. Here, we selected the Puguang gas field of the Sichuan Basin in Southwest China as a model system to study the ecological characteristics of methanotrophs using culture-independent molecular techniques. Initially, by comparing the abundance of the pmoA genes determined by quantitative PCR (qPCR), no significant difference was found between gas well and non-gas well soils, indicating that the abundance of total MOB may not necessarily reflect the distribution of the underlying gas reservoirs. 13C-DNA stable isotope probing (DNA-SIP) in combination with high-throughput sequencing (HTS) furthermore revealed that type II methanotrophic Methylocystis was the absolutely predominant active MOB in the non-gas-field soils, whereas the niche vacated by Methylocystis was gradually filled with type I RPC-2 (rice paddy cluster-2) and Methylosarcina in the surface soils of gas reservoirs after geoscale acclimation to trace- and continuous-methane supply. The sum of the relative abundance of RPC-2 and Methylosarcina was then used as specific biotic index (BI) in the Puguang gas field. A microbial anomaly distribution map based on the BI values showed that the anomalous zones were highly consistent with geological and geophysical data, and known drilling results. Therefore, the active but not total methanotrophs successfully reflected the microseepage intensity of the underlying active hydrocarbon system, and can be used as an essential quantitative index to determine the existence and distribution of reservoirs. Our results suggest that molecular microbial techniques are powerful tools for oil and gas prospecting.

Thrombosis is a key pathological event in cardiovascular diseases and is also the most important targeting process for their clinical management. In this study, arachidonic acid (AA) was used to induce thrombus formation in zebrafish larvae. Blood flow, red blood cell (RBCs) aggregation and cellular oxidative stress were measured to evaluate the antithrombotic effect of Tibetan tea (TT). Meanwhile, the potential molecular mechanism was further explored by transcriptome sequencing (RNA-seq). The results indicated that TT could significantly restore heart RBCs intensity of thrombotic zebrafish, whilst decreasing RBCs accumulation in the caudal vein. The transcriptome analysis revealed that the preventive effect of TT on thrombosis could be mostly attributed to changes in lipid metabolism related signaling pathways, such as fatty acid metabolism, glycerollipid metabolism, ECM-receptor interaction and steroid biosynthesis signaling pathway. This study demonstrated that Tibetan tea could alleviate thrombosis by reducing oxidative stress levels and regulating lipid metabolism.

Abstract Background Bladder cancer is the second most common malignant tumor in the urogenital system. The research investigated the prognostic role of immune‐related long non‐coding RNA (lncRNA) in bladder cancer. Methods We extracted 411 bladder cancer samples from The Cancer Genome Atlas database. Single‐sample gene set enrichment analysis was employed to assess the immune cell infiltration of these samples. We recognized differentially expressed lncRNAs between tumors and paracancerous tissues, and differentially expressed lncRNAs between the high and low immune cell infiltration groups. Venn diagram analysis detected differentially expressed lncRNAs that intersected the above groups. LncRNAs with prognostic significance were identified by regression analysis. Multivariate Cox analysis was used to establish the risk score model. Then we established and evaluated the nomogram. Additionally, we performed gene set enrichment analysis to explore the potential functions of the screened lncRNAs in tumor pathogenesis. Results Three hundred and twenty differentially expressed lncRNAs were recognized. We randomly divided patients into the training data set and the testing data set at a 2: 1 ratio. In the training data set, 9 immune‐related lncRNAs with prognostic significance were identified. The risk score model was constructed to classify patients as high‐ and low‐risk cohorts. Patients in the low‐risk cohort had better survival outcomes than those in the high‐risk cohort. The nomogram was established based on the indicators including age, gender, tumor‐node‐metastases stage, and risk score. The model's predictive performance was confirmed by the receiver operating characteristic curve analysis, concordance index method, calibration curve, and decision curve analysis. The testing data set also achieved similar results. Bioinformatics analysis suggested that the 9‐lncRNA signature was involved in the modulation of various immune responses, antigen processing and presentation, and T cell receptor signaling pathway. Conclusions Our study uncovered the prognostic value of immune‐related lncRNAs for bladder cancer and showed that they may regulate tumor pathogenesis in various ways.

