Developing and validating a nomogram for penile cancer survival: A comprehensive study based on SEER and Chinese data.

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.

A novel bioprospecting strategy via 13C-based high-throughput probing of active methylotrophs inhabiting oil reservoir surface soil.

Methane-oxidizing bacteria (MOB) have long been considered as a microbial indicator for oil and gas prospecting. However, due to the phylogenetically narrow breath of ecophysiologically distinct MOB, classic culture-dependent approaches could not discriminate MOB population at fine resolution, and accurately reflect the abundance of active MOB in the soil above oil and gas reservoirs. Here, we presented a novel microbial anomaly detection (MAD) strategy to quantitatively identify specific indicator methylotrophs in the surface soils for bioprospecting oil and gas reservoirs by using a combination of 13C-DNA stable isotope probing (SIP), high-throughput sequencing (HTS), quantitative PCR (qPCR) and geostatistical analysis. The Chunguang oilfield of the Junggar Basin was selected as a model system in western China, and type I methanotrophic Methylobacter was most active in the topsoil above the productive oil wells, while type II methanotrophic Methylosinus predominated in the dry well soils, exhibiting clear differences between non- and oil reservoir soils. Similar results were observed by quantification of Methylobacter pmoA genes as a specific bioindicator for the prediction of unknown reservoirs by grid sampling. A microbial anomaly distribution map based on geostatistical analysis further showed that the anomalous zones were highly consistent with petroleum, geological and seismic data, and validated by subsequent drilling. Over seven years, a total of 24 wells have been designed and drilled into the targeted anomaly, and the success rate via the MAD prospecting strategy was 83 %. Our results suggested that molecular techniques are powerful tools for oil and gas prospecting. This study indicates that the exploration efficiency could be significantly improved by integrating multi-disciplinary information in geophysics and geomicrobiology while reducing the drilling risk to a greater extent.

The predictive significance of chromobox family members in prostate cancer in humans.

PURPOSE: The Chromobox (CBX) family proteins are crucial elements of the epigenetic regulatory machinery and play a significant role in the development and advancement of cancer. Nevertheless, there is limited understanding regarding the role of CBXs in development or progression of prostate cancer (PCa). Our objective is to develop a unique prognostic model associated with CBXs to improve the accuracy of predicting outcomes of patients with PCa. METHODS: Data from TCGA and GEO databases were analyzed to assess differential expression, prognostic value, gene pathway enrichment, and immune cell infiltration. COX regression analysis was utilized to identify the independent prognostic factors that impact disease-free survival (DFS). The expression of CBX2 and FOXP3+ cells infiltration was verified by immunohistochemical staining of clinical tissue sections. In vitro proliferation, migration and invasion assay were conducted to examine the function of CBX2. RNA-seq was employed to examine the CBX2 related pathway enrichment. RESULTS: CBX2, CBX3, CBX4, and CBX8 were upregulated, while CBX6 and CBX7 were downregulated in PCa tissues. CBXs expression varied by stage and grade. Elevated expression of CBX1, CBX2, CBX3, CBX4 and CBX8 is correlated with poor outcome. CBX2 expression, T stage, and Gleason score were independent prognostic factors. The expression level of CBX2 in PCa tissues was significantly higher than that in adjacent normal tissues. More Treg infiltration was observed in the group with high CBX2 expression. CBX2 expression affected PCa cell growth, migration, and invasion. CONCLUSIONS: CBX2 is involved in the development and advancement of PCa, suggesting its potential as a reliable prognostic indicator for PCa patients.

Identifying Active Rather than Total Methanotrophs Inhabiting Surface Soil Is Essential for the Microbial Prospection of Gas Reservoirs.

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.

Establishment of a prognostic risk prediction model incorporating disulfidptosis-related lncRNA for patients with prostate cancer.

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.

Single-cell analysis extracted CAFs-related genes to established online app to predict clinical outcome and radiotherapy prognosis of prostate cancer.

