No genetic causal relationship between acne and prostate cancer through Mendelian randomization combined with meta-analysis.

Background: Previous observational studies regarding the relationship between acne and prostate cancer have reported inconsistent results. As such studies are prone to biases, we conducted this Mendelian randomization (MR) analysis to better explore the causal association between acne and prostate cancer. Methods: The genetic data for assessing acne were acquired from the largest genome-wide association study (GWAS) of acne by far, and the genetic data for assessing prostate cancer were acquired from the FinnGen consortium, UK Biobank, European Bioinformatics Institute, and IEU OpenGWAS project. We performed two-sample MR analyses using data from these GWASs followed by a meta-analysis to provide an overall evaluation. The primary MR methods used included inverse variance weighted, MR-Egger, and weighted median. Leave-one-out sensitivity tests, Cochran's Q tests, and MR-Egger intercept tests were used to bolster the robustness of the MR results. Results: Through MR combined with meta-analysis, our study found no genetic causal relationship between acne and prostate cancer (p=0.378; odds ratio=0.985; 95% confidence interval, 0.954-1.018). Sensitivity tests ensured the robustness of this result. Conclusion: Acne should not be considered as a morbidity hazard factor for prostate cancer.

Identification of cancer stem cell-related genes through single cells and machine learning for predicting prostate cancer prognosis and immunotherapy.

Background: Cancer stem cells (CSCs) are a subset of cells within tumors that possess the unique ability to self-renew and give rise to diverse tumor cells. These cells are crucial in driving tumor metastasis, recurrence, and resistance to treatment. The objective of this study was to pinpoint the essential regulatory genes associated with CSCs in prostate adenocarcinoma (PRAD) and assess their potential significance in the diagnosis, prognosis, and immunotherapy of patients with PRAD. Method: The study utilized single-cell analysis techniques to identify stem cell-related genes and evaluate their significance in relation to patient prognosis and immunotherapy in PRAD through cluster analysis. By utilizing diverse datasets and employing various machine learning methods for clustering, diagnostic models for PRAD were developed and validated. The random forest algorithm pinpointed HSPE1 as the most crucial prognostic gene among the stem cell-related genes. Furthermore, the study delved into the association between HSPE1 and immune infiltration, and employed molecular docking to investigate the relationship between HSPE1 and its associated compounds. Immunofluorescence staining analysis of 60 PRAD tissue samples confirmed the expression of HSPE1 and its correlation with patient prognosis in PRAD. Result: This study identified 15 crucial stem cell-related genes through single-cell analysis, highlighting their importance in diagnosing, prognosticating, and potentially treating PRAD patients. HSPE1 was specifically linked to PRAD prognosis and response to immunotherapy, with experimental data supporting its upregulation in PRAD and association with poorer prognosis. Conclusion: Overall, our findings underscore the significant role of stem cell-related genes in PRAD and unveil HSPE1 as a novel target related to stem cell.

The nuclear pore protein Nup2 is essential for growth and development, stress response, pathogenicity and deoxynivalenol biosynthesis in Fusarium graminearum.

BACKGROUND: Wheat is an important grain crop that has been under serious threat from Fusarium graminearum. Nup2, a member of the nuclear pore complex, plays an important role in regulating eukaryotic nuclear protein transport and participates in gene regulation. Dissecting the function of nuclear pore proteins in pathogenic fungi may provide effective targets for novel fungicides. RESULTS: Mutants exhibited nutritional growth defects, asexual/sexual developmental abnormalities. Deficiency of FgNup2 resulted in increased resistance of Fusarium graminearum to cell wall disruptors and increased sensitivity to metal ions. Pathogenicity analyses showed that the mutant was significantly less virulent on flowering wheat ears, consistent with the observed decrease in deoxynivalenol (DON) production. Furthermore, we showed that FgNup2 interacts synergistically with FgTri6, a transcription factor of the TRI family, to regulate the expression of toxin-producing genes, which, in turn, affects the biosynthesis of DON and related toxins. CONCLUSION: This study revealed that FgNup2 plays important roles in the growth and development, cell wall integrity, stress response, pathogenicity, and DON synthesis of F. graminearum. © 2024 Society of Chemical Industry.

