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Introduction: Interstitial cells are crucial to the development of kidney structure and function, although the mechanism underlying their role in it remains unclear to date. Our previous study identified cell clusters in human fetal kidney tissue, and we further analyzed the interstitial cell cluster within this context. Methods: We extracted the barcoded cDNA from tissue samples and prepared spatial transcriptome libraries. Sequencing data was quality-checked, normalized, and clusters were identified using Seurat. Single-cell and spatial data were integrated using MIA and cell types were deconvoluted. DEGs in interstitial cells were identified and functionally annotated using DAVID. CellPhoneDB was used to predict ligand-receptor interactions between cell types. Results: The results of the present study revealed that this cluster of interstitial cells appeared to be scattered in the junction between the cortical and medullary regions. The subsequent KEGG pathway analysis revealed that the differentially expressed genes (DEGs) in this cluster of interstitial cells were involved in the WNT signaling pathway. The Gene Ontology (GO) analysis revealed that these DEGs were involved in multiple pathways associated with kidney development, with six of the genes (NKD2, TCF21, WNT5A, WNT4, MDK, and SFRP1) associated with kidney development exhibiting significant upregulation. Accordingly, it was inferred that these interstitial cells might be involved in regulating epithelial cell differentiation, ureteral bud development, and morphogenesis. The subsequent cell-cell communication analysis revealed that the cellular crosstalk was primarily regulated mainly by ligand-receptor pairs. Additionally, 17 genes reported to be associated with kidney disease were focused on, and these genes were found to be predominantly expressed in a single cell type. Conclusion: In summary, the present study revealed the characteristics of a previously identified cluster of interstitial cells in the kidney tissue, thereby providing fresh insights into the process of kidney development.

Abstract Objective: To investigate the association between coal dust exposure and the occurrence of dyslipidemia in coal mine workers, and identify relevant risk factors. Methods: We selected a population who underwent occupational health examinations at Huainan Yangguang Xinkang Hospital from March 2020 to July 2022. Participants were divided into two groups based on the presence or absence of dyslipidemia, and their baseline information was collected, including records of coal dust exposure. We employed single-factor analysis to identify risk factors for dyslipidemia and adjusted for confounding factors in the adjusted models. Additionally, we explored the effects in different populations using stratified analysis, smooth curve fitting, and propensity score matching. Finally, we confirmed the causal relationship between coal dust exposure and dyslipidemia by examining tissue sections and lipid-related indicators in a mouse model of coal dust exposure. Results A total of 5,657 workers were included in the study, among whom 924 individuals had dyslipidemia and 4,743 individuals did not have dyslipidemia. The results of the single-factor analysis revealed that dust exposure, age, BMI, blood pressure, and smoking were statistically significant risk factors for dyslipidemia (p

Abstract Diabetic nephropathy affects a significant proportion of individuals with diabetes, and its progression often leads to cardiovascular disease and infections before the need for renal replacement therapy arises. Empagliflozin has been shown to have various protective effects in cardiovascular disease studies, such as improving diabetic myocardial structure and function, and reducing myocardial oxidative stress. However, the impact of empagliflozin on cardiac protein expression and signaling pathways has not been comprehensively analyzed. To address this gap, we conducted proteome analysis to identify specific protein markers in cardiac tissue from the diabetes model group, including Myh7, Wdr37, Eif3k, Acot1, Acot2, Cat, and Scp2, in cardiac tissue from the diabetes model group. In our drug model, empagliflozin primarily modulates the fat-related metabolic signaling pathway within the heart. Empagliflozin downregulated the protein expression levels of ACOX1, ACADVL and CPT1A in the model group. Overall, our findings demonstrate that empagliflozin provides cardiac protection by targeting metabolic signaling pathways, particularly those related to fat metabolism. Moreover, the identification of cardiac biomarkers in a mouse model of diabetic nephropathy lays the foundation for further exploration of disease biomarkers in cardiac tissue.

Abstract Background Previous studies have indicated that ψ-modified small RNAs play crucial roles in tumor metastasis. However, the ψ-modified small RNAs during metastasis of PTC are still unclear. Methods We compared the pseudouridine synthase 7 (PUS7) alteration between metastatic and non-metastatic PTCs, and investigated its correlation with clinicopathological features. Additionally, we employed a small RNA ψ modification microarray to examine the small RNA ψ modification profile in both metastatic and non-metastatic PTCs, as well as paired paracancerous tissues. The key molecule involved in ψ modification, pre-miR-8082, was identified and found to regulate the expression of CD47. Experiments in vitro were conducted to further investigate the function of PUS7 and CD47 in PTC. Results Our results demonstrated that PUS7 was down-regulated in PTC and was closely associated with metastasis. Moreover, the ψ modification of pre-miR-8082 was found to be decreased, resulting in down-expression of pre-miR-8082 and miR-8082, leading to the loss of the inhibitory effect on CD47, thereby promoting tumor migration. Conclusions Our study demonstrates that PUS7 promotes the inhibition of CD47 and inhibits metastasis of PTC cells by regulating the ψ modification of pre-miR-8082. These results suggest that PUS7 and ψ pre-miR-8082 may serve as potential targets and diagnostic markers for PTC metastasis.

Abstract Spatial proteomics is a multidimensional technique that studies the spatial distribution and function of proteins within cells or tissues across both spatial and temporal dimensions. This field multidimensionally reveals the complex structure of the human proteome, including the characteristics of protein spatial distribution, dynamic protein translocation, and protein interaction networks. Recently, as a crucial method for studying protein spatial localization, spatial proteomics has been applied in the clinical investigation of various diseases. This review summarizes the fundamental concepts and characteristics of tissue-level spatial proteomics, its research progress in common human diseases such as cancer, neurological disorders, cardiovascular diseases, autoimmune diseases, and anticipates its future development trends. The aim is to highlight the significant impact of spatial proteomics on understanding disease pathogenesis, advancing diagnostic methods, and developing potential therapeutic targets in clinical research.

Abstract Autoimmune related kidney diseases (ARKDs), including minimal change nephropathy (MCN), membranous nephropathy (MN), IgA nephropathy (IgAN), and lupus nephritis (LN), significantly affect renal function. These diseases are characterized by the formation of local immune complexes and the subsequent activation of the complement system, leading to kidney damage and proteinuria. Despite the known patterns of glomerular injury, the specific molecular mechanisms that contribute to renal tubular damage across ARKDs remain underexplored. Laser capture microdissection and liquid chromatography–tandem mass spectrometry (LC–MS/MS) were used to conduct a comparative proteomic analysis of renal tubular tissues from formalin-fixed paraffin-embedded samples. The cohort comprised of 10 normal controls (NC), 5 MCN, 4 MN, 17 IgAN, and 21 LN patients. Clinical parameters and histopathological assessments were integrated with proteomic findings to comprehensively investigate underlying pathogenic processes. Clinical evaluation indicated significant glomerular damage, as reflected by elevated urinary protein levels and reduced plasma albumin levels in patients with ARKD. Histological analyses confirmed varying degrees of tubular damage and deposition of immune complexes. Proteomic analyses identified significant changes in protein expression, particularly in complement components (C3, C4A, C4B, C8G, CFB, and SERPINA1) and mitochondrial proteins (ATP5F1E and ATP5PD), highlighting the common alterations in the complement system and mitochondrial proteins across ARKDs. These alterations suggest a novel complement–mitochondrial–epithelial–mesenchymal transition (EMT) pathway axis that contributes to tubular damage in ARKDs. Notably, significant alterations in CFB in tubular ARKD patients were revealed, implicating it as a therapeutic target. This study underscores the importance of complement activation and mitochondrial dysfunction in the pathogenesis of ARKDs, and proposes CFB as a potential therapeutic target to inhibit complement activation and mitigate tubular damage. Future research should validate the complement-mitochondrial-EMT pathway axis and explore the effects and mechanisms of CFB inhibitors in alleviating ARKD progression.

