Possible association between androgenic alopecia and risk of prostate cancer and testicular germ cell tumor: a systematic review and meta-analysis

Abstract Background A number of studies have investigated the association between androgenic alopecia (AGA) and cancer risk, but they have yielded inconsistent results. Therefore, this study was conducted to explore this controversial subject. Methods A literature database search was performed according to predefined criteria. An odds ratio (OR) or a hazard ratio (HR) with 95% confidence intervals (CIs) was retained to evaluate the relationship between the incidence of cancer or cancer-specific mortality and categories of AGA. Then a pooled OR or HR was derived. Results The pooled results showed that no specific degree of baldness had an influence on the incidence of cancer or cancer-specific mortality. However, AGA, especially frontal baldness, with the incidence of testicular germ cell tumor (TGCT) (OR = 0.69; 95% CI = 0.58–0.83). A significant increase of risk was observed in relation to high grade prostate cancer (PC) (OR = 1.42; 95% CI 1.02–1.99) and vertex with/without frontal baldness was associated with PC risk. Conclusions The study results supported the hypothesis that AGA is negatively associated with TGCT risk and suggested an overlapping pathophysiological mechanism between them, while the viewpoint that AGA can be used as a phenotypic marker for PC risk was poorly supported

Preparation and performance analysis of low-temperature SiO2 aerogel-based phase change composites

Shape-stabilized SiO2 aerogel phase change composites (PCCs) was prepared by physical adsorption method with SiO2 aerogel as support material, and then used for secondary packaging.The optimal adsorption ratio of SiO2aerogel and phase change materials was explored, and microscopic morphology, chemical composition, pore structure, phase change characteristics, thermal reliability, shape stability and thermal insulation performance of composites were also characterized. The results show that the PCCs with 80%(mass fraction) phase change material (LS-80) has the optimization proportion, the composites exhibit shape-stability during the phase change process, and the melting point and melting enthalpy are -15.6 ℃ and 170.2 J/g respectively. The successful adsorption of SiO2 aerogel makes the specific surface area, pore size and pore volume of LS-80 reduced to 59 m2/g, 13 nm and 0.2 cm3/g. After 20 thermal cycles, the latent heat of packaged phase change material is decreased by 13.4%, while the SL-80 is only decreased by 2.8%, which proves good thermal reliability. Besides, the thermal conductivity of the composites is reduced and the thermal insulation capacity is enhanced due to the addition of SiO2 aerogel. The results provide experimental basis for the application of SiO2 aerogel PCCs in the field of cold chain logistics

Additional file 3: of Possible association between androgenic alopecia and risk of prostate cancer and testicular germ cell tumor: a systematic review and meta-analysis

Table S2. NOS scores of cohort studies. Table S3. NOS scores of case control studies. (DOC 86 kb

Additional file 5: of Possible association between androgenic alopecia and risk of prostate cancer and testicular germ cell tumor: a systematic review and meta-analysis

Table S4. Meta-analysis results of association between androgenic alopecia and incidence of cancer. (DOCX 17 kb

Additional file 1: of Possible association between androgenic alopecia and risk of prostate cancer and testicular germ cell tumor: a systematic review and meta-analysis

Table S1. Review methodology for meta-analysis. (DOC 29 kb

Additional file 2: of Possible association between androgenic alopecia and risk of prostate cancer and testicular germ cell tumor: a systematic review and meta-analysis

Figure S1. Male balding patterns base on the Hamilton-Norwood scale. (TIFF 356 kb

Advances of Artificial Intelligence in Anti-Cancer Drug Design: A Review of the Past Decade

Anti-cancer drug design has been acknowledged as a complicated, expensive, time-consuming, and challenging task. How to reduce the research costs and speed up the development process of anti-cancer drug designs has become a challenging and urgent question for the pharmaceutical industry. Computer-aided drug design methods have played a major role in the development of cancer treatments for over three decades. Recently, artificial intelligence has emerged as a powerful and promising technology for faster, cheaper, and more effective anti-cancer drug designs. This study is a narrative review that reviews a wide range of applications of artificial intelligence-based methods in anti-cancer drug design. We further clarify the fundamental principles of these methods, along with their advantages and disadvantages. Furthermore, we collate a large number of databases, including the omics database, the epigenomics database, the chemical compound database, and drug databases. Other researchers can consider them and adapt them to their own requirements

Image_4_Novel prognostic biomarker TBC1D1 is associated with immunotherapy resistance in gliomas.tif

