Roxadustat Versus Erythropoietin: The Comparison of Efficacy in Reversing Ventricular Remodeling in Dialysis Patients with Anaemia.

Background: Renal anaemia and left ventricular hypertrophy are the main complications of chronic kidney disease and are shared among dialysis patients. This retrospective study aimed to compare the efficacies of the hypoxia-inducible factor prolyl hydroxylase inhibitor roxadustat and recombinant human erythropoietin in reversing ventricular remodeling in dialysis patients with renal anaemia. Methods: A total of 204 participants underwent baseline examinations, including echocardiograms and laboratory tests, before being administered either treatment for at least 24 weeks from January 2018 to October 2021, after which follow-up examinations were conducted at 6 months. Propensity score matching based on key variables included age, gender, cardiovascular diseases, cardiovascular medications, dialysis course and the vascular access at baseline was performed to include populations with similar characteristics between groups. Results: In total, 136 patients were included with roxadustat or recombinant human erythropoietin. The left ventricular mass index after treatment with roxadustat and recombinant human erythropoietin both significantly decreased after 6 months, but there was no significant difference in the change in left ventricular mass index between the two groups. In addition, the left ventricular end-diastolic diameters and left ventricular wall thickness, systolic blood pressure, and diastolic blood pressure significantly decreased in the roxadustat group. Roxadustat and recombinant human erythropoietin also increased haemoglobin significantly, but there was no significant difference in the change in haemoglobin between the two groups. The results of multiple linear regression showed that the change in haemoglobin was independent factor affecting the improvement of left ventricular mass index. Conclusions: The increase of haemoglobin was associated with improving left ventricular hypertrophy in dialysis patients. However, the beneficial effects between roxadustat and recombinant human erythropoietin on left ventricular mass index did not show clear superiority or inferiority in six months.

The ratio of neutrophils to lymphocytes effectively predicts clinical outcomes in idiopathic membranous nephropathy.

BACKGROUND: Systemic inflammatory indicators are important in the prognoses of various diseases. Such indicators, including the neutrophil-to-lymphocyte ratio (NLR), can be meaningful in predicting the clinical outcome in patients diagnosed with idiopathic membranous nephropathy (IMN). MATERIALS AND METHODS: 112 IMN patients diagnosed by renal biopsy were recruited retrospectively. The endpoint was defined as a combination of partial and complete remission. Statistical analysis determined the independent factors associated with clinical remission and the predictive utility of NLR. RESULTS: Within the 12-month follow-up period, 72 patients achieved clinical remission after treatment. Univariate analysis identified significant differences in serum albumin, estimated glomerular filtration rate (eGFR), proteinuria, neutrophil count, and NLR between the remission group and the non-remission group (all p < 0.05). Cox proportional hazards indicated that elevated eGFR (HR 1.022, 95% CI (1.009 - 1.035), p = 0.001), lower NLR (HR 0.345, 95% CI (0.237 - 0.501), p = 0.0001), and decreased proteinuria (HR 0.826, 95% CI (0.693 - 0.984), p = 0.032) were protective elements for remission. With an optimal cut-off value of 2.61, the pre-treatment NLR had an excellent ability to identify the remission (area under the curve (AUC), 0.785). Participants were separated into low- and high-NLR groups by using 2.61. Kaplan-Meier survival curves revealed significantly higher remission rates in the lower group (p < 0.0001). CONCLUSION: The NLR is an effective indicator for predicting clinical remission in patients with IMN.

Application of cloud server-based machine learning for assisting pathological structure recognition in IgA nephropathy.

BACKGROUND: Machine learning (ML) models can help assisting diagnosis by rapidly localising and classifying regions of interest (ROIs) within whole slide images (WSIs). Effective ML models for clinical decision support require a substantial dataset of 'real' data, and in reality, it should be robust, user-friendly and universally applicable. METHODS: WSIs of primary IgAN were collected and annotated. The H-AI-L algorithm which could facilitate direct WSI viewing and potential ROI detection for clinicians was built on the cloud server of matpool, a shared internet-based service platform. Model performance was evaluated using F1-score, precision, recall and Matthew's correlation coefficient (MCC). RESULTS: The F1-score of glomerular localisation in WSIs was 0.85 and 0.89 for the initial and pretrained models, respectively, with corresponding recall values of 0.79 and 0.83, and precision scores of 0.92 and 0.97. Dichotomous differentiation between global sclerotic (GS) and other glomeruli revealed F1-scores of 0.70 and 0.91, and MCC values of 0.55 and 0.87, for the initial and pretrained models, respectively. The overall F1-score of multiclassification was 0.81 for the pretrained models. The total glomerular recall rate was 0.96, with F1-scores of 0.68, 0.56 and 0.26 for GS, segmental glomerulosclerosis and crescent (C), respectively. Interstitial fibrosis/tubular atrophy lesion similarity between the true label and model predictions was 0.75. CONCLUSIONS: Our results underscore the efficacy of the ML integration algorithm in segmenting ROIs in IgAN WSIs, and the internet-based model deployment is in favour of widespread adoption and utilisation across multiple centres and increased volumes of WSIs.

