A single-center, open label, randomized, controlled study of hydroxychloroquine sulfate in the treatment of low risk PLA2R-associated membranous nephropathy.

OBJECTIVE: To evaluate the efficacy and safety of hydroxychloroquine sulfate (HCQ) in the treatment of low risk phospholipase A2 receptor (PLA2R)-associated membranous nephropathy (MN). METHODS: A total of 110 patients with low risk PLA2R-associated MN were included in the study. Patients who met the inclusion and exclusion criteria were assigned randomly to two groups: the HCQ treatment group and the control group. The control group received standard supportive treatment according to the guidelines, while the HCQ treatment group received HCQ in addition to the supportive treatment. The clinical data of the patients were analyzed, with comparisons made at baseline and during the six-month follow-up period. Any adverse reactions were recorded. RESULTS: The baseline data were comparable between the HCQ treatment group and the control group. At the end of the six-month follow-up period, the reductions in urine protein excretion and serum PLA2R antibody titer were more notable in the HCQ treatment group than those in the control group, with these differences being statistically significant (p < 0.05). Compared to the control group, the HCQ treatment group had fewer patients who were converted from low risk to moderate-to-high risk (p = 0.084). There were also no severe adverse reactions in the HCQ treatment group. CONCLUSION: In patients with low risk PLA2R-associated MN, adequate supportive therapy combined with HCQ is superior to supportive therapy alone in controlling proteinuria and reducing serum PLA2R antibody titers. Additionally, our study demonstrated that the incidence of adverse reactions did not increase. TRIAL REGISTRATION: This study was registered in the Chinese Clinical Trial Registry (Registration No.: ChiCTR1900021757, Date of registration: 2019-03-08).

Efficacy and safety of dual renin-angiotensin system (RAS) blockade for non-elderly diabetic kidney disease patients with preserved eGFR.

AIM: Although sodium glucose cotransporter2 inhibitor (SGLT-2I) is widely used in clinical practice, sufficient renin-angiotensin system (RAS) inhibition remains the cornerstone of diabetic kidney disease (DKD) treatment. The aim of this single-center study was to evaluate the efficacy and safety of dual RAS blockade compared with angiotensin-converting enzyme inhibitor (ACEI)/angiotensin II receptor blocker (ARB) monotherapy in non-elderly DKD patients with preserved eGFR (WHO Standard, < 60y). METHODS: This single-center study was registered in Chinese Clinical Trial Registry (ChiCTR1900024752), and approved by the ethical committee (KY201994). In this study, we recruited non-elderly type 2 diabetes volunteers with initial diagnosis of DKD to receive dual RAS blockade or monotherapy. 150 non-elderly DKD patients with preserved eGFR were recruited. The patients were randomly divided into dual RAS blockade group and monotherapy group. The dual RAS blockade group treatment regimen was an 80 mg valsartan plus a 4 mg perindopril tert-butylamine per day. At the same time, monotherapy group patients who received the 8 mg perindopril tert-butylamine or 160 mg valsartan monotherapy. The clinical data of the three groups were compared at baseline and collected during the follow-up period of 12 months. RESULTS: The baseline of patients who received dual RAS blockade was similar to that of monotherapy group. After 12 months of treatment, the median level of proteinuria in the dual RAS blockade group was significantly lower than that in the monotherapy group. There was no significant difference in the estimated glomerular filtration rate (eGFR) level, potassium, blood pressure and no serious adverse reactions. CONCLUSIONS: In non-elderly DKD patients with preserved eGFR, dual RAS blockade is superior to control proteinuria, and does not increase the probability of adverse reactions such as hyperkalemia, hypotension and acute kidney injury in 12 months.

Molecular cloning and characterization of duck Annexin A2 and its effect on DTMUV replication.

