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Abstract Background Prostate cancer (PCa) is the second leading cause of tumor-related mortality in men. Metastasis from advanced tumors is the primary cause of death among patients. Identifying novel and effective biomarkers is essential for understanding the mechanisms of metastasis in PCa patients and developing successful interventions. Methods Using the GSE8511 and GSE27616 data sets, 21 metastasis-related genes were identified through the weighted gene co-expression network analysis (WGCNA) method. Subsequent functional analysis of these genes was conducted on the gene set cancer analysis (GSCA) website. Cluster analysis was utilized to explore the relationship between these genes, immune infiltration in PCa, and the efficacy of targeted drug IC50 scores. Machine learning algorithms were then employed to construct diagnostic and prognostic models, assessing their predictive accuracy. Additionally, multivariate COX regression analysis highlighted the significant role of POLD1 and examined its association with DNA methylation. Finally, molecular docking and immunohistochemistry experiments were carried out to assess the binding affinity of POLD1 to PCa drugs and its impact on PCa prognosis. Results The study identified 21 metastasis-related genes using the WGCNA method, which were found to be associated with DNA damage, hormone AR activation, and inhibition of the RTK pathway. Cluster analysis confirmed a significant correlation between these genes and PCa metastasis, particularly in the context of immunotherapy and targeted therapy drugs. A diagnostic model combining multiple machine learning algorithms showed strong predictive capabilities for PCa diagnosis, while a transfer model using the LASSO algorithm also yielded promising results. POLD1 emerged as a key prognostic gene among the metastatic genes, showing associations with DNA methylation. Molecular docking experiments supported its high affinity with PCa-targeted drugs. Immunohistochemistry experiments further validated that increased POLD1 expression is linked to poor prognosis in PCa patients. Conclusions The developed diagnostic and metastasis models provide substantial value for patients with prostate cancer. The discovery of POLD1 as a novel biomarker related to prostate cancer metastasis offers a promising avenue for enhancing treatment of prostate cancer metastasis.

Abstract The lubrication performance of a straight-line conjugate internal meshing gear pump is poor under the low-speed, high-pressure operating conditions of the volumetric servo speed control system, and it is difficult to establish a full fluid lubricating oil film between the gear ring and the housing. This leads to significant wear and severe heating between the gear ring and the housing. The lubrication performance of the interface moving pair of the electro-hydraulic actuator pump gear ring housing can be improved by designing a reasonable lubrication bearing structure for the gear ring housing. In this study, a multi-field coupling multi-objective optimization model was established to improve lubrication performance and volumetric efficiency. The whole model consists of the dynamic model of the gear ring components, the fluid lubrication model of the gear ring housing interface, the oil film formation and sealing model considering the influence of temperature, and the multi-objective optimization model. The comprehensive performance of the straight-line conjugate internal meshing gear pump was verified experimentally using a test bench. The results show that the lubrication performance is improved, the mechanical loss is reduced by 31.52%, and the volumetric efficiency is increased by 4.91%.

This paper proposes a virtual position-offset injection based permanent magnet temperature estimation approach for permanent magnet synchronous machines (PMSMs). The concept of virtual position-offset injection is mathematically transforming the machine model to a virtual frame with a position-offset. The virtual frame temperature estimation model is derived to calculate the permanent magnet temperature (PMT) directly from the measurements with computation efficiency. The estimation model involves a combined inductance term, which can simplify the establishment of saturation compensation model with less measurements. Moreover, resistance and inverter distorted terms are cancelled in the estimation model, which can improve the robustness to the winding temperature rise and inverter distortion. The proposed approach can achieve simplified computation in temperature estimation and reduced memory usage in saturation compensation. While existing model-based approaches could be affected by either the need of resistance and inverter information or complex saturation compensation. Experiments are conducted on the test machine to verify the proposed approach under various operating conditions.

