Protective T Cell Responses Featured by Concordant Recognition of Middle East Respiratory Syndrome Coronavirus-Derived CD8+ T Cell Epitopes and Host MHC.

The coordinated recognition of virus-derived T cell epitopes and MHC molecules by T cells plays a pivotal role in cellular immunity-mediated virus clearance. It has been demonstrated that the conformation of MHC class I (MHC I) molecules can be adjusted by the presented peptide, which impacts T cell activation. However, it is still largely unknown whether the conformational shift of MHC I influences the protective effect of virus-specific T cells. In this study, utilizing the Middle East respiratory syndrome coronavirus-infected mouse model, we observed that through the unusual secondary anchor Ile5, a CD8+ T cell epitope drove the conformational fit of Trp73 on the α1 helix of murine MHC I H-2Kd In vitro renaturation and circular dichroism assays indicated that this shift of the structure did not influence the peptide/MHC I binding affinity. Nevertheless, the T cell recognition and the protective effect of the peptide diminished when we made an Ile to Ala mutation at position 5 of the original peptide. The molecular bases of the concordant recognition of T cell epitopes and host MHC-dependent protection were demonstrated through both crystal structure determination and tetramer staining using the peptide-MHC complex. Our results indicate a coordinated MHC I/peptide interaction mechanism and provide a beneficial reference for T cell-oriented vaccine development against emerging viruses such as Middle East respiratory syndrome coronavirus.

Detecting Succinylation sites from protein sequences using ensemble support vector machine.

BACKGROUND: Lysine succinylation is a new kind of post-translational modification which plays a key role in protein conformation regulation and cellular function control. To understand the mechanism of succinylation profoundly, it is necessary to identify succinylation sites in proteins accurately. However, traditional methods, experimental approaches, are labor-intensive and time-consuming. Computational prediction methods have been proposed recent years, and they are popular because of their convenience and high speed. In this study, we developed a new method to predict succinylation sites in protein combining multiple features, including amino acid composition, binary encoding, physicochemical property and grey pseudo amino acid composition, with a feature selection scheme (information gain). And then, it was trained using SVM (Support Vector Machine) and an ensemble learning algorithm. RESULTS: The performance of this method was measured with an accuracy of 89.14% and a MCC (Matthew Correlation Coefficient) of 0.79 using 10-fold cross validation on training dataset and an accuracy of 84.5% and a MCC of 0.2 on independent dataset. CONCLUSIONS: The conclusions made from this study can help to understand more of the succinylation mechanism. These results suggest that our method was very promising for predicting succinylation sites. The source code and data of this paper are freely available at https://github.com/ningq669/PSuccE .

Glypre: In Silico Prediction of Protein Glycation Sites by Fusing Multiple Features and Support Vector Machine.

Glycation is a non-enzymatic process occurring inside or outside the host body by attaching a sugar molecule to a protein or lipid molecule. It is an important form of post-translational modification (PTM), which impairs the function and changes the characteristics of the proteins so that the identification of the glycation sites may provide some useful guidelines to understand various biological functions of proteins. In this study, we proposed an accurate prediction tool, named Glypre, for lysine glycation. Firstly, we used multiple informative features to encode the peptides. These features included the position scoring function, secondary structure, AAindex, and the composition of k-spaced amino acid pairs. Secondly, the distribution of distinctive features of the residues surrounding the glycation and non-glycation sites was statistically analysed. Thirdly, based on the distribution of these features, we developed a new predictor by using different optimal window sizes for different properties and a two-step feature selection method, which utilized the maximum relevance minimum redundancy method followed by a greedy feature selection procedure. The performance of Glypre was measured with a sensitivity of 57.47%, a specificity of 90.78%, an accuracy of 79.68%, area under the receiver-operating characteristic (ROC) curve (AUC) of 0.86, and a Matthews's correlation coefficient (MCC) of 0.52 by 10-fold cross-validation. The detailed analysis results showed that our predictor may play a complementary role to other existing methods for identifying protein lysine glycation. The source code and datasets of the Glypre are available in the Supplementary File.

EPuL: An Enhanced Positive-Unlabeled Learning Algorithm for the Prediction of Pupylation Sites.