BACKGROUND: Cancer-associated fibroblasts (CAFs) play a significant role in regulating the clinical outcome and radiotherapy prognosis of prostate cancer (PCa). The aim of this study is to identify CAFs-related genes (CAFsRGs) using single-cell analysis and evaluate their potential for predicting the prognosis and radiotherapy prognosis in PCa. METHODS: We acquire transcriptome and single-cell RNA sequencing (scRNA-seq) results of PCa and normal adjacent tissues from The GEO and TCGA databases. The "MCPcounter" and "EPIC" R packages were used to assess the infiltration level of CAFs and examine their correlation with PCa prognosis. ScRNA-seq and differential gene expression analyses were used to extract CAFsRGs. We also applied COX and LASSO analysis to further construct a risk score (CAFsRS) to assess biochemical recurrence-free survival (BRFS) and radiotherapy prognosis of PCa. The predictive efficacy of CAFsRS was evaluated by ROC curves and subgroup analysis. Finally, we integrated the CAFsRS gene signature with relevant clinical features to develop a nomogram, enhancing the predictive accuracy. RESULTS: The abundance of CAFs is associated with a poor prognosis of PCa patients. ScRNA-seq and differential gene expression analysis revealed 323 CAFsRGs. After COX and LASSO analysis, we obtained seven CAFsRGs with prognostic significance (PTGS2, FKBP10, ENG, CDH11, COL5A1, COL5A2, and SRD5A2). Additionally, we established a risk score model based on the training set (n = 257). The ROC curve was used to confirm the performance of CAFsRS (The AUC values for 1, 3 and 5-year survival were determined to be 0.732, 0.773, and 0.775, respectively.). The testing set (n = 129), GSE70770 set (n = 199) and GSE116918 set (n = 248) revealed that the model exhibited exceptional predictive performance. This was also confirmed by clinical subgroup analysis. The violin plot demonstrated a statistically significant disparity in the CAFs infiltrations between the high-risk and low-risk groups of CAFsRS. Further analysis confirmed that both CAFsRS and T stage were independent prognostic factors for PCa. The nomogram was then established and its excellent predictive performance was demonstrated through calibration and ROC curves. Finally, we developed an online prognostic prediction app ( https://sysu-symh-cafsnomogram.streamlit.app/ ) to facilitate the practical application of the nomogram. CONCLUSIONS: The prognostic prediction risk score model we constructed could accurately predict BRFS and radiotherapy prognosis PCa, which can provide new ideas for clinicians to develop personalized PCa treatment and follow-up programs.

Mechanism of prognostic marker SPOCK3 affecting malignant progression of prostate cancer and construction of prognostic model.

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.

In-silico annotation of the chemical composition of Tibetan tea and its mechanism on antioxidant and lipid-lowering in mice.

BACKGROUND/OBJECTIVES: Tibetan tea is a kind of dark tea, due to the inherent complexity of natural products, the chemical composition and beneficial effects of Tibetan tea are not fully understood. The objective of this study was to unravel the composition of Tibetan tea using knowledge-guided multilayer network (KGMN) techniques and explore its potential antioxidant and hypolipidemic mechanisms in mice. MATERIALS/METHODS: The C57BL/6J mice were continuously gavaged with Tibetan tea extract (T group), green tea extract (G group) and ddH2O (H group) for 15 days. The activity of total antioxidant capacity (T-AOC) and superoxide dismutase (SOD) in mice was detected. Transcriptome sequencing technology was used to investigate the molecular mechanisms underlying the antioxidant and lipid-lowering effects of Tibetan tea in mice. Furthermore, the expression levels of liver antioxidant and lipid metabolism related genes in various groups were detected by the real-time quantitative polymerase chain reaction (qPCR) method. RESULTS: The results showed that a total of 42 flavonoids are provisionally annotated in Tibetan tea using KGMN strategies. Tibetan tea significantly reduced body weight gain and increased T-AOC and SOD activities in mice compared with the H group. Based on the results of transcriptome and qPCR, it was confirmed that Tibetan tea could play a key role in antioxidant and lipid lowering by regulating oxidative stress and lipid metabolism related pathways such as insulin resistance, P53 signaling pathway, insulin signaling pathway, fatty acid elongation and fatty acid metabolism. CONCLUSIONS: This study was the first to use computational tools to deeply explore the composition of Tibetan tea and revealed its potential antioxidant and hypolipidemic mechanisms, and it provides new insights into the composition and bioactivity of Tibetan tea.