Abstract Genomic instability (GI) was associated with tumorigenesis. However, GI-related lncRNA signature (GILncSig) in lung adenocarcinoma (LUAD) is still unknown. In this study, the lncRNA expression data, somatic mutation information and clinical survival information of LUAD were downloaded from The Cancer Genome Atlas (TCGA) and performed differential analysis. Functional and prognosis analysis revealed that multiple GI-related pathways were enriched. By using univariate and multivariate Cox regression analysis, 5 GI-associated lncRNAs (AC012085.2, FAM83A-AS1, MIR223HG, MIR193BHG, LINC01116) were identified and used to construct a GILncSig model. Mutation burden analysis indicated that the high-risk GI group had much higher somatic mutation count and the risk score constructed by the 5 GI-associated lncRNAs was an independent predictor for overall survival (OS) (P

Purpose: Previous studies have reported that miR-30d-5p gene expression can inhibit tumor proliferation, but its mechanism has not been fully elucidated. Methods: Based on previous findings, TGF-β1 was used to induce epithelial mesenchymal transformation in A549 cells. The expression levels of DUSP-1, E-cadherin and Vimentin were detected by Western blot. mRNA expression levels of DUSP-1, E-cadherin and Vimentin were determined by RT-qPCR. The expression level of miR-30d-5p was determined by RT-qPCR. Results: The induction effect of TGF-β1 could be reversed by the intervention of miR-30d-5p in A549 cells. miRNA inhibition experiment showed that miR-30d-5p inhibitor could effectively inhibit the expression of miR-30d-5p in A549 cells. After miR-30d-5p intervention, TGF-β1 was reversed on EMT-related genes (Dusp-1, E-cadherin, Vimentin). Conclusion: TGF-β1 can induce epithelial mesenchymal transformation of A549 cells, and miR-30d-5p may be a key regulatory mechanism in regulating gene and protein expression of TGF-β1-mediated DUSP-1, E-cadherin and Vimentin. This provides a new perspective for understanding the anti-tumor effect of miR-30d-5p gene.

Abstract Our study aimed to elucidate the molecular mechanisms underlying NAC1 (nucleus accumbens associated 1) transcriptional regulation of LDHA and its role in HBV immune evasion, thus contributing to the development of cirrhosis and hepatocellular carcinoma (HCC). Utilizing public datasets, we performed differential gene expression and weighted gene co-expression network analysis (WGCNA) on HBV-induced cirrhosis/HCC data. We identified candidate genes by intersecting differentially expressed genes with co-expression modules. We validated these genes using the TCGA database, conducting survival analysis to pinpoint key genes affecting HBV-HCC prognosis. We also employed the TIMER database for immune cell infiltration data and analyzed correlations with identified key genes to uncover potential immune escape pathways. In vitro, we investigated the impact of NAC1 and LDHA on immune cell apoptosis and HBV immune evasion. In vivo, we confirmed these findings using an HBV-induced cirrhosis model. Bioinformatics analysis revealed 676 genes influenced by HBV infection, with 475 genes showing differential expression in HBV-HCC. NAC1 emerged as a key gene, potentially mediating HBV immune escape through LDHA transcriptional regulation. Experimental data demonstrated that NAC1 transcriptionally activates LDHA, promoting immune cell apoptosis and HBV immune evasion. Animal studies confirmed these findings, linking NAC1-mediated LDHA activation to cirrhosis and HCC development. NAC1, highly expressed in HBV-infected liver cells, likely drives HBV immune escape by activating LDHA expression, inhibiting CD8 + T cells, and promoting cirrhosis and HCC development.

Abstract Background Observational studies have suggested a link between panic disorder (PD) and Alzheimer disease (AD). This study aimed to identify the underlying association of PD with the risk of AD using Mendelian randomization. Methods Genetic instrumental variables (IVs) were retrieved in the genome-wide association study between PD and AD. Then, five different models, namely inverse variance weighting (IVW), weighted median, weighted mode, MR-Egger and MR-robust adjusted profile scores (MR-RAPS), were used for MR Analysis. Finally, the heterogeneity and pleiotropy of identified IVs were verified by multiple sensitivity tests. Results The Cochran’s Q test based on MR Egger and IVW showed that no evidence of heterogeneity was found in the effects of instrumental variables, so a fixed-effect model was used. IVW analysis (OR 1.000479, 95% CI [1.000147056, 1.000811539], p = 0.005) indicated that PD was associated with an increased risk of AD, and a causal association existed between them. Meanwhile, weighted median (OR 1.000513373, 95% CI [1.000052145, 1.000974814], p = 0.029) and MR-RAPS (OR 1.000510118, 95% CI [1.000148046, 1.00087232], p = 0.006) also showed the similar findings. In addition, extensive sensitivity analyses confirmed the robustness and accuracy of these results. Conclusion This investigation provides evidence of a potential causal relationship between PD and the increased risk of AD. Based on our MR results, when diagnosing and treating patients with PD, clinicians should pay more attention to their AD-related symptoms to choose therapeutic measures or minimize comorbidities. Furthermore, the development of drugs that improve both PD and AD may better treat patients with these comorbidities.

The pathogenesis of rheumatoid arthritis (RA) remains elusive. The initiation of joint degeneration is characterized by the loss of self-tolerance in peripheral joints. Ferroptosis, a form of regulated cell death, holds significant importance in the pathophysiology of inflammatory arthritis, primarily due to iron accumulation and the subsequent lipid peroxidation.The present study investigated the association between synovial lesions and ferroptosis-related genes using previously published data from rheumatoid patients. Transcriptome differential gene analysis was employed to identify ferroptosis-related differentially expressed genes (FRDEGs). To validate FRDEGs and screen hub genes, we used weighted gene co-expression network analysis (WGCNA) and receiver operating characteristic (ROC) curves. Subsequently, immune infiltration analysis and single cell analysis were conducted to investigate the relationship between various synovial tissues cells and FRDEGs. The findings were further confirmed through reverse transcription-quantitative polymerase chain reaction (RT-qPCR), immunohistochemical staining, and immunofluorescence techniques.Upon intersecting DEGs with ferroptosis-related genes, we identified a total of 104 FRDEGs. Through the construction of a protein-protein interaction (PPI) network, we pinpointed the top 20 most highly concentrated genes as hub genes. Subsequent analyses using ROC curve and WGCNA validated eight FRDEGs: TIMP1, JUN, EGFR, SREBF1, ADIPOQ, SCD, AR, and FABP4. Immuno-infiltration analyses revealed significant infiltration of immune cell in RA synovial tissues and their correlations with the FRDEGs. Notably, TIMP1 demonstrated a positive correlation with various immune cell populations. Single-cell sequencing date of RA synovial tissue revealed predominant expression of TIMP1 is in fibroblasts. RT–qPCR, immunohistochemistry, and immunofluorescence analyses confirmed significant upregulation of TIMP1 at both mRNA and protein levels in RA synovial tissues and fibroblast-like synoviocytes (FLS).The findings provide novel insights into pathophysiology of peripheral immune tolerance deficiency in RA. The dysregulation of TIMP1, a gene associated with ferroptosis, was significantly observed in RA patients, suggesting its potential as a promising biomarker and therapeutic target.

As a common consequence of various neurogenic disorders, dysphagia has a significant impact on the quality of life for patients. To promote the development the field of swallowing, it will be helpful to clarify the pathological and therapeutic mechanisms of dysphagia. Through visual analysis of related papers from 1993 to 2023 in the Web of Science Core Collection (WoSCC) database, the research status and development trend of the pathogenesis of dysphagia were discussed. The co-occurrence study was finished using CiteSpace 6.2 R4 software, including keywords, countries, institutions, and authors. Finally, 1,184 studies satisfied the inclusion requirements. The findings of the visualization analysis suggested that aspiration and gastroesophageal reflux disease would be the areas of greatest interest for researchers studying the mechanism of dysphagia. As for the latest occurred research trends, fMRI, signals and machine learning emerging into the field of view of researchers. Based on an analysis of country co-occurrence, United States, Japan and China rank the top three, in terms of the number of publications on dysphagia. University System of Ohio is the organization that has published the most amount of articles regarding the mechanism of dysphagia. Other highly published schools in the top three include State University System of Florida and Northwestern University. For the prolific authors, German, Rebecca Z published the most articles at present, whose own research team working closely together. Several closely cooperating research teams have been formed at present, including the teams centered around German, Rebecca Z, Warnecke, Tobias and Hamdy Shaheen. This study intuitively analyzed the current research status of the mechanism of dysphagia, provided researchers with research hotspots in this field.

