High-Resolution Spatiotemporal Modeling for PM2.5 Major Components in the Pearl River Delta and Its Implications for Epidemiological Studies.

Distinguishing the effects of different fine particulate matter components (PMCs) is crucial for mitigating their effects on human health. However, the sparse distribution of locations where PM is collected for component analysis makes it challenging to investigate the relevant health effects. This study aimed to investigate the agreement between data-fusion-enhanced exposure assessment and site monitoring data in estimating the effects of PMCs on gestational diabetes mellitus (GDM). We first improved the spatial resolution and accuracy of exposure assessment for five major PMCs (EC, OM, NO3-, NH4+, and SO42-) in the Pearl River Delta region by a data fusion model that combined inputs from multiple sources using a random forest model (10-fold cross-validation R2: 0.52 to 0.61; root mean square error: 0.55 to 2.26 µg/m3). Next, we compared the associations between exposures to PMCs during pregnancy and GDM in a hospital-based cohort of 1148 pregnant women in Heshan, China, using both site monitoring data and data-fusion model estimates. The comparative analysis showed that the data-fusion-based exposure generated stronger estimates of identifying statistical disparities. This study suggests that data-fusion-enhanced estimates can improve exposure assessment and potentially mitigate the misclassification of population exposure arising from the utilization of site monitoring data.

The association between PM2.5 components and blood pressure changes in late pregnancy: A combined analysis of traditional and machine learning models.

BACKGROUND: PM2.5 is a harmful mixture of various chemical components that pose a challenge in determining their individual and combined health effects due to multicollinearity issues with traditional linear regression models. This study aimed to develop an analytical methodology combining traditional and novel machine learning models to evaluate PM2.5's combined effects on blood pressure (BP) and identify the most toxic components. METHODS: We measured late-pregnancy BP of 1138 women from the Heshan cohort while simultaneously analyzing 31 PM2.5 components. We utilized multiple linear regression modeling to establish the relationship between PM2.5 components and late-pregnancy BP and applied Random Forest (RF) and generalized Weighted Quantile Sum (gWQS) regression to identify the most toxic components contributing to elevated BP and to quantitatively evaluate the cumulative effect of the PM2.5 component mixtures. RESULTS: The results revealed that 16 PM2.5 components, such as EC, OC, Ti, Fe, Mn, Cu, Cd, Mg, K, Pb, Se, Na+, K+, Cl-, NO3-, and F-, contributed to elevated systolic blood pressure (SBP), while 26 components, including two carbon components (EC, OC), fourteen metallics (Ti, Fe, Mn, Cr, Mo, Co, Cu, Zn, Cd, Na, Mg, Al, K, Pb), one metalloid (Se), and nine water-soluble ions (Na+, K+, Mg2+, Ca2+, NH4+, Cl-, NO3-, SO42-, F-), contributed to elevated diastolic blood pressure (DBP). Mn and Cr were the most toxic components for elevated SBP and DBP, respectively, as analyzed by RF and gWQS models and verified against each other. Exposure to PM2.5 component mixtures increased SBP by 1.04 mmHg (95% CI: 0.33-1.76) and DBP by 1.13 mmHg (95% CI: 0.47-1.78). CONCLUSIONS: Our study highlights the effectiveness of combining traditional and novel models as an analytical strategy to quantify the health effects of PM2.5 constituent mixtures.

Apelin Prevents and Alleviates Crystalline Silica-induced Pulmonary Fibrosis via Inhibiting Transforming Growth Factor Beta 1-triggered Fibroblast Activation.

Silicosis is a common and ultimately fatal occupational disease, yet the limited therapeutic option remains the major clinical challenge. Apelin, an endogenous ligand of the G-protein-coupled receptor (APJ), is abundantly expressed in diverse organs. The apelin-APJ axis helps to control pathological and physiological processes in lung. The role of apelin in the pathological process and its possible therapeutic effects on silicosis have not been elucidated. In this study, we found that lung expression and circulating levels of apelin were markedly decreased in silicosis patients and silica-induced fibrotic mice and associated with the severity. Furthermore, in vivo data demonstrated that pre-treatment from day 3 and post-treatment from day 15 with apelin could both alleviate silica-induced pulmonary fibrosis in mice. Besides, apelin inhibited pulmonary fibroblast activation via transforming growth factor beta 1 (TGF-ß1) signaling. Our study suggested that apelin could prevent and reverse silica-induced pulmonary fibrosis by inhibiting the fibroblast activation through TGF-ß1 signaling pathway, thus providing a new potential therapeutic strategy for silicosis and other pulmonary fibrosis.

Preliminary Validation of the Revised Illness Perception Questionnaire for Patients with Nasopharyngeal Carcinoma in China.

Nasopharyngeal carcinoma is a common and highly malignant cancer in southern China. It is important to accurately assess the illness perception of nasopharyngeal carcinoma according to the common-sense model of self-regulation. The purpose was to validate the Chinese version of the Revised Illness Perception Questionnaire for patients with Nasopharyngeal carcinoma. A cross-sectional survey of 631 patients with Nasopharyngeal carcinoma was conducted in Guangzhou, China. The reliability of the scale was evaluated using Cronbach's alpha. The factor structure was assessed using exploratory factor analysis (EFA) of each dimension. The EFA revealed that the 29-item self-rated scale has a seven-factor structure consistent with the original scale and explained 67.3% of the variance after extraction and rotation. The scale showed satisfactory reliability. The item-total correlations ranged from -0.16 to 0.64 (p < 0.05). The item-subscale correlations ranged from 0.46 to 0.91 (p < 0.05). The item-other subscale correlations ranged from -0.38 to 0.51 and from -0.21 to 0.56 (p < 0.05). Significant correlations were found between the timeline (acute/chronic) (r = 0.224, r = 0.166), consequences (r = 0.415, r = 0.338), timeline cyclical (r = 0.366, r = 0.284), emotional representations (r = 0.497, r = 0.465), personal control (r = -0.122, r = -0.134), treatment control (r = -0.135, r = -0.148), and illness coherence (r = -0.261, r = -0.213) subscales, and depression, anxiety (p < 0.05). The scale revealed acceptable reliability, factorial validity, and construct validity. It could be used to assess the illness representations of Chinese patients with nasopharyngeal carcinoma.