Protein pupylation is a type of post-translation modification, which plays a crucial role in cellular function of bacterial organisms in prokaryotes. To have a better insight of the mechanisms underlying pupylation an initial, but important, step is to identify pupylation sites. To date, several computational methods have been established for the prediction of pupylation sites which usually artificially design the negative samples using the verified pupylation proteins to train the classifiers. However, if this process is not properly done it can affect the performance of the final predictor dramatically. In this work, different from previous computational methods, we proposed an enhanced positive-unlabeled learning algorithm (EPuL) to the pupylation site prediction problem, which uses only positive and unlabeled samples. Firstly, we separate the training dataset into the positive dataset and the unlabeled dataset which contains the remaining non-annotated lysine residues. Then, the EPuL algorithm is utilized to select the reliably negative initial dataset and then iteratively pick out the non-pupylation sites. The performance of the proposed method was measured with an accuracy of 90.24%, an Area Under Curve (AUC) of 0.93 and an MCC of 0.81 by 10-fold cross-validation. A user-friendly web server for predicting pupylation sites was developed and was freely available at http://59.73.198.144:8080/EPuL.

[The molecular mechanism of interaction of trivalent dimethylarsinous acid (DMA(III)) binding to rat hemoglobin].

In our previous work, we found that trivalent dimethylarsinous acid (DMA(III)) have high affinity binding to cysteine residue 13 of rat hemoglobin. However, it is still unknown why arsenic intermediate metabolite DMA(III) has high binding affinity for Cysl3 but not for other cysteine residues 93, 140, 111 and 125. In order to better understand the molecular mechanism of DMA(III) with rat hemoglobin, we have done current study. So, SD rats were divided into control and arsenic-treated groups randomly. Arsenic species in lysate of red blood cells were analyzed by HPLC-ICP-MS, and then determined by a hybrid quadrupole TOF MS. In addition, trivalent DMA(III) binds to different cysteine residues in rat hemoglobin alpha and beta chains were also simulated by Molecular Docking. Only Cys13 in alpha chain is able to bind to DMA(III) from the experiment results. Cys13 of alpha chain in rat hemoglobin is a specific binding site for DMA(III), and we found that amino acids compose pockets structure and surround Cys13 (but not other cysteine residues), make DMA(III) much easy to bind cysteine 13. Taken together, the DMA(III) specific binding to Cys13 is related to spatial structure of Cys13.

The global burden of breast cancer in women from 1990 to 2030: assessment and projection based on the global burden of disease study 2019.

Background and aim: This study aims to analyze the worldwide prevalence, mortality rates, and disability-adjusted life years (DALYs) attributed to breast cancer in women between 1990 and 2019. Additionally, it seeks to forecast the future trends of these indicators related to the burden of breast cancer in women from 2020 to 2030. Methods: Data from the Global Burden of Disease Study (GBD) 2019 was analyzed to determine the age-standardized incidence rate (ASIR) and age-standardized death rate (ASDR) of DALYs due to breast cancer in women across 204 countries and territories from 1990 to 2019. Socio-economic development levels of countries and regions were assessed using Socio-demographic Indexes, and trends in the burden of breast cancer in women worldwide from 2020 to 2030 were projected using generalized additive models (GAMs). Results: The estimated annual percentage change (EAPC) in the ASIR breast cancer in women globally was 0.36 from 1990 to 2019 and is expected to increase to 0.44 from 2020 to 2030. In 2019, the ASIR of breast cancer in women worldwide was 45.86 and is projected to reach 48.09 by 2030. The burden of breast cancer in women generally rises with age, with the highest burden expected in the 45-49 age group from 2020 to 2030. The fastest increase in burden is anticipated in Central sub-Saharan Africa (EAPC in the age-standardized death rate: 1.62, EAPC in the age-standardized DALY rate: 1.52), with the Solomon Islands (EAPC in the ASIR: 7.25) and China (EAPC in the ASIR: 2.83) projected to experience significant increases. Furthermore, a strong positive correlation was found between the ASIR breast cancer in women globally in 1990 and the projected rates for 2030 (r = 0.62). Conclusion: The anticipated increase in the ASIR of breast cancer in women globally by 2030 highlights the importance of focusing on women aged 45-49 in Central sub-Saharan Africa, Oceania, the Solomon Islands, and China. Initiatives such as breast cancer information registries, raising awareness of risk factors and incidence, and implementing universal screening programs and diagnostic tests are essential in reducing the burden of breast cancer and its associated morbidity and mortality.