The eighth experiment of the SINQ Target Irradiation Program (STIP-VIII) included a total of 941 specimens from 25 steels, 8 zircaloys, 6 tungsten based alloys (W-alloys) and 2 silicon carbide (SiC) composites. Specimens were prepared in 2016 and 2017. Irradiation was carried out in SINQ Target-13 in two periods: June 26 to December 21, 2018 and July 30 to December 23, 2020. The total proton charge received by Target-13 is 7.8 Ah, corresponding to 1.75×1023 protons. The irradiated specimens were unpacked in 2022 and 2023 and more than 98 % of the specimens were recovered. The specimens were irradiated at temperatures between 100 and 450 °C. The maximum doses are 10.4 dpa for steels, 14.8 dpa for zircaloys, 11.5 dpa for W-alloys, and 3.5 dpa for SiC composites. The He-to-dpa ratio is in the range of 22–42 appm/dpa for steels, 13–16 appm/dpa for zircaloys, 30–36 appm/dpa for W-alloys and 90–125 appm/dpa for SiC composites.

Abstract Lung tissue is an important organ of the fetus, and genomic research on its development has improved our understanding of the biology of this tissue. However, the proteomic research of developing fetal lung tissue is still very scarce. We conducted comprehensive analysis of two developmental stages of fetal lung tissue of proteomics. It showed the developmental characteristics of lung tissue, such as the down-regulation of metabolism-related protein expression, the up-regulation of cell cycle-related proteins, and the regulation in proteins and pathways related to lung development. In addition, we also discovered some key core proteins related to lung development, and provided some key crotonylation modification sites that regulation during lung tissue development. Our comprehensive analysis of lung proteomics can provide a more comprehensive understanding of the developmental status of lung tissue, and provide a certain reference for future research and epigenetics of lung tissue.

In this paper, a flux–torque regulation hybrid excitation machine (FTRHEM) with axial–radial dual air gaps, which can increase torque and regulate magnetic flux by changing the exciting current, is studied. Dual air gaps have a huge impact on the magnetic flux and additional torque. The effect of the air gap reluctances on the magnetic flux of the machine is obtained by establishing equivalent magnetic network models, which show that the dual air gaps are the key component in the axial–radial magnetic circuit. This study examines the flux regulation ability and the enhanced torque performance of an FTRHEM with dual air gaps. The mechanism by which the dual air gaps affect the machine’s magnetic field is clarified, and the constraints and relationships between the dual air gaps are explained, offering a theoretical foundation for future machine optimization. As the axial air gap decreases from 0.95 mm to 0.35 mm, the flux regulation capability improves from 15.44% to 26.51%, while the additional torque increases by 40.77%. Ultimately, prototypes are manufactured for experimental testing to validate the viability of the structure and the accuracy of the FEA for the FTRHEM featuring an axial–radial magnetic circuit.

BackgroundThe mechanism by which high-frequency repetitive transcranial magnetic stimulation (HF-rTMS) improves swallowing function by regulating intestinal flora remains unexplored. We aimed to evaluate this using fecal metabolomics and 16S rRNA sequencing.MethodsA Post-stroke dysphagia (PSD) rat model was established by middle cerebral artery occlusion. The magnetic stimulation group received HF-rTMS from the 7th day post-operation up to 14th day post-surgery. Swallowing function was assessed using a videofluoroscopic swallowing study (VFSS). Hematoxylin-eosin (H&E) staining was used to assess histopathological changes in the intestinal tissue. Intestinal flora levels were evaluated by sequencing the 16S rRNA V3-V4 region. Metabolite changes within the intestinal flora were evaluated by fecal metabolomics using liquid chromatography-tandem mass spectrometry.ResultsVFSS showed that the bolus area and pharyngeal bolus speed were significantly decreased in PSD rats, while the bolus area increased and pharyngeal transit time decreased after HF-rTMS administration (p < 0.05). In the PSD groups, H&E staining revealed damaged surface epithelial cells and disrupted cryptal glands, whereas HF-rTMS reinforced the integrity of the intestinal epithelial cells. 16S rRNA sequencing indicated that PSD can disturb the intestinal flora and its associated metabolites, whereas HF-rTMS can significantly regulate the composition of the intestinal microflora. Firmicutes and Lactobacillus abundances were lower in the PSD group than in the baseline group at the phylum and genus levels, respectively; however, both increased after HF-rTMS administration. Levels of ceramides (Cer), free fatty acids (FA), phosphatidylethanolamine (PE), triacylglycerol (TAG), and sulfoquinovosyl diacylglycerol were increased in the PSD group. The Cer, FA, and DG levels decreased after HF-rTMS treatment, whereas the TAG levels increased. Peptococcaceae was negatively correlated with Cer, Streptococcus was negatively correlated with DG, and Acutalibacter was positively correlated with FA and Cer. However, these changes were effectively restored by HF-rTMS, resulting in recovery from dysphagia.ConclusionThese findings suggest a synergistic role for the gut microbiota and fecal metabolites in the development of PSD and the therapeutic mechanisms underlying HF-rTMS.

Recently, extreme wildfires occur frequently around the world and emit substantial brown carbon (BrC) into the atmosphere, whereas the molecular compositions and photochemical evolution of BrC remain poorly understood. In this work, primary smoke aerosols were generated from wood smoldering, and secondary smoke aerosols were formed by the OH radical photooxidation in an oxidation flow reactor, where both primary and secondary smoke samples were collected on filters. After solvent extraction of filter samples, the molecular composition of dissolved organic carbon (DOC) was determined by Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS). The molecular composition of dissolved BrC was obtained based on the constraints of DOC formulae. The proportion of dissolved BrC fractions accounted for approximately 1/3–1/2 molecular formulae of DOC. The molecular characteristics of dissolved BrC showed higher levels of carbon oxidation state, double bond equivalents, and modified aromaticity index than those of DOC, indicating that dissolved BrC fractions were a class of organic structures with relatively higher oxidation state, unsaturated and aromatic degree in DOC fractions. The comparative analysis suggested that aliphatic and olefinic structures dominated DOC fractions (contributing to 70.1%-76.9%), while olefinic, aromatic, and condensed aromatic structures dominated dissolved BrC fractions (contributing to 97.5%-99.9%). It is worth noting that dissolved BrC fractions only contained carboxylic-rich alicyclic molecules (CRAMs)-like structures, unsaturated hydrocarbons, aromatic structures, and highly oxygenated compounds. CRAMs-like structures were the most abundant species in both DOC and dissolved BrC fractions. Nevertheless, the specific molecular characteristics for DOC and dissolved BrC fractions varied with subgroups after aging. The results highlight the similarities and differences in the molecular compositions and characteristics of DOC and dissolved BrC fractions with aging. This work will provide insights into understanding the molecular composition of DOC and dissolved BrC in smoke.

