Integrated Analysis of CD1A Immune Infiltration and Competing Endogenous RNA Networks in COAD.

Background: The CD1A gene, a key component of the human immune system and part of the CD1 family, plays a crucial role in presenting lipid antigens to T cells. Abnormal CD1A expression is associated with various immune-related diseases and tumors. However, the biological function of CD1A in COAD is unclear. Methods: Multiple databases were systematically employed to conduct an analysis of CD1A expression in pan-cancer and COAD, along with its clinical-pathological features. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses of CD1A were performed using the 'clusterProfiler' package. The Protein-protein interaction (PPI) analysis of CD1A was used the STRING database. Additionally, TIMER and ssGSEA tools were used to explore the relationship between CD1A expression in COAD and immune cell infiltration. The study also investigated the association between CD1A expression and N6-methyladenosine (m6A) modification genes in the TCGA COAD cohort and constructed a CD1A-centric competing endogenous RNA (ceRNA) regulatory network. Results: CD1A displays varying expression levels in various tumors, including COAD, and is closely linked to clinical-pathological characteristics. GO analysis suggests that CD1A plays a role in important processes like antigen processing and presentation, leukocyte-mediated immunity, and lymphocyte-mediated immunity. KEGG analysis identifies CD1A's involvement in key pathways such as the Chemokine signaling pathway and Cytokine-cytokine receptor interaction. PPI analysis highlights CD1A's interactions with CD207, CD1C, CD1E, FOXP3, and ITGB2. ssGSEA analysis indicates a significant relationship between CD1A expression and the infiltration of various immune cells in COAD. Significant associations were found between CD1A and m6A modification genes in COAD. Furthermore, a CD1A-centered ceRNA regulatory network has been constructed. Conclusion: CD1A emerges as a potential biomarker for the diagnosis and treatment of COAD, showing a strong association with tumor immune infiltration, m6A modification, and the ceRNA network.

Downregulation of NAT1 Expression is Associated with Poor Prognosis and Immune Infiltration in COAD.

Background: An increasing corpus of evidence has identified the involvement of N-acetyltransferase 1 (NAT1), a member of the NAT family, in the progression of various cancers. However, the specific function of NAT1 in colon cancer (COAD) remains elusive. This study aims to decip her the role of NAT1 in COAD and its associated mechanisms. Methods: The Tumor Immunity Evaluation Resource (TIMER), The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO) databases were employed to assess the NAT1 expression level in COAD. The differential expression between COAD and normal colon tissue was further validated using quantitative real-time reverse-transcription PCR (RT-qPCR) and Western blot (WB) analyses. Additionally, survival analysis of NAT1 in COAD was carried out using the PrognoScan database and TCGA dataset. The functions of NAT1 were explored through gene set enrichment analysis (GSEA) and immuno-infiltration analysis. Results: There was a significant reduction in NAT1 expression in COAD samples compared to normal tissue. Notably, low NAT1 expression in COAD correlated significantly with various clinical parameters such as tumor stage (T stage, N stage, M stage, pathologic stage), primary therapy outcome, carcinoembryonic antigen (CEA) level, and lymphatic invasion. The downregulation of NAT1 was also strongly linked with poor outcomes in overall survival (OS), progression-free interval (PFI), and disease-specific survival (DSS). Cox regression analysis highlighted NAT1 as an independent prognostic indicator for overall survival in COAD patients. GSEA results revealed NAT1's involvement in multiple pathways, including the neuroactive ligand-receptor interaction, olfactory transduction, olfactory signaling, extracellular matrix receptor interaction, calcium signaling, and focal adhesion pathways. Furthermore, NAT1 expression was found to significantly correlate with infiltration levels of various immune cells. Conclusion: The findings reveal NAT1's potential as a valuable prognostic biomarker for COAD. Moreover, its associated mechanisms offer insights that might pave the way for therapeutic interventions for COAD patients.

Complementary and alternative medicine in relation to chemotherapy-induced peripheral neuropathy: A narrative review.