Annexin A2 (ANXA2) is a multifaceted protein implicated in various stages of viral infections, particularly in envelope virus replication through mechanisms such as endocytosis and exocytosis. This study delves into the characterization and functional dynamics of duck ANXA2 (duANXA2). We successfully cloned the full-length coding sequence of duANXA2 and conducted a detailed structural analysis. The open reading frame (ORF) of duANXA2 is 1020 bp, encoding 339 amino acids and featuring 4 conserved domains. Phylogenetic tree analysis indicates that duANXA2 is most closely related to Gallus gallus, with significantly lesser homology to fish species. We evaluated the tissue-specific expression of duANXA2 in healthy ducks, noting its ubiquitous presence but varying expression levels across different organs, with notably high expression in the esophagus and immune organs. Upon infecting duck embryo fibroblast (DEF) cells with the duck Tembusu virus (DTMUV), a flavivirus causing ducks substantial mortality and a dramatic decline in egg production, we observed a pronounced upregulation of duANXA2. Functional assays demonstrated that overexpression of duANXA2 in DEF cells augments DTMUV replication, while its interference markedly reduces DTMUV replication. These findings underscore the role of duANXA2 as a facilitator of DTMUV replication, presenting it as a potential target for therapeutic intervention in managing DTMUV infections.

Adaptive Temporal-Spatial Pyramid Variational Autoencoder Model for Multirate Dynamic Chemical Process Soft Sensing Application.

Data-driven soft sensors play an important role in practical processes and have been widely applied. They provide real-time prediction of quality variables and then guide production and improve product quality. In practical chemical production processes, nonlinear dynamic multirate data is widespread and challenging to model. This paper innovatively proposes a temporal-spatial pyramid variational autoencoder (TS-PVAE) model for the nonlinear temporal-spatial feature pyramid extraction from multirate data. This structure not only selectively utilizes multirate data but also handles complex nonlinear time-series data. Based on this, integrated with just-in-time (JIT) learning, an adaptive TS-PVAE (ATS-PVAE) model is developed. In this model, historical data are used for real-time fine-tuning of the model, leading to the development of an adaptive model. Finally, the proposed models are validated by an industrial case of a methanation furnace, demonstrating a superior estimation performance.

Global Prevalence of Overweight and Obesity in Children and Adolescents: A Systematic Review and Meta-Analysis.

Importance: Overweight and obesity in childhood and adolescence is a global health issue associated with adverse outcomes throughout the life course. Objective: To estimate worldwide prevalence of overweight and obesity in children and adolescents from 2000 to 2023 and to assess potential risk factors for and comorbidities of obesity. Data Sources: MEDLINE, Web of Science, Embase, and Cochrane. Study Selection: The inclusion criteria were: (1) studies provided adequate information, (2) diagnosis based on body mass index cutoffs proposed by accepted references, (3) studies performed on general population between January 2000 and March 2023, (4) participants were younger than 18 years. Data Extraction and Synthesis: The current study was performed in accordance with the Meta-analysis of Observational Studies in Epidemiology guidelines. DerSimonian-Laird random-effects model with Free-Tukey double arcsine transformation was used for data analysis. Sensitivity analysis, meta-regression, and subgroup analysis of obesity among children and adolescents were conducted. Main Outcomes and Measures: Prevalence of overweight and obesity among children and adolescents assessed by World Health Organization, International Obesity Task Force, the US Centers for Disease Control and Prevention, or other national references. Results: A total of 2033 studies from 154 different countries or regions involving 45 890 555 individuals were included. The overall prevalence of obesity in children and adolescents was 8.5% (95% CI 8.2-8.8). We found that the prevalence varied across countries, ranging from 0.4% (Vanuatu) to 28.4% (Puerto Rico). Higher prevalence of obesity among children and adolescents was reported in countries with Human Development Index scores of 0.8 or greater and high-income countries or regions. Compared to 2000 to 2011, a 1.5-fold increase in the prevalence of obesity was observed in 2012 to 2023. Substantial differences in rates of obesity were noted when stratified by 11 risk factors. Children and adolescents with obesity had a high risk of depression and hypertension. The pooled estimates of overweight and excess weight in children and adolescents were 14.8% (95% CI 14.5-15.1) and 22.2% (95% CI 21.6-22.8), respectively. Conclusions and Relevance: This study's findings indicated 1 of 5 children or adolescents experienced excess weight and that rates of excess weight varied by regional income and Human Development Index. Excess weight among children and adolescents was associated with a mix of inherent, behavioral, environmental, and sociocultural influences that need the attention and committed intervention of primary care professionals, clinicians, health authorities, and the general public.

Self-assembly of PEG-PPS polymers and LL-37 peptide nanomicelles improves the oxidative microenvironment and promotes angiogenesis to facilitate chronic wound healing.

