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BACKGROUND: Emerging evidence suggests that gut microbiota dysbiosis may play a critical role in the development of lupus nephritis (LN). However, the specific characteristics of the gut microbiota in individuals with LN have not been fully clarified. METHODS: The PubMed, Web of Science, and Embase databases were systematically searched for clinical and animal studies related to the relationship between LN and gut microbiota from inception until October 1, 2023. A semiquantitative analysis was used to assess the changes in gut microbial profiles. RESULTS: A total of 15 clinical studies were selected for analysis, which included 138 LN patients, 441 systemic lupus erythematosus patients, and 1526 healthy controls (HCs). Five different types of LN mouse models were included in 5 animal studies. The alpha diversity was decreased in LN patients compared to HCs. A significant decrease in the Firmicutes/Bacteroidetes (F/B) ratio is considered a hallmark of pathological conditions. Specifically, alterations in the abundance of the phylum Proteobacteria, genera Streptococcus and Lactobacillus, and species Ruminococcus gnavus and Lactobacillus reuteri may play a critical role in the pathogenesis of LN. Remarkably, the gut taxonomic chain Bacteroidetes-Bacteroides-Bacteroides thetaiotaomicron was enriched in LN patients, which could be a crucial characteristic of LN patients. The increased level of interleukin-6, imbalance of regulatory T cells and T helper 17 cells, and decreased level of the intestinal tight junction proteins zonula occludens-1 and claudin-1 also might be related to the pathogenesis of LN. CONCLUSIONS: Specific changes in the abundance of gut microbiota such as decreased F/B ratio, and the level of inflammatory indicators, and markers of intestinal barrier dysfunction may play a crucial role in the pathogenesis of LN. These factors could be effective diagnostic and potential therapeutic targets for LN.
Assuntos
Microbioma Gastrointestinal , Enteropatias , Lúpus Eritematoso Sistêmico , Nefrite Lúpica , Animais , Camundongos , Humanos , Interleucina-6RESUMO
Super-resolution ultrasound (SRUS) can image microvascular structure and flow at subwave-diffraction resolution based on localizing and tracking microbubbles (MBs). Currently, tracking MBs accurately under limited imaging frame rates and high MB concentrations remains a challenge, especially under the effect of cardiac pulsatility and in highly curved vessels. In this study, an acceleration-incorporated MB motion model is introduced into a Kalman tracking framework. The tracking performance was evaluated using simulated microvasculature with different MB motion parameters, concentrations, and acquisition frame rates, and in vivo human breast tumor US datasets. The simulation results show that the acceleration-based method outperformed the nonacceleration-based method at different levels of acceleration and acquisition frame rates and achieved significant improvement in true positive rate (TPR; up to 11.3%) and false negative rate (FNR; up to 13.2%). The proposed method can also reduce errors in vasculature reconstruction via the acceleration-based nonlinear interpolation, compared with linear interpolation (up to [Formula: see text]). The tracking results from temporally downsampled low frame rate in vivo datasets from human breast tumors show that the proposed method has better MB tracking performance than the baseline method, if using results from the initial high frame data as a reference. Finally, the acceleration estimated from tracking results also provides a spatial speed gradient map that may contain extra valuable diagnostic information.
Assuntos
Aceleração , Processamento de Imagem Assistida por Computador , Humanos , Processamento de Imagem Assistida por Computador/métodos , Movimento (Física) , Ultrassonografia/métodos , MicrobolhasRESUMO
Background: Emerging evidence revealed that gut microbial dysbiosis is implicated in the development of plasma cell dyscrasias and amyloid deposition diseases, but no data are available on the relationship between gut microbiota and immunoglobulin light chain (AL) amyloidosis. Methods: To characterize the gut microbiota in patients with AL amyloidosis, we collected fecal samples from patients with AL amyloidosis (n=27) and age-, gender-, and BMI-matched healthy controls (n=27), and conducted 16S rRNA MiSeq sequencing and amplicon sequence variants (ASV)-based analysis. Results: There were significant differences in gut microbial communities between the two groups. At the phylum level, the abundance of Actinobacteriota and Verrucomicrobiota was significantly higher, while Bacteroidota reduced remarkably in patients with AL amyloidosis. At the genus level, 17 genera, including Bifidobacterium, Akkermansia, and Streptococcus were enriched, while only 4 genera including Faecalibacterium, Tyzzerella, Pseudomonas, and Anaerostignum decreased evidently in patients with AL amyloidosis. Notably, 5 optimal ASV-based microbial markers were identified as the diagnostic model of AL amyloidosis and the AUC value of the train set and the test set was 0.8549 (95% CI 0.7310-0.9789) and 0.8025 (95% CI 0.5771-1), respectively. With a median follow-up of 19.0 months, further subgroup analysis also demonstrated some key gut microbial markers were related to disease severity, treatment response, and even prognosis of patients with AL amyloidosis. Conclusions: For the first time, we demonstrated the alterations of gut microbiota in AL amyloidosis and successfully established and validated the microbial-based diagnostic model, which boosted more studies about microbe-based strategies for diagnosis and treatment in patients with AL amyloidosis in the future.
