Phthalate metabolites and sex steroid hormones in relation to obesity in US adults: NHANES 2013-2016

BackgroundObesity and metabolic syndrome pose significant health challenges in the United States (US), with connections to disruptions in sex hormone regulation. The increasing prevalence of obesity and metabolic syndrome might be associated with exposure to phthalates (PAEs). Further exploration of the impact of PAEs on obesity is crucial, particularly from a sex hormone perspective.MethodsA total of 7780 adult participants in the National Health and Nutrition Examination Survey (NHANES) from 2013 to 2016 were included in the study. Principal component analysis (PCA) coupled with multinomial logistic regression was employed to elucidate the association between urinary PAEs metabolite concentrations and the likelihood of obesity. Weighted quartiles sum (WQS) regression was utilized to consolidate the impact of mixed PAEs exposure on sex hormone levels (total testosterone (TT), estradiol and sex hormone-binding globulin (SHBG)). We also delved into machine learning models to accurately discern obesity status and identify the key variables contributing most to these models.ResultsPrincipal Component 1 (PC1), characterized by mono(2-ethyl-5-carboxypentyl) phthalate (MECPP), mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), and mono(2-ethyl-5-oxohexyl) phthalate (MEOHP) as major contributors, exhibited a negative association with obesity. Conversely, PC2, with monocarboxyononyl phthalate (MCNP), monocarboxyoctyl phthalate (MCOP), and mono(3-carboxypropyl) phthalate (MCPP) as major contributors, showed a positive association with obesity. Mixed exposure to PAEs was associated with decreased TT levels and increased estradiol and SHBG. During the exploration of the interrelations among obesity, sex hormones, and PAEs, models based on Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) algorithms demonstrated the best classification efficacy. In both models, sex hormones exhibited the highest variable importance, and certain phthalate metabolites made significant contributions to the model’s performance.ConclusionsIndividuals with obesity exhibit lower levels of TT and SHBG, accompanied by elevated estradiol levels. Exposure to PAEs disrupts sex hormone levels, contributing to an increased risk of obesity in US adults. In the exploration of the interrelationships among these three factors, the RF and XGBoost algorithm models demonstrated superior performance, with sex hormones displaying higher variable importance

Ubiquitin ligase RNF125 targets PD-L1 for ubiquitination and degradation

As a critical immune checkpoint molecule, PD-L1 is expressed at significantly higher levels in multiple neoplastic tissues compared to normal ones. PD-L1/PD-1 axis is a critical target for tumor immunotherapy, blocking the PD-L1/PD-1 axis is recognized and has achieved unprecedented success in clinical applications. However, the clinical efficacy of therapies targeting the PD-1/PD-L1 pathway remains limited, emphasizing the need for the mechanistic elucidation of PD-1/PD-L1 expression. In this study, we found that RNF125 interacted with PD-L1 and regulated PD-L1 protein expression. Mechanistically, RNF125 promoted K48-linked polyubiquitination of PD-L1 and mediated its degradation. Notably, MC-38 and H22 cell lines with RNF125 knockout, transplanted in C57BL/6 mice, exhibited a higher PD-L1 level and faster tumor growth than their parental cell lines. In contrast, overexpression of RNF125 in MC-38 and H22 cells had the opposite effect, resulting in lower PD-L1 levels and delayed tumor growth compared with parental cell lines. In addition, immunohistochemical analysis of MC-38 tumors with RNF125 overexpression showed significantly increased infiltration of CD4+, CD8+ T cells and macrophages. Consistent with these findings, analyses using The Cancer Genome Atlas (TCGA) public database revealed a positive correlation of RNF125 expression with CD4+, CD8+ T cell and macrophage tumor infiltration. Moreover, RNF125 expression was significantly downregulated in several human cancer tissues, and was negatively correlated with the clinical stage of these tumors, and patients with higher RNF125 expression had better clinical outcomes. Our findings identify a novel mechanism for regulating PD-L1 expression and may provide a new strategy to increase the efficacy of immunotherapy

Enhancing security in e-business processes: Utilizing dynamic slicing of Colored Petri Nets for logical vulnerability detection

The field of e-business covers multiple aspects and has undergone rapid development, profoundly changing our transaction methods and shopping experiences. However, with the increasing complexity of its business processes, logical vulnerabilities have become an inevitable issue. These logical vulnerabilities can lead to a range of security problems, seriously threatening business stability and consumer trust. To address the challenge of logical vulnerabilities in e-business, we developed a model based on Colored Petri Nets (CPN), the Interactive Business Process Fusion (IBPF) net, which is adept at identifying such vulnerabilities during the design phase. However, the analysis methods for IBPF net still urgently need innovation. In addressing this issue, we use dynamic slicing techniques to analyze IBPF net, serving as a method for revealing logical vulnerabilities. We obtain backward slice, partial forward slice, and bidirectional slice through the slicing algorithms. Eventually, these three types of slices are merged to form the final dynamic slice. This technique, which involves a more targeted analysis than examining the entire IBPF net, simplifies analysis process and prevents state space explosion, thereby providing a distinct advantage. The results of this research are of great value in enhancing system reliability, reducing maintenance costs, and providing analysis techniques in the field of e-business security

