The causal relationship between serum metabolites and acne vulgaris: a Mendelian randomization study.

In individuals with acne vulgaris, alterations occur in serum metabolite composition, yet the exact causal link between these metabolites and acne development remains elusive. Using genome-wide association datasets, we performed bidirectional Mendelian randomization (MR) to investigate the potential causal relationship between 309 serum metabolites and acne vulgaris. We performed sensitivity analysis to evaluate the presence of heterogeneity and pleiotropy. Forward MR analysis found 14 serum metabolites significantly associated with acne vulgaris, and reverse MR analysis found no significant association between acne vulgaris and these serum metabolites. Through validation using data from the FinnGen database of acne vulgaris studies, we found a conclusive and significant correlation between stearoylcarnitine and acne vulgaris. This provides new evidence in the search for new targets for the treatment of acne vulgaris.

Association between non-scarring alopecia and hypothyroidism: a bidirectional two-sample Mendelian randomization study.

Background: Non-scarring alopecia is typically represented by two main types: alopecia areata (AA) and androgenetic alopecia (AGA). While previous observational studies have indicated a link between non-scarring alopecia and hypothyroidism, the precise causal relationship remains uncertain. To determine the potential links between non-scarring alopecia and hypothyroidism, we conducted a bidirectional two-sample Mendelian randomization (MR) analysis. Methods: We used independent genetic instruments from the FinnGen consortium for AA (682 cases, 361,140 controls) and AGA (195 cases, 201,019 controls) to investigate the association with hypothyroidism in the UK Biobank study (22,687 cases, 440,246 controls). The primary analysis was performed using the inverse variance-weighted method. Complementary approaches were employed to evaluate the pleiotropy and heterogeneity. Results: Genetically predicted AA exhibited a positive causal effect on hypothyroidism (odds ratio [OR], 1.0017; 95% confidence interval [CI], 1.0004-1.0029; P = 0.0101). Additionally, hypothyroidism was found to be strongly correlated with an increase in the risk of AA (OR, 45.6839; 95% CI, 1.8446-1131.4271, P = 0.0196). However, no causal relationship was demonstrated between AGA and hypothyroidism. A sensitivity analysis validated the integrity of these causal relationships. Conclusion: This MR study supports a bidirectional causal link between AA and hypothyroidism. Nevertheless, additional research is needed to gain a more thorough comprehension of the causal relationship between non-scarring alopecia and hypothyroidism.

Different Dual-Task Paradigm Reduce Postural Control Ability and Dynamic Stability of Healthy Young Adults during Stair Descent.

Objective: This study aimed to compare the impacts of different dual-task paradigms on the postural control ability and dynamic stability of the youth during stair descent. Method: Twenty young adults without regular exercise habits were randomly recruited to perform stair descent tasks with three different paradigms: single-task, cognitive dual-task, and manual dual-task. Kinematic and dynamic data were collected using an 8 Vicon motion analysis system and a Kistler force plate to evaluate postural control ability and dynamic stability during stair descent. Results: The variation trends of lower limb joint moment were similar under the three task models. Compared with a single-task, both dual-task paradigms significantly reduced the mechanical parameters and dynamic stability during stair descent. Conclusion: The dual-task paradigm increases the risk of stair-related falls. Both cognitive and manual tasks have similar impacts on postural control ability and dynamic stability during stair walking. It is recommended that people avoid performing dual tasks during stair descent.

Mendelian randomization analysis reveals an independent causal relationship between four gut microbes and acne vulgaris.