Optimizing the Sintering Conditions of (Fe,Co)1.95(P,Si) Compounds for Permanent Magnet Applications.

(Fe,Co)2(P,Si) quaternary compounds combine large uniaxial magnetocrystalline anisotropy, significant saturation magnetization and tunable Curie temperature, making them attractive for permanent magnet applications. Single crystals or conventionally prepared bulk polycrystalline (Fe,Co)2(P,Si) samples do not, however, show a significant coercivity. Here, after a ball-milling stage of elemental precursors, we optimize the sintering temperature and duration during the solid-state synthesis of bulk Fe1.85Co0.1P0.8Si0.2 compounds so as to obtain coercivity in bulk samples. We pay special attention to shortening the heat treatment in order to limit grain growth. Powder X-ray diffraction experiments demonstrate that a sintering of a few minutes is sufficient to form the desired Fe2P-type hexagonal structure with limited secondary-phase content (~5 wt.%). Coercivity is achieved in bulk Fe1.85Co0.1P0.8Si0.2 quaternary compounds by shortening the heat treatment. Surprisingly, the largest coercivities are observed in the samples presenting large amounts of secondary-phase content (>5 wt.%). In addition to the shape of the virgin magnetization curve, this may indicate a dominant wall-pining coercivity mechanism. Despite a tenfold improvement of the coercive fields for bulk samples, the achieved performances remain modest (HC ≈ 0.6 kOe at room temperature). These results nonetheless establish a benchmark for future developments of (Fe,Co)2(P,Si) compounds as permanent magnets.

Identification and verification of a PANoptosis-related long noncoding ribonucleic acid signature for predicting the clinical outcomes and immune landscape in lung adenocarcinoma.

PANoptosis is a type of programmed cell death (PCD) characterised by apoptosis, necroptosis and pyroptosis. Long non-coding ribonucleic acids (lncRNAs) are participating in the malignant behaviour of tumours regulated by PCD. Nevertheless, the function of PANoptosis-associated lncRNAs in lung adenocarcinoma remains to be investigated. In this work, a PANoptosis-related lncRNA signature (PRLSig) was developed based on the least absolute shrinkage and selection operator algorithm. The stability and fitness of PRLSig were confirmed by systematic evaluation of Kaplan-Meier, Cox analysis algorithm, receiver operating characteristic analysis, stratification analysis. In addition, ESTIMATE, single sample gene set enrichment analysis, immune checkpoints and the cancer immunome database confirmed the predictive value of the PRLSig in immune microenvironment and helped to identify populations for which immunotherapy is advantageous. The present research provides novel insights to facilitate risk stratification and optimise personalised treatment for LUAD.

Association between serum 25-hydroxyvitamin D level and inflammatory markers in hemodialysis-treated patients.

OBJECTIVE: To investigate the relationship between serum 25-hydroxyvitamin D (25(OH)D) level with novel inflammatory markers in hemodialysis-treated patients. METHODS: A total of 167 maintenance hemodialysis-treated patients were enrolled in this cross-sectional study. The patients were divided into vitamin D deficiency (a serum 25(OH)D level <20 ng/mL) and nondeficiency (a serum 25(OH)D level ≥20 ng/mL) groups. The neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and monocyte to lymphocyte ratio (MLR) were calculated by the complete blood cell count. The relationship between 25(OH)D level with other parameters was assessed by bivariate correlation analysis and linear regression analysis. RESULTS: There were significant differences between the two groups in terms of age, diabetes, levels of albumin, creatinine, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) as well as NLR and MLR (p = .004, p = .031, p < .001, p = .043, p = .008, p = .006, p = .002, and p < .001, respectively). There exist negative correlations between serum 25(OH)D level with age, diabetes, alkaline phosphatase level, NLR, PLR, and MLR (p = .002, p = .002, p = .037, p = .001, p = .041, and p < .001, respectively) and positive correlations between serum 25(OH)D level with albumin level, creatinine level, phosphorus level, HDL-C, and LDL-C (p < .001, p < .001, p = .013, p = .02, p = .002, respectively). Multiple analysis results showed that sex, diabetes, albumin level and NLR were independently associated with serum 25(OH)D level (p = .021, p = .015, p = .033, and p = .041, respectively). High values of NLR and MLR were associated with patients with serum 25(OH)D deficiency. There were negative interplays between serum 25(OH) D level with NLR, PLR, and MLR and also an independent association between serum 25(OH) D level with NLR. CONCLUSION: Collectively, serum 25(OH)D level has a negative correlation with inflammatory markers.

