Characteristics, clinical significance, and cancer immune interactions of lipid metabolism in prostate cancer.

Background: The relationship between lipid metabolism, immune response, and immunotherapy in prostate cancer (PCa) is closely intertwined, and targeted intervention in lipid metabolism may facilitate the success of anticancer immunotherapy. This research attempted to explore effective immunotherapy for PCa. Methods: We obtained RNA sequencing (RNA-seq) data for PCa patients from the UCSC Xena platform. Data analysis of differentially expressed genes (DEGs) was performed using package limma in R. Then, DEGs were subjected to enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The Human Protein Atlas (HPA) database was conducted to validate the protein expression of the up-regulated lipid metabolism related genes (LMRGs) between PCa tissues and normal prostate tissues. And then we identified critical transcription factors (TFs), LMRGs and miRNA by constructing a regulatory network of TF-gene-miRNA. Furthermore, we determined the high and low groups based on the score of lipid metabolism enrichment. The hallmark gene sets were derived from gene expression profiles using the gene set variation analysis (GSVA) R package. Finally, we conducted immune infiltration analysis and drug sensitivity analysis. Results: Immune response and lipid metabolism have undergone significant changes in PCa and paracancerous tissues compared to normal tissues. A total of 21 LMRGs were differentially up-regulated in PCa. The TF-gene-miRNA network showed that PLA2G7, TWIST1, and TRIB3 may be the key genes that elevated lipid metabolism in PCa. The high group had more infiltration of B cell memory, macrophage M0, macrophage M1, and myeloid dendritic cell resting, and the low group had more infiltration of B cell plasma, monocyte, myeloid dendritic cell activated, and mast cell resting. The majority of checkpoint genes exhibited high expression levels in the low group. Lipid metabolism was remarkedly correlated with drug sensitivity. Conclusions: The analysis of lipid metabolism and related genes has revealed a complex regulatory mechanism that has a significant influence on immune response, immunotherapy, and medication guidance for patients with PCa. Keywords: Prostate cancer (PCa); lipid metabolism; cancer immune; RNA sequencing (RNA-seq).

Prevalence and genotype distribution of human papillomavirus infection among 66000 women from 2014 to 2023 in the plateau region of Southwest China.

BACKGROUND: Persistent infection with high-risk human papillomavirus (HR-HPV) plays a key role in the onset of cervical cancer. This study was designed to examine the epidemiological trends and genotype distribution of HPV from 2014 to 2023 in the plateau region of Southwest China. METHODS: The findings could offer valuable insights for clinical screening of cervical cancer and the formulation of HPV vaccination policies. This retrospective study analyzed 66,000 women who received HPV-DNA testing at the First People's Hospital of Qujing, Yunnan, China, between 2014 and 2023. The cohort consisted of 33,512 outpatients, 3,816 inpatients, and 28,672 individuals undergoing health examinations. Cervical cells were collected for DNA extraction, and PCR amplification along with Luminex xMAP technology were used to detect 27 HPV genotypes. The data analysis was conducted using GraphPad Prism and IBM SPSS Statistics 27 software. RESULTS: The overall HPV infection rate at the First People's Hospital of Qujing declined from 24.92% in 2014 to 16.29% in 2023, averaging 16.02%. Specific infection rates were 18.50% among outpatients, 12.97% among inpatients, and 13.53% for health examination attendees. The predominant high-risk HPV genotypes identified were HPV52 (2.61%), HPV16 (2.06%), HPV58 (1.81%), HPV53 (1.55%), and HPV39 (1.09%). Meanwhile, the most frequent low-risk HPV genotypes were HPV6 (1.30%), HPV61 (1.21%), and HPV11 (0.85%). In HPV-positive cases, the distribution of single, double, triple, and quadruple or more infections were 79.90%, 15.17%, 3.59%, and 1.33%, respectively. The proportions of pure LR-HPV, pure HR-HPV, and mixed infections were 22.16%, 67.82%, and 10.02%, respectively. Age-specific analysis revealed a bimodal distribution of HPV infection, with the infection rate rapidly decreasing from 44.02% in the ≤ 19 age group to 19.55% in the 20-29 age group and 13.84% in the 30-39 age group, followed by a gradual increase to 14.64% in the 40-49 age group, 16.65% in the 50-59 age group, and 22.98% in the ≥ 60 age group. The coverage rates of the three available vaccines are all below 50%. The results of this study indicated a declining trend in HPV prevalence in the plateau region of Southwest China over the period from 2014 to 2023, especially in the reduction of genotypes targeted by vaccines. CONCLUSION: There were significant variations in the genotypes prevalent among different age groups, years, and patient sources within the same region. The underwhelming vaccination rates emphasize the critical need for developing either a multivalent vaccine or a personalized vaccine that targets the HPV genotypes common in the Chinese population. Furthermore, vaccinating adolescents to curb HPV infection and ensuring regular cervical cancer screenings for postmenopausal women are crucial steps.