Indole produced during dysbiosis mediates host-microorganism chemical communication.

An imbalance of the gut microbiota, termed dysbiosis, has a substantial impact on host physiology. However, the mechanism by which host deals with gut dysbiosis to maintain fitness remains largely unknown. In Caenorhabditis elegans, Escherichia coli, which is its bacterial diet, proliferates in its intestinal lumen during aging. Here, we demonstrate that progressive intestinal proliferation of E. coli activates the transcription factor DAF-16, which is required for maintenance of longevity and organismal fitness in worms with age. DAF-16 up-regulates two lysozymes lys-7 and lys-8, thus limiting the bacterial accumulation in the gut of worms during aging. During dysbiosis, the levels of indole produced by E. coli are increased in worms. Indole is involved in the activation of DAF-16 by TRPA-1 in neurons of worms. Our finding demonstrates that indole functions as a microbial signal of gut dysbiosis to promote fitness of the host.

Outer membrane vesicles derived from gut microbiota mediate tubulointerstitial inflammation: a potential new mechanism for diabetic kidney disease.

Rationale: Chronic tubulointerstitial inflammation is a common pathological process in diabetic kidney disease (DKD). However, its underlying mechanism is largely unknown. This study aims at investigating the role of gut microbiota-derived outer membrane vesicles (OMVs) in tubulointerstitial inflammation in DKD. Methods: Gut microbiota in diabetes mellitus rats was manipulated by microbiota depletion and fecal microbiota transplantation to explore its role in tubulointerstitial inflammation. To check the direct effects of OMVs, fecal bacterial extracellular vesicles (fBEVs) were administrated to mice orally and HK-2 cells in vitro. For mechanistic investigations, HK-2 cells were treated with small interfering RNA against caspase-4 and fBEVs pre-neutralized by polymyxin B. Results: By performing gut microbiota manipulation, it was confirmed that gut microbiota mediated tubulointerstitial inflammation in DKD. In diabetic rats, gut microbiota-derived OMVs were increased and were clearly detected in distant renal tubulointerstitium. Diabetic fBEVs directly administered by gavage translocated into tubular epithelial cells and induced tubulointerstitial inflammation and kidney injury. In vitro, OMVs were internalized through various endocytic pathways and triggered cellular inflammatory response. Mechanistically, it was revealed that OMVs-derived lipopolysaccharide induced tubular inflammation, which was mediated by the activation of the caspase-11 pathway. Conclusions: Increased OMVs due to dysbiosis translocated through leaky gut barrier into distant tubulointerstitium and induced cellular inflammation and renal tubulointerstitial injury in DKD. These findings enrich the mechanism understanding of how gut microbiota and its releasing OMVs influence the development and progression of kidney disease.

The EGL-30 pathway regulates experience-dependent aversive behavior of Caenorhabditis elegans to the pathogenic bacterium Pseudomonas aeruginosa.

Avoidance of harmful substances is survival strategy used cross invertebrates and vertebrates. For example, the nematode Caenorhabditis elegans evolves a sufficient avoidance response to pathogenic bacteria. Despite G protein has been found to exert neural plasticity for avoidance behaviours in C. elegans, the function of Gi/o and Gq subunit signalling in experience-dependent aversive behaviour remains unclear. In this study, we show that EGL-30/Gq coupled with EGL-8/UNC-13 regulates aversive behaviour of C. elegans to pathogenic bacterium Pseudomonas aeruginosa PA01 via acetylcholine and its receptor nAChR. Pyocyanin, a toxin secreted from P. aeruginosa, acts as a signal molecule to trigger aversive behaviour. ODR-3 and ODR-7 in AWA and AWC neurons function as upstream of EGL-30 to induce experience-dependent aversive behaviour to P. aeruginosa, respectively. These results suggested that a novel signalling pathway to regulate a behavioural response.

Using a machine learning model to predict the development of acute kidney injury in patients with heart failure.

Background: Heart failure (HF) is a life-threatening complication of cardiovascular disease. HF patients are more likely to progress to acute kidney injury (AKI) with a poor prognosis. However, it is difficult for doctors to distinguish which patients will develop AKI accurately. This study aimed to construct a machine learning (ML) model to predict AKI occurrence in HF patients. Materials and methods: The data of HF patients from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database was retrospectively analyzed. A ML model was established to predict AKI development using decision tree, random forest (RF), support vector machine (SVM), K-nearest neighbor (KNN), and logistic regression (LR) algorithms. Thirty-nine demographic, clinical, and treatment features were used for model establishment. Accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUROC) were used to evaluate the performance of the ML algorithms. Results: A total of 2,678 HF patients were engaged in this study, of whom 919 developed AKI. Among 5 ML algorithms, the RF algorithm exhibited the highest performance with the AUROC of 0.96. In addition, the Gini index showed that the sequential organ function assessment (SOFA) score, partial pressure of oxygen (PaO2), and estimated glomerular filtration rate (eGFR) were highly relevant to AKI development. Finally, to facilitate clinical application, a simple model was constructed using the 10 features screened by the Gini index. The RF algorithm also exhibited the highest performance with the AUROC of 0.95. Conclusion: Using the ML model could accurately predict the development of AKI in HF patients.