BackgroundGlioma, an aggressive brain tumor, poses a challenge in understanding the mechanisms of treatment resistance, despite promising results from immunotherapy.MethodsWe identified genes associated with immunotherapy resistance through an analysis of The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) databases. Subsequently, qRT-PCR and western blot analyses were conducted to measure the mRNA and protein levels of TBC1 Domain Family Member 1 (TBC1D1), respectively. Additionally, Gene Set Enrichment Analysis (GSEA) was employed to reveal relevant signaling pathways, and the expression of TBC1D1 in immune cells was analyzed using single-cell RNA sequencing (scRNA-seq) data from GEO database. Tumor Immune Dysfunction and Exclusion (TIDE) database was utilized to assess T-cell function, while Tumor Immunotherapy Gene Expression Resource (TIGER) database was employed to evaluate immunotherapy resistance in relation to TBC1D1. Furthermore, the predictive performance of molecules on prognosis was assessed using Kaplan-Meier plots, nomograms, and ROC curves.ResultsThe levels of TBC1D1 were significantly elevated in tumor tissue from glioma patients. Furthermore, high TBC1D1 expression was observed in macrophages compared to other cells, which negatively impacted T cell function, impaired immunotherapy response, promoted treatment tolerance, and led to poor prognosis. Inhibition of TBC1D1 was found to potentially synergistically enhance the efficacy of immunotherapy and prolong the survival of cancer patients with gliomas.ConclusionHeightened expression of TBC1D1 may facilitate an immunosuppressive microenvironment and predict a poor prognosis. Blocking TBC1D1 could minimize immunotherapy resistance in cancer patients with gliomas.</p

Image_1_Novel prognostic biomarker TBC1D1 is associated with immunotherapy resistance in gliomas.tif

BackgroundGlioma, an aggressive brain tumor, poses a challenge in understanding the mechanisms of treatment resistance, despite promising results from immunotherapy.MethodsWe identified genes associated with immunotherapy resistance through an analysis of The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) databases. Subsequently, qRT-PCR and western blot analyses were conducted to measure the mRNA and protein levels of TBC1 Domain Family Member 1 (TBC1D1), respectively. Additionally, Gene Set Enrichment Analysis (GSEA) was employed to reveal relevant signaling pathways, and the expression of TBC1D1 in immune cells was analyzed using single-cell RNA sequencing (scRNA-seq) data from GEO database. Tumor Immune Dysfunction and Exclusion (TIDE) database was utilized to assess T-cell function, while Tumor Immunotherapy Gene Expression Resource (TIGER) database was employed to evaluate immunotherapy resistance in relation to TBC1D1. Furthermore, the predictive performance of molecules on prognosis was assessed using Kaplan-Meier plots, nomograms, and ROC curves.ResultsThe levels of TBC1D1 were significantly elevated in tumor tissue from glioma patients. Furthermore, high TBC1D1 expression was observed in macrophages compared to other cells, which negatively impacted T cell function, impaired immunotherapy response, promoted treatment tolerance, and led to poor prognosis. Inhibition of TBC1D1 was found to potentially synergistically enhance the efficacy of immunotherapy and prolong the survival of cancer patients with gliomas.ConclusionHeightened expression of TBC1D1 may facilitate an immunosuppressive microenvironment and predict a poor prognosis. Blocking TBC1D1 could minimize immunotherapy resistance in cancer patients with gliomas.</p

Image_5_Novel prognostic biomarker TBC1D1 is associated with immunotherapy resistance in gliomas.tif

BackgroundGlioma, an aggressive brain tumor, poses a challenge in understanding the mechanisms of treatment resistance, despite promising results from immunotherapy.MethodsWe identified genes associated with immunotherapy resistance through an analysis of The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) databases. Subsequently, qRT-PCR and western blot analyses were conducted to measure the mRNA and protein levels of TBC1 Domain Family Member 1 (TBC1D1), respectively. Additionally, Gene Set Enrichment Analysis (GSEA) was employed to reveal relevant signaling pathways, and the expression of TBC1D1 in immune cells was analyzed using single-cell RNA sequencing (scRNA-seq) data from GEO database. Tumor Immune Dysfunction and Exclusion (TIDE) database was utilized to assess T-cell function, while Tumor Immunotherapy Gene Expression Resource (TIGER) database was employed to evaluate immunotherapy resistance in relation to TBC1D1. Furthermore, the predictive performance of molecules on prognosis was assessed using Kaplan-Meier plots, nomograms, and ROC curves.ResultsThe levels of TBC1D1 were significantly elevated in tumor tissue from glioma patients. Furthermore, high TBC1D1 expression was observed in macrophages compared to other cells, which negatively impacted T cell function, impaired immunotherapy response, promoted treatment tolerance, and led to poor prognosis. Inhibition of TBC1D1 was found to potentially synergistically enhance the efficacy of immunotherapy and prolong the survival of cancer patients with gliomas.ConclusionHeightened expression of TBC1D1 may facilitate an immunosuppressive microenvironment and predict a poor prognosis. Blocking TBC1D1 could minimize immunotherapy resistance in cancer patients with gliomas.</p