Background: Numerous studies have suggested a correlation between gut microbiota and acne vulgaris; however, no specific causal link has been explored. Materials and methods: To investigate the possible causal relationship between gut microbiota and acne vulgaris, this study employed a large-scale genome-wide association study (GWAS) summary statistic. Initially, a two-sample Mendelian randomization (MR) analysis was utilized to identify the specific gut microflora responsible for acne vulgaris. We used the Inverse Variance Weighted (IVW) method as the main MR analysis method. Additionally, we assessed heterogeneity and horizontal pleiotropy, while also examining the potential influence of individual single-nucleotide polymorphisms (SNPs) on the analysis results. In order to eliminate gut microbiota with reverse causal associations, we conducted reverse MR analysis. Multivariate Mendelian randomization analysis (MVMR) was then employed to verify the independence of the causal associations. Finally, we performed SNP annotation on the instrumental variables of independent gut microbiota and acne vulgaris to determine the genes where these genetic variations are located. We also explored the biological functions of these genes through enrichment analysis. Result: The IVW method of forward MR identified nine gut microbes with a causal relationship with acne vulgaris (p < 0.05). The findings from the sensitivity analysis demonstrate the absence of heterogeneity or horizontal pleiotropy, and leave-one-out analysis indicates that the results are not driven by a single SNP. Additionally, the Reverse MR analysis excluded two reverse-correlated pathogenic gut microbes. And then, MVMR was used to analyze seven gut microbes, and it was found that Cyanobacterium and Family XIII were risk factors for acne vulgaris, while Ruminococcus1 and Ruminiclostridium5 were protective factors for acne vulgaris. After conducting biological annotation, we identified six genes (PLA2G4A, FADS2, TIMP17, ADAMTS9, ZC3H3, and CPSF4L) that may be associated with the pathogenic gut microbiota of acne vulgaris patients. The enrichment analysis results indicate that PLA2G4A/FADS2 is associated with fatty acid metabolism pathways. Conclusion: Our study found independent causal relationships between four gut microbes and acne vulgaris, and revealed a genetic association between acne vulgaris patients and gut microbiota. Consider preventing and treating acne vulgaris by interfering with the relative content of these four gut microbes.

Crosstalk of cuproptosis-related prognostic signature and competing endogenous RNAs regulation in hepatocellular carcinoma.

BACKGROUND: Cuproptosis is a new type of programmed cell death involved in the regulation of neuroendocrine tumors, immune microenvironment, and substance metabolism. However, the role of cuproptosis-related genes (CRGs) in Hepatocellular carcinoma (HCC) remains unclear. METHOD: Through multiple bioinformatics analysis, we constructed a prognostic gene model and competing endogenous RNA (ceRNA) network. The correlation between CRGs and prognosis, immune infiltration, immune checkpoints, microsatellite instability (MSI) and tumor mutational burden (TMB) was analyzed by Kaplan-Meier curve, univariate Cox, multivariate regression, and Spearman's analysis in HCC patients. Besides, the qRT-PCR and immunohistochemistry assays were used to determine prognostic CRGs mRNA and protein expression in HCC. RESULTS: We established a novel 3-gene signature related to CRGs for evaluating the prognosis of HCC patients. HCC patients with high risk scores had a poor prognosis with an area under the curve of 0.737, 0.646, and 0.634 on 1-year, 3-year, and 5-year receiver operating characteristic curves. Significant correlation was observed between prognostic CRGs and immune infiltration, immune checkpoints, MSI and TMB. We also developed five ceRNA networks to regulate the occurrence and progression of HCC. CDKN2A, DLAT, and PDHA1 protein expression was up-regulated in HCC versus normal tissues. Besides, the mRNA expression levels of CDKN2A, DLAT, GLS, and PDHA1 were elevated in the HCC cell lines compared to the normal liver cell lines. CONCLUSIONS: This novel prognostic CRGs signature could be accurately predict the prognosis of patients with HCC. The ceRNA regulatory network might be potential prognostic biomarkers and therapeutic targets for HCC patients.

Development and validation of a nomogram based on multiple preoperative immunoinflammatory indexes for survival prediction in patients with stage IA-IB endometrial cancer.

OBJECTIVES: To evaluate the preoperative systemic immune-inflammation index (SII), advanced lung cancer inflammation index (ALI), neutrophil to lymphocyte ratio (NLR), and prognostic nutritional index (PNI) capacity to predict the prognosis of stage IA-IB endometrial carcinoma (EC) patients after operation, and establish a nomogram model to guide clinical practice. METHODS: A total of 387 patients with EC (R0 resection, stage IA-IB) were assessed. Clinical information and the SII, NLR, ALI, and PNI values were obtained. The low and high ratio groups were separated using the receiver operating characteristic curve (ROC). Pearson's χ2-test or Fisher's exact test was used to determine their relationship with clinical variables. To determine the independent prognostic factors, Cox regression was utilized to do the univariate and multivariate survival analyses. The Kaplan-Meier method was used to draw the survival curve in our survival analysis. Depending upon the independent prognostic factors, the nomogram for Overall survival (OS) and Disease-free survival (DFS) nomogram was developed, and its discrimination ability was validated by the consistency index (C-index) and calibration curve. RESULTS: Cox regression analysis revealed that FIGO staging, Ki-67 expression level, PNI, and ALI are independent prognostic factors for both OS and DFS. Then a novel predictive nomogram was developed, and its C-index value for OS and DFS was 0.829 and 0.814, respectively. The calibration curves demonstrated consistency amid the predicted prognosis using the developed nomogram and the actual observed outcomes. CONCLUSIONS: The ALI and PNI could serve as readily available prognostic indicators for OS and DFS prediction in stage IA-IB EC patients. The nomogram developed owned superior power for OS and DFS prediction in stage IA-IB EC patients, and it would assist clinical oncologists in accurately predicting the individual's OS and DFS.