Refractory diabetic wounds are associated with high incidence, mortality, and recurrence rates and are a devastating and rapidly growing clinical problem. However, treating these wounds is difficult owing to uncontrolled inflammatory microenvironments and defective angiogenesis in the affected areas, with no established effective treatment to the best of our knowledge. Herein, we optimized a dual functional therapeutic agent based on the assembly of LL-37 peptides and diblock copolymer poly(ethylene glycol)-poly(propylene sulfide) (PEG-PPS). The incorporation of PEG-PPS enabled responsive or controlled LL-37 peptide release in the presence of reactive oxygen species (ROS). LL-37@PEG-PPS nanomicelles not only scavenged excessive ROS to improve the microenvironment for angiogenesis but also released LL-37 peptides and protected them from degradation, thereby robustly increasing angiogenesis. Diabetic wounds treated with LL-37@PEG-PPS exhibited accelerated and high-quality wound healing in vivo. This study shows that LL-37@PEG-PPS can restore beneficial angiogenesis in the wound microenvironment by continuously providing angiogenesis-promoting signals. Thus, it may be a promising drug for improving chronic refractory wound healing.

Loss of nephric augmenter of liver regeneration facilitates acute kidney injury via ACSL4-mediated ferroptosis.

Ferroptosis, characterized by lipid accumulation in intracellular compartments, is related to acute kidney injury (AKI), but the mechanism remains obscure. In our previous study, the protective effect of augmenter of liver regeneration (ALR) on AKI was not fully clarified. In this study, we established an AKI mouse model by knocking out proximal tubule-specific ALR and an AKI cell model by inducing hypoxia, as well as enrolled AKI patients, to investigate the effects of ALR on ferroptosis and the progression of AKI. We found that ALR knockout aggravated ferroptosis and increased ROS accumulation and mitochondrial damage, whereas ALR overexpression attenuated ferroptosis through clearance of ROS and maintenance of mitochondrial morphology. Mechanistically, we demonstrated that ALR could directly bind to long-chain-fatty-acid-CoA ligase 4 (ACSL4) and further inhibit the expression of ACSL4 by interacting with certain regions. By resolution liquid chromatography coupled with triple quadruple mass spectrometry, we found that ALR could reduce the contents of polyunsaturated fatty acids, especially arachidonic acid. In addition, we showed that ALR binds to ACSL4 and attenuates oxylipin accumulation, exerting a protective effect against ferroptosis in AKI. Therefore, targeting renal ALR can attenuate ferroptosis and can offer a promising strategy for the treatment of AKI.

Optimization of the Solid-State Culture Conditions and Chemical Component Analysis of Poria cocos (Agaricomycetes).

The optimal cultivation conditions and chemical components of Poria cocos fruiting bodies were examined by employing the single factor and response surface methods to screen for optimal conditions for artificial cultivation. The differences in chemical composition among the fruiting bodies, fermented mycelium, and sclerotia of P. cocos were compared using UV spectrophotometry and high-performance liquid chromatography (HPLC). The optimal growth conditions for P. cocos fruiting bodies were 28.5°C temperature, 60% light intensity, and 2.5 g pine sawdust, which resulted in the production of numerous basidiocarps and basidiospores under microscopic examination. Polysaccharides, triterpenoids, and other main active components of P. cocos were found in the fruiting bodies, sclerotia, and fermented mycelium. The triterpenoid components of the fruiting bodies were consistent with those of the sclerotia. The content of pachymic acid in the fruiting bodies was significantly higher than that in the sclerotia, with a value of 33.37 ± 0.1902 mg/g. These findings provide novel insights into the sexual breeding and comprehensive development and utilization of P. cocos.

Clinical features and prognosis of pregnancy-related renal damage and pregnancy after chronic kidney disease.