Abstract Background Post-translational modifications (PTMs) are considered to be an important factor in the pathogenesis of Systemic lupus erythematosus (SLE). Lysine 2-hydroxyisobutyryl (Khib), as an emerging post-translational modification of proteins, is involved in some important biological metabolic activities. However, there are poor studies on its correlation with diseases, especially SLE. Objective We performed quantitative, comparative, and bioinformatic analysis of Khib proteins in Peripheral blood mononuclear cells (PBMCs) of SLE patients and PBMCs of healthy controls. Searching for pathways related to SLE disease progression and exploring the role of Khib in SLE. Methods Khib levels in SLE patients and healthy controls were compared based on liquid chromatography tandem mass spectrometry, then proteomic analysis was conducted. Results Compared with healthy controls, Khib in SLE patients was up-regulated at 865 sites of 416 proteins and down-regulated at 630 sites of 349 proteins. The site abundance, distribution and function of Khib protein were investigated further. Bioinformatics analysis showed that Complement and coagulation cascades and Platelet activation in immune-related pathways were significantly enriched, suggesting that differentially modified proteins among them may affect SLE. Conclusion Khib in PBMCs of SLE patients was significantly up- or down-regulated compared with healthy controls. Khib modification of key proteins in the Complement and coagulation cascades and Platelet activation pathways affects platelet activation and aggregation, coagulation functions in SLE patients. This result provides a new direction for the possible significance of Khib in the pathogenesis of SLE patients.

Abstract Background End-stage renal disease (ESRD) is a condition that is characterized by the loss of kidney function. ESRD patients suffer from various endothelial dysfunctions, inflammation, and immune system defects. Lysine malonylation (Kmal) is a recently discovered post-translational modification (PTM). Although Kmal has the ability to regulate a wide range of biological processes in various organisms, its specific role in ESRD is limited. Methods In this study, the affinity enrichment and liquid chromatography-tandem mass spectrometry (LC-MS/MS) techniques have been used to create the first global proteome and malonyl proteome (malonylome) profiles of peripheral blood mononuclear cells (PBMCs) from twenty patients with ESRD and eighty-one controls. Results On analysis, 793 differentially expressed proteins (DEPs) and 12 differentially malonylated proteins (DMPs) with 16 Kmal sites were identified. The Rap1 signaling pathway and platelet activation pathway were found to be important in the development of chronic kidney disease (CKD), as were DMPs TLN1 and ACTB, as well as one malonylated site. One conserved Kmal motif was also discovered. Conclusions These findings provided the first report on the Kmal profile in ESRD, which could be useful in understanding the potential role of lysine malonylation modification in the development of ESRD.

Abstract Purpose Oral adenoid cystic carcinoma (OACC) has high rates of both local–regional recurrence and distant metastasis. The objective of this study is to investigate the impact of Khib on OACC and its potential as a targeted therapeutic intervention. Experimental design We investigated the DEPs (differentially expressed proteins) and DHMPs between OACC-T and OACC-N using LC–MS/MS-based quantitative proteomics and using several bioinformatics methods, including GO enrichment analysis, KEGG pathway analysis, subcellular localization prediction, MEA (motif enrichment analysis), and PPI (protein–protein interaction networks) to illustrate how Khib modification interfere with OACC evolution. Results Compared OACC-tumor samples (OACC-T) with the adjacent normal samples (OACC-N), there were 3243 of the DEPs and 2011 Khib sites were identified on 764 proteins (DHMPs). DEPs and DHMPs were strongly associated to glycolysis pathway. GAPDH of K254, ENO of K228, and PGK1 of K323 were modified by Khib in OACC-T. Khib may increase the catalytic efficiency to promote glycolysis pathway and favor OACC progression. Conclusions and clinical relevance Khib may play a significant role in the mechanism of OACC progression by influencing the enzyme activity of the glycolysis pathway. These findings may provide new therapeutic options of OACC.

Background: Glioma is the most frequent type of malignancy that may damage the brain with high morbidity and mortality rates and patients' prognoses are still dismal. Ferroptosis, a newly uncovered mode of programmed cell death, may be triggered to destroy glioma cells. Nevertheless, the significance of ferroptosis-related genes (FRGs) in predicting prognosis in glioma individuals is still a mystery. Methods: The CGGA (The Chinese Glioma Atlas), GEO (Gene Expression Omnibus), and TCGA (The Cancer Genome Atlas) databases were all searched to obtain the glioma expression dataset. First, TCGA was searched to identify differentially expressed genes (DEGs). This was followed by a machine learning algorithm-based screening of the glioma's most relevant genes. Additionally, these genes were subjected to Gene Ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Genomes) functional enrichment analyses. The chosen biological markers were then submitted to single-cell, immune function, and gene set enrichment analysis (GSEA). In addition, we performed functional enrichment and Mfuzz expression profile clustering on the most promising biological markers to delve deeper into their regulatory mechanisms and assess their clinical diagnostic capacities. Results: We identified 4444 DEGs via differential analysis and 564 FRGs from the FerrDb database. The two were subjected to intersection analysis, which led to the discovery of 143 overlapping genes. After that, glioma biological markers were identified in fourteen genes by the use of machine learning methods. In terms of its use for clinical diagnosis, SMG9 stands out as the most significant among these biomarkers. Conclusion: In light of these findings, the identification of SMG9 as a new biological marker has the potential to provide information on the mechanism of action and the effect of the immune milieu in glioma. The promise of SMG9 in glioma prognosis prediction warrants more study.

Diabetic kidney disease (DKD) is a significant contributor to end-stage renal disease worldwide. Despite extensive research, the exact mechanisms responsible for its development remain incompletely understood. Notably, patients with diabetes and impaired kidney function exhibit a hypercoagulable state characterized by elevated levels of coagulation molecules in their plasma. Recent studies propose that coagulation molecules such as thrombin, fibrinogen, and platelets are interconnected with the complement system, giving rise to an inflammatory response that potentially accelerates the progression of DKD. Remarkably, investigations have shown that inhibiting the coagulation system may protect the kidneys in various animal models and clinical trials, suggesting that these systems could serve as promising therapeutic targets for DKD. This review aims to shed light on the underlying connections between coagulation and complement systems and their involvement in the advancement of DKD.

Circular RNAs (circRNAs) and long noncoding RNAs (lncRNAs) have a role in monitoring the appearance and progression of a great many diseases. They are useful markers for the prognosis and diagnosis of some diseases. In previous studies, the expression patterns of mRNAs, circRNAs, and lncRNAs related to immunoglobulin A (IgA) nephropathy have not been sufficiently discussed. Active prevention methods and treatment for IgA nephropathy (IgAN) are still not used. Integrated analyses and identification of the circRNAs and lncRNAs in IgAN have not been executed. We carried out a deep RNA sequencing analysis between controls and subjects with IgAN. In total, 125 antisense lncRNAs were identified to be greatly differentially expressed between the control and experimental groups. In addition, 606 mRNAs and 1275 circRNAs with differential expression levels were found between the groups. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways were used as bioinformatic methods in this study. Our study showed the expression patterns of mRNAs, circRNAs, and lncRNAs in IgAN. We revealed the key roles of circRNAs and lncRNAs in the molecular mechanism of IgAN.

Abstract Purpose Esophageal squamous cell carcinoma (ESCC) remains one of the most common causes of cancer death due to the lack of effective therapeutic options. New targets and the targeted drugs are required to be identified and developed. Methods Highly expressed genes in ESCA were identified using the edgeR package from public datasets. Immunostaining assay verified the high expression level of EFNA1 in ESCC. CCK-8, colony formation and wound healing assays were performed to examine the role of EFNA1 and EPHA2 in ESCC progression. Cell cycle was analyzed by flow cytometry and autophagy activation was determined by autophagolysosome formation using transmission electron microscopy. The small molecule targeting to EFNA1 was identified by molecular docking and the anti-tumor effects were verified by in vitro and in vivo models with radiation treatment. Results EFNA1 was highly expressed in esophageal cancer and significantly associated with poor prognosis. Downregulation of EFNA1 remarkably inhibited cell proliferation and migration. Furthermore, decreased EFNA1 significantly suppressed the expression of cMYC along with its representative downstream genes involved in cell cycle, and activated autophagy. Similar effects on ESCC progression were obtained from knockdown of the corresponding receptor, EPHA2. The potential small molecule targeting to EFNA1, salvianolic acid A (SAA), could significantly suppress ESCC progression and increase the sensitivity to radiotherapy. Conclusion We revealed that EFNA1 facilitated the ESCC progression via the possible mechanism of activating cMYC-modulated cell proliferation and suppressing autophagy, and identified SAA as a potential drug targeting EFNA1, providing new options for the future treatments for ESCC patients.