CD33 Ameliorates Surgery-Induced Spatial Learning and Memory Impairments Through TREM2.

Neuroinflammation is implicated in the onset of postoperative cognitive dysfunction (POCD), with CD33 and triggering receptor expressed on myeloid cells 2 (TREM2) playing crucial roles in immune response modulation and neuroinflammatory processes. A total of 96 aged male C57/BL6 mice (9-12 months) were randomly assigned to one of four groups, each receiving an siRNA injection into the lateral ventricle. Subsequently, the mice underwent partial hepatectomy under general anesthesia. To assess cognitive function, the Morris water maze tests were conducted both pre- and post-surgery. Following behavioral assessments, hippocampal tissues were swiftly harvested. The regulation of CD33 and TREM2 expression was achieved through siRNA in the BV2 microglia cell line. Expression levels of CD33 and TREM2 were evaluated both in vitro and in vivo using quantitative RT-PCR and western blot analyses. This study explored the impact of CD33 and TREM2 on POCD in aged mice and revealed that surgery and anesthesia increased CD33 expression, leading to spatial learning and memory impairments. Inhibiting CD33 expression via siRNA administration ameliorated cognitive deficits and mitigated the neuroinflammatory response triggered by surgery. Additionally, CD33 inhibition reversed the surgery-induced decrease in synaptic-related proteins, highlighting its role in preserving synaptic integrity. Moreover, our experiments suggest that CD33 may influence neuroinflammation and cognitive function through mechanisms involving TREM2. This is evidenced by the suppression of pro-inflammatory cytokines following CD33 knockdown in microglia and the reversal of these effects when both CD33 and TREM2 are concurrently knocked down. These findings imply that CD33 might promote neuroinflammation by inhibiting TREM2. This study highlights the potential of targeting CD33 as a promising therapeutic strategy for preventing and treating POCD. It provides valuable insights into the intricate mechanisms underlying cognitive dysfunction following surgical procedures.

Clinical features of thymoma with and without myasthenia gravis.

Objective: To explore the clinical features of thymoma with and without myasthenia gravis (MG). Methods: This was a retrospective study. Two hundred and thirty-three patients with mediastinal masses who were initially diagnosed in People's Hospital of Shijiazhuang, China, between January 2014 and June 2022 and had complete clinical data and underwent surgical treatment at People's Hospital of Shijiazhuang were retrospectively analyzed. Result: The age of patients with thymoma alone was significantly older than that of thymoma patients complicated with MG. The number of female patients was slightly more than males for both groups. Proportions of type A, AB, B1, B2, and B3 thymomas in Group-A were 0.77, 11.54, 11.51, 33.85, and 31.54%, respectively, and the proportions in Group-B were 9.68, 22.58, 12.90, 32.26, and 22.58%. The size of tumors in patients with thymoma alone was larger than that of patients with thymoma complicated with MG. The proportion of patients with tumor size of more than 10 cm in the thymoma alone group was significantly higher than that in the MG group. There were no relapses in patients with type A disease and relapses were noted in a few patients with type B1, B2 and B3 diseases. The same survival rates were reported for the two groups. Conclusion: MG rarely occurs in type A and type C diseases. The prognosis of thymoma with MG is similar to that of thymoma alone. The main causes of death may be myasthenia crisis in thymoma patients with MG and advanced tumor stage in patients with thymoma alone.

[Correlation of environment temperature with the incidence of testicular torsion].