Single cell transcriptional zonation of human psoriasis skin identifies an alternative immunoregulatory axis conducted by skin resident cells

Psoriasis is the most common skin disease in adults. Current experimental and clinical evidences suggested the infiltrating immune cells could target local skin cells and thus induce psoriatic phenotype. However, recent studies indicated the existence of a potential feedback signaling loop from local resident skin cells to infiltrating immune cells. Here, we deconstructed the full-thickness human skins of both healthy donors and patients with psoriasis vulgaris at single cell transcriptional level, and further built a neural-network classifier to evaluate the evolutional conservation of skin cell types between mouse and human. Last, we systematically evaluated the intrinsic and intercellular molecular alterations of each cell type between healthy and psoriatic skin. Cross-checking with psoriasis susceptibility gene loci, cell-type based differential expression, and ligand-receptor communication revealed that the resident psoriatic skin cells including mesenchymal and epidermis cell types, which specifically harbored the target genes of psoriasis susceptibility loci, intensively evoked the expression of major histocompatibility complex (MHC) genes, upregulated interferon (INF), tumor necrosis factor (TNF) signalling and increased cytokine gene expression for primarily aiming the neighboring dendritic cells in psoriasis. The comprehensive exploration and pathological observation of psoriasis patient biopsies proposed an uncovered immunoregulatory axis from skin local resident cells to immune cells, thus provided a novel insight for psoriasis treatment. In addition, we published a user-friendly website to exhibit the transcriptional change of each cell type between healthy and psoriatic human skin.Peer reviewe

The Syncretic Effect of Dual-Source Data on Affective Computing in Online Learning Contexts: A Perspective From Convolutional Neural Network With Attention Mechanism

Affective computing (AC) has been regarded as a relevant approach to identifying online learners’ mental states and predicting their learning performance. Previous research mainly used one single-source data set, typically learners’ facial expression, to compute learners’ affection. However, a single facial expression may represent different affections in various head poses. This study proposed a dual-source data approach to solve the problem. Facial expression and head pose are two typical data sources that can be captured from online learning videos. The current study collected a dual-source data set of facial expressions and head poses from an online learning class in a middle school. A deep learning neural network using AlexNet with an attention mechanism was developed to verify the syncretic effect on affective computing of the proposed dual-source fusion strategy. The results show that the dual-source fusion approach significantly outperforms the single-source approach based on the AC recognition accuracy between the two approaches (dual-source approach using Attention-AlexNet model 80.96%; single-source approach, facial expression 76.65% and head pose 64.34%). This study contributes to the theoretical construction of the dual-source data fusion approach, and the empirical validation of the effect of the Attention-AlexNet neural network approach on affective computing in online learning contexts

Diacylglycerol Acyltransferase 3(DGAT3) Is Responsible for the Biosynthesis of Unsaturated Fatty Acids in Vegetative Organs of Paeonia rockii

‘Diacylglycerol acyltransferase (DGAT)’ acts as a key rate-limiting enzyme that catalyzes the final step of the de novo biosynthesis of triacylglycerol (TAG). The study was to characterize the function of the DGAT3 gene in Paeonia rockii, which is known for its accumulation of high levels of unsaturated fatty acids (UFAs). We identified a DGAT3 gene which encodes a soluble protein that is located within the chloroplasts of P. rockii. Functional complementarity experiments in yeast demonstrated that PrDGAT3 restored TAG synthesis. Linoleic acid (LA, C18:2) and α-linolenic acid (ALA, C18:3) are essential unsaturated fatty acids that cannot be synthesized by the human body. Through the yeast lipotoxicity test, we found that the yeast cell density was largely increased by adding exogenous LA and, especially, ALA to the yeast medium. Further ectopic transient overexpression in Nicotiana benthamiana leaf tissue and stable overexpression in Arabidopsis thaliana indicated that PrDGAT3 significantly enhanced the accumulation of the TAG and UFAs. In contrast, we observed a significant decrease in the total fatty acid content and in several major fatty acids in PrDGAT3-silenced tree peony leaves. Overall, PrDGAT3 is important in catalyzing TAG synthesis, with a substrate preference for UFAs, especially LA and ALA. These results suggest that PrDGAT3 may have practical applications in improving plant lipid nutrition and increasing oil production in plants

A novel strategy for the construction of covalent organic frameworks from nonporous covalent organic polymers

The field of covalent organic frameworks (COFs) has been developed significantly in the past decade on account of their important characteristics and vast application potential. On the other hand, the discovery of novel synthetic methodology is still a challenging task to further promote the preparation of COFs. Herein, an interesting protocol for the conversion of amorphous nonporous covalent organic polymers (COPs) to COFs was established, affording four COFs with high crystallinity and porosity. Specifically, imine-linked amorphous COP-1 was successfully converted to COF-1-4 by replacing one type of linker with other organic building blocks. The realization of this conversion provides a facile method for constructing COFs from COPs.Ministry of Education (MOE)This work was supported by the National Natural Science Foundation of China (21771138) and the Natural Science Foundation of Tianjin (16JCYBJC19700). This research is also supported by the Singapore Academic Research Fund (RG5/16, RG11/17 and RG114/17)