Abstract Background and Aims Distinguishing pancreatic cancer from nonneoplastic masses is critical and remains a clinical challenge. The study aims to construct a deep learning‐based artificial intelligence system to facilitate pancreatic mass diagnosis, and to guide EUS‐guided fine‐needle aspiration (EUS‐FNA) in real time. Methods This is a prospective study. The CH‐EUS MASTER system is composed of Model 1 (real‐time capture and segmentation) and Model 2 (benign and malignant identification). It was developed using deep convolutional neural networks and Random Forest algorithm. Patients with pancreatic masses undergoing CH‐EUS examinations followed by EUS‐FNA were recruited. All patients underwent CH‐EUS and were diagnosed both by endoscopists and CH‐EUS MASTER. After diagnosis, they were randomly assigned to undergo EUS‐FNA with or without CH‐EUS MASTER guidance. Results Compared with manual labeling by experts, the average overlap rate of Model 1 was 0.708. In the independent CH‐EUS video testing set, Model 2 generated an accuracy of 88.9% in identifying malignant tumors. In clinical trial, the accuracy, sensitivity, and specificity for diagnosing pancreatic masses by CH‐EUS MASTER were significantly better than that of endoscopists. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were respectively 93.8%, 90.9%, 100%, 100%, and 83.3% by CH‐EUS MASTER guided EUS‐FNA, and were not significantly different compared to the control group. CH‐EUS MASTER‐guided EUS‐FNA significantly improved the first‐pass diagnostic yield. Conclusion CH‐EUS MASTER is a promising artificial intelligence system diagnosing malignant and benign pancreatic masses and may guide FNA in real time. Trial registration number: NCT04607720.

Objectives: This study aimed to assess the feasibility of the home-based kyphosis-specific exercises among Chinese older adults with different exercise habits and explore its potential effects on reducing the kyphosis angle and improving physical performance. Methods: A single-group, pre-and post-test design was conducted according to CONSORT 2010 statement: extension for pilot and feasibility trials. A total of 20 participants aged ≥60 with thoracic hyperkyphosis and rehabilitation potential were recruited from four local communities in Wuhan, China. Participants underwent a six-week home-based kyphosis-specific exercises intervention that included warm-up, muscle strengthens, spinal alignment, spinal mobility and flexibility, and cool down five sections (22 exercises). The intervention involved seven 1-h group classes and 35 times daily home practice with identical content. At pre- and post-intervention, the participants' kyphosis angle in two standing postures, static balance, dynamic balance, cardiopulmonary function, dynamic gait assessment, pain, and self-image were assessed and compared. Feasibility was assessed by group class attendance, home practice adherence, and participant evaluations. Results: All participants completed group classes and >75% home practice. Post-intervention, the participant’s kyphosis angle in relaxed and best-standing postures was changed by −12.0° (−15.5°, −4.0°) (Z = − 3.98, P

The stability of underground entry-type excavations will directly affect the working environment and the safety of staff. Empirical critical span graphs and traditional statistics learning methods can not meet the requirements of high accuracy for stability assessment of entry-type excavations. Therefore, this study proposes a new prediction method based on machine learning to scientifically adjust the critical span graph. Accordingly, the particle swarm optimization (PSO) algorithm is used to optimize the core parameters of the gradient boosting decision tree (GBDT), abbreviated as PSO-GBDT. Moreover, the classification performance of eight other classifiers including GDBT, k-nearest neighbors (KNN), two kinds of support vector machines (SVM), Gaussian naive Bayes (GNB), logistic regression (LR) and linear discriminant analysis (LDA) are also applied to compare with the proposed model. Findings revealed that compared with the other eight models, the prediction performance of PSO-GBDT is undoubtedly the most reliable, and its classification accuracy is up to 0.93. Therefore, this model has great potential to provide a more scientific and accurate choice for the stability prediction of underground excavations. In addition, each classification model is used to predict the stability category of several grid points divided by the critical span graph, and the updated critical span graph of each model is discussed in combination with previous studies. The results show that the PSO-GBDT model has the advantages of being scientific, accurate and efficient in updating the critical span graph, and its output decision boundary has strict theoretical support, which can help mine operators make favorable economic decisions.

Abstract Background End-stage renal disease (ESRD) is the final stage of chronic kidney disease (CKD). In addition to the structurally intact chromosome genomic DNA, there is a double-stranded circular DNA called extrachromosomal circular DNA (eccDNA), which is thought to be involved in the epigenetic regulation of human disease. However, the features of eccDNA in ESRD patients are barely known. In this study, we identified eccDNA from ESRD patients and healthy people, as well as revealed the characteristics of eccDNA in patients with ESRD. Methods Using the high-throughput Circle-Sequencing technique, we examined the eccDNA in peripheral blood mononuclear cells (PBMCs) from healthy people (NC) (n = 12) and ESRD patients (n = 16). We analyzed the length distribution, genome elements, and motifs feature of eccDNA in ESRD patients. Then, after identifying the specific eccDNA in ESRD patients, we explored the potential functions of the target genes of the specific eccDNA. Finally, we investigated the probable hub eccDNA using algorithms. Results In total, 14,431 and 11,324 eccDNAs were found in the ESRD and NC groups, respectively, with sizes ranging from 0.01 kb to 60 kb at most. Additionally, the ESRD group had a greater distribution of eccDNA on chromosomes 4, 11, 13, and 20. In two groups, we also discovered several motifs of specific eccDNAs. Furthermore, we identified 13,715 specific eccDNAs in the ESRD group and 10,585 specific eccDNAs in the NC group, both of which were largely annotated as mRNA catalog. Pathway studies using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) showed that the specific eccDNA in ESRD was markedly enriched in cell junction and communication pathways. Furthermore, we identified potentially 20 hub eccDNA-targeting genes from all ESRD-specific eccDNA-targeting genes. Also, we found that 39 eccDNA-targeting genes were associated with ESRD, and some of these eccDNAs may be related to the pathogenesis of ESRD. Conclusions Our findings revealed the characteristics of eccDNA in ESRD patients and discovered potentially hub and ESRD-relevant eccDNA-targeting genes, suggesting a novel probable mechanism of ESRD.

Background: N-glycosylation is one of the most common posttranslational modifications in humans, and these alterations are associated with kidney diseases. Methods: A novel technological approach, single-cell N-acetyllactosamine sequencing (scLacNAc-seq), was applied to simultaneously detect N-glycosylation expression and the transcriptome at single-cell resolution in three human kidney tissues from zero-time biopsy. Cell clusters, glycation abundance in each cell cluster, functional enrichment analysis, cell-cell crosstalk, and pseudotime analysis were applied. Results: Using scLacNAc-seq, 24,247 cells and 22 cell clusters were identified, and N-glycan abundance in each cell was obtained. Transcriptome analysis revealed a close connection between capillary endothelial cells (CapECs) and parietal epithelial cells (PECs). PECs and CapECs communicate with each other through several pairs of ligand receptors (e.g., TGFB1-EGFR, GRN-EGFR, TIMP1-FGFR2, VEGFB-FLT1, ANGPT2-TEK, and GRN-TNFRSF1A). Finally, a regulatory network of cell-cell crosstalk between PECs and CapECs was constructed, which is involved in cell development. Conclusions: We here, for the first time, constructed the glycosylation profile of 22 cell clusters in the human kidney from zero-time biopsy. Moreover, cell-cell communication between PECs and CapECs through the ligand-receptor system may play a crucial regulatory role in cell proliferation.