Research on the Current Application Status of Magnesium Metal Stents in Human Luminal Cavities.

The human body comprises various tubular structures that have essential functions in different bodily systems. These structures are responsible for transporting food, liquids, waste, and other substances throughout the body. However, factors such as inflammation, tumors, stones, infections, or the accumulation of substances can lead to the narrowing or blockage of these tubular structures, which can impair the normal function of the corresponding organs or tissues. To address luminal obstructions, stenting is a commonly used treatment. However, to minimize complications associated with the long-term implantation of permanent stents, there is an increasing demand for biodegradable stents (BDS). Magnesium (Mg) metal is an exceptional choice for creating BDS due to its degradability, good mechanical properties, and biocompatibility. Currently, the Magmaris® coronary stents and UNITY-BTM biliary stent have obtained Conformité Européene (CE) certification. Moreover, there are several other types of stents undergoing research and development as well as clinical trials. In this review, we discuss the required degradation cycle and the specific properties (anti-inflammatory effect, antibacterial effect, etc.) of BDS in different lumen areas based on the biocompatibility and degradability of currently available magnesium-based scaffolds. We also offer potential insights into the future development of BDS.

DNA methylation mediated genetic risk in severe acne in a young men population.

Background: Acne is a chronic inflammatory skin disease that affects the pilosebaceous follicle and is influenced by heredity, hormones, inflammation, and the environment. At present, the recognized pathogenesis mainly includes four categories: excessive sebum secretion, excessive Cutibacterium acnes proliferation, excessive keratinization of sebaceous glands in hair follicles, and inflammatory mechanisms. Previous studies have found that DNA methylation is closely related to some chronic inflammatory skin diseases, and there is evidence that DNA methylation is controlled by genetic factors, making us want to know the relationship between DNA methylation, genetic variation and acne. Materials and methods: In our previous study, we performed genome-wide DNA methylation analysis in peripheral blood samples from 44 patients with severe acne and 44 unaffected normal subjects, and identified 23 differentially methylated probes (DMPs). In this study, we identified single nucleotide polymorphisms (SNPs) associated with severe acne by genome-wide association analysis in these 88 samples. To test the association between SNPs and DMPs, we conducted DNA methylation quantitative trait loci (methQTL) analysis. Next, causal inference testing (CIT) was used to determine whether genetic variation influences DNA methylation, which impacts disease phenotypes. Result: We found 38,269 SNPs associated with severe acne. By methQTL analysis, we obtained 24 SNP-CpG pairs that reached the threshold (FDR < 0.05), which included 7 unique CpGs and 22 unique methQTL SNPs. After CIT analysis, we found that 11 out of 24 pairs of SNP-CpG showed a weakened SNP effect after adjustment for methylation, indicating a methylation-mediated relationship between SNPs and severe acne. These 11 SNP-CpG pairs consist of four unique CpG sites and 11 SNPs, of which three CpG sites, cg03020863, cg20652636, and cg19964325, are located on the gene body of PDGFD, the intron of SH2D6, and the 5'UTR of the IL1R1 gene, respectively. Conclusion: During this study, the DNA methylation of certain genes was found to be influenced by genetic factors and mediated the risk of severe acne in a young Chinese male population, providing a new perspective on the pathogenesis of severe acne.

Identification of differentially methylated genes for severe acne by genome-wide DNA methylation and gene expression analysis.

Severe acne is a chronic inflammatory skin condition that is affected by both genetic and environmental factors. DNA methylation is associated with a variety of inflammatory skin diseases, but its role in severe acne is unclear. In this study, we conducted a two-stage epigenome correlation study using 88 blood samples to identify disease-related differential methylation sites. We found close associations between the DNA methylation at 23 differentially methylated sites (DMSs) and severe acne, including PDGFD, ARHGEF10, etc. Further analysis revealed that differentially methylated genes (PARP8 and MAPKAPK2) were also expressed differently between severe acne and health control groups. These findings lead us to speculation that epigenetic mechanisms may play an important role in the pathogenesis of severe acne.

UAV imaging and deep learning based method for predicting residual film in cotton field plough layer.

