Identification of diagnostic hub genes related to neutrophils and infiltrating immune cell alterations in idiopathic pulmonary fibrosis

BackgroundThere is still a lack of specific indicators to diagnose idiopathic pulmonary fibrosis (IPF). And the role of immune responses in IPF is elusive. In this study, we aimed to identify hub genes for diagnosing IPF and to explore the immune microenvironment in IPF.MethodsWe identified differentially expressed genes (DEGs) between IPF and control lung samples using the GEO database. Combining LASSO regression and SVM-RFE machine learning algorithms, we identified hub genes. Their differential expression were further validated in bleomycin-induced pulmonary fibrosis model mice and a meta-GEO cohort consisting of five merged GEO datasets. Then, we used the hub genes to construct a diagnostic model. All GEO datasets met the inclusion criteria, and verification methods, including ROC curve analysis, calibration curve (CC) analysis, decision curve analysis (DCA) and clinical impact curve (CIC) analysis, were performed to validate the reliability of the model. Through the Cell Type Identification by Estimating Relative Subsets of RNA Transcripts algorithm (CIBERSORT), we analyzed the correlations between infiltrating immune cells and hub genes and the changes in diverse infiltrating immune cells in IPF.ResultsA total of 412 DEGs were identified between IPF and healthy control samples, of which 283 were upregulated and 129 were downregulated. Through machine learning, three hub genes (ASPN, SFRP2, SLCO4A1) were screened. We confirmed their differential expression using pulmonary fibrosis model mice evaluated by qPCR, western blotting and immunofluorescence staining and analysis of the meta-GEO cohort. There was a strong correlation between the expression of the three hub genes and neutrophils. Then, we constructed a diagnostic model for diagnosing IPF. The areas under the curve were 1.000 and 0.962 for the training and validation cohorts, respectively. The analysis of other external validation cohorts, as well as the CC analysis, DCA, and CIC analysis, also demonstrated strong agreement. There was also a significant correlation between IPF and infiltrating immune cells. The frequencies of most infiltrating immune cells involved in activating adaptive immune responses were increased in IPF, and a majority of innate immune cells showed reduced frequencies.ConclusionOur study demonstrated that three hub genes (ASPN, SFRP2, SLCO4A1) were associated with neutrophils, and the model constructed with these genes showed good diagnostic value in IPF. There was a significant correlation between IPF and infiltrating immune cells, indicating the potential role of immune regulation in the pathological process of IPF

GABNet: global attention block for retinal OCT disease classification

IntroductionThe retina represents a critical ocular structure. Of the various ophthalmic afflictions, retinal pathologies have garnered considerable scientific interest, owing to their elevated prevalence and propensity to induce blindness. Among clinical evaluation techniques employed in ophthalmology, optical coherence tomography (OCT) is the most commonly utilized, as it permits non-invasive, rapid acquisition of high-resolution, cross-sectional images of the retina. Timely detection and intervention can significantly abate the risk of blindness and effectively mitigate the national incidence rate of visual impairments.MethodsThis study introduces a novel, efficient global attention block (GAB) for feed forward convolutional neural networks (CNNs). The GAB generates an attention map along three dimensions (height, width, and channel) for any intermediate feature map, which it then uses to compute adaptive feature weights by multiplying it with the input feature map. This GAB is a versatile module that can seamlessly integrate with any CNN, significantly improving its classification performance. Based on the GAB, we propose a lightweight classification network model, GABNet, which we develop on a UCSD general retinal OCT dataset comprising 108,312 OCT images from 4686 patients, including choroidal neovascularization (CNV), diabetic macular edema (DME), drusen, and normal cases.ResultsNotably, our approach improves the classification accuracy by 3.7% over the EfficientNetV2B3 network model. We further employ gradient-weighted class activation mapping (Grad-CAM) to highlight regions of interest on retinal OCT images for each class, enabling doctors to easily interpret model predictions and improve their efficiency in evaluating relevant models.DiscussionWith the increasing use and application of OCT technology in the clinical diagnosis of retinal images, our approach offers an additional diagnostic tool to enhance the diagnostic efficiency of clinical OCT retinal images

Homozygous p.Ser267Phe in SLC10A1 is associated with a new type of hypercholanemia and implications for personalized medicine.

SLC10A1 codes for the sodium-taurocholate cotransporting polypeptide (NTCP), which is a hepatocellular transporter for bile acids (BAs) and the receptor for hepatitis B and D viruses. NTCP is also a target of multiple drugs. We aimed to evaluate the medical consequences of the loss of function mutation p.Ser267Phe in SLC10A1. We identified eight individuals with homozygous p.Ser267Phe mutation in SLC10A1 and followed up for 8-90 months. We compared their total serum BAs and 6 species of BAs with 170 wild-type and 107 heterozygous healthy individuals. We performed in-depth medical examinations and exome sequencing in the homozygous individuals. All homozygous individuals had persistent hypercholanemia (P = 5.8 × 10-29). Exome sequencing excluded the involvement of other BA metabolism-associated genes in the hypercholanemia. Although asymptomatic, all individuals had low vitamin D levels. Of six adults that were subjected to bone mineral density analysis, three presented with osteoporosis/osteopenia. Sex hormones and blood lipids were deviated in all subjects. Homozygosity of p.Ser267Phe in SLC10A1 is associated with asymptomatic hypercholanemia. Individuals with homozygous p.Ser267Phe in SLC10A1 are prone to vitamin D deficiency, deviated sex hormones and blood lipids. Surveillance of these parameters may also be needed in patients treated with drugs targeting NTCP.This project is supported by the National Natural Science Foundation of China (31471193, 81570539, 81370535, 91331204 and 31525014). S.X. acknowledges financial support from the Strategic Priority Research Program (XDB13040100) and Key Research Program of Frontier Sciences (QYZDJ-SSW-SYS009) of the Chinese Academy of Sciences (CAS)