The ORB (Oriented fast and rotated brief, ORB) algorithm is limited by its inability to extract feature points or extract only a small number of feature points when a fixed threshold is used in complex lighting conditions. To address this issue, this paper proposes a method that combines image enhancement with truncated adaptive threshold to improve the ORB feature extraction algorithm. Firstly, the original image is converted to grayscale. Secondly, the image is enhanced by applying Gaussian filtering for noise reduction, truncated adaptive gamma brightness adjustment, and unsharp masking operation. Then, the enhanced image is segmented into subregions of a specified size, and an improved truncated OTUS method is employed to calculate the adaptive threshold for each subregion. Finally, ORB feature points are extracted by utilizing the adaptive threshold. Experimental results show that the improved ORB algorithm can significantly increase the number of feature points in complex lighting conditions, with good accuracy, real-time performance, and robustness.

Abstract Background Hepatocellular carcinoma (HCC) is one of the deadliest cancers and is mainly developed from chronic liver diseases such as hepatitis-B infection-associated liver cirrhosis (LC). The progression from LC to HCC makes the detection of diagnostic biomarkers to be challenging. Hence, there have been constant efforts to improve on identifying the critical and predictive changes accompanying the disease progression. Methods In this study, we looked to using the mass spectrometry mediated spatial metabolomics technique to simultaneous examine hundreds of metabolites in an untargeted fashion. Additionally, metabolic profiles were compared between six subregions within the HCC tissue to collect spatial information. Results Through those metabolites, altered metabolic pathways in LC and HCC were identified. Specifically, the amino acid metabolisms and the glycerophospholipid metabolisms experienced the most changes. Many of the altered metabolites and metabolic pathways were able to be connected through the urea cycle. Conclusions The identification of the key metabolites and pathways can expand our knowledge on HCC metabolic reprogramming and help us exam potential biomarkers for earlier detection of the malignant disease progression.

Abstract Background Diabetic kidney disease (DKD) is among the most important causes for chronic kidney disease. Anthocyanins (ANT) are polyphenolic compounds present in various food and play an important role in ameliorating hyperglycemia and insulin sensitivity. However, the effects of ANT in DKD are still poorly understood. This study aimed to investigate the effect of ANT (cyanidin-3-O-glucoside [C3G]) on the renal function of DKD, and whether the anti-DKD effect of ANT is related to metabolic pathways. Methods To explore the role of ANT in DKD, we performed the examination of blood glucose, renal function, and histopathology. As for the mechanism, we designed the label-free quantification proteomics and nontargeted metabolomics analysis for kidney and serum. Subsequently, we revealed the anti-DKD effect of ANT through the bioinformatic analysis. Results We showed that the fasting blood glucose level (− 6.1 mmol/L, P = 0.037), perimeter of glomerular lesions (− 24.1 μm, P = 0.030), fibrosis score of glomerular (− 8.8%, P = 0.002), and kidney function (Cystatin C: − 701.4 pg/mL, P = 0.043; urine creatinine: − 701.4 mmol/L, P = 0.032) were significantly alleviated in DKD mice after ANT treatment compared to untreated in the 20th week. Further, proteins and metabolites in the kidneys of DKD mice were observed to be dramatically altered due to changes in amino acid metabolism with ANT treatment; mainly, taurine and hypotaurine metabolism pathway was upregulated (P = 0.0001, t value = 5.97). Furthermore, upregulated tryptophan metabolism (P

Abstract Background According to the Global Cancer Statistics in 2020, the incidence and mortality of colorectal cancer (CRC) rank third and second among all tumors. The disturbance of ubiquitination plays an important role in the initiation and development of CRC, but the ubiquitinome of CRC cells and the survival-relevant ubiquitination are poorly understood. Methods The ubiquitinome of CRC patients (n = 6) was characterized using our own data sets of proteomic and ubiquitin-proteomic examinations. Then, the probable survival-relevant ubiquitination was searched based on the analyses of data sets from public databases. Results For the ubiquitinomic examination, we identified 1690 quantifiable sites and 870 quantifiable proteins. We found that the highly-ubiquitinated proteins (n ≥ 10) were specifically involved in the biological processes such as G-protein coupling, glycoprotein coupling, and antigen presentation. Also, we depicted five motif sequences frequently recognized by ubiquitin. Subsequently, we revealed that the ubiquitination content of 1172 proteins were up-regulated and 1700 proteins were down-regulated in CRC cells versus normal adjacent cells. We demonstrated that the differentially ubiquitinated proteins were relevant to the pathways including metabolism, immune regulation, and telomere maintenance. Then, integrated with the proteomic datasets from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) (n = 98), we revealed that the increased ubiquitination of FOCAD at Lys583 and Lys587 was potentially associated with patient survival. Finally, we depicted the mutation map of FOCAD and elucidated its potential functions on RNA localization and translation in CRC. Conclusions The findings of this study described the ubiquitinome of CRC cells and identified abnormal ubiquitination(s) potentially affecting the patient survival, thereby offering new probable opportunities for clinical treatment.

Abstract Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease (ESRD) worldwide. SGLT2 inhibitors are clinically effective in halting DKD progression. However, the underlying mechanisms remain unclear. The serum and kidneys of mice with DKD were analyzed using liquid chromatography with tandem mass spectrometry (LC–MS/MS)-based metabolomic and proteomic analyses. Three groups were established: placebo-treated littermate db/m mice, placebo-treated db/db mice and EMPA-treated db/db mice. Empagliflozin (EMPA) and placebo (10 mg/kg/d) were administered for 12 weeks. EMPA treatment decreased Cys-C and urinary albumin excretion compared with placebo by 78.60% and 57.12%, respectively (p

Background: Diabetic kidney disease (DKD) is a common and potentially fatal consequence of diabetes. Chronic renal failure or end-stage renal disease may result over time. Numerous studies have demonstrated the function of the microbiota in health and disease. The use of advanced urine culture techniques revealed the presence of resident microbiota in the urinary tract, undermining the idea of urine sterility. Studies have demonstrated that the urine microbiota is related with urological illnesses; nevertheless, the fundamental mechanisms by which the urinary microbiota influences the incidence and progression of DKD remain unclear. The purpose of this research was to describe key characteristics of the patients with DKD urinary microbiota in order to facilitate the development of diagnostic and therapeutic for DKD. Methods: We evaluated the structure and composition of the microbiota extracted from urine samples taken from DKD patients (n = 19) and matched healthy controls (n = 15) using 16S rRNA gene sequencing. Meanwhile, serum metabolite profiles were compared using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Associations between clinical characteristics, urine microbiota, and serum metabolites were also examined. Finally, the interaction between urine microbiota and serum metabolites was clarified based on differential metabolite abundance analysis. Results: The findings indicated that the DKD had a distinct urinary microbiota from the healthy controls (HC). Taxonomic investigations indicated that the DKD microbiome had less alpha diversity than a control group. Proteobacteria and Acidobacteria phyla increased in the DKD, while Firmicutes and Bacteroidetes decreased significantly (P

Objective This study aims to establish a real-time dynamic monitoring system for silent aspiration (SA) to provide evidence for the early diagnosis of and precise intervention for SA after stroke. Methods Multisource signals, including sound, nasal airflow, electromyographic, pressure and acceleration signals, will be obtained by multisource sensors during swallowing events. The extracted signals will be labeled according to videofluoroscopic swallowing studies (VFSSs) and input into a special dataset. Then, a real-time dynamic monitoring model for SA will be built and trained based on semisupervised deep learning. Model optimization will be performed based on the mapping relationship between multisource signals and insula-centered cerebral cortex–brainstem functional connectivity through resting-state functional magnetic resonance imaging. Finally, a real-time dynamic monitoring system for SA will be established, of which the sensitivity and specificity will be improved by clinical application. Results Multisource signals will be stably extracted by multisource sensors. Data from a total of 3200 swallows will be obtained from patients with SA, including 1200 labeled swallows from the nonaspiration category from VFSSs and 2000 unlabeled swallows. A significant difference in the multisource signals is expected to be found between the SA and nonaspiration groups. The features of labeled and pseudolabeled multisource signals will be extracted through semisupervised deep learning to establish a dynamic monitoring model for SA. Moreover, strong correlations are expected to be found between the Granger causality analysis (GCA) value (from the left middle frontal gyrus to the right anterior insula) and the laryngeal rise time (LRT). Finally, a dynamic monitoring system will be established based on the former model, by which SA can be identified precisely. Conclusion The study will establish a real-time dynamic monitoring system for SA with high sensitivity, specificity, accuracy and F1 score.