BackgroundMonocytes play a critical role in tumor initiation and progression, with their impact on prostate adenocarcinoma (PRAD) not yet fully understood. This study aimed to identify key monocyte-related genes and elucidate their mechanisms in PRAD.MethodUtilizing the TCGA-PRAD dataset, immune cell infiltration levels were assessed using CIBERSORT, and their correlation with patient prognosis was analyzed. The WGCNA method pinpointed 14 crucial monocyte-related genes. A diagnostic model focused on monocytes was developed using a combination of machine learning algorithms, while a prognostic model was created using the LASSO algorithm, both of which were validated. Random forest and gradient boosting machine singled out CCNA2 as the most significant gene related to prognosis in monocytes, with its function further investigated through gene enrichment analysis. Mendelian randomization analysis of the association of HLA-DR high-expressing monocytes with PRAD. Molecular docking was employed to assess the binding affinity of CCNA2 with targeted drugs for PRAD, and experimental validation confirmed the expression and prognostic value of CCNA2 in PRAD.ResultBased on the identification of 14 monocyte-related genes by WGCNA, we developed a diagnostic model for PRAD using a combination of multiple machine learning algorithms. Additionally, we constructed a prognostic model using the LASSO algorithm, both of which demonstrated excellent predictive capabilities. Analysis with random forest and gradient boosting machine algorithms further supported the potential prognostic value of CCNA2 in PRAD. Gene enrichment analysis revealed the association of CCNA2 with the regulation of cell cycle and cellular senescence in PRAD. Mendelian randomization analysis confirmed that monocytes expressing high levels of HLA-DR may promote PRAD. Molecular docking results suggested a strong affinity of CCNA2 for drugs targeting PRAD. Furthermore, immunohistochemistry experiments validated the upregulation of CCNA2 expression in PRAD and its correlation with patient prognosis.ConclusionOur findings offer new insights into monocyte heterogeneity and its role in PRAD. Furthermore, CCNA2 holds potential as a novel targeted drug for PRAD.

Abstract Wind has been admitted as one of the most promising renewable energy resources in multinational regionalization policies. However, the energy conversion and utilization are challenging due to the technique reliability and cost issues. Hydraulic wind turbine (HWT) may solve the above problems. HWT is taken as a research object, and the maximum power point tracking (MPPT) control strategy is proposed collaborating with active disturbance rejection control (ADRC) and linear quadratic regulator (LQR) control methods, to solve multiplicative nonlinearity problems in the plant models and the influence of external disturbance on control performance in the MPPT control process. A nonlinear simulation model is built to explain the main findings from the experiments and obtain a better understanding of the effect of time‐varying system parameters and random fluctuation in wind speed. The collaborative control algorithm is experimentally verified on a 24‐kW HWT semi‐physical test platform that results in a promising energy conversion rate, plus the hydraulic parameters can satisfy the demand, accordingly. Ultimately, the potential challenges of implementing this technique in a smart wind energy conversion system are discussed to give a further design guidance, either theoretically or practically.

BackgroundAngiogenesis, the process of forming new blood vessels from pre-existing ones, plays a crucial role in the development and advancement of cancer. Although blocking angiogenesis has shown success in treating different types of solid tumors, its relevance in prostate adenocarcinoma (PRAD) has not been thoroughly investigated.MethodThis study utilized the WGCNA method to identify angiogenesis-related genes and assessed their diagnostic and prognostic value in patients with PRAD through cluster analysis. A diagnostic model was constructed using multiple machine learning techniques, while a prognostic model was developed employing the LASSO algorithm, underscoring the relevance of angiogenesis-related genes in PRAD. Further analysis identified MAP7D3 as the most significant prognostic gene among angiogenesis-related genes using multivariate Cox regression analysis and various machine learning algorithms. The study also investigated the correlation between MAP7D3 and immune infiltration as well as drug sensitivity in PRAD. Molecular docking analysis was conducted to assess the binding affinity of MAP7D3 to angiogenic drugs. Immunohistochemistry analysis of 60 PRAD tissue samples confirmed the expression and prognostic value of MAP7D3.ResultOverall, the study identified 10 key angiogenesis-related genes through WGCNA and demonstrated their potential prognostic and immune-related implications in PRAD patients. MAP7D3 is found to be closely associated with the prognosis of PRAD and its response to immunotherapy. Through molecular docking studies, it was revealed that MAP7D3 exhibits a high binding affinity to angiogenic drugs. Furthermore, experimental data confirmed the upregulation of MAP7D3 in PRAD, correlating with a poorer prognosis.ConclusionOur study confirmed the important role of angiogenesis-related genes in PRAD and identified a new angiogenesis-related target MAP7D3.