Objective： To explore the influence of environment temperature on the incidence of testicular torsion. METHODS: We collected the clinical data on 172 cases of testicular torsion diagnosed in the Second Hospital of Hebei Medical University from December 2013 to December 2020. According to the local environment temperature on the day of onset, we divided the patients into groups A (below 0℃), B (0－10℃), C (10－20℃) and D (above 20℃), and compared the incidence rates of testicular torsion among the four groups, followed by correlation analysis. RESULTS: The incidence rate of testicular torsion was 12.8% (n = 22) in group A, 35.5% (n = 61) in B, 34.9% (n = 60) in C and 16.9% (n = 29) in D, the highest at 0－10℃ in group B, with statistically significant difference among the four groups (χ2 = 29.07, P <0.001). Spearman correlation analysis indicated that the incidence of testicular torsion was negatively correlated with the environment temperature (r = －0.261, P <0.01), with no statistically significant difference among different seasons (χ2 = 5.349, P >0.05), but higher in autumn and winter than in the other two seasons. CONCLUSION: The incidence of testicular torsion is negatively correlated with the environment temperature, elevated when the temperature decreases, but has no statistically significant difference among different seasons, though relatively higher in autumn and winter.

Prediction of Drug-Induced Liver Injury: From Molecular Physicochemical Properties and Scaffold Architectures to Machine Learning Approaches.

The process of developing new drugs is widely acknowledged as being time-intensive and requiring substantial financial investment. Despite ongoing efforts to reduce time and expenses in drug development, ensuring medication safety remains an urgent problem. One of the major problems involved in drug development is hepatotoxicity, specifically known as drug-induced liver injury (DILI). The popularity of new drugs often poses a significant barrier during development and frequently leads to their recall after launch. In silico methods have many advantages compared with traditional in vivo and in vitro assays. To establish a more precise and reliable prediction model, it is necessary to utilize an extensive and high-quality database consisting of information on drug molecule properties and structural patterns. In addition, we should also carefully select appropriate molecular descriptors that can be used to accurately depict compound characteristics. The aim of this study was to conduct a comprehensive investigation into the prediction of DILI. First, we conducted a comparative analysis of the physicochemical properties of extensively well-prepared DILI-positive and DILI-negative compounds. Then, we used classic substructure dissection methods to identify structural pattern differences between these two different types of chemical molecules. These findings indicate that it is not feasible to establish property or substructure-based rules for distinguishing between DILI-positive and DILI-negative compounds. Finally, we developed quantitative classification models for predicting DILI using the naïve Bayes classifier (NBC) and recursive partitioning (RP) machine learning techniques. The optimal DILI prediction model was obtained using NBC, which combines 21 physicochemical properties, the VolSurf descriptors and the LCFP_10 fingerprint set. This model achieved a global accuracy (GA) of 0.855 and an area under the curve (AUC) of 0.704 for the training set, while the corresponding values were 0.619 and 0.674 for the test set, respectively. Moreover, indicative substructural fragments favorable or unfavorable for DILI were identified from the best naïve Bayesian classification model. These findings may help prioritize lead compounds in the early stage of drug development pipelines.

CagA 3' region polymorphism of Helicobacter pylori and its association with chronic gastritis in the Chinese population.

Introduction. Cytotoxin-associated gene A (CagA) from Helicobacter pylori is highly related to chronic gastritis. Tyrosine phosphorylation of Glu-Pro-Ile-Tyr-Ala (EPIYA) motifs from CagA determines the pathogenicity of H. pylori.Gap statement. The precise amino acid variations surrounding the EPIYA motifs and their correlation with clinical outcomes have been poorly explored.Aim. The purpose of this study was to examine the CagA 3' region polymorphism of H. pylori and its association with chronic gastritis in the Chinese population.Method. A total of 86 cagA-positive H. pylori strains were isolated from patients with chronic gastritis in two different hospitals in Beijing, PR China. Genomic DNA was extracted commercial kits, and the cagA 3' variable region of H. pylori was amplified by polymerase chain reaction (PCR). The PCR products were sequenced and analysed using the CLC Sequence Viewer, BioEdit, and WebLogo 3.Results. Two hundred and fifty-nine EPIYA motifs were identified from cagA-positive H. pylori strains. Notably, EPIYA-B exhibited a higher frequency of variation in comparison to EPIYA-A, EPIYA-C, and EPIYA-D. The prevalent sequences for East-Asian-type CagA were QVNK and TIDF, while KVNK and TIDD were most commonly observed for Western-type CagA. The CRPIA motifs of East-Asian-type CagA and Western-type CagA varied at positions 4, 6, 7, 8, and 10. CagA-ABD (73.2%) was the most prevalent type, followed by CagA-ABC (18.6%) and CagA-AB (3.4%). The ratio of CagA-ABD was observed to be higher in cases of chronic non-atrophic gastritis with erosive (NAGE) or chronic atrophic gastritis (AG) compared to chronic non-atrophic gastritis (NAG), and the difference was found to be statistically significant (χ2=59.000/64.000, P<0.001).Conclusions. The EPIYA segments of Western-type CagA and East-Asian-type CagA differ significantly and the presence of CagA-ABD may be associated with severe chronic gastritis from this study.