An accurate parameter extraction of the proton exchange membrane fuel cell (PEMFC) is crucial for establishing a reliable cell model, which is also of great significance for subsequent research on the PEMFC. However, because the parameter identification of the PEMFC is a nonlinear optimization problem with multiple variables, peaks, and a strong coupling, it is difficult to solve this problem using traditional numerical methods. Furthermore, because of insufficient current and voltage data measured by the PEMFC, the precision rate of cell parameter extraction is also very low. The study proposes a parameter extraction method using a generalized regression neural network (GRNN) and meta-heuristic algorithms (MhAs). First of all, a GRNN is used to de-noise and predict the data to solve the problems in the field of PEMFC, which include insufficient data and excessive noise data of the measured data. After that, six typical algorithms are used to extract the parameters of the PEMFC under three operating conditions, namely high temperature and low pressure (HTLP), medium temperature and medium pressure (MTMP), and low temperature and high pressure (LTHP). The last results demonstrate that the application of GRNN can prominently decrease the influence of data noise on parameter identification, and after data prediction, it can greatly enhance the precision rate and reliability of MhAs parameter identification, specifically, under HTLP conditions, the V-I fitting accuracy achieved 99.39%, the fitting accuracy was 99.07% on MTMP, and the fitting accuracy was 98.70%.

BackgroundPrevious studies suggest that alcohol dependence is associated with depression, however, the effect of alcohol dependence varies from individual to individual, which may be due to different genetic backgrounds. The interactions between alcohol dependence and different gene polymorphisms may finally shape the onset of depression. Neuropeptide Y (NPY), which can maintain homeostasis from high-stress stimulation, may protect individuals from the onset of depression. Here, we explored whether the NPY rs16147:T>C has an association with depression in individuals with alcohol dependence during the period of alcohol dependence withdrawal.MethodsA total of 455 males with alcohol dependence were recruited. The scale of Michigan Alcoholism Screening Test (MAST) and Self-Depression Scale (SDS) were respectively used to analyze the condition of alcohol dependence and depression. Genomic DNA was extracted from each blood sample and NPY polymorphisms were genotyped. The interaction between NPY rs16147:T>C and alcohol dependence on depression was first analyzed. Then, region of significance analysis was used to confirm which model provided the best fit for the interaction (diathesis-stress or differential susceptibility). Finally, by using internal replication analyses, the accuracy and robustness of the interaction results were improved.ResultsAlcohol dependence was positively correlated with depression. CC homozygotes of NPY rs16147:T>C exhibited less depression when exposed to low alcohol dependence, but more depression when exposed to high alcohol dependence. Individuals with the T allele showed the opposite result.ConclusionNPY rs16147:T>C might be correlated with susceptibility for depression in males during alcohol dependence withdrawal. The findings support the differential susceptibility model.

Microbial prospecting for oil and gas (MPOG) is a surface exploration technology derived from the principle of light hydrocarbon micro-seepage from oil and gas reservoirs. The light hydrocarbons (C1-C5) in oil and gas reservoirs permeate the overlying sedimentary layer in the way of micro-seepage, which induces the growth of microorganisms specializing in the consumption of light hydrocarbons in near-surface soil. As a result, the microbial concentration and community structure in oil and gas areas will be different from that without underlying oil and gas reservoirs. By analyzing the abnormal characteristics of microbial concentration and community structure, the oil and gas enrichment areas and oil and gas reservoirs are predicted. In recent years, the research team has established sample acquisition and pretreatment techniques for different geomorphology and surface types, and combined with traditional culturing and molecular biology methods, the precise diagnosis of oil and gas from the perspective of both hydrocarbon indication microorganism quantity and community structure is realized. The artificial simulation results lasting three years show that there are obvious differences and responsive relationships between the microorganisms and community structure under the acclimation of different hydrocarbon components. The strains found are consistent with the actual oil and gas reservoir, providing a theory basis for microbial exploration. In addition, the correlation among environmental conditions, hydrocarbon geochemistry and hydrocarbon microbial group distribution was studied using different oil and gas reservoir types and different geographical conditions. The rule of microbial community in situ of oil and gas reservoir samples was analyzed, and a database of oil and gas indicators in typical oil and gas basins in China was preliminarily constructed. The results showed that the surface microbial anomaly was closely related to the location of oil and gas reservoirs, and can reflectthe characteristics of oil and gas reservoirs of different types. Combined with petroleum geology and geophysical data, the microbial exploration technology can effectively predict the favorable enrichment areas of oil and gas. This paper also presents nine development trends of MPOG.