OBJECTIVE: To explore the clinical features of renal damage related to pregnancy and pregnancy after chronic kidney disease (CKD), providing clinical evidence for the relationship between renal damage and pregnancy. METHODS: A retrospective analysis was performed on patients admitted to our hospital between March 2013 and February 2021 who had both pregnancy and kidney damage. The study collected pathology results from renal biopsies, 24-hour urinary protein quantity, albumin (Alb), serum creatinine (Scr), blood lipids, coagulation function, blood routine, and other indicators during and after pregnancy. RESULTS: This study included 82 cases, with 48 cases in the pregnancy-related renal damage group. Thirty-four cases were in the post-CKD pregnancy group. Of the patients, 30 cases (88.24%) had CKD stage 1-2. Results showed better pregnancy and fetal outcomes in the post-CKD pregnancy group compared to the pregnancy-related renal damage group (Ρ was 0.029 and 0.036, respectively). Renal biopsy pathology revealed that 16 cases (33.33%) in the pregnancy-related renal damage group mainly had focal segmental glomerulosclerosis (FSGS), while the post-CKD pregnancy group was dominated by 14 cases (43.75%) of IgA nephropathy. The first blood test indicators revealed that the pregnancy-related renal damage group had lower estimated glomerular filtration (eGFR) and Alb levels compared to the post-CKD pregnancy group (Ρ was 0.003 and 0.000, respectively). Additionally, 24-hour urinary protein quantity, total cholesterol (Tch), triglyceride (TG), and platelet (PLT) counts were higher in the pregnancy-related renal damage group compared to the post-CKD pregnancy group (Ρ was 0.005, 0.001, 0.008, and 0.031, respectively). The abnormal rate of Scr during pregnancy was 41.67% (20/48) in the pregnancy-related renal damage group and 17.39% (4/23) in the post-CKD pregnancy group, with a statistically significant difference (Ρ was 0.043). CONCLUSION: The pregnancy-related renal damage group is mainly associated with FSGS, while the post-CKD pregnancy group is characterized by IgA nephropathy. Patients with CKD1-2 can have a successful pregnancy after achieving good control of eGFR, albumin, 24-hour urinary protein quantity and other indicators, resulting in better pregnancy and fetal outcomes. Abnormal Scr levels during pregnancy of pregnancy-related renal damage can be improved within 3 months after delivery.

Construction and validation of 3-genes hypoxia-related prognostic signature to predict the prognosis and therapeutic response of hepatocellular carcinoma patients.

BACKGROUND: Previous studies have shown that the hypoxia microenvironment significantly impacted tumor progression. However, the clinical prognostic value of hypoxia-related risk signatures and their effects on the tumor microenvironment (TME) in hepatocellular carcinoma (HCC) remains hazy. This study aimed to conduct novel hypoxia-related prognostic signatures and improve HCC prognosis and treatment. METHODS: Differentially expressed hypoxia-related genes (HGs) were identified with the gene set enrichment analysis (GSEA). Univariate Cox regression was utilized to generate the tumor hypoxia-related prognostic signature, which consists of 3 HGs, based on the least absolute shrinkage and selection operator (LASSO) algorithm. Then the risk score for each patient was performed. The prognostic signature's independent prognostic usefulness was confirmed, and systematic analyses were done on the relationships between the prognostic signature and immune cell infiltration, somatic cell mutation, medication sensitivity, and putative immunological checkpoints. RESULTS: A prognostic risk model of four HGs (FDPS, SRM, and NDRG1) was constructed and validated in the training, testing, and validation datasets. To determine the model's performance in patients with HCC, Kaplan-Meier curves and time-dependent receiver operating characteristic (ROC) curves analysis was implemented. According to immune infiltration analysis, the high-risk group had a significant infiltration of CD4+ T cells, M0 macrophages, and dendritic cells (DCs) than those of the low-risk subtype. In addition, the presence of TP53 mutations in the high-risk group was higher, in which LY317615, PF-562271, Pyrimethamine, and Sunitinib were more sensitive. The CD86, LAIR1, and LGALS9 expression were upregulated in the high-risk subtype. CONCLUSIONS: The hypoxia-related risk signature is a reliable predictive model for better clinical management of HCC patients and offers clinicians a holistic viewpoint when determining the diagnosis and course of HCC treatment.

Composite nanofibrous dressing loaded with Prussian blue and heparin for anti-inflammation therapy and diabetic wound healing.