Effects of Pu-erh and Dian Hong tea polyphenols on the gut-liver axis in mice.

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.

Circular RNA circARHGEF28 inhibited the progression of prostate cancer via the miR-671-5p/LGALS3BP/NF-κB axis.

Circular RNAs (circRNAs) play crucial roles in various biological processes, including prostate cancer (PCa). However, the precise roles and mechanism of circRNAs are complicated. Hence, we studied the function of a circRNA that might be involved in the progression of PCa. In this study, we found that circARHGEF28 was frequently downregulated in PCa tissues and cell lines. Furthermore, gain- and loss-of function experiments in vitro showed that circARHGEF28 inhibited proliferation, migration, and invasion of PCa. Additionally, circARHGEF28 suppressed PCa progression in vivo. Bioinformatics analysis and RNA pull-down and capture assay found that circARHGEF28 sponged miR-671-5p in PCa cells. Importantly, qRT-PCR and dual luciferase assays found that Lectin galactoside-binding soluble 3 binding protein (LGALS3BP) was downstream of miR-671-5p, and western blot analysis further confirmed that LGALS3BP negatively regulated the nuclear factor kappa-B (NF-κB) pathway. These results demonstrated that circARHGEF28 abolished the degradation of LGALS3BP by sponging miR-671-5p, thus blocking the activation of the NF-κB pathway. Our findings revealed that circARHGEF28/miR-671-5p/LGALS3BP/NF-κB may be an important axis that regulates PCa progression.

Mock circulatory loop applications for testing cardiovascular assist devices and in vitro studies.

The mock circulatory loop (MCL) is an in vitro experimental system that can provide continuous pulsatile flows and simulate different physiological or pathological parameters of the human circulation system. It is of great significance for testing cardiovascular assist device (CAD), which is a type of clinical instrument used to treat cardiovascular disease and alleviate the dilemma of insufficient donor hearts. The MCL installed with different types of CADs can simulate specific conditions of clinical surgery for evaluating the effectiveness and reliability of those CADs under the repeated performance tests and reliability tests. Also, patient-specific cardiovascular models can be employed in the circulation of MCL for targeted pathological study associated with hemodynamics. Therefore, The MCL system has various combinations of different functional units according to its richful applications, which are comprehensively reviewed in the current work. Four types of CADs including prosthetic heart valve (PHV), ventricular assist device (VAD), total artificial heart (TAH) and intra-aortic balloon pump (IABP) applied in MCL experiments are documented and compared in detail. Moreover, MCLs with more complicated structures for achieving advanced functions are further introduced, such as MCL for the pediatric application, MCL with anatomical phantoms and MCL synchronizing multiple circulation systems. By reviewing the constructions and functions of available MCLs, the features of MCLs for different applications are summarized, and directions of developing the MCLs are suggested.

HMMR promotes prostate cancer proliferation and metastasis via AURKA/mTORC2/E2F1 positive feedback loop.

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.

Identification of a potential structure-based GPCR drug for interstitial cystitis/bladder pain syndrome: in silico protein structure analysis and molecular docking.