The three-degree-of-freedom (3-DoF) parallel mechanism (PM) is widely used due to its simple structure and ability to avoid coupling problems commonly found in high-DoF PMs. The conventional control approach is usually independent control for each branch of the mechanism using a PID controller, without considering the consistency among branches. This paper proposes a novel cooperative control strategy for the 3-DoF PM to achieve both synchronized and differential motion. A pneumatic actuated test rig was constructed to validate the effectiveness of the cooperative controller. The results demonstrate our control approach outperforms the PID controller. Our self-designed platform is functional and intuitive, which can be regarded as a control scheme test bench for a 3-DoF PM.

A valve-controlled hydraulic motor system operating in a complex environment is subject to complex load changes. In extreme cases, the load can be regarded as a disturbance signal with complex frequency and strong amplitude fluctuations, which greatly affects the speed stability of the hydraulic motor and reduces the operating efficiency. In this paper, the structure of valve-controlled hydraulic motor systems is analyzed, and a valve-controlled hydraulic motor system model with uncertain parameters is established after considering the actual target parameter error and model linearization error. Different from the common H-infinity control, which regards the load disturbance as external disturbance, this paper presents a robust H-infinity tracking control strategy, which considers uncertain parameters and the load torque of the valve-controlled hydraulic motor system as internal disturbances. The simulation results show that the proposed control scheme has better control characteristics and robustness than the traditional PID control.

Strongylocentrotus intermedius is an economically valuable sea urchin species in China. However, its growth and survival are severely constrained by ocean warming and the hypoxia that often accompanies high water temperatures. MicroRNAs (miRNAs) are important regulators of gene expression in response to environmental change. In this study, high-throughput RNA sequencing was used to investigate changes in miRNA expression in S. intermedius under heat (25°C), hypoxia (2 mg/L O2), and combined heat and hypoxia stresses. Twelve small RNAs libraries were constructed and 17, 14, and 23 differentially expressed miRNAs (DEMs) were identified in the heat, hypoxia, and combined stress groups (P

Background/objectives: To assess the effects of clinical factors and treatments on the overall survival (OS) of patients with prostate sarcomas. Methods: We reported 41 cases diagnosed with prostate sarcomas from eight hospitals in China and retrospectively analyzed the prognostic factors by combining our data with cases from five previously published cohorts, including one extra Chinese cohort and four cohorts from US cohorts. Additionally, we investigated the differences in treatment regimens between China (n = 66) and the USA (n = 74). Results: The median survival time of the 41 cases was 18.6 months (95% confidence interval [CI]: 13.9–23.2). The status of negative distant metastasis (P = 0.004) and radical tumor resection with negative margin (P = 0.001) were significantly associated with better overall survival, whereas age, tumor size, duration of initial symptoms, and chemo/radiotherapy were not significantly related to OS. The survival time was longer in patients with rhabdomyosarcoma than in those with leiomyosarcoma (P = 0.049). Combined analysis of the current and 5 prior cohorts showed that more patients in the US cohorts underwent radical surgery (P = 0.005), and the overall survival was better among those with radical cystoprostatectomy compared to those with radical prostatectomy alone (P = 0.008). Conclusion: Radical resection to achieve a negative margin contributes to better survival for patients with prostate sarcoma.