The complete chloroplast genome sequences of nine melon varieties (Cucumis melo L.): lights into comparative analysis and phylogenetic relationships.

Melon (Cucumis melo L.) is one of the most extensively grown horticulture crops of the world. Based on the morphological characters, melon was formerly divided into two subspecies, Cucumis melo ssp. melo and C. melo ssp. agrestis. However, the present methods are still inadequate to distinguish between them. The phylogenetic analysis based on chloroplast genome sequences could provide essential evidence for the classification of melon varieties. We sequenced the chloroplast genomes of nine different melon varieties by the Illumina Hiseq and performed bioinformatic analyses including repeat element analysis, genome comparison and phylogenetic analysis. The results showed that the melon chloroplast genome has a typical quadripartite structure that was conserved across the analyzed sequences. Its length ranges between 155, 558 and 156, 569 bp, with a total GC content varying from 36.7% to 37%. We found 127-132 genes in melon chloroplast genomes, including 85-87 protein-coding regions, 34-37 tRNA and 6-8 rRNA genes. The molecular structure, gene order, content, codon usage, long repeats, and simple sequence repeats (SSRs) were mostly conserved among the nine sequenced genomes. Phylogenetic analysis showed that the chloroplast genome could clearly distinguish between C. melo ssp. melo and C. melo ssp. agrestis. This study not only provides valuable knowledge on melon chloroplasts, but also offers a theoretical basis and technical support for the genetic breeding of melons.

Association between triglyceride-glucose index and femoral bone mineral density in community-dwelling, nondiabetic men and women: a NHANES analysis of 1,928 US individuals.

OBJECTIVE: To determine the potential association between the triglyceride-glucose (TyG) index and bone mineral density (BMD) in community-dwelling adults without diabetes using a nationally representative database from the United States (US). METHODS: Data were extracted from the National Health and Nutrition Examination Survey (NHANES) 2005-2010, 2013-2014, and 2017-2018. Men and postmenopausal women aged ≥50 years with complete data on femoral neck BMD, triglycerides, and fasting plasma glucose levels were eligible for inclusion. Participants with diabetes, history of malignancy, thyroid disease, underweight status, end-stage kidney disease, rheumatoid arthritis, estrogen/selective estrogen receptor modulators, bisphosphonate or bone resorption inhibitors, or missing dataset weight values were excluded. Univariate and multivariable logistic regression analyses were performed to determine the associations between low BMD, TyG index, and other study variables. RESULTS: A total of 1,844 participants (1,161 men and 683 women) were included, representing 31,517,106 community-dwelling individuals in the US. The mean age of the study population was 60.7 years old, and 26.7% of the men and 60.4% of the women had low bone density. In both males and females, the mean TyG index was 8.6. After adjusting for demographic, lifestyle, and clinical factors, no significant association was observed between TyG and femoral neck BMD among men (adjusted odds ratio [aOR] = -0.0002, 95% confidence interval [CI]: -0.02 to 0.02) and women (aBeta = 0.005, 95% CI: -0.02 to 0.04). Similarly, no significant association was observed between TyG index and the odds for low bone density among men (aOR = 1.09, 95% CI: 0.73-1.63) and women (aOR = 0.99, 95% CI: 0.49-2.01). CONCLUSIONS: Based on data from a large sample in the US, this study did not find an association between the TyG index and femoral neck BMD or the occurrence of low bone density in community-dwelling males and females without diabetes.

Rational tuning of binding properties of pillar [5] arene-based sensing material by synergistic effect and its application for fluorescent turn-on detection of isoniazid and controlled reversible morphology.