PKCα/GSK3β/NF-κB signaling pathway and the possible involvement of TRIM21 in TRAIL-induced apoptosis

Tumor necrosis factor related apoptosis-inducing ligand (TRAIL) is a highly promising therapeutic agent for cancer treatment due to its ability to selectively target tumor cells for cell death, while has little effect on most of normal cells. However, recent research has found that many cancers including non-small cell lung cancer (NSCLC) display resistance to TRAIL. Therefore, it is important to elucidate the molecular mechanism governing the resistance to TRAIL treatment in tumor cells. In this study, we showed the negative regulation of TRAIL-induced apoptosis by GSK3β in H1299 NSCLC cells, and determined the PKCα isozyme as an upstream regulator of GSK3β that phosphorylates and inactivates GSK3β, thereby sensitizing cancer cells to TRAIL-induced apoptosis. Furthermore, we demonstrated that the anti-apoptotic effect of GSK3β is mediated by NF-κB pathway, while the tripartite motif 21 (TRIM21) was able to inhibit the activation of NF-κB by GSK3β, and leads to the promotion of cell apoptosis. Taken together, our study further delineated the underpinning mechanism of resistance to TRAIL-induced apoptosis in H1299 cells and provided new clues for sensitizing NSCLC cells to TRAIL therapy.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Reducing Endogenous Labile Zn May Help to Reduce Smooth Muscle Cell Injury around Vascular Stents

Vascular stent service involves complex service environments and performance requirements, among which the histocompatibility of the stent could seriously affect the therapeutic effect. In the pathology of vascular disease, the thin fiber cap is easily ruptured, exposing the necrotic core below, and triggering a series of dangerous biochemical reactions. In contrast, the thin neointima, considered an essential structure growing on the stent, may evolve into vulnerable plaque structures due to lesions induced by the stent. Therefore, the reduction of necrosis around the stent below the thin neointima is indispensable. In this work, different cell model experiments suggested that the content of endogenous labile Zn positively correlated with cell injury. Zinquin-Zn fluorescence experiments and zinc ion channels research suggested that the change in the content of endogenous labile Zn in smooth muscle cells is affected by different stent coatings. The content of endogenous labile Zn in cells negatively correlated with cell viability. Animal experiments indirectly verified the increase in endogenous labile Zn by detecting the expression of Zn regulatory protein (metallothionein) in the necrotic tissues. Reducing the content of endogenous labile Zn may favor a reduction in smooth muscle cell injury and necrosis. This biochemical mechanism is effective in improving the therapeutic effect of vascular stents

Shift in controlling factors of carbon stocks across biomes on the Qinghai-Tibetan Plateau

The Qinghai-Tibetan Plateau (TP) accumulated a large amount of organic carbon, while its size and response to environmental factors for the whole area remain uncertain. Here, we synthesized a dataset to date with the largest data volume and broadest geographic coverage over the TP, composing of 7196 observations from multiple field campaigns since the 1980s, and provided a comprehensive assessment of the size and spatial distribution of carbon pools for both plant and soils on the TP using machine learning algorithms. The estimated soil organic carbon (SOC) storage to 1 m depth was ${\text{32}}{\text{.01}}_{{\text{19}}{\text{.69}}}^{{\text{47}}{\text{.9}}}$ Pg ( ${\text{11}}{\text{.72}}_{{\text{7}}{\text{.2}}}^{{\text{17}}{\text{.53}}}$ kg m ^−2 on average), accounting for approximately ${\text{37}}{\text{.2}}_{{\text{22}}{\text{.9}}}^{{\text{55}}{\text{.6}}}$ % of China’s SOC stock on its <30% land area. There was ${\text{15}}{\text{.52}}_{{\text{9}}{\text{.91}}}^{{\text{23}}{\text{.52}}}{ }$ Pg C stored in grassland soils (1 m), which played as the largest C pool on the TP, followed by shrubland ( ${\text{7}}{\text{.52}}_{{\text{4}}{\text{.8}}}^{11.6}$ Pg) and forest ( ${\text{3}}{\text{.72}}_{{\text{2}}{\text{.5}}}^{{\text{5}}{\text{.36}}}$ Pg). The estimated plant C pool was ${\text{2}}{\text{.4}}_{{\text{0}}{\text{.95}}}^{{\text{5}}{\text{.16}}}$ Pg ( ${\text{1}}{\text{.03}}_{{\text{0}}{\text{.2}}}^{{\text{2}}{\text{.7}}}$ Pg in aboveground biomass (AGB) and ${\text{1}}{\text{.37}}_{{\text{0}}{\text{.75}}}^{{\text{2}}{\text{.45}}}$ Pg in belowground biomass). Soil and biomass C density presented a similar spatial pattern, which generally decreased from the east and southeast parts to the central and western parts. We found both vegetation and soil C (1 m depth) were primarily regulated by climatic variables and C input across the entire TP. However, main driving factors of the C stocks varied among vegetation types and depth intervals. Though AGB played as an important role in SOC variation for both topsoil (0–30 cm) and subsoil (30–100 cm), the strength of the correlation weakened with depth and was gradually attenuated from grassland to shrubland, and forest. The outcomes of this study provided an updated geospatial estimate of SOC stocks for the entire TP and their relationships with environmental factors, which are essential to carbon model benchmarking and better understanding the feedbacks of C stocks to global change