Objective: To conduct a meta-analysis assessing the perioperative, functional and oncological outcomes of partial nephrectomy (PN) and radical nephrectomy (RN) for T1b tumours. The primary endpoints were the oncological outcomes. The secondary endpoints were the perioperative and functional outcomes. Methods: A systematic literature review was performed by searching multiple databases through February 2019 to identify eligible comparative studies according to the Preferred Reporting Items for Systematic Review and Meta-analysis statement. Identified reports were assessed according to the Newcastle-Ottawa Scale for nonrandomized controlled trials. Results: Overall, 13 retrospective cohort studies were included in the analysis. Patients undergoing PN were younger (weighted mean difference [WMD] −3.49 years, 95% confidence interval [CI] −5.16 to −1.82; p

Abstract Background Organoids play an important role in basic research, drug screening, and regenerative medicine. Here, we aimed to develop a novel kind of three-dimensional (3D) organoids generated from urine-derived stem cells (USCs) and to explore whether kidney-specific extracellular matrix (kECM) could enable such organoids for renal function in vitro. Methods USCs were isolated from human urine samples and cultured with kECM extraction to generate 3D organoids in vitro. Eight densities from 1000 to 8000 cells per organoids were prepared, and both ATP assay and Live/Dead staining were used to determine the optimal USC density in forming organoids and kECM additive concentration. The morphology and histology of as-made organoids were evaluated by hematoxylin and eosin (H.E.) staining, immunofluorescence staining and whole mount staining. Additionally, RT-qPCR was implemented to detect renal-related gene expression. Drug toxicity test was conducted to evaluate the potential application for drug screening. The renal organoids generated from whole adult kidney cells were used as a positive control in multiple assessments. Results The optimized cell density to generate ideal USC-derived organoids (USC-organoids) was 5000 cells/well, which was set as applying density in the following experiments. Besides, the optimal concentration of kECM was revealed to be 10%. On this condition, Live/Dead staining showed that USC-organoids were well self-organized without significant cell death. Moreover, H.E. staining showed that compact and viable organoids were generated without obvious necrosis inside organoids, which were very close to renal organoids morphologically. Furthermore, specific proximal tubule marker Aquaporin-1 (AQP1), kidney endocrine product erythropoietin (EPO), kidney glomerular markers Podocin and Synaptopodin were detected positively in USC-organoids with kECM. Nephrotoxicity testing showed that aspirin, penicillin G, and cisplatin could exert drug-induced toxicity on USC-organoids with kECM. Conclusions USC-organoids could be developed from USCs via an optimal procedure. Combining culture with kECM, USC-organoid properties including morphology, histology, and specific gene expression were identified to be similar with real renal organoids. Additionally, USC-organoids posed kECM in vitro showed the potential to be a drug screening tool which might take the place of renal organoids to some extent in the future.

OBJECTIVE: This review aimed to confirm the association between ambient temperature and incidence of urolithiasis and evaluate the impact thereof. METHODS: A systematic literature review was performed up to September 2019 using multiple databases. The effect of temperature on urolithiasis risk was assessed using risk ratio (RR). Pearson correlation coefficient (Pearson’s r) was used to evaluate the linear association between ambient temperature and urolithiasis incidence. The non-linear association between climatic temperature and the urolithiasis incidence was also evaluated. RESULTS: Twenty-four studies related to the temperature and urolithiasis risk in 14 different countries or regions of five continent involving over 2.5 million cases were included in the meta-analysis. High climatic or workplace temperature was a significant risk factor of urolithiasis. The weighted correlation coefficient (Pearson’s r) of monthly temperature and urolithiasis risk was 0.49 [95% confidence interval (CI) 0.40–0.57], a moderate correlation (0.4