Isoniazid (INH) is crucial in the treatment of tuberculosis; however, its overuse may induce significant gastrointestinal and hepatic side effects. On October 27, 2017, the International Agency for Research on Cancer, under the auspices of the World Health Organization, published a list of carcinogens for preliminary collation and reference. Isoniazid was categorized as a Group 3 carcinogen. The efficient detection of INH poses an important and challenging task. In this study, a "synergistic effect" is incorporated into the pillar (Yamagishi and Ogoshi, 2018) [5] arene-based macrocyclic host (DPA) by strategically attaching bis-p-hydroxybenzoic acid groups to the opposite ends of the pillar (Yamagishi and Ogoshi, 2018) [5] arene. This combination endows DPA with a reversible and selective fluorescence response to isoniazid. Additionally, DPA exhibits excellent analytical capabilities for isoniazid, including speed and selectivity, with a detection limit as low as 4.85 nM. Concurrently, DPA can self-assemble into a microsphere structure, which is convertible into micrometer-sized tubular structures through host-guest interactions with isoniazid. The introduction of a competitive guest, trimethylamine, enables the reversion to its microsphere structure. Consequently, this study presents an innovative and straightforward synthetic approach for smart materials that facilitates the reversible morphological transition between microspheres and microtubes in response to external chemical stimuli. This discovery provides a valuable strategy for designing "synergistic effects" in constructing trace-level isoniazid-responsive interfaces, with potential applications across various fields, such as controlled drug delivery.

Enhanced industrial text classification via hyper variational graph-guided global context integration.

Background: Joint local context that is primarily processed by pre-trained models has emerged as a prevailing technique for text classification. Nevertheless, there are relatively few classification applications on small sample of industrial text datasets. Methods: In this study, an approach of employing global enhanced context representation of the pre-trained model to classify industrial domain text is proposed. To achieve the application of the proposed technique, we extract primary text representations and local context information as embeddings by leveraging the BERT pre-trained model. Moreover, we create a text information entropy matrix through statistical computation, which fuses features to construct the matrix. Subsequently, we adopt BERT embedding and hyper variational graph to guide the updating of the existing text information entropy matrix. This process is subjected to iteration three times. It produces a hypergraph primary text representation that includes global context information. Additionally, we feed the primary BERT text feature representation into capsule networks for purification and expansion as well. Finally, the above two representations are fused to obtain the final text representation and apply it to text classification through feature fusion module. Results: The effectiveness of this method is validated through experiments on multiple datasets. Specifically, on the CHIP-CTC dataset, it achieves an accuracy of 86.82% and an F1 score of 82.87%. On the CLUEEmotion2020 dataset, the proposed model obtains an accuracy of 61.22% and an F1 score of 51.56%. On the N15News dataset, the accuracy and F1 score are 72.21% and 69.06% respectively. Furthermore, when applied to an industrial patent dataset, the model produced promising results with an accuracy of 91.84% and F1 score of 79.71%. All four datasets are significantly improved by using the proposed model compared to the baselines. The evaluation result of the four dataset indicates that our proposed model effectively solves the classification problem.

ANGPTL4, a direct target of hsa-miR-133a-3p, accelerates lung adenocarcinoma lipid metabolism, proliferation and invasion.

BACKGROUND: Globally, lung adenocarcinoma (LUAD) is the most common type of lung cancer. The secreted protein angiopoietin-like 4 (ANGPTL4) has been implicated in a number of physiological and pathological processes, including angiogenesis and lipid metabolism. But the role of ANGPTL4 in LUAD remains unknown. METHODS: The expression of ANGPTL4 and miR-133a-3p was confirmed by public database analysis. Xenograft model, MTT, Clone formation and EdU analysis were used to confirm the effects of miR-133a-3p/ANGPTL4 on LUAD cell proliferation and growth. Wound healing and Transwell analysis were used to elucidate the role of miR-133a-3p/ANGPTL4 in LUAD cell migration and invasion. Oil red O staining was used to confirm ANGPTL4 in LUAD lipids production. Dual-luciferase reporter gene analysis was used to demonstrate miR-133a-3p could directly bind ANGPTL4 3'-UTR. WB and PCR were used to confirm the protein expression of ANGPTL4. RESULTS: ANGPTL4 was significantly increased in LUAD samples, which could promote LUAD cell proliferation, migration, invasion, growth and lipid production. miR-133a-3p could directly bind to ANGPTL4 mRNA, and repress the expression ANGPTL4, resulting in suppressing LUAD proliferation and metastasis. CONCLUSION: In conclusion, miR-133a-3p/ANGPTL4 axis might be a potential biomarker and therapeutic target for LUAD patients.