Diabetic ulcer is a severe complication of diabetes that can lead to amputation due to the overproduction of pro-inflammatory factors and reactive oxygen species (ROS). In this study, a composite nanofibrous dressing was developed by combining Prussian blue nanocrystals (PBNCs) and heparin sodium (Hep) through electrospinning, electrospraying, and chemical deposition. The nanofibrous dressing (PPBDH) was designed to take advantage of the excellent pro-inflammatory factor-adsorbing capability of Hep and the ROS-scavenging capabilities of PBNCs, resulting in synergistic treatment. It is worth noting that the nanozymes were firmly anchored to the fiber surfaces through slight polymer swelling caused by the solvent during electrospinning, thereby guaranteeing the preservation of the enzyme-like activity levels of PBNCs. The PPBDH dressing was found to be effective in reducing intracellular ROS levels, protecting cells from ROS-induced apoptosis, and capturing excessive pro-inflammatory factors, including chemoattractant protein-1 (MCP-1) and interleukin-1ß (IL-1ß). Furthermore, a chronic wound healing evaluation conducted in vivo demonstrated that the PPBDH dressing was able to effectively alleviate the inflammatory response and accelerate wound healing. This research presents an innovative approach to fabricate nanozyme hybrid nanofibrous dressings, which have great potential in accelerating the healing of chronic and refractory wounds with uncontrolled inflammation.

USP33 promotes pancreatic cancer malignant phenotype through the regulation of TGFBR2/TGFß signaling pathway.

Pancreatic cancer (PC) ranked fourth among cancer-related death worldwide with a survival rate less than 5%. The abnormal proliferation and distant metastasis are major obstacles for the diagnosis and treatment of pancreatic cancer, therefore, it is urgent for researchers to uncover the molecular mechanisms underlying the PC proliferation and metastasis. In current study, we found that USP33, a member of deubiquitinating enzyme family, was upregulated among PC samples and cells, meanwhile, the high expression of USP33 correlated with poor prognosis of patients. Function experiments revealed that USP33 overexpression promoted the proliferation, migration and invasion of PC cells while the inhibition of USP33 expression in PC cells exhibited the opposite effect. The mass spectrum and luciferase complementation assay screened TGFBR2 as the potential binding protein of USP33. Mechanistically, USP33 triggered the deubiquitination of TGFBR2 and prevented its degradation by lysosome, therefore promoted TGFBR2 accumulation in cell membrane and eventually contributed to the sustained activation of TGF-ß signaling. Moreover, our results revealed that the activation of TGF-ß targeted gene ZEB1 promoted the transcription of USP33. In conclusion, our study found that USP33 contributed to the proliferation and metastasis of pancreatic cancer through a positive feedback loop with TGF-ß signaling pathway. Moreover, this study suggested that USP33 may serve as a potential prognostic and therapeutic target in PC.

Supervised Attention-Based Bidirectional Long Short-Term Memory Network for Nonlinear Dynamic Soft Sensor Application.

Soft sensors are mathematical methods that describe the dependence of primary variables on secondary variables. A nonlinear characteristic commonly appears in modern industrial process data with increasing complexity and dynamics, which has brought challenges to soft sensor modeling. To solve these issues, a novel supervised attention-based bidirectional long short-term memory (SA-BiLSTM) is first proposed in this paper to handle the nonlinear industrial process modeling with dynamic features. In this SA-BiLSTM model, an attention mechanism is introduced to calculate the correlation between hidden features in each time step, thus avoiding the loss of important information. Furthermore, this approach combines historical quality information and a moving window through a supervised strategy of quality variables. Such manipulation not only extracts and exploits nonlinear dynamic latent information from the process and quality variables but also enhances the model's learning efficiency and overall prediction performance. Finally, two real industrial examples demonstrate the superiority of the proposed method compared to conventional methods.

Predictive Modeling With Multiresolution Pyramid VAE and Industrial Soft Sensor Applications.

In industrial processes, the sampling rates of process variables are discrepant because of the nature of instruments and measuring demands, which forms the challenging issue, that is, the multirate modeling in the data-driven soft sensor development. In this work, a multiresolution pyramid variational autoencoder (MR-PVAE) predictive model is proposed to solve this problem based on the deep feature extraction and feature pyramid augmentation. First, a multirate data filter is designed through a resolution searching strategy to turn the original process data into a multiresolution dataset. Then, the pyramid variational autoencoder (PVAE) is proposed to extract deep nonlinear features from the data with different resolutions. In PVAE, the augmented feature pyramid is constructed layer by layer to fuse extracted features from low resolution to the high. As a consequence, the extracted features with various resolutions are gathered to form the regression model, where the process information contained in data with discrepant sampling rates can be fully utilized. Due to the layer-by-layer enhanced features, the prediction accuracy of the soft sensing model are gradually improved. Meanwhile, an optimized training strategy is established to select the optimal feature pyramid for prediction. A numerical experiment and an industrial soft sensing case are given to validate the effectiveness and superiority of the proposed MR-PVAE model.