Predicting treatment outcomes in major depressive disorder using brain magnetic resonance imaging: a meta-analysis.

Recent studies have provided promising evidence that neuroimaging data can predict treatment outcomes for patients with major depressive disorder (MDD). As most of these studies had small sample sizes, a meta-analysis is warranted to identify the most robust findings and imaging modalities, and to compare predictive outcomes obtained in magnetic resonance imaging (MRI) and studies using clinical and demographic features. We conducted a literature search from database inception to July 22, 2023, to identify studies using pretreatment clinical or brain MRI features to predict treatment outcomes in patients with MDD. Two meta-analyses were conducted on clinical and MRI studies, respectively. The meta-regression was employed to explore the effects of covariates and compare the predictive performance between clinical and MRI groups, as well as across MRI modalities and intervention subgroups. Meta-analysis of 13 clinical studies yielded an area under the curve (AUC) of 0.73, while in 44 MRI studies, the AUC was 0.89. MRI studies showed a higher sensitivity than clinical studies (0.78 vs. 0.62, Z = 3.42, P = 0.001). In MRI studies, resting-state functional MRI (rsfMRI) exhibited a higher specificity than task-based fMRI (tbfMRI) (0.79 vs. 0.69, Z = -2.86, P = 0.004). No significant differences in predictive performance were found between structural and functional MRI, nor between different interventions. Of note, predictive MRI features for treatment outcomes in studies using antidepressants were predominantly located in the limbic and default mode networks, while studies of electroconvulsive therapy (ECT) were restricted mainly to the limbic network. Our findings suggest a promise for pretreatment brain MRI features to predict MDD treatment outcomes, outperforming clinical features. While tasks in tbfMRI studies differed, those studies overall had less predictive utility than rsfMRI data. Overlapping but distinct network-level measures predicted antidepressants and ECT outcomes. Future studies are needed to predict outcomes using multiple MRI features, and to clarify whether imaging features predict outcomes generally or differ depending on treatments.

[Causal relationship between obesity and male infertility: A two-sample Mendelian randomization study].

OBJECTIVE: To clarify the causal relationship between obesity and male infertility through Mendelian randomization (MR) study. METHODS: We assessed the causal effect of genetically predicted body mass index (BMI) on the risk of male infertility via a two-sample MR analysis, with the BMIs of 99 998 cases and 12 746 controls as the exposure factor and genetic information on male infertility obtained from a genome-wide association study of 73 479 Europeans. In the univariable MR (UVMR) analysis of the causal relationship, we mainly used inverse variance weighting (IVW), with MR-Egger regression and weighted median filtering as the supplementary methods. Sensitivity analyses including the Cochran's Q test, Egger intercept test, MR-PRESSO, leave-one-out analysis and funnel plot were performed to verify the robustness of the MR results. To evaluate the direct causal effects of BMI on MI risk, multivariable MR (MVMR) was performed. RESULTS: UVMR indicated a causal relationship between genetically predicted BMI and an increased risk of male infertility (OR: 1.237, 95% CI: 1.090－1.404, P = 0.001). Sensitivity analysis revealed little evidence of bias in the current study (P> 0.05). With such risk factors as type 2 diabetes, alcohol consumption and smoking adjusted, MVMR confirmed a direct causal effect of genetically predicted BMI on the risk of male infertility (P<0.05). CONCLUSION: Genetically predicted BMI may be associated with an increased risk of male infertility. Further studies are expected to explore the underlying mechanisms of this association and provide some new strategies for the prevention and treatment of BMI-related male infertility.