Hedan tablet ameliorated non-alcoholic steatohepatitis by moderating NF-κB and lipid metabolism-related pathways via regulating hepatic metabolites.

Non-alcoholic steatohepatitis (NASH) is a severe form of fatty liver disease. If not treated, it can lead to liver damage, cirrhosis and even liver cancer. However, advances in treatment have remained relatively slow, and there is thus an urgent need to develop appropriate treatments. Hedan tablet (HDP) is used to treat metabolic syndrome. However, scientific understanding of the therapeutic effect of HDP on NASH remains limited. We used HDP to treat a methionine/choline-deficient diet-induced model of NASH in rats to elucidate the therapeutic effects of HDP on liver injury. In addition, we used untargeted metabolomics to investigate the effects of HDP on metabolites in liver of NASH rats, and further validated its effects on inflammation and lipid metabolism following screening for potential target pathways. HDP had considerable therapeutic, anti-oxidant, and anti-inflammatory effects on NASH. HDP could also alter the hepatic metabolites changed by NASH. Moreover, HDP considerable moderated NF-κB and lipid metabolism-related pathways. The present study found that HDP had remarkable therapeutic effects in NASH rats. The therapeutic efficacy of HDP in NASH mainly associated with regulation of NF-κB and lipid metabolism-related pathways via arachidonic acid metabolism, glycine-serine-threonine metabolism, as well as steroid hormone biosynthesis.

An novel effective and safe model for the diagnosis of nonalcoholic fatty liver disease in China: gene excavations, clinical validations, and mechanism elucidation.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases. NAFLD leads to liver fibrosis and hepatocellular carcinoma, and it also has systemic effects associated with metabolic diseases, cardiovascular diseases, chronic kidney disease, and malignant tumors. Therefore, it is important to diagnose NAFLD early to prevent these adverse effects. METHODS: The GSE89632 dataset was downloaded from the Gene Expression Omnibus database, and then the optimal genes were screened from the data cohort using lasso and Support Vector Machine Recursive Feature Elimination (SVM-RFE). The ROC values of the optimal genes for the diagnosis of NAFLD were calculated. The relationship between optimal genes and immune cells was determined using the DECONVOLUTION algorithm CIBERSORT. Finally, the specificity and sensitivity of the diagnostic genes were verified by detecting the expression of the diagnostic genes in blood samples from 320 NAFLD patients and liver samples from 12 mice. RESULTS: Through machine learning we identified FOSB, GPAT3, RGCC and RNF43 were the key diagnostic genes for NAFLD, and they were further demonstrated by a receiver operating characteristic curve analysis. We found that the combined diagnosis of the four genes identified NAFLD samples well from normal samples (AUC = 0.997). FOSB, GPAT3, RGCC and RNF43 were strongly associated with immune cell infiltration. We also experimentally examined the expression of these genes in NAFLD patients and NAFLD mice, and the results showed that these genes are highly specific and sensitive. CONCLUSIONS: Data from both clinical and animal studies demonstrate the high sensitivity, specificity and safety of FOSB, GPAT3, RGCC and RNF43 for the diagnosis of NAFLD. The relationship between diagnostic key genes and immune cell infiltration may help to understand the development of NAFLD. The study was reviewed and approved by Ethics Committee of Tianjin Second People's Hospital in 2021 (ChiCTR1900024415).

A novel model based on serum N-glycan markers for evaluating stage of liver necroinflammation in treatment-naïve chronic hepatitis B patients.

This study aimed to establish a novel noninvasive model based on the serum N-glycan spectrum for providing an objective value for determining the stage of liver necroinflammation related to chronic hepatitis B (CHB) patients. N-glycan profiles of the sera of 295 treatment-naïve CHB patients were analyzed. N-glycan profiles were tested for different liver necroinflammation stages using DNA sequence-assisted fluorophore-assisted carbohydrate electrophoresis. A serum N-glycan model named N-glycan-LI (NGLI) using support vector machine was selected to evaluate the classification of liver necroinflammation (G < 2 and G ≥ 2). The area under the receiver operating characteristic curves (AUROCs) was 0.898 (training set, n = 236) and 0.911 (validation set, n = 59) regardless of the stage of liver fibrosis (AUROC = 0.886 and 0.926, respectively, in S < 2 and S ≥ 2 group). The NGLI correspondingly had the highest specificity (SP) of 90.79% and negative predictive value of 92.00% in an inactive stage (including immune-tolerant [IT] and inactive-carrier [IC] stage), had the highest positive predictive value of 95.18% in stage immune-active, and had the highest SP of 93.94% in grey zone IT + IC. N-glycan profiles appear to correlate well with hepatic necroinflammation in CHB when compared with liver biopsy. The newly developed model appears to reliably predict liver damage in naïve-treatment patients with CHB.