BackgroundSjögren’s syndrome (SS) is a systemic autoimmune disease that affects about 0.04-0.1% of the general population. SS diagnosis depends on symptoms, clinical signs, autoimmune serology, and even invasive histopathological examination. This study explored biomarkers for SS diagnosis.MethodsWe downloaded three datasets of SS patients’ and healthy pepole’s whole blood (GSE51092, GSE66795, and GSE140161) from the Gene Expression Omnibus (GEO) database. We used machine learning algorithm to mine possible diagnostic biomarkers for SS patients. Additionally, we assessed the biomarkers’ diagnostic value using the receiver operating characteristic (ROC) curve. Moreover, we confirmed the expression of the biomarkers through the reverse transcription quantitative polymerase chain reaction (RT-qPCR) using our own Chinese cohort. Eventually, the proportions of 22 immune cells in SS patients were calculated by CIBERSORT, and connections between the expression of the biomarkers and immune cell ratios were studied.ResultsWe obtained 43 DEGs that were mainly involved in immune-related pathways. Next, 11 candidate biomarkers were selected and validated by the validation cohort data set. Besides, the area under curves (AUC) of XAF1, STAT1, IFI27, HES4, TTC21A, and OTOF in the discovery and validation datasets were 0.903 and 0.877, respectively. Subsequently, eight genes, including HES4, IFI27, LY6E, OTOF, STAT1, TTC21A, XAF1, and ZCCHC2, were selected as prospective biomarkers and verified by RT-qPCR. Finally, we revealed the most relevant immune cells with the expression of HES4, IFI27, LY6E, OTOF, TTC21A, XAF1, and ZCCHC2.ConclusionIn this paper, we identified seven key biomarkers that have potential value for diagnosing Chinese SS patients.

Clarification of the cause of overpressure is of great significance for the study of hydrocarbon generation, migration and accumulation processes under an overpressure environment, and the prediction of predrilling pressure. The cause of overpressure in Xihu Depression is still controversial. This study, based on mudstone compaction research and organic matter correction of logging data, ascertained the causes of overpressure in the Pinghu tectonic zone, Xihu Depression. A modified discrimination method for overpressure genesis was used and the overpressure–hydrocarbon distribution relationship was explored. The results show the following: (1) Vertically, overpressure is located in the lower section of the Pinghu Formation, with a pressure coefficient of 1.1–1.7 and a pressure relief feature. On the plane, the pressure coefficient in the Pingzhong area exceeds that in the Pingbei area. (2) The main causes of abnormal high pressure in the research area are undercompaction and fluid expansion. The fluid expansion mechanisms include overpressure transmission and hydrocarbon charging within the reservoir as well as hydrocarbon generation pressurisation and overpressure transmission within the source rock. (3) In the surge section of kaolinite, under fluid pressure, kaolin migrates toward the low-pressure areas, decreasing the porosity in low-pressure areas and preserving pores in high-pressure areas. The evolution of fluid pressure can be divided into two stages: pressurisation; and both pressurisation and pressure relief. Pressurisation and pressure relief drive hydrocarbon charging, but hydrocarbons are more enriched in overpressure layers.

Background: Osteogenesis imperfecta (OI) is a rare genetic disorder characterized by recurring bone fractures. Some OI patients have other clinical manifestations such as growth retardation, dental abnormalities, blue sclera, and hearing loss. The relationship between the phenotype and genotype of OI is indistinct, and there is no cure for OI. Therefore, an appropriate disease model is urgently needed to understand the pathophysiology of OI. Induced pluripotent stem cells (iPSCs) are capable of developing into three germ layers and have the same genetic background as the donor cells they were derived from; thus, they are an appropriate disease model. Methods: Blood samples collected from the proband and her affected children and one unaffected child were used forgenotyping by whole genome sequencing. A patient-specific iPSC line and a healthy donor iPSC line were generated by reprogramming peripheral blood mononuclear cells with episomal plasmids containing seven transcription factors, namely, OCT4, SOX2, NANOG, LIN28, cMYC, KLF4, and SV40LT. Results: The proband and her two affected children were homozygous for a mutation in collagen type I alpha 1 exon 10, c.725G>T, predicting a p.G242V substitution. A patient-specific iPSC line and a healthy donor iPSC line were generated and characterized in terms of their human embryonic stem cell-like morphology, expression of pluripotency markers, and the ability to differentiate into cells of three germ layers. Conclusions: Here, we report the phenotyping and iPSC disease modeling of an OI family. The detailed phenotyping of the OI family and establishment of iPSCs from an OI patient and healthy family member will provide a powerful tool to evaluate the pathophysiology of OI and develop targeted therapies.

With the CMOS technology downscaling to the deep nanoscale, the aging effects of devices degrade circuit performance and even lead to functional failure. The stress analysis is critical to evaluate the influence of aging effects on digital circuits. Some related analytical work has recently focused on reliability-aware circuit analysis. Nevertheless, the aging dependence among different devices is not considered, which will induce errors of degradation evaluation in the digital circuit. In order to improve the accuracy of reliability-aware static timing analysis, an improved analytical method is proposed by employing logical resolving. Experimental results show that the proposed method has a better evaluation accuracy of aging path delay than traditional strategies. For aging timing evaluation on aging paths, excessive pessimism can be reduced by employing the proposed method. And, a 378× speedup is achieved while having a 0.56% relative error compared with precise SPICE simulation. Moreover, the circuit performance sacrifice of an aging-aware synthesis flow with the proposed method can be decreased. Due to the high efficiency and high accuracy, the proposed method can meet the speed demands of large-scale digital circuit reliability analysis while achieving transistor simulation accuracy.

Abstract Background Research on spatiotemporal gene landscape can provide insights into the spatial characteristics of human kidney development and facilitate kidney organoid cultivation. Here, we profiled the spatiotemporal gene programs of the human embryonic kidneys at 9 and 18 post-conception weeks (PCW) by integrating the application of microarray-based spatial transcriptomics and single-cell transcriptomics. Results We mapped transcriptomic signatures of scRNA-seq cell types upon the 9 and 18 PCW kidney sections based on cell-type deconvolution and multimodal intersection analyses, depicting a spatial landscape of developing cell subpopulations. We established the gene characteristics in the medullary regions and revealed a strong mitochondrial oxidative phosphorylation and glycolysis activity in the deeper medullary region. We also built a regulatory network centered on GDNF-ETV4 for nephrogenic niche development based on the weighted gene co-expression network analysis and highlighted the key roles of Wnt, FGF, and JAG1-Notch2 signaling in maintaining renal branching morphogenesis. Conclusions Our findings obtained by this spatiotemporal gene program are expected to improve the current understanding of kidney development.

Among urological cancers, renal cancer has the highest fatality rate. In a previous pan-cancer study of the METTL family, we observed a stronger association between the METTL family members and the risk of renal cancer compared to other cancers. Among these members, METTL7A, a potential methyltransferase, was identified as a protective factor, although its role and mechanism in renal cancer remain unclear. In this study, we utilized public databases to examine the expression of METTL7A in renal cancer tissues and normal tissues and found that METTL7A expression was much lower in renal cancer tissues. We also noticed a link between low METTL7A expression and poor prognosis for patients. According to the results of our functional enrichment analysis, METTL7A may have a role in immunological functions in renal cancer. METTL7A expression was strongly linked with the degrees of immune cell infiltration and expression of numerous immunological components. METTL7A had significantly different effects on the survival times of renal cancer patients with high or low immune infiltration. Our findings suggest that METTL7A may be used as both a prognostic biomarker and an immunological target for kidney cancer. In conclusion, our study sheds light on the importance of METTL7A in renal cancer and emphasizes the potential of targeting METTL7A as a novel therapeutic strategy for kidney cancer.