Comprehensive assessment of regulatory T-cells-related scoring system for predicting the prognosis, immune microenvironment and therapeutic response in hepatocellular carcinoma.

INTRODUCTION: Regulatory T cells (Tregs) play important roles in tumor immunosuppression and immune escape. The aim of the present study was to construct a novel Tregs-associated biomarker for the prediction of tumour immune microenvironment (TIME), clinical outcomes, and individualised treatment in hepatocellular carcinoma (HCC). METHODS: Single-cell sequencing data were obtained from the three independent cohorts. Cox and LASSO regression were utilised to develop the Tregs Related Scoring System (TRSSys). GSE140520, ICGC-LIRI and CHCC cohorts were used for the validation of TRSSys. Kaplan-Meier, ROC, and Cox regression were utilised for the evaluation of TRSSys. The ESTIMATE, TIMER 2.0, and ssGSEA algorithm were utilised to determine the value of TRSSys in predicting the TIME. GSVA, GO, KEGG, and TMB analyses were used for mechanistic exploration. Finally, the value of TRSSys in predicting drug sensitivity was evaluated based on the oncoPredict algorithm. RESULTS: Comprehensive validation showed that TRSSys had good prognostic predictive efficacy and applicability. Additionally, ssGSEA, TIMER and ESTIMATE algorithm suggested that TRSSys could help to distinguish different TIME subtypes and determine the beneficiary population of immunotherapy. Finally, the oncoPredict algorithm suggests that TRSSys provides a basis for individualised treatment. CONCLUSIONS: TRSSys constructed in the current study is a novel HCC prognostic prediction biomarker with good predictive efficacy and stability. Additionally, risk stratification based on TRSSys can help to identify the TIME landscape subtypes and provide a basis for individualized treatment options.

Association between weight-adjusted waist index and serum total testosterone in males aged 6-19 years in the United States: Data from NHANES 2013-2016.

Objective: This study aimed to estimate the association between weight-adjusted waist index and serum total testosterone (sTT) in males aged 6-19 years in the United States. Methods: A cross-sectional study was conducted using data from the National Health and Nutrition Examination Survey (NHANES) 2013-2016. sTT was considered as the response variable, and weight-adjusted waist circumference index (WWI) as the independent variable. Multiple linear regression was performed to estimate the association between the two variables, and subgroup analysis was performed to identify sensitive cohorts. Smoothing curve fitting and threshold effects analysis was carried out to assess possible nonlinear relationships between WWI and sTT. Results: The study included 4207 participants. The mean value of sTT (117.93 ng/dl) was used as the grouping basis, with 1066 participants having serum total testosterone levels above the mean. A negative association was observed between WWI and sTT [beta coefficient (ß) = -72.50, 95% confidence interval (CI): -79.45, -65.55], which decreased as WWI increased (P for trend<0.05). Subgroup analysis indicated a stronger negative correlation in late adolescent (16-19 years) males (ß = -128.94, 95% CI: -146.75, -111.13). The smoothing curve fit analysis revealed a U-shaped curve relationship for the negative correlation between WWI and sTT. Threshold effect analysis suggested a significant change when WWI exceeded 10.09 (ß = -15.82, 95% CI: -24.11, -7.54), and stepwise threshold effect analysis indicated that this negative correlation became less stable when WWI exceeded 11.45 (ß = -0.80, 95% CI: -9.15, 7.56). Conclusions: Participants with higher WWI exhibited lower total testosterone levels, and a negative association was found between WWI and total testosterone, particularly in late adolescent males aged 16-19 years. Among males aged 6-19 years, caution should be exercised regarding the risk of lower testosterone levels associated with elevated WWI, particularly when WWI is below 10.09.