In recent years, microbial analysis has become a new detection technology in oil and gas surface exploration. The microbial diversity above a shale gas field was studied in order to further understand microbial information. High-throughput sequencing technology was used to study the abundance and diversity of hydrocarbon species in a shale gas field in the Dingshan area of the southeastern Sichuan Basin. Three main microorganisms were identified, including Methylophilales, Methylocystis, and Methylococcus, which are worthy of further biochemical research and can be used as potential oil and gas indicating bacteria. The developmental abundance of three kinds of microorganisms has a good matching relationship with the distribution of the fugitive area in Dingshan. The high-throughput analytical technology can be applied well in the study of oil and gas microorganisms in Dingshan area, and the distribution characteristics of microorganisms in bedrock samples were obtained. Furthermore, a preliminary analysis of the differences between oil and gas microbes in Dingshan and Jiaoshiba areas was made, indicating that the identified potential oil and gas indicating bacteria deserve further study.

The outbreak of COVID-19 epidemic has increased work demands for medical staff and has a certain impact on their mental health. The present study aimed to examine the role of perceived stress and social support in explaining the association between the occupational stressors and three mental health symptoms (i.e., anxiety, depression, and insomnia) of frontline medical staff. Five hundred twenty five frontline medical staff were investigated online after the outbreak of the COVID-19 (16 February, 2020–2 March, 2020) in China. The results found that the prevalence of anxiety, depression, and insomnia among frontline medical staff were 39.8, 29.9, and 37.9%, respectively. Occupational stressors were associated with anxiety, depression, and insomnia symptoms. Perceived stress significantly mediated this link. Social support moderated the second half of the indirect effect of occupational stressors on anxiety and depression symptoms. Under the epidemic situation of COVID-19, for frontline medical staff, high perceived stress and low social support may increase vulnerability for mental health symptoms triggered by occupational stressors. Thus, improving the social support and promoting the cognitive reappraisal of perceived stress may help to maintain mental health among medical staff.

Abstract Background To compare the safety and efficacy of retrograde intrarenal surgery (RIRS) and modified Ultra-mini percutaneous nephrolithotomy (UMP) in semi-supine combined lithotomy position for the management of 1.5–3.5 cm lower pole renal stones (LPSs). Methods A total of 63 patients with 1.5–3.5 cm LPSs who underwent RIRS (n = 33) or modified UMP (n = 30) in diameter between January 2017 and January 2019 were analyzed retrospectively. Modified UMP was performed in semi-supine combined lithotomy position and a 9.5/11.5 F ureteral access sheath (UAS) was inserted during the procedure in order to maintain low pelvic pressure and to facilitate the removal of stone fragments. Base-line parameters, stone characteristics, illness condition, operation time, postoperative hemoglobin (Hb) drop, postoperative creatinine (Cr) elevation, length of hospital stay, length of postoperative hospital stay, stone-free rate (SFR) and complications were compared between the two groups. Results There were no significant differences between the two groups in base-line parameters, stone characteristics and illness condition. The mean operating time of RIRS group was longer than UMP group (95.61 ± 21.9 vs. 55.0 ± 16.1 min, p

Background and Aims: Nicotine dependence (ND)-induced anxiety might be modulated by genetic polymorphisms. The gene-by-environment interaction can be fitted into the diathesis-stress and differential susceptibility models. Nevertheless, knowledge of the interaction between adiponectin (ADPN) polymorphisms and ND on the incident mental disorder is currently scarce. This study aims to understand the role of ADPN rs266729 on anxiety in patients with ND while elucidating the psychology model and the various reactions across genotypes. Methods: We included 315 Chinese males with confirmed ND, measured using the Fagerstrom test for nicotine dependence (FTND). Anxiety was assessed using the Self-rating Anxiety Scale. Genomic DNA was extracted and genotyped from peripheral blood. Hierarchical regression models were used to test the interactions. Results: There was a significant interaction between ADPN rs266729 and ND (β = –0.19, p < 0.05). The CC homozygote was more likely to be affected by ND-induced anxiety (β = 0.14, t = 4.43, p < 0.01). Re-parameterized regression models revealed that the interaction between ADPN rs266729 and ND could fit the strong differential susceptibility model (R2 = 0.05, p < 0.001). Conclusions: ADPN rs266729 was correlated with susceptibility to anxiety symptoms among male adults with ND and could fit the differential susceptibility model. The CC homozygote of rs266729 was a plasticity factor that increased anxiety symptoms in individuals with ND.