Identification and analysis of DNA methylation-driven signatures for prognostic and immune microenvironments evaluation in hepatocellular carcinoma.

Liver cancer is the main reason of cancer deaths globally, with an unfavorable prognosis. DNA methylation is one of the epigenetic modifications and maintains the right adjustment of gene expression and steady gene silencing. We aim to explore the novel signatures for prognosis by using DNA methylation-driven genes. To acquire the DNA methylation-driven genes, we perform the difference analysis from the gene expression data and DNA methylation data in TCGA or GEO databases. And we obtain the 31 DNA methylation-driven genes. Subsequently, consensus clustering analysis was utilized to identify the molecular subtypes based on the 31 DNA methylation-driven genes. So, two molecular subtypes were identified to perform those analyses: Survival, immune cell infiltration, and tumor mutation. Results showed that two subtypes were clustered with distinct prognoses, tumor-infiltrating immune cell and tumor mutation burden. Furthermore, the 31 DNA methylation-driven genes were applied to perform the survival analysis to select the 14 survival-related genes. Immediately, a five methylation-driven genes risk model was built, and the patients were divided into high and low-risk groups. The model was established with TCGA as the training cohort and GSE14520 as the validation cohort. According to the risk model, we perform the systematical analysis, including survival, clinical feature, immune cell infiltration, somatic mutation status, underlying mechanisms, and drug sensitivity. Results showed that the high and low groups possessed statistical significance. In addition, the ROC curve was utilized to measure the accuracy of the risk model. AUCs at 1-year, 3-years, and 5-years were respectively 0.770, 0.698, 0.676 in training cohort and 0.717, 0.649, 0.621 in validation cohort. Nomogram was used to provide a better prediction for patients' survival. Risk score increase the accuracy of survival prediction in HCC patients. In conclusion, this study developed a novel risk model of five methylation-driven genes based on the comprehensive bioinformatics analysis, which accurately predicts the survival of HCC patients and reflects the immune and mutation features of HCC. This study provides novel insights for immunotherapy of HCC patients and promotes medical progress.

Identification and Analysis of Immune-Related Gene Signature in Hepatocellular Carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) originates from the hepatocytes and accounts for 90% of liver cancer. The study intends to identify novel prognostic biomarkers for predicting the prognosis of HCC patients based on TCGA and GSE14520 cohorts. METHODS: Differential analysis was employed to obtain the DEGs (Differentially Expressed Genes) of the TCGA-LIHC-TPM cohort. The lasso regression analysis was applied to build the prognosis model through using the TCGA cohort as the training group and the GSE14520 cohort as the testing group. Next, based on the prognosis model, we performed the following analyses: the survival analysis, the independent prognosis analysis, the clinical feature analysis, the mutation analysis, the immune cell infiltration analysis, the tumor microenvironment analysis, and the drug sensitivity analysis. Finally, the survival time of HCC patients was predicted by constructing nomograms. RESULTS: Through the lasso regression analysis, we obtained a prognosis model of ten genes including BIRC5 (baculoviral IAP repeat containing 5), CDK4 (cyclin-dependent kinase 4), DCK (deoxycytidine kinase), HSPA4 (heat shock protein family A member 4), HSP90AA1 (heat shock protein 90 α family class A member 1), PSMD2 (Proteasome 26S Subunit Ubiquitin Receptor, Non-ATPase 2), IL1RN (interleukin 1 receptor antagonist), PGF (placental growth factor), SPP1 (secreted phosphoprotein 1), and STC2 (stanniocalcin 2). First, we found that the risk score is an independent prognosis factor and is related to the clinical features of HCC patients, covering AFP (α-fetoprotein) and stage. Second, we observed that the p53 mutation was the most obvious mutation between the high-risk and low-risk groups. Third, we also discovered that the risk score is related to some immune cells, covering B cells, T cells, dendritic, macrophages, neutrophils, etc. Fourth, the high-risk group possesses a lower TIDE score, a higher expression of immune checkpoints, and higher ESTIMATE score. Finally, nomograms include the clinical features and risk signatures, displaying the clinical utility of the signature in the survival prediction of HCC patients. CONCLUSIONS: Through the comprehensive analysis, we constructed an immune-related prognosis model to predict the survival of HCC patients. In addition to predicting the survival time of HCC patients, this model significantly correlates with the tumor microenvironment. Furthermore, we concluded that these ten immune-related genes (BIRC5, CDK4, DCK, HSPA4, HSP90AA1, PSMD2, IL1RN, PGF, SPP1, and STC2) serve as novel targets for antitumor immunity. Therefore, this study plays a significant role in exploring the clinical application of immune-related genes.