Evolutionary and Characteristic Analysis of RING-DUF1117 E3 Ubiquitin Ligase Genes in Gossypium Discerning the Role of GhRDUF4D in Verticillium dahliae Resistance.

Verticillium wilt, primarily induced by the soil-borne fungus Verticillium dahliae, is a serious threat to cotton fiber production. There are a large number of really interesting new gene (RING) domain-containing E3 ubiquitin ligases in Arabidopsis, of which three (At2g39720 (AtRHC2A), At3g46620 (AtRDUF1), and At5g59550 (AtRDUF2)) have a domain of unknown function (DUF) 1117 domain in their C-terminal regions. This study aimed to detect and characterize the RDUF members in cotton, to gain an insight into their roles in cotton's adaptation to environmental stressors. In this study, a total of 6, 7, 14, and 14 RDUF (RING-DUF1117) genes were detected in Gossypium arboretum, G. raimondii, G. hirsutum, and G. barbadense, respectively. These RDUF genes were classified into three groups. The genes in each group were highly conserved based on gene structure and domain analysis. Gene duplication analysis revealed that segmental duplication occurred during cotton evolution. Expression analysis revealed that the GhRDUF genes were widely expressed during cotton growth and under abiotic stresses. Many cis-elements related to hormone response and environment stressors were identified in GhRDUF promoters. The predicted target miRNAs and transcription factors implied that GhRDUFs might be regulated by gra-miR482c, as well as by transcription factors, including MYB, C2H2, and Dof. The GhRDUF genes responded to cold, drought, and salt stress and were sensitive to jasmonic acid, salicylic acid, and ethylene signals. Meanwhile, GhRDUF4D expression levels were enhanced after V. dahliae infection. Subsequently, GhRDUF4D was verified by overexpression in Arabidopsis and virus-induced gene silencing treatment in upland cotton. We observed that V. dahliae resistance was significantly enhanced in transgenic Arabidopsis, and weakened in GhRDUF4D silenced plants. This study conducted a comprehensive analysis of the RDUF genes in Gossypium, hereby providing basic information for further functional studies.

Evolution and Characterization of Acetyl Coenzyme A: Diacylglycerol Acyltransferase Genes in Cotton Identify the Roles of GhDGAT3D in Oil Biosynthesis and Fatty Acid Composition.

Cottonseed oil is rich in unsaturated fatty acids (UFAs) and serves as an edible oil in human nutrition. Reports suggest that acyl-coenzyme A: diacylglycerol acyltransferases (DGAT) and wax ester synthase/DGAT (WSD1) genes encode a key group of enzymes that catalyze the final step for triacylglycerol biosynthesis and enable an important rate-limiting process. However, their roles in oil biosynthesis and the fatty acid profile of cotton seed are poorly understood. Therefore, the aim of this study was to identify and characterize DGAT and WSD1 genes in cotton plants and examine their roles in oil biosynthesis, the fatty acid profile of cotton seeds, and abiotic stress responses. In this study, 36 GhDGAT and GhWSD1 genes were identified in upland cotton (G. hirsutum) and found to be clustered into four groups: GhDGAT1, GhDGAT2, GhDGAT3, and GhWSD1. Gene structure and domain analyses showed that the GhDGAT and GhWSD1 genes in each group are highly conserved. Gene synteny analysis indicated that segmental and tandem duplication events occurred frequently during cotton evolution. Expression analysis revealed that GhDGAT and GhWSD1 genes function widely in cotton development and stress responses; moreover, several environmental stress and hormone response-related cis-elements were detected in the GhDGAT and GhWSD1 promoter regions. The predicted target transcription factors and miRNAs imply an extensive role of GhDGAT and GhWSD1 genes in stress responses. Increases in GhDGAT3 gene expression with increases in cottonseed oil accumulation were observed. Transformation study results showed that there was an increase in C18:1 content and a decrease in C18:2 and C18:3 contents in seeds of Arabidopsis transgenic plants overexpressing GhDGAT3D compared with that of control plants. Overall, these findings contributed to the understanding of the functions of GhDGAT and GhWSD1 genes in upland cotton, providing basic information for further research.

Long Noncoding RNA 00472: A Novel Biomarker in Human Diseases.

Long non-coding RNAs (lncRNAs) play important roles in human diseases. They control gene expression levels and influence various biological processes through multiple mechanisms. Functional abnormalities in lncRNAs are strongly associated with occurrence and development of various diseases. LINC00472, which is located on chromosome 6q13, is involved in several human diseases, particularly cancers of the breast, lung, liver, osteosarcoma, bladder, colorectal, ovarian, pancreatic and stomach. Importantly, LINC00472 can be used as a biomarker for breast cancer cell sensitivity to chemotherapeutic regimens, including doxorubicin. LINC00472 is regulated by microRNAs and several signaling pathways. However, the significance of LINC00472 in human diseases has not been clearly established. In this review, we elucidate on the significance of LINC00472 in various human diseases, indicating that LINC00472 may be a diagnostic, prognostic as well as therapeutic target for these diseases.