BackgroundProstate cancer (PCa) is one of the most prevalent cancers among males, and its mortality rate is increasing due to biochemical recurrence (BCR). Glycolysis has been proven to play an important regulatory role in tumorigenesis. Although several key regulators or predictors involved in PCa progression have been found, the relationship between glycolysis and PCa is unclear; we aimed to develop a novel glycolysis-associated multifactor prediction model for better predicting the prognosis of PCa.MethodsDifferential mRNA expression profiles derived from the Cancer Genome Atlas (TCGA) PCa cohort were generated through the “edgeR” package. Glycolysis-related genes were obtained from the GSEA database. Univariate Cox and LASSO regression analyses were used to identify genes significantly associated with disease-free survival. ROC curves were applied to evaluate the predictive value of the model. An external dataset derived from Gene Expression Omnibus (GEO) was used to verify the predictive ability. Glucose consumption and lactic production assays were used to assess changes in metabolic capacity, and Transwell assays were used to assess the invasion and migration of PC3 cells.ResultsFive glycolysis-related genes were applied to construct a risk score prediction model. Patients with PCa derived from TCGA and GEO (GSE70770) were divided into high-risk and low-risk groups according to the median. In the TCGA cohort, the high-risk group had a poorer prognosis than the low-risk group, and the results were further verified in the GSE70770 cohort. In vitro experiments demonstrated that knocking down HMMR, KIF20A, PGM2L1, and ANKZF1 separately led to less glucose consumption, less lactic production, and inhibition of cell migration and invasion, and the results were the opposite with GPR87 knockdown.ConclusionThe risk score based on five glycolysis-related genes may serve as an accurate prognostic marker for PCa patients with BCR.

Background Although immune checkpoint inhibitors (ICIs), especially programmed cell death protein 1 (PD-1)/programmed death ligand 1 (PD-L1) axis blockers, exhibit prominent antitumor effects against numerous malignancies, their benefit for patients with prostate cancer (PCa) has been somewhat marginal. This study aimed to assess the feasibility of B7-H3 or HHLA2 as alternative immunotherapeutic targets in PCa.Methods Immunohistochemistry was performed to evaluate the expression pattern of PD-L1, B7-H3 and HHLA2 and the infiltration of CD8+ and Foxp3+ lymphocytes in 239 PCa tissues from two independent cohorts. The correlations between B7-H3 and HHLA2 and clinicopathological features, including the presence of CD8+ and Foxp3+ tumor-infiltrating lymphocytes (TILs), were explored.Results HHLA2 expression was much higher than PD-L1 expression but lower than B7-H3 expression in PCa tissues. High expression of both B7-H3 and HHLA2 was significantly associated with higher Gleason score and tumor stage, lymph node metastasis and dismal overall survival (OS) and cancer-specific survival (CSS). Moreover, a high B7 score, defined as high B7-H3 expression and/or high HHLA2 expression, was an independent prognostic predictor for PCa. Of note, a high B7 score was negatively correlated with CD8+ TILs. Importantly, a new immune classification, based on the B7 score and CD8+ TILs, successfully stratified OS and CSS in PCa.Conclusions Both B7-H3 and HHLA2 have a critical impact on the immunosuppressive microenvironment, and the B7 score could be used as an independent prognostic factor for PCa. The B7 score combined with CD8+ TILs could be used as a new immune classification to stratify the risk of death, especially cancer-related death, for patients with PCa. These findings may provide insights that could improve response to immune-related comprehensive therapy for PCa in the future.

