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Objective To explore the predictive value of the proportion of glomerulosclerosis (GS) incidences on the progression of membranous nephropathy with non-nephrotic proteinuria (NNP).Methods This study was a single-center, retrospective, cohort study. Patients with biopsy-proven idiopathic membranous nephropathy were divided into three groups based on the proportion of glomerular sclerosis, and their demographic, clinical, and pathological data were compared. The proportions of primary and secondary endpoints were recorded, and the relationship between GS and primary outcomes (progression to nephrotic syndrome, complete remission, and persistent NNP) and the renal composite endpoint was analyzed.Results A total of 112 patients were divided into three groups according to the proportions of glomerulosclerosis. The median follow-up time was 26.5 (13–51) months. There were significant differences in blood pressure (p

Introduction Renal osteodystrophy (ROD) is a type of bone metabolic disorder in patients with chronic kidney disease (CKD). Inflammation is associated with bone loss in ROD. However, its precise mechanism has not yet been elucidated. The present study was conducted to investigate whether exosomes (Exos) in bone marrow (BM) are involved in the pathogenesis of high-turnover ROD.Methods Bone mass, osteoclast number, and pro-inflammatory cytokines levels of BM supernatant were detected in adenine-induced ROD rats. The effect of Exos derived from BM (BM-Exos) of ROD (ROD-Exos) on inflammatory genes and osteoclast differentiation of BM-derived macrophages (BMMs) were further examined. Then, exosomal miRNA sequencing was performed and an miRNA-mRNA-pathway network was constructed.Results we found increased osteoclasts and decreased bone mass in ROD rats, as well as inflammatory activation in the BM niche. Furthermore, BMMs from ROD rats displayed overproduction of proinflammatory cytokines and increased osteoclast differentiation, accompanied by nuclear factor κB (NF-κB) signaling activation. Mechanistically, we found that ROD-Exos activates NF-κB signaling to promote the release of proinflammatory cytokines and increase osteoclast differentiation of BMMs. Meanwhile, a total of 24 differentially expressed miRNAs were identified between BM-Exos from ROD and normal control (NC). The miRNA-mRNA-pathway network suggests that rno-miR-9a-5p, rno-miR-133a-3p, rno-miR-30c-5p, rno-miR-206-3p, and rno-miR-17-5p might play pivotal roles in inflammation and osteoclast differentiation. Additionally, we validated that the expression of miR-9a-5p is upregulated in ROD-Exos.Conclusion The BM niche of ROD alters the miRNA cargo of BM-Exos to promote inflammation and osteoclast differentiation of BMMs, at least partially contributing to the pathogenesis of high-turnover ROD.

Two-stage remote sensing image captioning (RSIC) methods have achieved promising results by incorporating additional pre-trained remote sensing tasks to extract supplementary information and improve caption quality. However, these methods face limitations in semantic comprehension, as pre-trained detectors/classifiers are constrained by predefined labels, leading to an oversight of the intricate and diverse details present in remote sensing images (RSIs). Additionally, the handling of auxiliary remote sensing tasks separately can introduce challenges in ensuring seamless integration and alignment with the captioning process. To address these problems, we propose a novel cross-modal retrieval and semantic refinement (CRSR) RSIC method. Specifically, we employ a cross-modal retrieval model to retrieve relevant sentences of each image. The words in these retrieved sentences are then considered as primary semantic information, providing valuable supplementary information for the captioning process. To further enhance the quality of the captions, we introduce a semantic refinement module that refines the primary semantic information, which helps to filter out misleading information and emphasize visually salient semantic information. A Transformer Mapper network is introduced to expand the representation of image features beyond the retrieved supplementary information with learnable queries. Both the refined semantic tokens and visual features are integrated and fed into a cross-modal decoder for caption generation. Through extensive experiments, we demonstrate the superiority of our CRSR method over existing state-of-the-art approaches on the RSICD, the UCM-Captions, and the Sydney-Captions datasets

Abstract Background The prevalence of idiopathic membranous nephropathy (IMN) is increasing worldwide and the gut microbiota is recognized to play a role in its pathology. The aim of this study was to understand the involvement of the gut–kidney axis in IMN by analyzing the composition of the gut microbiota of biopsy-proven IMN patients compared with healthy controls (HC). Methods Fecal samples from 30 patients with IMN diagnosed by renal biopsy and 30 healthy co-residents (control group) were collected for analysis in the Nephrology Department of the Second Affiliated Hospital of Harbin Medical University. The microbiota composition was analyzed by a 16S rRNA microbial profiling approach. Results The results indicated that the α- and β-diversity of IMN patients differed significantly from those of the HC groups (P 2). Abundant bacterial functions related to lipid metabolism were observed among IMN group. Conclusion Patients with IMN appear to have an altered gut microbiome, which could provide reference for future research on the interaction mechanism between the intestinal flora and IMN.

Chronic kidney disease (CKD) is a global public health problem, and cardiovascular disease is the most common cause of death in patients with CKD. The incidence and prevalence of cardiovascular events during the early stages of CKD increases significantly with a decline in renal function. More than 50% of dialysis patients die from cardiovascular disease, including coronary heart disease, heart failure, arrhythmia, and sudden cardiac death. Therefore, developing effective methods to control risk factors and improve prognosis is the primary focus during the diagnosis and treatment of CKD. For example, the SPRINT study demonstrated that CKD drugs are effective in reducing cardiovascular and cerebrovascular events by controlling blood pressure. Uncontrolled blood pressure not only increases the risk of these events but also accelerates the progression of CKD. A co-crystal complex of sacubitril, which is a neprilysin inhibitor, and valsartan, which is an angiotensin receptor blockade, has the potential to be widely used against CKD. Sacubitril inhibits neprilysin, which further reduces the degradation of natriuretic peptides and enhances the beneficial effects of the natriuretic peptide system. In contrast, valsartan alone can block the angiotensin II-1 (AT1) receptor and therefore inhibit the renin–angiotensin–aldosterone system. These two components can act synergistically to relax blood vessels, prevent and reverse cardiovascular remodeling, and promote natriuresis. Recent studies have repeatedly confirmed that the first and so far the only angiotensin receptor–neprilysin inhibitor (ARNI) sacubitril/valsartan can reduce blood pressure more effectively than renin–angiotensin system inhibitors and improve the prognosis of heart failure in patients with CKD. Here, we propose clinical recommendations based on an expert consensus to guide ARNI-based therapeutics and reduce the occurrence of cardiovascular events in patients with CKD.