Background Idiopathic membranous nephropathy (IMN) is an organ-specific autoimmune disease with multiple and complex pathogenic mechanisms. Currently, renal biopsy is considered the gold standard for diagnosing membranous nephropathy. However, there were limitations to the renal puncture biopsy, such as the relatively high cost, longer time consuming, and the risk of invasive procedures. We investigated the profile of serum metabolites in IMN patients based on the UHPLC-QE-MS metabolomics technique for exploring the potential disease biomarkers and clinical implementation. Methods In our research, we collected serum samples from healthy control (n = 15) and IMN patients (n = 25) to perform metabolomics analysis based on the UHPLC-QE-MS technique. Result We identified 215 differentially expressed metabolites (DEMs) between the IMN and healthy control (HC) groups. Furthermore, these DEMs were significantly identified in histidine metabolism, arginine and proline metabolism, pyrimidine metabolism, purine metabolism, and steroid hormone biosynthesis. Several key DEMs were significantly correlated with the level of clinical parameters, such as serum albumin, IgG, UTP, and cholesterol. Among them, dehydroepiandrosterone sulfate (DHEAS) was considered the reliable diagnostic biomarker in the IMN group. There was an increased abundance of actinobacteria, phylum proteobacteria, and class gammaproteobacterial in IMN patients for host-microbiome origin analysis. Conclusion Our study revealed the profiles of DEMs from the IMN and HC groups. The result demonstrated that there were disorders of amino acids, nucleotides, and steroids hormones metabolism in IMN patients. The down-regulation of DHEAS may be associated with the imbalance of the immune environment in IMN patients. In host-microbiome origin analysis, the gut microbiota and metabolite disturbances were present in IMN patients.

BackgroundIgA nephropathy (IgAN), (LN), membranous nephropathy (MN), and minimal change nephropathy (MCN) are all belonged to autoimmune glomerulonephritis. This study aimed to identify the specific proteomic characteristics of the four GNs diseases in order to provide frameworks for developing the appropriate drug for patients diagnosed with GNs disease.MethodsLiquid chromatography−tandem mass spectrometry (LC-MS/MS) was utilized to investigate proteomic features of glomerular tissues obtained by laser capture microdissection (LCM). 8 normal control cases, 11 IgAN cases, 19 LN cases, 5 MN cases, and 3 MCN cases in this study were selected for bioinformatics analyses.ResultsThe shared overlapping proteins among the top 100 DEPs of each GNs type were mostly downregulated, in which only FLII was significantly downregulated in the four GNs diseases. A2M was significantly upregulated in MN, IgAN, and LN subgroups. The pathway of complement and coagulation cascades was notably activated with NES value ranging 2.77 to 3.39 among MCN, MN, IgAN, and LN diseases, but the pattern of protein expression level were significantly different. In LN patients, the increased activity of complement and coagulation cascades was contributed by the high expression of multiple complements (C1QB, C3, C4A, C4B, C6, C8B, C8G, C9). Meanwhile, both C1QC and C4B were remarkably upregulated in MN patients. On the contrary, complement-regulating proteins (CD59) was substantially decreased in MCN and IgAN subgroup.ConclusionsThe integrative proteomics analysis of the four GNs diseases provide insights into unique characteristics of GNs diseases and further serve as frameworks for precision medicine diagnosis and provide novel targets for drug development.

Conical picks are widely used as cutting tools in shearers and roadheaders, and the mean cutting force (MCF) is one of the important parameters affecting conical pick performance. As MCF depends on a number of parameters and due to that the existing empirical and theoretical formulas and numerical modelling are not sufficient enough and reliable to predict MCF in a proficient manner. So, in this research, a novel intelligent model based on a random forest algorithm (RF) and a heuristic algorithm called the salp swarm algorithm (SSA) have been applied to determine the optimal hyper-parameters in RF, and root mean square error is used as a fitness function. A total of 188 data samples including 50 rock types and seven parameters (tensile strength of the rock σt, compressive strength of the rock σc, cone angle θ, cutting depth d, attack angle γ, rake angle α and back-clearance angle β) were collected to develop an SSA-RF model for mean cutting force prediction. The prediction results of the SSA-RF model were compared with seven influential formulas and four classical models, such as random forest, extreme learning machine, support vector machine and radial basis function neural network. The mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE) and Pearson correlation coefficient (R2) were employed as evaluation indexes to compare the capability of different predicting models. The MAE (0.509 and 0.996), RMSE (0.882 and 1.165), MAPE (0.146 and 0.402) and R2 (0.975 and 0.910) values between measured and predicted MCF for training and testing phases of the SSA-RF model clearly demonstrate the superiority in prediction compared to the other tools. A sensitivity analysis has also been performed to understand the influence of each input parameter on MCF, which indicates that σc, d and σt are the most important variables for MCF prediction.

In this study, a post-irradiation examination of pure tungsten (W) and tantalum (Ta) specimens irradiated at the Swiss Spallation-Neutron Source is conducted. W is used as a potential candidate for a solid spallation-target material owing to its favorable properties, namely, high neutron yield, good thermal conductivity, and low thermal-expansion coefficient. However, W also suffers from several disadvantages such as poor corrosion resistance to water coolant and irradiation embrittlement. To improve these properties, cladding technologies using Ta for W alloys have been developed. In the present study, we investigated the irradiation effects on two tungsten materials—poly-crystal W (W-Poly) and single-crystal W (W-Sin)—along with pure polycrystalline Ta. The tensile-test results revealed that W-Poly exhibited almost no ductility after irradiation of 10.2–35.0 displacement per atom (dpa). W-Sin was irradiated up to 10.2 dpa and demonstrated 6% of total elongation (TE). With regard to Ta, TE decreased based on the increase in irradiation, reaching almost zero at doses of more than 10.3 dpa. For pure Ta, grain size was one of the key parameters in investigating the irradiated-material properties.

Abstract Background The complicated hyperglycaemic and chronic inflammation of diabetic wounds in orthopaedic surgery leads to dysregulated immune cell function and potential infection risk. Immune interventions in diabetic wounds face a possible contradiction between simultaneous establishment of the pro-inflammatory microenvironment in response to potential bacterial invasion and the anti-inflammatory microenvironment required for tissue repair. To study this contradiction and accelerate diabetic-wound healing, we developed a photocurable methacryloxylated silk fibroin hydrogel (Sil-MA) system, co-encapsulated with metformin-loaded mesoporous silica microspheres (MET@MSNs) and silver nanoparticles (Ag NPs). Results The hydrogel system (M@M–Ag–Sil-MA) enhanced diabetic-wound healing via spatiotemporal immunomodulation. Sil-MA imparts a hydrogel system with rapid in situ Ultra-Violet-photocurable capability and allows preliminary controlled release of Ag NPs, which can inhibit bacterial aggregation and create a stable, sterile microenvironment. The results confirmed the involvement of Met in the immunomodulatory effects following spatiotemporal dual-controlled release via the mesoporous silica and Sil-MA. Hysteresis-released from Met shifts the M1 phenotype of macrophages in regions of diabetic trauma to an anti-inflammatory M2 phenotype. Simultaneously, the M@M–Ag–Sil-MA system inhibited the formation of neutrophil extracellular traps (NETs) and decreased the release of neutrophil elastase, myeloperoxidase, and NETs-induced pro-inflammatory factors. As a result of modulating the immune microenvironmental, the M@M–Ag–Sil-MA system promoted fibroblast migration and endothelial cell angiogenesis in vivo, with verification of enhanced diabetic-wound healing accompanied with the spatiotemporal immunoregulation of macrophages and NETs in a diabetic mouse model. Conclusions Our findings demonstrated that the M@M–Ag–Sil-MA hydrogel system resolved the immune contradiction in diabetic wounds through spatiotemporal immunomodulation of macrophages and NETs, suggesting its potential as a promising engineered nano-dressing for the treatment of diabetic wounds in orthopaedic surgery. Graphical Abstract