During sexual reproduction the parental homologous chromosomes find each other (pair) and align along their lengths by integrating local sequence homology with large-scale contiguity, thereby allowing for precise exchange of genetic information. The Synaptonemal Complex (SC) is a conserved zipper-like structure that assembles between the homologous chromosomes, bringing them together and regulating exchanges between them. However, the molecular mechanisms by which the SC carries out these functions remain poorly understood. Here we isolated and characterized two mutations in the dimerization interface in the middle of the SC zipper in C. elegans. The mutations perturb both chromosome alignment and the regulation of genetic exchanges. Underlying the chromosome-scale phenotypes are distinct alterations to the way SC subunits interact with one another. We propose a model whereby the SC brings homologous chromosomes together through two activities: obligate zipping that prevents assembly on unpaired chromosomes; and a tendency to extend pairing interactions along the entire length of the chromosomes.

This paper focuses on investigating the dynamic cross-correlation relationship between online sentiment and returns of major global stock markets based on the MF-DCCA method. We use Daily Happiness (DHS), an index derived from Twitter posts through textual analysis as a proxy of online sentiment. By dividing the global financial markets into developed and developing ones, we are able to test the heterogeneous relationship between stock market performance and sentiment at different economic developing level. Empirical results show that there exists a power-law cross-correlation relationship between financial market and online sentiment in some developed countries and all developing countries, and the relationship is more stable in the developing countries. Moreover, we apply rolling window analysis to capture the dynamic evolution characteristics and find the relationship has a strong consistency over time. Our work provides a much more delicate perspective to test the relationship between online sentiment and financial markets performance and enriches the existing literature.

Abstract Background The gold standard for bladder cancer detection is cystoscopy, which is an invasive procedure that causes discomfort in patients. The currently available non-invasive approaches either show limited sensitivity in low-grade tumours or possess unsatisfying specificity. The aim of the present study is to develop a new non-invasive strategy based on chromosomal imbalance levels to detect bladder cancer effectively. Methods We enrolled 74 patients diagnosed with bladder cancer (BC), 51 healthy participants and 27 patients who were diagnosed with non-malignant urinary disease (UD). The Chromosomal Imbalance Analysis (CIA) was conducted in the tumours and urine of participants via the multiple annealing and looping-based amplification cycles-next-generation sequencing (MALBAC-NGS) strategy. The threshold of the CIA was determined with the receiver operating characteristic (ROC) curve. The comparison of the CIA with voided urine cytology was also performed in a subgroup of 55 BC patients. The consistency and discrepancy of the different assays were studied with the Kappa analysis and the McNemar test, respectively. The performance of the urinary CIA was also validated in an additional group of 120 BC patients, 15 UD and 45 healthy participants. Results Good concordance (87.0%) in the assessments of patient tumour tissues and urine was observed. The urine-based evaluation also demonstrated a good performance (accuracy = 89.0%, sensitivity = 83.1%, specificity = 94.5%, NPV = 85.4% and PPV = 93.7%; AUC = 0.917, 95%CI =0.868–0.966, P

Abstract Background MicroRNAs have emerged as critical modulators of carcinogenesis and tumor progression including renal cell carcinoma (RCC). MiR-622 plays as a tumor inhibitor in some types of cancer, however, its role in kidney cancer is unknown. The purpose of the present work is to investigate the functional behaviors and regulatory mechanism of miR-622 in RCC. Results We examined the expression of miR-622 in RCC and adjacent normal tissues and then explored the roles of miR-622. The results of this analysis indicated that miR-622 activity was significantly downregulated in RCC tissues compared with the corresponding normal tissues, so did in RCC cell lines. MiR-622 was associated with RCC aggressiveness. MiR-622 in RCC cells decreased CCL18 expression and suppressed CCL18 activated MAPK signal pathway. Using Western blot and luciferase reporter assays, it was verified that CCL18 was a direct target of miR-622. A specific and inverse correlation between miR-622 and CCL18 expression was found in human RCC samples. Conclusions The results demonstrated that miR-622 acted as a tumor-promoting miRNA by targeting CCL18 in RCC.