Summary: Objective: To report our experience in treating endophytic renal tumor by robot-assisted partial nephrectomy (RPN) with a standard laparoscopic ultrasound probe and our original approach for separating renal mass. Methods: All patients with endophytic renal tumor who underwent RPN in our department from January 2015 to December 2017 were retrospectively analyzed. All surgeries were performed by transperitoneally by a single, experienced surgeon. Baseline characteristics, tumor characteristics, operative profile and follow-up data were collected. Results: Among these 29 patients, 23 patients were male. The mean age of patients was 47.42 years old. 69% (20/29) tumors were completely endophytic tumors. The average tumor size was 3.1 cm. The average R.E.N.A.L. score was 9.0. Tumors from 3 patients were pathologically confirmed to be renal angiomyolipomas. And the rest were malignant including 23 clear cell renal cell carcinoma and 3 chromophobe renal cell carcinoma. The mean operative time was 3.0 h. The mean warm ischemia time was 22.3 min. All tumor margins were pathologically confirmed negative. No patient needed blood transfusion. Two patients presented had Grade II complication. Both of them had a fever after surgery with body temperature over 38 °C, leading to a prolonged postoperative hospitalization time. The mean postoperative hospitalization time was 6.8 days. During mean 21.3-month follow-up, no patient was confirmed to relapse by CT scan. Conclusion: RPN with a standard laparoscopic ultrasound probe is safe, effective and feasible in treating endophytic renal tumor. Our original approach for separating renal mass can avoid some problems caused by the standard laparoscopic ultrasound probe. Keywords: Robot-assisted partial nephrectomy, Standard laparoscopic ultrasound probe, Retrospective study

Histone lysine methyltransferases (HMT) comprise a subclass of epigenetic regulators; dysregulation of these enzymes affects gene expression, which may lead to tumorigenesis. Here, we performed an integrated analysis of 50 HMTs in bladder cancer and found intrinsic links between copy number alterations, mutations, gene expression levels, and clinical outcomes. Through integrative analysis, we identified six HMT genes (PRDM9, ASH1L, SETD3, SETD5, WHSC1L1, and KMT2D) that may play a key role in the development and progression of bladder cancer. Of these six HMTs, histone lysine N‐methyltransferase 2D (KMT2D) exhibited the highest mutation rate in bladder cancer. Our comparison of the mRNA and miRNA expression profiles of mutated and wild‐type KMT2D suggested that two signaling pathways (FOX1–miR‐1224‐5p–DLK1 and HIF/GATA5–miR‐133a‐3p–DRD5) may mediate the tumor suppressive effect of the KMT2D mutation. In summary, our findings indicate that mutations in HMT genes, especially KMT2D mutation, may play a role in the development of bladder cancer.

Dysregulation of transcription factors contributes to the carcinogenesis and progression of cancers. However, their roles in clear cell renal cell carcinoma remain largely unknown. This study aimed to evaluate the clinical significance of TFs and investigate their potential molecular mechanisms in ccRCC. Data were accessed from the cancer genome atlas kidney clear cell carcinoma cohort. Bioinformatics algorithm was used in copy number alterations mutations, and differentially expressed TFs’ analysis. Univariate and multivariate Cox regression analyses were performed to identify clinically significant TFs and construct a six-TF prognostic panel. TFs’ expression was validated in human tissues. Gene set enrichment analysis (GSEA) was utilized to find enriched cancer hallmark pathways. Functional experiments were conducted to verify the cancer-promoting effect of BARX homeobox 1 (BARX1) and distal-less homeobox 4 (DLX4) in ccRCC, and Western blot was performed to explore their downstream pathways. As for results, many CNAs and mutations were identified in transcription factor genes. TFs were differentially expressed in ccRCC. An applicable predictive panel of six-TF genes was constructed to predict the overall survival for ccRCC patients, and its diagnostic efficiency was evaluated by the area under the curve (AUC). BARX1 and DLX4 were associated with poor prognosis, and they could promote the proliferation and migration of ccRCC. In conclusion, the six-TF panel can be used as a prognostic biomarker for ccRCC patients. BARX1 and DLX4 play oncogenic roles in ccRCC via promoting proliferation and epithelial–mesenchymal transition. They have the potential to be novel therapeutic targets for ccRCC.