In this paper, a method for predicting residual film content in the cotton field plough layer based on UAV imaging and deep learning was proposed to solve the issues of high labour intensity, low efficiency, and high cost of traditional methods for residual film content monitoring. Images of residual film on soil surface in the cotton field were collected by UAV, and residual film content in the plough layer was obtained by manual sampling. Based on the three deep learning frameworks of LinkNet, FCN, and DeepLabv3, a model for segmenting residual film from the cotton field image was built. After comparing the segmentation results, DeepLabv3 was determined to be the best model for segmenting residual film, and then the area of residual film was obtained. In addition, a linear regression prediction model between the residual film coverage area on the cotton field surface and the residual film content in the plough layer was built. The results showed that the correlation coefficient (R2), root mean square error, and average relative error of the prediction of residual film content in the plough layer were 0.83, 0.48, and 11.06%, respectively. It indicates that a quick and accurate prediction of residual film content in the cotton field plough layer can be realized based on UAV imaging and deep learning. This study provides certain technical support for monitoring and evaluating residual film pollution in the cotton field plough layer.

Evaluation of residual plastic film pollution in pre-sowing cotton field using UAV imaging and semantic segmentation.

To accurately evaluate residual plastic film pollution in pre-sowing cotton fields, a method based on modified U-Net model was proposed in this research. Images of pre-sowing cotton fields were collected using UAV imaging from different heights under different weather conditions. Residual films were manually labelled, and the degree of residual film pollution was defined based on the residual film coverage rate. The modified U-Net model for evaluating residual film pollution was built by simplifying the U-Net model framework and introducing the inception module, and the evaluation results were compared to those of the U-Net, SegNet, and FCN models. The segmentation results showed that the modified U-Net model had the best performance, with a mean intersection over union (MIOU) of 87.53%. The segmentation results on images of cloudy days were better than those on images of sunny days, with accuracy gradually decreasing with increasing image-acquiring height. The evaluation results of residual film pollution showed that the modified U-Net model outperformed the other models. The coefficient of determination(R2), root mean square error (RMSE), mean relative error (MRE) and average evaluation time per image of the modified U-Net model on the CPU were 0.9849, 0.0563, 5.33% and 4.85 s, respectively. The results indicate that UAV imaging combined with the modified U-Net model can accurately evaluate residual film pollution. This study provides technical support for the rapid and accurate evaluation of residual plastic film pollution in pre-sowing cotton fields.

Seven key hub genes identified by gene co-expression network in cutaneous squamous cell carcinoma.

BACKGROUND: Cutaneous squamous cell carcinoma (cSCC) often follows actinic keratosis (AK) and is the second most common skin cancer worldwide. To reduce metastasis risk, it is important to diagnose and treat cSCC early. This study aimed to identify hub genes associated with cSCC and AK. METHODS: This study used three datasets GSE45216, GSE98774, and GSE108008. We combined samples from the GSE45216 and GSE98774 datasets into the new dataset GSE45216-98774. We applied a weighted gene co-expression network analysis (WGCNA) to investigate key modules and hub genes associated with cSCC and AK. We considered the hub genes found in both the GSE45216-98774 and GSE108008 datasets as validated hub genes. We tested whether the expression of hub genes could predict patient survival outcomes in other cancers using TCGA pan-cancer data. RESULTS: We identified modules most relevant to cSCC and AK. Additionally, we identified and validated seven hub genes of cSCC: GATM, ARHGEF26, PTHLH, MMP1, POU2F3, MMP10 and GATA3. We did not find validated hub genes for AK. Each hub gene was significantly associated with the survival of various cancer types. Only GATA3 was significantly associated with melanoma survival. CONCLUSIONS: We applied WGCNA to find seven hub genes that play important roles in cSCC tumorigenesis. These results provide new insights that help explain the pathogenesis of cSCC. These hub genes may become biomarkers or therapeutic targets for accurate diagnosis and treatment of cSCC in the future.

Characterization of the Complete Chloroplast Genome of Hygroryza aristata (Retz.) Nees ex Wight & Arn. (Zizaniinae, Poaceae).

The complete chloroplast genome sequence of Hygroryza aristata was sequenced, assembled and published for the first time here. The chloroplast genome was 135,681 bp in length and comprised of a large single-copy (LSC, 81,532 bp) region and a small single-copy (SSC, 12,383 bp) region interspersed by two inverted repeats (IRs, 20,883 bp). Gene annotation resulted in the identification of 113 unique genes including 79 protein-coding genes, 30 transfer RNA (tRNA) genes, and four ribosomal RNA (rRNA) genes. In addition, 118 simple sequence repeats (SSRs) and 47 long repeats were identified. Phylogenetic analysis based on maximum likelihood analysis (ML) resolved the placement of H. aristata sister to a clade of Rhynchoryza subulata and Zizania.