A novel necroptosis-related lncRNA signature predicts the prognosis and immune microenvironment of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the malignant tumors with high mortality and a worse prognosis globally. Necroptosis is a programmed death mediated by receptor-interacting Protein 1 (RIP1), receptor-interacting Protein 1 (RIP3), and Mixed Lineage Kinase Domain-Like (MLKL). Our study aimed to create a new Necroptosis-related lncRNAs (NRlncRNAs) risk model that can predict survival and tumor immunity in HCC patients. The RNA expression and clinical data originated from the TCGA database. Pearson correlation analysis was applied to identify the NRlncRNAs. The LASSO-Cox regression analysis was employed to build the risk model. Next, the ROC curve and the area under the Kaplan-Meier curve were utilized to evaluate the accuracy of the risk model. In addition, based on the two groups of risk model, we performed the following analysis: clinical correlation, differential expression, PCA, TMB, GSEA analysis, immune cells infiltration, and clinical drug prediction analysis. Plus, qRT-PCR was applied to test the expression of genes in the risk model. Finally, a prognosis model covering six necroptosis-related lncRNAs was constructed to predict the survival of HCC patients. The ROC curve results showed that the risk model possesses better accuracy. The 1, 3, and 5-years AUC values were 0.746, 0.712, and 0.670, respectively. Of course, we also observed that significant differences exist in the following analysis, such as functional signaling pathways, immunological state, mutation profiles, and medication sensitivity between high-risk and low-risk groups of HCC patients. The result of qRT-PCR confirmed that three NRlncRNAs were more highly expressed in HCC cell lines than in the normal cell line. In conclusion, based on the bioinformatics analysis, we constructed an NRlncRNAs associated risk model, which predicts the prognosis of HCC patients. Although our study has some limitations, it may greatly contribute to the treatment of HCC and medical progression.

TRPC6 inhibits renal tubular epithelial cell pyroptosis through regulating zinc influx and alleviates renal ischemia-reperfusion injury.

Canonical transient receptor potential-6 (TRPC6) has been reported to be involved in cell damage after ischemia/reperfusion (I/R) injury in target organs. While the effect and of TRPC6 on pyroptosis in renal I/R injury remain unclear. In our study, we first established the renal I/R mouse model and oxygen-glucose deprivation and re-oxygenation (OGD/R) cell model, and investigated the impacts of TRPC6 on the pyroptosis-related proteins using CCK-8, western blot, ELISA, and immunofluorescence probes. Besides, we also explored the mechanism of TRPC6 in pyroptosis of renal tubular epithelial cells through A20 knockdown or overexpression and zinc chloride (ZnCl2 ) or a zinc ion chelator (TPEN) treatment. Our results indicated that I/R injury could cause downregulation of TRPC6 both in vivo and in vitro. In the I/R injury murine model, TRPC6 inhibition exacerbated tissue damage and upregulated NLRP3, ASC, caspase-1, IL-18, and IL-1ß, which could be alleviated by the administration of ZnCl2 . In the OGD/R cell model, inhibitor of TRPC6 (SAR7334) reduced zinc ion influx, aggravated cell death and upregulated pyroptosis-related protein. The pyroptosis phenotype also could be alleviated by ZnCl2 and intensified by TPEN. Overexpression of A20 reduced the expression of pyroptosis-related protein, increased cell viability in the sh-TRPC6 and TPEN-treated OGD/R cell models, while A20 deficiency impaired the protective effect of zinc ion. Therefore, our results indicate that TRPC6 could promote zinc ion influx in renal tubular epithelial cells, thereby upregulating intracellular A20, inhibiting the activation of inflammasome NLRP3, and ultimately attenuating renal I/R injury.