The kidney function of patients with chronic kidney disease (CKD) is impaired irreversibly. Organ transplantation is the only treatment to restore kidney function in CKD patients. The assessment of new potential therapeutic procedures relies heavily on experimental animal models, but it is limited by its human predictive capacity. In addition, the frequently used two-dimensional in vitro human renal cell models cannot replicate all the features of the in vivo situation. In this study, we developed a three-dimensional (3D) in vitro human renal organoid model from whole kidney cells as a promising drug screening tool. At present, the renal tissue generated from human pluripotent stem cells (hPSCs) exhibits intrinsic tumorigenicity properties. Here we first developed a 3D renal organoid culture system that originated from adult differentiated cells without gene modification. Renal organoids composed of multiple cell types were created under optimal experimental conditions and evaluated for morphology, viability and erythropoietin production. As a novel screening tool for renal toxicity, 3D organoids were exposed to three widely used drugs: aspirin, penicillin G and cisplatin. The study results showed this 3D renal organoid model can be used as a drug screening tool, a new in vitro 3D human kidney model, and provide hope for potential regenerative therapies for CKD.

In this research, on an Illumina platform, the full mitochondrial genome of Holothuria spinifera was listed in a sequence and also gathered by using the NovoPlasty v. 2.7.1. It was submitted to NCBI GenBank, and is available with accession number MN816440. The size of genome was 15,812 bp and contained 12 protein-coding genes, two rRNA genes, and 22 tRNA genes. The configuration of A + T in Holothuria spinifera mtDNA was 60.44%. Except five tRNAs and ND6, others are placed on the H-strand. By using the Neighbor-Joining method by software MEGA5.0, the phylogenetic relationship of 13 species of sea cucumber was analyzed. Holothuria spinifera was most closely associated to Parastichopus parvimensis.

In this study, the complete mitochondrial genome of Holothuria fuscocinerea was sequenced on an Illumina platform and assembled using NovoPlasty v. 2.7.1. It was submitted to NCBI GenBank and is available with accession number MN542416. The genome was 15,827 bp in size and contains 22 tRNA genes, 12 protein-coding genes, and 2 rRNA genes. The composition of A + T in Holothura spinifera mtDNA was 60.30%. Except ND6 and 5 tRNAs, the others are not on the H-strand. The phylogenetic relationship of 13 species of sea cucumber were analyzed using the neighbor-joining method by software MEGA5.0. Holothuria fuscocinerea was most closely related to Holothuria polii.

Background Histone lysine methyltransferases (HMTs), a category of enzymes, play essential roles in regulating transcription, cellular differentiation, and chromatin construction. The genomic landscape and clinical significance of HMTs in renal cell carcinoma (RCC) remain uncovered. Methods We conducted an integrative analysis of 50 HMTs in RCC and discovered the internal relations among copy number alterations (CNAs), expressive abundance, mutations, and clinical outcome. Results We confirmed 12 HMTs with the highest frequency of genetic alterations, including seven HMTs with high-level amplification, two HMTs with somatic mutation, and three HMTs with putative homozygous deletion. Patterns of copy number and expression varied among different subtypes of RCC, including clear cell renal cell carcinoma, papillary cell carcinoma, and chromophobe renal carcinoma. Kaplan–Meier survival analysis and multivariate analysis identified that CNA or mRNA expression in some HMTs were significantly associated with shorter overall patient survival. Systematic analysis identified six HMTs (ASH1L, PRDM6, NSD1, EZH2, WHSC1L1, SETD2) which were dysregulated by genetic alterations as candidate therapeutic targets. Discussion In summary, our findings strongly evidenced that genetic alteration of HMTs may play an important role in generation and development of RCC, which lays a solid foundation for the mechanism for further research in the future.