Recombinant adenovirus-p53 (Gendicine) sensitizes a pancreatic carcinoma cell line to radiation.

OBJECTIVE: In this study, we examine the effects of recombinant adenovirus-p53 (rAd-p53) on the pancreatic carcinoma cell line SW1990. Specifically, we determine if expression of rAd-p53 sensitizes these cells to radiation. METHODS: Following transfection of SW1990 cells with rAd-p53, we measured expression of P53, P21 and Bax by immunocytochemistry. Both transfected and control cell lines were irradiated with a range of doses, and the survival fractions (SF) were calculated. Dose survival curves were constructed and modeled for comparison. RESULTS: Transfection of SW1990 cells with rAd-p53 resulted in increased expression of P53, P21 and Bax in a time-dependent manner. At 96 h after transfection, 89.92% of cells expressed P53, 56.8% expressed P21, and 76.50% expressed Bax. The SF following radiation was lower in the rAd-p53 transfected cells compared to the control cells, suggesting that rAd-p53 sensitizes SW1990 cells to radiation (D0 for the experimental and control groups was 2.199 and 2.462, respectively). CONCLUSIONS: Use of the adenoviral vector is an effective means of transfecting SW1990 cells with wild-type P53, and this sensitizes the cell line to irradiation. This work suggests that combining rAd-p53 with radiation therapy in pancreatic cancer may be therapeutically beneficial.

Identification and validation of a cancer-associated fibroblasts-related scoring system to predict prognosis and immune landscape in hepatocellular carcinoma through integrated analysis of single-cell and bulk RNA-sequencing.

BACKGROUND: Cancer-associated fibroblasts (CAFs) regulate the malignant biological behaviour of hepatocellular carcinoma (HCC) as a significant component of the tumour immune microenvironment (TIME). This study aimed to develop a CAFs-based scoring system to predict the prognosis and TIME of patients with HCC. METHODS: Data for the TCGA-LIHC and GSE14520 cohorts were downloaded from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Single-cell RNA-sequencing data for HCC samples were retrieved from the GSE166635 cohort. The Least Absolute Shrinkage and Selection Operator algorithm was employed to develop a CAFs-related scoring system (CAFRss). The predictive value of the CAFRss was determined using Kaplan-Meier, Cox regression and Receiver Operating Characteristic curves. Additionally, the TIMER platform, single sample Gene Set Enrichment Analysis and the Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data algorithms were performed to determine the TIME landscape. Finally, the pRRophic algorithm was utilised for drug sensitivity analysis. RESULTS: The evaluation of the CAFRss system demonstrated its superior ability to predict the clinical outcome of patients with HCC. Additionally, CAFRss effectively distinguished HCC populations with distinct TIME landscapes. Furthermore, CAFRss-based risk stratification identified individuals with immune 'hot tumours' and predicted the survival of patients treated with ICBs. CONCLUSIONS: The developed CAFRss can serve as a predictive tool for determining the clinical outcome of HCC and differentiating populations with diverse TIME characteristics.

An angiogenesis-related three-long non-coding ribonucleic acid signature predicts the immune landscape and prognosis in hepatocellular carcinoma.

The tumour microenvironment is a key determinant of the efficacy of immunotherapy. Angiogenesis is closely linked to tumour immunity. We aimed to screen long non-coding ribonucleic acids (lncRNAs) associated with angiogenesis to predict the prognosis of individuals with hepatocellular carcinoma (HCC) and characterise the tumour immune microenvironment (TIME). Patient data, including transcriptome and clinicopathological parameters, were retrieved from The Cancer Genome Atlas database. Moreover, co-expression algorithm was utilized to obtain angiogenesis-related lncRNAs. Additionally, survival-related lncRNAs were identified using Cox regression and the least absolute shrinkage and selection operator algorithm, which aided in constructing an angiogenesis-related lncRNA signature (ARLs). The ARLs was validated using Kaplan-Meier method, time-dependent receiver operating characteristic analyses, and Cox regression. Additionally, an independent external HCC dataset was used for further validation. Then, gene set enrichment analysis, immune landscape, and drug sensitivity analyses were implemented to explore the role of the ARLs. Finally, cluster analysis divided the entire HCC dataset into two clusters to distinguish different subtypes of TIME. This study provides insight into the involvement of angiogenesis-associated lncRNAs in predicting the TIME characteristics and prognosis for individuals with HCC. Furthermore, the developed ARLs and clusters can predict the prognosis and TIME characteristics in HCC, thereby aiding in selecting the appropriate therapeutic strategies involving immune checkpoint inhibitors and targeted drugs.

