Monobutyl phthalate induces the expression change of G-Protein-Coupled Receptor 30 in rat testicular Sertoli cells

The aim of the study was to explore whether G-Protein-Coupled Receptor 30 (GPR30) was expressed in rat testicular Sertoli cells and to assess the impact of monobutyl phthalate (MBP) on the expression of GPR30 in Sertoli cells. By using RT-PCR, Western-Blot and immunofluorescent microscopy, the expression of GPR30 in rat Sertoli cells was found at both gene and protein level. Cultures of Sertoli cells were exposed to MBP (10– –1000 mM) or a vehicle. The results indicated that the expression of GPR30 increased at gene and protein levels in Sertoli cells following administration of MBP even at a relatively low concentration. We suggest that changes of GPR30 expression may play an important role in the effects of the xenoestrogen MBP on Sertoli cell function. (Folia Histochemica et Cytobiologica 2013, Vol. 51, No. 1, 18–24

Fine-grained Private Knowledge Distillation

Knowledge distillation has emerged as a scalable and effective way for privacy-preserving machine learning. One remaining drawback is that it consumes privacy in a model-level (i.e., client-level) manner, every distillation query incurs privacy loss of one client's all records. In order to attain fine-grained privacy accountant and improve utility, this work proposes a model-free reverse $k$-NN labeling method towards record-level private knowledge distillation, where each record is employed for labeling at most $k$ queries. Theoretically, we provide bounds of labeling error rate under the centralized/local/shuffle model of differential privacy (w.r.t. the number of records per query, privacy budgets). Experimentally, we demonstrate that it achieves new state-of-the-art accuracy with one order of magnitude lower of privacy loss. Specifically, on the CIFAR-$10$ dataset, it reaches $82.1\%$ test accuracy with centralized privacy budget $1.0$; on the MNIST/SVHN dataset, it reaches $99.1\%$/$95.6\%$ accuracy respectively with budget $0.1$. It is the first time deep learning with differential privacy achieve comparable accuracy with reasonable data privacy protection (i.e., $\exp(\epsilon)\leq 1.5$). Our code is available at https://github.com/liyuntong9/rknn

Natural gas sweetening using tailored ionic liquid-methanol mixed solvent with selective removal of H₂S and CO₂

Natural gas is often preferred in various energy applications due to its many advantages over conventional fossil fuels such as oil and coal. However, the removal of pollutants from natural gas, particularly hydrogen sulfide (H2S) and carbon dioxide (CO2), requires complex treatment strategies, significantly impacting the cost of natural gas production. In this work, we propose a mixed solvent combining ionic liquid (IL) and methanol, which can selectively and simultaneously remove H2S and CO2 by customizing the IL structure and its ratio in the solvent. This purification process offers improved efficiency and energy savings compared to traditional methods. To determine the optimal IL structure in the mixed solvent, a computer-aided design method was employed. Through solving the formulated MINLP problem, the IL 1-methyl pyridinium trifluoroacetate ([C1OHPy][TFA]) was identified as having the highest affinity for H2S, making it suitable for use in the IL-methanol mixed solvent. Furthermore, the upgrading process of high-sulfur natural gas using the IL-methanol mixed solvent was simulated and evaluated, comparing it to the benchmark natural gas upgrading (Rectisol) process. The results demonstrate that the IL-methanol mixed solvent natural gas upgrading process achieved a 55.57 % power savings and reduced the annual total cost (TAC) by 23.90 % compared to the Rectisol process. These findings highlight the significant potential of our tailored IL-methanol mixed solvent in natural gas production.</p

New insights into autophagy in inflammatory subtypes of asthma

Asthma is a heterogeneous airway disease characterized by airway inflammation and hyperresponsiveness. Autophagy is a self-degrading process that helps maintain cellular homeostasis. Dysregulation of autophagy is involved in the pathogenesis of many diseases. In the context of asthma, autophagy has been shown to be associated with inflammation, airway remodeling, and responsiveness to drug therapy. In-depth characterization of the role of autophagy in asthma can enhance the understanding of the pathogenesis, and provide a theoretical basis for the development of new biomarkers and targeted therapy for asthma. In this article, we focus on the relationship of autophagy and asthma, and discuss its implications for asthma pathogenesis and treatment

The interaction between the soluble programmed death ligand-1 (sPD-L1) and PD-1+ regulator B cells mediates immunosuppression in triple-negative breast cancer