INTRODUCTION AND HYPOTHESIS: There is currently no effective treatment for interstitial cystitis / bladder pain syndrome (IC/BPS) and thus seriously reduces the quality of life of patients. The purpose of this study is to analyze the structure and function of G protein coupled receptors related to IC/BPS by integrating bioinformatics and provide basis for the development of new drugs for IC/BPS. METHODS: We used ProtParam and DNAMAN to analyze the physical and chemical properties of GPR18 and GPR183 proteins. The secondary and tertiary structure, conservative domain, phosphorylation site of both proteins were predicted by ProtScale, PredictProtein, SWISS-MODEL and GPS5.0 respectively. Multiple sequence alignment of the proteins were carried out by DNAMAN and the phylogenetic tree was constructed by MEGA. Further, the molecular docking verification of cannabidiol and both proteins were carried out by using AutoDock Vin. RESULTS: GPR18 and GPR183 proteins were composed of 331 and 361 amino acids respectively. α-helix is the highest in the secondary structure of the two proteins. Both proteins contain seven transmembrane domains specific to G protein coupled receptors. And homology analysis showed that the two proteins had high homology. In terms of molecular docking, cannabidiol, a non psychoactive component extracted from the cannabis, can form effective molecular binding with GPR18 and GPR183 proteins. CONCLUSIONS: We identified the structures of GPR18 and GPR183 proteins and their highly homologous evolutionary properties. Furthermore, both proteins can form effective binding with cannabidiol which provides new insights for the development of IC/BPS drugs by targeting G protein coupled receptors.

Synergism Between Multi-Pseudomonas and Cutinase for Biodegradation of Crude Oil-Based Derivatives.

Polyethylene terephthalate (PET) as one of the main crude oil-based derivatives, produces a significant amount of waste that is difficult to degrade. Currently, microbial degradation of PET is an eco-friendly, efficient, and economical method. This study was conducted to propose a novel screening strategy for PET-degrading bacteria, and evaluate their degradation efficiency of PET. Two strains, Pseudomonas nitroreducens S8 and Pseudomonas monteilii S17, were isolated and could utilize PET as a carbon source by co-culture. The combined use of both bacteria gave a synergistic effect on the disruption of the PET surface through colonization behavior, which could enhance the subsequent degradation of PET. Its time of reaching a peak value of PET degradation rate (94.5% at 6 d) was 2 days earlier than these of single bacteria. A similar synergistic effect was also observed in the metabolization of PET monomers, and the metabolic rate was expressed as 82.4% of bis (2-hydroxyethyl) terephthalate (BHET), 64.0% of mono (2-hydroxyethyl) terephthalate (MHET), and 20.0% of terephthalic acid (TPA), respectively. This study is novel in showing the degradation of PET waste by combinations of bacterial pretreatment and enzymatic treatment, which can be a promising method.

Adiponectin. rs266729 Polymorphism and Nicotine Dependence Interaction: Genetic Investigations on the Anxiety Susceptibility.

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 (ß = -0.19, p < 0.05). The CC homozygote was more likely to be affected by ND-induced anxiety (ß = 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.

Metal ions in cerebrospinal fluid: Associations with anxiety, depression, and insomnia among cigarette smokers.

OBJECTIVE: The study aimed to investigate the relationship between cerebrospinal fluid (CSF) metal ions and anxiety, depression, and insomnia among cigarette smokers. METHODS: We measured CSF levels of various metal ions from 178 Chinese male subjects. Apart from sociodemographic and clinical characteristics data, the Fagerstrom Test for Nicotine Dependence (FTND), Beck Depression Inventory (BDI), Self-Rating Anxiety Scale (SAS), and Pittsburgh Sleep Quality Index (PSQI) were applied. RESULTS: BDI and PSQI scores (all p < 0.001) were significantly higher in active smokers than nonsmokers. Active smokers have significantly higher CSF levels of magnesium, zinc, iron, lead, lithium, and aluminum (all p ≤ 0.002). Some metal ions, including zinc, iron, lead, and aluminum, were found to have a significant correlation with BDI scores, whereas metal ions, including zinc and lead, were found to have a significant correlation with PSQI scores in the general group. More interesting, mediation analysis showed that aluminum mediated the relationship between smoking and depression. CONCLUSIONS: Cigarette smoking was indeed associated with depression and insomnia. Active smokers had significantly higher CSF levels of magnesium, zinc, iron, lead, lithium, and aluminum. Furthermore, CSF aluminum played a mediating role in the relationship between smoking and depression, which further confirmed its neurotoxicity.