Thermodynamic and thermo-economic analyses of a coupled heat-pump system for low-grade exhaust-air heat exchange in mines.

Combining mine exhaust waste heat with existing heat pump technology is a promising technical route to realise the efficient extraction and scientific use of low-grade waste heat resources in mines and to solve the problem of insufficient heat supply in remote mining areas. This study proposes a new type of mine-exhaust-air heat exchange coupled with heat-pump waste-heat-utilisation system based on deep enthalpy heat extraction. Using a mining area in Northwest China as a representative case, this study establishes a systematic exergy analytical model and a thermo-economic model. Through an in-depth analysis of the different evaporation temperatures and condensing temperatures, the system's energy efficiency ratio (COP) reaches its optimal performance, with the total exergy efficiency surpassing 90%. The minimum efficiency of the subsystem return air heat exchanger is 35%. The unit thermal costs of the mine exhaust air waste heat utilisation system and a conventional coal-fired boiler system are 0.1291 and 0.1573 million RMB/kW·h, respectively. This is a thermal economics cost saving of 21%. The studied system demonstrates great economic viability and the potential for energy saving throughout its life cycle.

Exosomal miRNA-profiling of pleural effusion in lung adenocarcinoma and tuberculosis.

Background: Pleural effusion (PE) caused by lung cancer is prevalent, and it is difficult to differentiate it from PE caused by tuberculosis. Exosome-based liquid biopsy offers a non-invasive technique to diagnose benign and malignant PE. Exosomal miRNAs are potential diagnostic markers and play an essential role in signal transduction and biological processes in tumor development. We hypothesized that exosomal miRNA expression profiles in PE would contribute to identifying its diagnostic markers and elucidating the molecular basis of PE formation in lung cancer. Methods: The exosomes from PE caused by lung adenocarcinoma (LUAD) and pulmonary tuberculosis were isolated and verified by transmission electron microscopy. The exosomal miRNA profiles were identified using deep sequencing and validated with quantitative real-time PCR (qRT-PCR). We performed bioinformatic analysis for differentially expressed miRNAs to explore how exosomal miRNAs regulate pleural effusion. Results: We identified 99 upregulated and 91 downregulated miRNAs in malignant pleural effusion (MPE) compared to tuberculous pleural effusion (TPE). Seven differentially expressed miRNAs (DEmiRNAs) were validated by qRT-PCR, out of which 5 (71.4%) were confirmed through sequencing. Gene Ontology (GO) analysis revealed that most exosomal miRNAs target genes were involved in regulating cellular processes and nitrogen compound metabolism. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, the exosomal miRNAs target genes were mainly involved in Fc gamma R-mediated phagocytosis, Rap1 signaling pathway, and breast cancer. The hub genes, including ITGAM, FOXO1, MAPK14, YWHAB, GRIN1, and PRF1, were screened through plug-in cytoHubba. The PFR1 was identified as a critical gene in MPE formation using single-cell sequencing analysis. Additionally, we hypothesized that tumor cells affected natural killer cells and promoted the generation of PE in LUAD via the exosomal hsa-miR-3120-5p-PRF1 axis. Conclusions: We identified exosomal miRNA profiles in LUAD-MPE and TPE, which may help in the differential diagnosis of MPE and TPE. Bioinformatic analysis revealed that these miRNAs might affect PE generation through tumor immune response in LUAD. Our results provided a new theoretical basis for understanding the function of exosomal miRNAs in LUAD-MPE.