Assuntos
Microbioma Gastrointestinal , Amiloidose de Cadeia Leve de Imunoglobulina , Humanos , Microbioma Gastrointestinal/fisiologia , RNA Ribossômico 16S/genética , Disbiose/microbiologia , Fezes/microbiologia , BiomarcadoresRESUMO
Multiple myeloma (MM), an incurable hematological malignancy with clonal proliferation of plasma cells, is mainly characterized by excessive production of monoclonal immunoglobulins and free light chains (FLCs). Kidney injury is one of the main clinical manifestations and is also a significant predictor of the prognosis of symptomatic MM patients, especially those who require dialysis-supported treatment. Overproduction of FLCs is the trigger for kidney injury, as they can induce the transcription of inflammatory and profibrotic cytokines in the proximal tubule and bind to Tamm-Horsfall protein in the distal tubules to form casts that obstruct the tubules, leading to kidney injury and even renal fibrosis. In addition to traditional antimyeloma treatment, high-cutoff hemodialysis (HCO-HD), which can effectively remove FLCs in vitro, has attracted much attention in recent years. Due to its greater membrane pore size, it has significant advantages in removing larger molecules and can be applied in rhabdomyolysis, sepsis, and even myeloma cast nephropathy. However, mounting questions have recently been raised regarding whether HCO-HD can truly provide clinical benefits in MM patients with acute kidney injury (AKI). Therefore, in this study, we discussed the pathological causes of AKI secondary to MM and summarized the current situation of HCO-HD in MM patients compared with other available extracorporeal techniques. In addition, pivotal clinical trials that reflect the ability of the clearance of FLCs and the side effects of HCO-HD are highlighted, and the relevant protocol of HCO-HD is also provided to assist clinicians in decision-making.
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Although patients with light chain amyloidosis (AL) may present with co-deposition of amyloid and immune complexes (ICs) in renal biopsies, data on clinical characteristics and prognostic value of renal IC deposition are limited. A total of 73 patients with AL amyloidosis who were newly diagnosed by renal biopsy in Xijing Hospital (Xi'an, China) were divided into two groups (IC and non-IC groups). As a result, renal IC deposition was found in 26% of patients. Patients with IC deposition were associated with more urinary protein excretion and lower serum albumin. Notably, patients in the non-IC group achieved higher hematological overall response rate (81.5% vs. 47.4%, p = 0.007) and ≥VGPR rate (75.9% vs. 39.8%, p = 0.004) compared with those in IC group. Renal response rate was also higher in the non-IC group (63% vs. 31.6%, p = 0.031). With the median follow-up time of 19 months, a significantly worse overall survival was observed in patients with the IC group as compared with those without renal IC deposition in the Kaplan-Meier analysis (p = 0.036). Further multivariate analysis demonstrated that renal immune complex deposition was associated with worse overall survival in patients with AL amyloidosis (HR 5.927, 95% CI 2.148-16.356, p = 0.001).
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Due to rapid development of high-throughput sequencing and biotechnology, it has brought new opportunities and challenges in developing efficient computational methods for exploring personalized genomics data of cancer patients. Because of the high-dimension and small sample size characteristics of these personalized genomics data, it is difficult for excavating effective information by using traditional statistical methods. In the past few years, network control methods have been proposed to solve networked system with high-dimension and small sample size. Researchers have made progress in the design and optimization of network control principles. However, there are few studies comprehensively surveying network control methods to analyze the biomolecular network data of individual patients. To address this problem, here we comprehensively surveyed complex network control methods on personalized omics data for understanding tumor heterogeneity in precision medicine of individual patients with cancer.