Intestinal microbiota-derived membrane vesicles and their role in chronic kidney disease.

Intestinal microbiota-derived membrane vesicles (MVs) play essential roles in immunomodulation and maintenance of the intestinal micro-ecosystem. The relationship between MVs and chronic kidney disease (CKD) has remained undefined. This review provides a survey of the structure and biological function of different vesicle types and summarizes the possible pathogenic mechanisms mediated by MVs, which may be of great clinical significance in the diagnosis and treatment of chronic kidney disease.

Antioxidant response is a protective mechanism against nutrient deprivation in C. elegans.

Animals often experience periods of nutrient deprivation; however, the molecular mechanisms by which animals survive starvation remain largely unknown. In the nematode Caenorhabditis elegans, the nuclear receptor DAF-12 acts as a dietary and environmental sensor to orchestrate diverse aspects of development, metabolism, and reproduction. Recently, we have reported that DAF-12 together with co-repressor DIN-1S is required for starvation tolerance by promoting fat mobilization. In this report, we found that genetic inactivation of the DAF-12 signaling promoted the production of reactive oxygen species (ROS) during starvation. ROS mediated systemic necrosis, thereby inducing organismal death. The DAF-12/DIN-1S complex up-regulated the expression of antioxidant genes during starvation. The antioxidant enzyme GST-4 in turn suppressed ROS formation, thereby conferring worm survival. Our findings highlight the importance of antioxidant response in starvation tolerance and provide a novel insight into multiple organisms survive and adapt to periods of nutrient deprivation.

GPH1 is involved in glycerol accumulation in the three-dimensional networks of the nematode-trapping fungus Arthrobotrys oligospora.

Turgor is very important for the invasive growth of fungal pathogens. Glycerol, a highly osmotic solvent, is considered to play an important role in turgor generation. The nematophagous fungus Arthrobotrys oligospora mainly lives as a saprophyte. In the presence of nematodes, A. oligospora enters the parasitic stage by forming three-dimensional networks (traps) to capture nematodes. In A. oligospora, we found that glycerol accumulated during nematode-induced trap formation. We demonstrated that deleting gph1, which encodes glycogen phosphorylase, decreased the glycerol content, compared with that of a wild-type strain. Although the number of traps induced by nematodes was not affected in the Δgph1 mutant, the capture rate was lower. Meanwhile, deleting gph1 also affected the growth rate and conidiation capacity of the fungus. These results indicate that glycerol derived from GPH1 is essential for the full virulence of A. oligospora against nematodes.

Systematic analyses reveal uniqueness and origin of the CFEM domain in fungi.

CFEM domain commonly occurs in fungal extracellular membrane proteins. To provide insights for understanding putative functions of CFEM, we investigate the evolutionary dynamics of CFEM domains by systematic comparative genomic analyses among diverse animals, plants, and more than 100 fungal species, which are representative across the entire group of fungi. We here show that CFEM domain is unique to fungi. Experiments using tissue culture demonstrate that the CFEM-containing ESTs in some plants originate from endophytic fungi. We also find that CFEM domain does not occur in all fungi. Its single origin dates to the most recent common ancestors of Ascomycota and Basidiomycota, instead of multiple origins. Although the length and architecture of CFEM domains are relatively conserved, the domain-number varies significantly among different fungal species. In general, pathogenic fungi have a larger number of domains compared to other species. Domain-expansion across fungal genomes appears to be driven by domain duplication and gene duplication via recombination. These findings generate a clear evolutionary trajectory of CFEM domains and provide novel insights into the functional exchange of CFEM-containing proteins from cell-surface components to mediators in host-pathogen interactions.

Inhibition Effects of Some Bioactive Peroxovanadium Complexes on the Tyrosine Phosphatase.

In order to study the structure-activity relationship and molecular mechanism of insulin-mimetic peroxovanadium complexes, the low-molecular-weight BHPTPase from bovine heart has been purified mainly by chromatography of DEAE-cellulose and Sephadex G-75, which was showed homogenicity on SDS-PAGE. Four bioactive peroxovanadium(pV) complexes bpV(ox), bpV(bipy), bpV(phen) and bpV(pic), [VO(O(2))(2)L](n-), where L = oxalic acid dianion(ox), bipyridine(bipy), 1,10-phenanthroline(phen), pyridine-2-carboxylic acid(pic) have been synthesized the bonding properties of center metal and its ligand were characterized by (51)V NMR, (13)C NMR, IR and elemental analysis. The complexes displayed remarkable inhibitory effects on the bovine heart tyrosine phosphatase. Their IC(50) were 0.22, 0.36 and 0.90 and 0.28 &mgr;mol/L, respectively. The structure-activity relationship of the complexes were discussed by their oxidizing ability and through the steric space hindrance of the organic ligands.