The efficacy and safety of an improved percutaneous peritoneal dialysis catheter placement technique in urgent-start peritoneal dialysis patients: a retrospective cohort study.

BACKGROUND: Urgent-start peritoneal dialysis has high catheterization skill requirements and that early complications. The optimal catheter placement method remains debatable in urgent-start peritoneal dialysis patients. Safe and effective peritoneal dialysis catheterization is needed in clinical work. METHODS: We retrospectively analyzed the data of 34 patients diagnosed with end-stage renal disease who opt for peritoneal dialysis, 19 males and 15 females, with an average age of 62.3±14.7 years, peritoneal dialysis catheter implantation was completed by the improved percutaneous catheterization technique. They were followed for 6 months, early and late complications were observed and the survival rate of the catheter technique was calculated. RESULTS: All 34 patients diagnosed with end-stage renal disease successfully underwent catheter placement using the improved percutaneous technique; the catheterization success rate was 100%. No severe organ injuries, such as intestinal perforation and bladder perforation, occurred intraoperatively. Peritoneal dialysis was started immediately after surgery. The early complications included one case of leakage, one case of omental wrapping, and six cases of rectus abdominis hemorrhage. The late complications included one case of pleuro-abdominal fistula and two cases of peritonitis. The 6-month technical survival rate for the catheter was 94.1% (32/34). Compared to previously reported studies, this technique may reduce leakage and early catheter dysfunction, and improve the technical survival of catheters. CONCLUSIONS: The improved percutaneous peritoneal dialysis catheter placement technique might be an effective and safe method for urgent­start peritoneal dialysis patients.

Construction of a Necroptosis-Associated Long Non-Coding RNA Signature to Predict Prognosis and Immune Response in Hepatocellular Carcinoma.

Background: Necroptosis is a form of programmed cell death, and studies have shown that long non-coding RNA molecules (lncRNAs) can regulate the process of necroptosis in various cancers. We sought to screen lncRNAs associated with necroptosis to predict prognosis and tumor immune infiltration status in patients with hepatocellular carcinoma (HCC). Methods: Transcriptomic data from HCC tumor samples and normal tissues were extracted from The Cancer Genome Atlas database. Necroptosis-associated lncRNAs were obtained by co-expression analysis. Necroptosis-associated lncRNAs were then screened by Cox regression and least absolute shrinkage and selection operator methods to construct a risk model for HCC. The models were also validated and evaluated by Kaplan-Meier analysis, univariate and multivariate Cox regression, and time-dependent receiver operating characteristic (ROC) curves. In addition, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes enrichment, gene set enrichment, principal component, immune correlation, and drug sensitivity analyses were applied to assess model risk groups. To further differentiate the immune microenvironment of different HCC subtypes, the entire dataset was divided into three clusters, based on necroptosis-associated lncRNAs, and a series of analyses performed. Results: We constructed a model comprising four necroptosis-associated lncRNAs: POLH-AS1, DUXAP8, AC131009.1, and TMCC1-AS1. Overall survival (OS) duration was significantly longer in patients classified as low-risk than those who were high-risk, according to our model. Univariate and multivariate Cox regression analyses further confirmed risk score stability. The analyzed models had area under the ROC curve values of 0.786, 0.713, and 0.639 for prediction of 1-, 3-, and 5-year OS, respectively, and risk score was significantly associated with immune cell infiltration and ESTIMATE score. In addition, differences between high and low-risk groups in predicted half-maximal inhibitory concentration values for some targeted and chemical drugs, providing a potential basis for selection of treatment approach. Finally, cluster analysis facilitated more refined differentiation of the immune microenvironment in patients with HCC and may allow prediction of the effectiveness of immune checkpoint inhibitors. Conclusions: This study contributes to understanding of the function of necroptosis-related lncRNAs in predicting the prognosis and immune infiltration status of HCC. The risk model constructed and cluster analysis provide a basis for predicting the prognosis of patients with HCC and to inform the selection of immunotherapeutic strategies.

Long-term efficacy, safety, and medication compliance of roxadustat on peritoneal dialysis patients with renal anemia affected by the COVID-19 pandemic: a retrospective study.