PURPOSE: To summarizes the available evidence on the effectiveness, safety, and feasibility of complementary and alternative medicine (CAM) in the management of chemotherapy-induced peripheral neuropathy (CIPN). METHODS: We searched for systematic reviews, and meta-analyzes published up to April 2023 in the Pubmed and Web of Science databases. The latest original research on related topics was also reviewed. The search was restricted to English-language papers. Two independent reviewers performed a quality assessment of the identified literature. RESULTS: The results of 35 systematic reviews and meta-analyzes were included in this study. Preliminary evidence suggests that CAM, including acupuncture, physical activity (PA), herbal and nutritional supplements, mind-body therapies, touch therapy, and non-invasive neuromodulation techniques, have shown tremendous potential for the prevention and treatment of CIPN. Of these, there is strong evidence supporting acupuncture, PA, and herbal medicine. However, existing clinical studies are also limited by the heterogeneity of study methods, insufficient sample size, and poor study design. Further studies are needed to validate the efficacy of CAM in patients with CIPN and to elucidate potential therapeutic mechanisms. CONCLUSIONS: Current research has reached a preliminary conclusion suggesting the potential efficacy of certain CAMs in the management of CIPN. Future clinical trials should incorporate more robust study design protocols and larger sample sizes to enhance the validity of findings.

Identification and Validation of Key miRNAs for Colon Cancer Based on miRNA-Gene Integration Analysis.

Background: MicroRNAs (miRNAs) plays an essential role in the pathogenesis of colon cancer. This study aims to identify and verify key miRNAs that may serve as potential biomarkers for early diagnosis and treatment of colon cancer. Methods: Two miRNA microarray datasets (GSE53339 and GSE126093) were downloaded from the Gene Expression Omnibus (GEO) database, and the common differentially expressed miRNAs (DEMis) of both were identified by the "limma" package and the intersect function in R. Then, the miRwalk online tool was used to predict the target genes of the common DEMis and perform Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on those DEMis. The miRNA-gene network was constructed using Cytoscape software to identify key miRNAs and validated using quantitative real-time PCR (qRT-PCR) and The Cancer Genome Atlas (TCGA) dataset information for experimental and external database validation, respectively. In addition, we explored the correlation between key miRNAs and infiltrating immune cells and immunotherapy biomarkers. Results: Fourteen common DEMis were identified from the GEO database, and five targeted genes were predicted. A microRNA-gene network was subsequently constructed to identify three key miRNAs (miR-363-3p, miR-520e, and miR-330-5p). Both qRT-PCR and external database validation confirmed our findings. In addition, we found that miR-520e was significantly associated with infiltrating immune cells and established immune checkpoints. Conclusion: Our study identified three key miRNAs that influence the development of colon cancer. In addition, further studies suggest that infiltrating immune cells may play an essential role in the pathogenesis of colon cancer. These findings assist in early diagnosis and precision-targeted therapies.

Comparison of logistic regression with machine learning methods for the prediction of fetal growth abnormalities: a retrospective cohort study.

BACKGROUND: While there is increasing interest in identifying pregnancies at risk for adverse outcome, existing prediction models have not adequately assessed population-based risks, and have been based on conventional regression methods. The objective of the current study was to identify predictors of fetal growth abnormalities using logistic regression and machine learning methods, and compare diagnostic properties in a population-based sample of infants. METHODS: Data for 30,705 singleton infants born between 2009 and 2014 to mothers resident in Nova Scotia, Canada was obtained from the Nova Scotia Atlee Perinatal Database. Primary outcomes were small (SGA) and large for gestational age (LGA). Maternal characteristics pre-pregnancy and at 26 weeks were studied as predictors. Logistic regression and select machine learning methods were used to build the models, stratified by parity. Area under the curve was used to compare the models; relative importance of predictors was compared qualitatively. RESULTS: 7.9% and 13.5% of infants were SGA and LGA, respectively; 48.6% of births were to primiparous women and 51.4% were to multiparous women. Prediction of SGA and LGA was poor to fair (area under the curve 60-75%) and improved with increasing parity and pregnancy information. Smoking, previous low birthweight infant, and gestational weight gain were important predictors for SGA; pre-pregnancy body mass index, gestational weight gain, and previous macrosomic infant were the strongest predictors for LGA. CONCLUSIONS: The machine learning methods used in this study did not offer any advantage over logistic regression in the prediction of fetal growth abnormalities. Prediction accuracy for SGA and LGA based on maternal information is poor for primiparous women and fair for multiparous women.

Meteorological conditions conducive to PM2.5 pollution in 2016/2017 in the Western Yangtze River Delta, China.