A Scoring System for Optimal Selection of Endoscopic Treatment for 1-2cm Lower Pole Renal Calculi.

PURPOSE: To explore the establishment of a scoring system that can provide a reference for clinical decision making regarding the endoscopic treatment of 1-2 cm lower pole stones (LPS). MATERIALS AND METHODS: The data of patients with renal calculi who were treated with percutaneous nephrolithotomy (PCNL) or retrograde intrarenal surgery (RIRS) in three hospitals from January 2013 to December 2017 were analyzed retrospectively. Multivariable logistic analysis was performed to determine the statistically significant indicators and regression coefficients, which were used to construct the scoring system. The stone-free rate (SFR) and postoperative complication rates of PCNL and RIRS within the two fractional segments of the scoring system were compared to select the optimal procedures. RESULTS: A total of 137 patients in the PCNL group and 152 patients in the RIRS group were included in this study. Five factors were found to be most predictive of endoscopic treatment choice: stone number, stone diameter, infundibulopelvic angle (IPA), infundibular length (IL), and infundibular width (IW), yielding a total score ranging from 0-5. In the 0-2 segments, the RIRS group had better outcomes than the PCNL group in terms of the postoperative complication rates (6.8% versus 18.0%, P = .026). In segments 3-5, the SFR of the PCNL group was significantly higher than that of the RIRS group (88.5% versus 70.6%, P = .017). CONCLUSION: Our scoring system was based on the patient's preoperative imaging examination to measure the stone number, stone diameter, IPA, IL and IW. RIRS was recommended at 0-2 segments, and PCNL was recommended at 3-5 segments. This new scoring system is expected to provide guidance for urologists to make endoscopic treatment decisions for 1-2 cm LPS.

WGCNA and molecular docking reveal key hub genes and potential natural inhibitor in interstitial cystitis/bladder pain syndrome.

INTRODUCTION AND HYPOTHESIS: The etiology and treatment of interstitial cystitis/bladder pain syndrome are still controversial. The purpose of this study is to determine the key genes and specific regulatory pathways related to it and to find potential drug-active components through integrated bioinformatics. METHODS: The data set GSE11783 was downloaded from GEO database. The modules significantly related to interstitial cystitis/bladder pain syndrome were identified by weighted correlation network analysis. The genes in the key modules were analyzed by functional enrichment and protein interaction by Cytoscape software, and finally the core hub genes were screened. Furthermore, the molecular docking verification of active components and key proteins was carried out by using AutoDock Vin software. RESULTS: Among the 14 modules derived from WGCNA, turquoise module had the highest correlation with IC/BPS (r = 0.85, P < 0.001). The genes in the module were mainly enriched in the biological processes such as the interaction between cytokines and cytokine receptors and chemokine signaling pathway. The genes in the related modules of differentially expressed genes and WGCNA traits were intersected to obtain the core hub genes. Protein-protein interaction network analysis showed that the key genes were upregulated genes CCR7 and CCL19. In terms of molecular docking, triptolide, the active component in the traditional anti-inflammatory drug Tripterygium wilfordii, can form effective molecular binding with both core hub genes. CONCLUSIONS: Our study identified the core hub genes CCR7 and CCL19, which acted as essential components in interstitial cystitis/bladder pain syndrome. Furthermore, CCR7 and CCL19 can form effective binding with triptolide, which will provide new insights into the development of new therapies for interstitial cystitis/bladder pain syndrome.

A Novel Risk Factor Model Based on Glycolysis-Associated Genes for Predicting the Prognosis of Patients With Prostate Cancer.

BACKGROUND: Prostate 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. METHODS: Differential 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. RESULTS: Five 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. CONCLUSION: The risk score based on five glycolysis-related genes may serve as an accurate prognostic marker for PCa patients with BCR.