BACKGROUND: Current studies have limited data on long-term treatment safety and medication compliance of roxadustat for renal anemia in peritoneal dialysis (PD) patients. We aimed to analyze the long-term efficacy, safety, and medication compliance of roxadustat in the treatment of renal anemia in patients with PD who discontinued recombinant human erythropoietin (rhEPO) treatment due to the corona virus disease 2019 (COVID-19) outbreak. METHODS: We retrospectively collected patients who were switched from rhEPO to roxadustat in our hospital due to the pandemic. The criteria for subject inclusion: aged >18 years with a dialysis vintage >3 months, without malignant tumor, no severe cardiovascular and cerebrovascular diseases, and not combined hemodialysis. Patients were followed up until the end of December 2021. Hemoglobin (Hb), red blood cell (RBC) and hematocrit (Hct) were recorded at baseline, month 1-12 and month 20, and iron parameters at baseline, 3, 6, 9, 12, and 20 months were collected. The Morisky Medication Adherence Scale-8 (MMAS-8) was used to score medication compliance during rhEPO treatment and roxadustat treatment, and adverse reactions occurred during treatment were collected. The efficacy and medication compliance of roxadustat were analyzed using Wilcoxon rank sum test or t-test. RESULTS: The median follow-up time was 21.1 (20.6, 21.7) months. After 1 month of treatment, the Hb level was significantly increased by 9.4 g/L (95% CI: 6.0-12.8 g/L) compared with the baseline, follow up at 20 months showed the Hb level had remained stable, increased by 20.7 g/L (95% CI: 15.9-25.4 g/L) compared with before treatment. At the beginning of treatment, total iron binding capacity increased, transferrin saturation and serum ferritin decreased, serum iron remained stable during treatment. During roxadustat treatment, no patient discontinued treatment due to the pandemic, and the Morisky score was improved compared with that during rhEPO treatment [5.75 (4.25, 6.00) vs. 6.75 (5.75, 7.00), P=0.000]. There were no serious adverse events associated with roxadustat were observed. CONCLUSIONS: Roxadustat can effectively improve anemia and had good tolerance in patients undergoing PD who have difficult using rhEPO, and the medication compliance was better than rhEPO during the COVID-19.

The predictive value of coronary artery calcification score combined with bone mineral density for the 2-year risk of cardiovascular events in maintenance hemodialysis patients.

PURPOSE: Cardiovascular disease is the leading cause of death in maintenance hemodialysis (MHD) patients. The aim of this study is to investigate the predictive value of coronary artery calcification score (CACs) combined with bone mineral density (BMD) for the risk of cardiovascular diseases in MHD patients. METHODS: From January 2017 to January 2019, we enrolled 112 MHD patients and 112 controls in Ningbo First Hospital, and retrospectively counted the cardiovascular events in the next 2 years after enrollment. According to the occurrence of cardiovascular events, the MHD patients were divided into CVD group and non-CVD group. The differences of vertebral BMD and CACs between the two groups were compared. ROC curve, Kaplan-Meier curve and Cox regression analyses were used for assess the predictive value of 2-year cardiovascular events in MHD patients. RESULTS: Among 112 MHD patients, 49 (43.75%) patients had cardiovascular events. The results showed that the average value of BMD in MHD patients was significantly lower than that in the control group (99.88 ± 30.99 VS. 108.35 ± 23.98, P = 0.0231). The CACs in MHD patients were significantly higher than that in the control group (317.81 ± 211.53 VS. 190.03 ± 100.50, P < 0.001). The results between CVD group and the non-CVD group were to the same direction (BMD: 81.12 ± 31.28 VS. 114.48 ± 21.61, P < 0.001; CACs: 447.16 ± 234.11 VS. 217.21 ± 119.03, P < 0.001). Besides, CACs combined with BMD yield an AUC of 0.875 with a sensitivity of 79.60%, a specificity of 82.50%. Kaplan-Meier curve and Cox regression analyses indicated that CACs and BMD were independently associated with high risk of cardiovascular events in MHD patients. CONCLUSION: The combination of CACs and vertebral BMD could predict the occurrence of cardiovascular events in MHD patients to some extent.