NAP1L1 Functions as a Novel Prognostic Biomarker Associated With Macrophages and Promotes Tumor Progression by Influencing the Wnt/ß-Catenin Pathway in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is regarded as one of the universal cancers in the world. Therefore, our study is based on clinical, molecular mechanism and immunological perspectives to analyze how NAP1L1 affects the progression of HCC. To begin with, the gene expression datasets and clinical data of GSE14520, GSE76427, ICGC, and TCGA are originated from GEO, ICGC, and TCGA databases. Subsequently, DEG screening was performed on data using R studio, and we finally found that 2,145 overlapping DEGs were screened from four datasets at the end. Then, we used R studio to filter the survival-related genes of the GSE76427 and ICGC datasets, and we screened out 101 survival-related genes. Finally, 33 common genes were screened out from 2,145 overlapping DEGs and 101 survival-related genes. Then, NAP1L1 was screened from 33 common genes using the CytoHubba plug-in in Cytoscape software. Furthermore, ground on GEO, ICGC, and TCGA databases, the survival analysis, clinical feature analysis, univariate/multivariate regression analysis, and multiple GSEA were used to study NAP1L1. The Conclusion claimed that HCC patients with higher expression levels of NAP1L1 had a poorer prognosis than those with lower expression levels. Thus, we believe that NAP1L1 is an independent prognostic factor for HCC. In order to shed light on NAP1L1's molecular mechanism promoting the progression of HCC closely, the GSEA tool was applied to complete the GSEA of the four datasets. Furthermore, the results confirmed that NAP1L1 could promote HCC progression by regulating the G2/M transition of the cell cycle and Wnt signaling pathway. Western blot and flow cytometry were also performed to understand those mechanisms in this study. The result of Western blot showed that NAP1L1 silencing led to downregulation of CDK1 and ß-catenin proteins; the result of flow cytometry showed that cell numbers in the G2 phase were significantly increased when NAP1L1 was silenced. Thus, we claimed that NAP1L1 might promote HCC progression by activating the Wnt signaling pathway and promoting cell cycle G2/M transition. In addition, ground on GSE14520 and GSE76427 datasets, and ICGC and TCGA databases, the correlation between NAP1L1 and immune cells was analyzed in HCC patients. At the same time, the TISIDB online database and the TIMER online database were testified to the association between NAP1L1 and immune cells. Hence, the summary shows that NAP1L1 was connected with a certain amount of immune cells. We can speculate that NAP1L1 may influence macrophages to promote HCC progression through some potential mechanisms.

Integrated Network Pharmacology and Metabolomics Analysis to Reveal the Potential Mechanism of Siwu Paste on Aplastic Anemia Induced by Chemotherapy Drugs.

Purpose: This study aimed to reveal the multicomponent synergy mechanisms of SWP based on network pharmacology and metabolomics for exploring the relationships of active ingredients, biological targets, and crucial metabolic pathways. Materials: Network pharmacology, including TRRUST, GO, and KEGG, enrichment was used to discover the active ingredients and potential regulation mechanisms of SWP. LC-MS and multivariate data analysis method were further applied to analyze serum metabolomics profiling for discovering the potential metabolic mechanisms of SWP on AA induced by Cyclophosphamide (CTX) and 1-Acetyl-2-phenylhydrazine (APH). Results: A total of 27 important bioactive ingredients meeting the ADME (absorption, distribution, metabolism, and excretion) screening criteria from SWP were selected. Interaction networks were constructed and validated based on the 10 associated ingredients with the relevant targets. A total of 125 biomarkers were found by Metabolomics approach, which associated with the development of AA, mainly involved in amino acid metabolism and lipid metabolism. While SWP can reverse the above 12 metabolites changed by AA. Network analysis revealed the synergistic effects of SWP through the 43 crucial pathways, including Sphingolipid signaling pathway, Sphingolipid metabolism, Arginine and proline metabolism, VEGF signaling pathway, Estrogen signaling pathway. Conclusion: The study suggested that SWP is a useful alternative for the treatment of AA induced by CTX + APH. Its potential mechanisms are to improve hematopoietic microenvironment and promote bone marrow hematopoiesis therapies.