Colorectal Cancer that Highly Express Both ACE2 and TMPRSS2, Suggesting Severe Symptoms to SARS-CoV-2 Infection.

The epidemic of the novel, pathogenic SARS-coronavirus 2 (SARS-CoV-2) in the world pose a global health emergency. Cancer has been identified as a risk factor for the novel Coronavirus disease 2019 (COVID-19). The ACE2 and TMPRSS2 have been implicated in SARS-CoV-2 infection for mediating viral entry into the host cell. However, a systematic analysis of aberrant expression of ACE2 and TMPRSS2 was not yet reported in multiple human cancers. Here, we analyzed gene expression of ACE2 and TMPRSS2 across 31 types of tumors. Notably, overexpression of ACE2 and TMPRSS2 have been observed in colorectal cancer including colon adenocarcinoma (COAD), and rectum adenocarcinoma (READ). In addition, the colorectal tumors with upregulated gene expressing presented with decreased DNA methylation levels. DNA methylation might be one of the reasons for abnormal expression of ACE2 and TMPRSS2. Conclusively, colorectal cancer was the only cancer with the upregulated expression of ACE2 and TMPRSS2. More care of colorectal cancer patients is needed in multiple cancers affected by the COVID-19 outbreak.

RTP4 is a novel prognosis-related hub gene in cutaneous melanoma.

OBJECTIVE: Melanoma accounts for 80% of skin cancer deaths. The pathogenesis of melanoma is regulated by gene networks. Thus, we aimed here to identify gene networks and hub genes associated with melanoma and to further identify their underlying mechanisms. METHODS: GTEx (normal skin) and TCGA (melanoma tumor) RNA-seq datasets were employed for this purpose. We conducted weighted gene co-expression network analysis (WGCNA) to identify key modules and hub genes associated with melanoma. Log-rank analysis and multivariate Cox model analysis were performed to identify prognosis genes, which were validated using two independent melanoma datasets. We also evaluated the correlation between prognostic gene and immune cell infiltration. RESULTS: The blue module was the most relevant for melanoma and was thus considered the key module. Intersecting genes were identified between this module and differentially expressed genes (DEGs). Finally, 72 genes were identified and verified as hub genes using the Oncomine database. Log-rank analysis and multivariate Cox model analysis identified 13 genes that were associated with the prognosis of the metastatic melanoma group, and RTP4 was validated as a prognostic gene using two independent melanoma datasets. RTP4 was not previously associated with melanoma. When we evaluated the correlation between prognostic gene and immune cell infiltration, we discovered that RTP4 was associated with immune cell infiltration. Further, RTP4 was significantly associated with genes encoding components of immune checkpoints (PDCD1, TIM-3, and LAG3). CONCLUSIONS: RTP4 is a novel prognosis-related hub gene in cutaneous melanoma. The novel gene RTP4 identified here will facilitate the exploration of the molecular mechanism of the pathogenesis and progression of melanoma and the discovery of potential new target for drug therapy.

Transcriptomic profile of tobacco in response to Phytophthora nicotianae infection.

Black shank, caused by Phytophthora nicotianae (P. nicotianae), is a serious disease of cultivated tobacco (Nicotiana tabacum) worldwide. The interactions between tobacco and P. nicotianae are complex and the outcomes of the interactions depend on the tobacco genotype, P. nicotianae strain, and environmental conditions. In this study, we used RNA-sequencing (RNA-Seq) to investigate and compare transcriptional changes in the stems of tobacco upon inoculation with P. nicotianae strain race 0. We used two tobacco varieties: RBST (named from resistance to black shank and tobacco mosaic virus), which was resistant to the P. nicotianae strain race 0, and Honghuadajinyuan (HD), which was susceptible to P. nicotianae race 0. Samples were collected 12 and 72-hour post inoculation (hpi). Analysis of differentially expressed genes (DEGs) and significantly enriched GO terms indicated that several basic defense mechanisms were suppressed in both varieties, which included response to wounding (GO: 0009611), and defense response to fungus (GO: 0050832). We also found some genes that may especially be related to mechanisms of resistance in RBST, such as the one encoding a chitinase. These results will provide a valuable resource for understanding the interactions between P. nicotianae and tobacco plants.