Cities in Anhui province in the western Yangtze River Delta (YRD), China experienced more PM2.5 pollution days in the winter of 2016/2017 (Dec 2016 to Feb 2017) than in the previous two winters under conditions of emission deductions. By employing back-trajectory-clustering analysis together with daily air quality index (AQI) data from 2015 to 2017, routine and reanalysis meteorological data, and some climate indices, we investigated the transport paths, large-scale vertical motion and related climate background conducive to PM2.5 pollution in Anhui province. We obtained 5 air-mass paths affecting Anhui province in winter; among them, the slow-moving air-masses from the northeast and northwest often led to PM2.5 pollution. Thus, they belong to adverse transport paths, which accounted for approximately 52% in northern Anhui and 62% in central Anhui. Compared with winter 2015/2016, the proportions of adverse transport paths in winter 2016/2017 increased 13% in Hefei (central site), 3% in Suzhou (northern site), and 9% in Chizhou (southern site); correspondingly, east winds increased, and north winds weakened in the boundary layer, which favoured the accumulation of pollutants in Anhui. The processes of pollution and cleaning in Anhui were also closely related to vertical motion of the middle troposphere (500 hPa), and the sinking (ascending) corresponding to the aggravation (mitigation) of pollution. Compared with the winter of 2015/2016, the percentage of downward vertical velocity at 500 hPa exceeding 0.2 Pa/s increased evidently in the winter of 2016/2017. Thus, the vertical velocity at 500 hPa can be used as an important factor for air quality prediction in winter. The interannual changes in transport conditions are related to changes in the Asia zonal and meridional circulations and may further be ascribed to the thermal and dynamic conditions in the Tropical Ocean.

The association between prenatal exposure to organochlorine pesticides and thyroid hormone levels in newborns in Yancheng, China.

Organochlorine pesticides can interfere with the thyroid hormones that play an important role in early neurodevelopment. Although organochlorine pesticides have been banned in China since 1983, their residues are still detectable in the environment. However, few studies have investigated the adverse health effects of prenatal exposure to organochlorine pesticide residues on newborns in China. The present study, conducted in Yancheng City, Jiangsu Province, China, aimed to examine the association between the levels of organochlorine pesticides in maternal and cord sera and to assess the impact of prenatal exposure to organochlorine pesticides on thyroid hormone levels in cord serum. Eleven organochlorine pesticides in maternal and cord sera were measured in 247 mother-infant pairs recruited from Yancheng City between February 2010 and June 2010. The concentration of the thyroid hormones free triiodothyronine (FT3), free thyroxine (FT4), and thyrotropin (TSH) were determined in cord serum. Among the 11 tested organochlorine pesticides, the detectable levels of hexachlorobenzene (HCB), ß-hexachlorocycolohexane (ß-HCH) and p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE) in both maternal and cord sera were above 50%. The levels of ß-HCH and p,p'-DDE in maternal sera were positively associated with the levels in cord sera (r=0.421, P<0.01; r=0.288, P<0.01). After adjusting for confounders, the TSH level in cord serum samples was negatively associated with the HCB level (OR=0.535, 95% CI=(0.304-0.941)). Our data demonstrated that DDT, ß-HCH and HCB residues bioconcentrate in maternal and cord sera. Moreover, the correlation analysis suggested that organochlorine pesticides in maternal blood can transfer through the placenta and affect newborn thyroid hormone levels.

Serum zinc, copper, and zinc/copper in healthy residents of Jinan.

Sera of 890 healthy Jinan residents were chosen randomly, and the concentrations of serum Zn and Cu were detected by atomic absorption spectrometry. The mean serum Zn and Cu concentrations and Zn/Cu were 1.32 +/- 0.49 mg/l, 0.99 +/- 0.26 mg/l, and 1.41 +/- 0.56, respectively. Significantly higher levels of serum Zn and Zn/Cu but lower serum Cu were found in the men. Descending tendency of serum Zn and Zn/Cu was observed with social-economic status and age but not significant. Alcohol consumption produced higher level of serum Zn and Zn/Cu but lower Cu concentration. Smoking caused significant lower level in serum Cu concentration but no significance in serum Zn and Zn/Cu. Serum Zn and Zn/Cu were normal only when hours of sleep a night were kept within 7-9 h. Higher level of serum Zn and Cu concentrations and Zn/Cu were observed in individuals with regular physical exercise, but still no significant difference existed. No clear relationship between educational levels with serum Zn and Cu concentrations and Zn/Cu was observed.