Accumulating evidence suggests that regulatory B cells (Bregs) play important roles in inhibiting the immune response in tumors. Programmed death 1 (PD-1) and programmed death ligand 1 (PD-L1) are important molecules that maintain the balance of the immune response and immune tolerance. This study aims to evaluate the soluble form of PD-L1 and its function in inducing the differentiation of B lymphocytes, investigate the relationship between soluble PD-L1 (sPD-L1) and B-cell subsets, and explore the antitumor activity of T lymphocytes after PD-L1 blockade in coculture systems. In an effort to explore the role of sPD-L1 in human breast cancer etiology, we examined the levels of sPD-L1 and interleukin-10 (IL-10) in the serum of breast tumor patients and the proportions of B cells, PD-1+ B cells, Bregs, and PD-1+ Bregs in the peripheral blood of patients with breast tumors and assessed their relationship among sPD-L1, IL-10, and B-cell subsets. The levels of sPD-L1 and IL-10 in serum were found to be significantly higher in invasive breast cancer (IBCa) patients than in breast fibroadenoma (FIBma) patients. Meanwhile, the proportions and absolute numbers of Bregs and PD-1+ Bregs in the peripheral blood of IBCa patients were significantly higher than those of FIBma patients. Notably, they were the highest in triple-negative breast cancer (TNBC) among other subtypes of IBCa. Positive correlations of sPD-L1 and IL-10, IL-10 and PD-1+ Bregs, and also sPD-L1 and PD-1+ Bregs were observed in IBCa. We further demonstrated that sPD-L1 could induce Breg differentiation, IL-10 secretion, and IL-10 mRNA expression in a dose-dependent manner in vitro. Finally, the induction of regulatory T cells (Tregs) by Bregs was further shown to suppress the antitumor response and that PD-L1 blockade therapies could promote the apoptosis of tumor cells. Together, these results indicated that sPD-L1 could mediate the differentiation of Bregs, expand CD4+ Tregs and weaken the antitumor activity of CD4+ T cells. PD-L1/PD-1 blockade therapies might be a powerful therapeutic strategy for IBCa patients, particularly for TNBC patients with high level of PD-1+ Bregs

Preparation and Application of Starch/Polyvinyl Alcohol/Citric Acid Ternary Blend Antimicrobial Functional Food Packaging Films

Ternary blend films were prepared with different ratios of starch/polyvinyl alcohol (PVA)/citric acid. The films were characterized by field emission scanning electron microscopy (FE-SEM), thermogravimetric analysis, as well as Fourier transform infrared (FTIR) analysis. The influence of different ratios of starch/polyvinyl alcohol (PVA)/citric acid and different drying times on the performance properties, transparency, tensile strength (TS), water vapor permeability (WVP), water solubility (WS), color difference (ΔE), and antimicrobial activity of the ternary blends films were investigated. The starch/polyvinyl alcohol/citric acid (S/P/C1:1:0, S/P/C3:1:0.08, and S/P/C3:3:0.08) films were all highly transparent. The S/P/C3:3:0.08 had a 54.31 times water-holding capacity of its own weight and its mechanical tensile strength was 46.45 MPa. In addition, its surface had good uniformity and compactness. The S/P/C3:1:0.08 and S/P/C3:3:0.08 showed strong antimicrobial activity to Listeria monocytogenes and Escherichia coli, which were the food-borne pathogenic bacteria used. The freshness test results of fresh figs showed that all of the blends prevented the formation of condensed water on the surface of the film, and the S/P/C3:1:0.08 and S/P/C3:3:0.08 prevented the deterioration of figs during storage. The films can be used as an active food packaging system due to their strong antibacterial effect

Construction of a prognostic assessment model for colon cancer patients based on immune-related genes and exploration of related immune characteristics

Objectives: To establish a novel risk score model that could predict the survival and immune response of patients with colon cancer.Methods: We used The Cancer Genome Atlas (TCGA) database to get mRNA expression profile data, corresponding clinical information and somatic mutation data of patients with colon cancer. Limma R software package and univariate Cox regression were performed to screen out immune-related prognostic genes. GO (Gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) were used for gene function enrichment analysis. The risk scoring model was established by Lasso regression and multivariate Cox regression. CIBERSORT was conducted to estimate 22 types of tumor-infiltrating immune cells and immune cell functions in tumors. Correlation analysis was used to demonstrate the relationship between the risk score and immune escape potential.Results: 679 immune-related genes were selected from 7846 differentially expressed genes (DEGs). GO and KEGG analysis found that immune-related DEGs were mainly enriched in immune response, complement activation, cytokine-cytokine receptor interaction and so on. Finally, we established a 3 immune-related genes risk scoring model, which was the accurate independent predictor of overall survival (OS) in colon cancer. Correlation analysis indicated that there were significant differences in T cell exclusion potential in low-risk and high-risk groups.Conclusion: The immune-related gene risk scoring model could contribute to predicting the clinical outcome of patients with colon cancer

An 11-bp Insertion in Zea mays fatb Reduces the Palmitic Acid Content of Fatty Acids in Maize Grain

The ratio of saturated to unsaturated fatty acids in maize kernels strongly impacts human and livestock health, but is a complex trait that is difficult to select based on phenotype. Map-based cloning of quantitative trait loci (QTL) is a powerful but time-consuming method for the dissection of complex traits. Here, we combine linkage and association analyses to fine map QTL-Pal9, a QTL influencing levels of palmitic acid, an important class of saturated fatty acid. QTL-Pal9 was mapped to a 90-kb region, in which we identified a candidate gene, Zea mays fatb (Zmfatb), which encodes acyl-ACP thioesterase. An 11-bp insertion in the last exon of Zmfatb decreases palmitic acid content and concentration, leading to an optimization of the ratio of saturated to unsaturated fatty acids while having no effect on total oil content. We used three-dimensional structure analysis to explain the functional mechanism of the ZmFATB protein and confirmed the proposed model in vitro and in vivo. We measured the genetic effect of the functional site in 15 different genetic backgrounds and found a maximum change of 4.57 mg/g palmitic acid content, which accounts for ∼20–60% of the variation in the ratio of saturated to unsaturated fatty acids. A PCR-based marker for QTL-Pal9 was developed for marker-assisted selection of nutritionally healthier maize lines. The method presented here provides a new, efficient way to clone QTL, and the cloned palmitic acid QTL sheds lights on the genetic mechanism of oil biosynthesis and targeted maize molecular breeding