Intermetallics: dislocation climb promotes precipitate dissolution Instead of gliding, dislocations in intermetallic precipitates interact to climb, leaving defects behind. Qing Zhou and colleagues at Xi’an Jiaotong University in China and their collaborators in the United States of America used molecular dynamics simulations to investigate the interactions of dislocations in intermetallic precipitates in aluminium-copper during deformation. They showed that instead of traditional glide, dislocations that do not lie on the same plane can interact by climbing then gliding along a new atomic plane without cancelling each other out, leaving vacancies behind. This defect creation happened faster at higher temperatures, creating extended dislocation cores and vacancy clusters that could facilitate precipitate dissolution. Research into intermetallic stability during deformation may thus help us avoid failure of alloys strengthened with precipitates.

Nanoparticles (NPs) are intensively investigated as adjuvants in new generation vaccines, while how these NPs promote the immune responses has not been well understood. In this research, we have tried to elucidate the possible pathways for layered double hydroxide (LDH) NPs to provoke immune responses. As previously reported, LDH NPs efficiently deliver antigens to antigen presenting cells (APCs). In this research, we have found that these internalized LDH NPs are not released by these APCs within 8 h. We have for the first time found that macrophage cells exchange the internalized LDH NPs with other surrounding ones, which may promote immune responses in an additional way. Moreover, the internalized LDH-antigen NPs significantly facilitate the maturation of immature DCs and enhance cross-presentation of epitope/MHC class I complexes on the DC surface. This research would help understand the NP adjuvant mechanism and further assist the design of new specific NPs as more efficient nano-adjuvants.

Catalytic cutting by metal particles under an atmosphere environment is a promising method for patterning graphene. Here, long straight micro-trenches are produced by the sliding of metal particles (Ag and In) on epitaxial graphene (EG) substrate under the ultra-high vacuum (UHV) annealing. The morphology and orientation relationship of the micro-trenches are observed by scanning electron microscopy (SEM), and the damage effect is confirmed by Raman scattering. Atomic force microscopy (AFM) and scanning tunneling microscopy (STM) are further adopted to atomically characterize the sliding behavior of metal particles, which resembles a similar etching method and can be used to make graphene nano-trenches. The study provides us with more understanding about the mutual effects between metals on EG, which hopes to pave the way for the applications of graphene-based devices.

In men with adverse prognostic factors (APFs) after radical prostatectomy (RP), the most appropriate timing to administer radiotherapy remains a subject for debate. We conducted a systemic review and meta-analysis to evaluate the therapeutic strategies: adjuvant radiotherapy (ART) and salvage radiotherapy (SRT).We comprehensively searched PubMed, EMBASE, Web of Science and the Cochrane Library and performed the meta-analysis of all randomized controlled trials (RCTs) and retrospective comparative studies assessing the prognostic factors of ART and SRT.Between May 1998 and July 2012, 2 matched control studies and 16 retrospective studies including a total of 2629 cases were identified (1404 cases for ART and 1185 cases for SRT). 5-year biochemical failure free survival (BFFS) for ART was longer than that for SRT (Hazard Ratio [HR]: 0.37; 95% CI, 0.30-0.46; p

BACKGROUND: With the establishment of minimally invasive surgery in society, the robot has been increasingly widely used in the urologic field, including in partial nephrectomy. This study aimed to comprehensively summarize the currently available evidence on the feasibility and safety of robotic partial nephrectomy for renal tumors of >4 cm. METHOD AND FINDINGS: An electronic database search of PubMed, Scopus, Web of Science, and the Cochrane Library was performed. This systematic review and meta-analysis was based on all relevant studies that assessed robotic partial nephrectomy for renal tumors of >4 cm. Five studies were included. The meta-analysis involved 3 studies from 11 institutions including 154 patients, while the narrative review involved the remaining 2 studies from 5 institutions including 64 patients. In the meta-analysis, the mean ischemic time, operation time, and console time was 28, 319, and 189 minutes, respectively. The estimated blood loss and length of stay was 317 ml and 3.8 days, respectively. The rates of conversion, positive margins, intraoperative complications, postoperative complications, hilar clamping, and collecting system repair were 7.0%, 3.5%, 7.0%, 9.8%, 93.9%, and 47.5%, respectively. The narrative review showed results similar to those of the meta-analysis. CONCLUSIONS: Robotic partial nephrectomy is feasible and safe for renal tumors of >4 cm with an acceptable warm ischemic time, positive margin rate, conversion rate, complication rate, operation time, estimated blood loss, and length of stay.