Association between genetic variants of transmembrane transporters and susceptibility to anthracycline-induced cardiotoxicity: Current understanding and existing evidence.

Anthracyclines remain the cornerstone of numerous chemotherapeutic protocols, with beneficial effects against haematological malignancies and solid tumours. Unfortunately, the clinical usefulness of anthracyclines is compromised by the development of cardiotoxic side effects, leading to dose limitations or treatment discontinuation. There is no absolute linear correlation between the incidence of cardiotoxicity and the threshold dose, suggesting that genetic factors may modify the association between anthracyclines and cardiotoxicity risk. And the majority of single nucleotide polymorphisms (SNPs) associated with anthracycline pharmacogenomics were identified in the ATP-binding cassette (ABC) and solute carrier (SLC) transporters, generating increasing interest in the pharmacogenetic implications of their genetic variations for anthracycline-induced cardiotoxicity (AIC). This review focuses on the influence of SLC and ABC polymorphisms on AIC and highlights the prospects and clinical significance of pharmacogenetics for individualised preventive approaches.

Benzo(a)anthracene Targeting SLC1A5 to Synergistically Enhance PAH Mixture Toxicity.

Human exposure to polycyclic aromatic hydrocarbons (PAHs) as mutagenic and carcinogenic pollutants in the environment often occurs in the form of mixtures. Although the mixture effects of PAHs have been previously recognized, the toxicological mechanisms to explain them still remain quite unclear. This study combined metabolomics and chemical proteomics methods to comprehensively understand the mixture effects of a PAH mixture including benzo(a)anthracene (BaA), benzo(b)fluoranthene (BbF), benzo(a)pyrene (BaP), and chrysene (CHR). Among them, BaA has shown a strong synergistic effect with other PAHs. Interestingly, BaA alone is not a potent oxidative stress inducer in liver cells but dose-dependently amplifies oxidative damage caused by the PAH mixture. Global metabolomics analysis results revealed damage to the antioxidant glutathione synthesis, which was caused by the glutamine depletion caused by BaA in the mixture. Subsequently, the label-free chemical proteomics and cellular thermal shift analysis (CETSA) demonstrated that the PAH mixture altered the thermal shift of glutamine transporter SLC1A5. Furthermore, Western blotting and the isothermal titration calorimetry (ITC) interaction measurements showed nanomolar KD values between BaA and SLC1A5. Overall, this study showed that BaA synergistically contributed to PAH mixture induced oxidative damage by targeting SLC1A5 to inhibit glutamate transport into cells, resulting in the inhibition of glutathione synthesis.

Efficacy of Therapeutic Apheresis for Cryoglobulinemic Vasculitis Patients with Renal Involvement: A Systematic Review.

INTRODUCTION: Therapeutic apheresis (TA) is commonly used for cryoglobulinemic vasculitis (CV) patients, but its efficacy remains uncertain. This systematic review aimed to assess the efficacy of different TA modalities, such as plasma exchange (PE), plasmapheresis (PP), and cryofiltration (CF), in treating CV patients with renal involvement. METHODS: Literature search of MEDLINE, EMBASE, and Cochrane Databases was conducted up to December 2022. Studies that reported the outcomes of TA in adult CV patients with renal involvement were assessed. The protocol for this systematic review has been registered with PROSPERO (No. CRD42023417727). The quality of each study was evaluated by the investigators using the validated methodological index for non-randomized studies (minors) quality score. RESULTS: 154 patients who encountered 170 episodes of serious events necessitating TA were evaluated across 76 studies. Among them, 51% were males, with a mean age ranging from 49 to 58 years. The CV types included 15 type I, 97 type II, and 13 type III, while the remaining patients exhibited mixed (n = 17) or undetermined CV types (n = 12). Among the treatment modalities, PE, PP, and CF were performed in 85 (56%), 52 (34%), and 17 patients (11%), respectively, with no identical protocol for TA treatment. The overall response rate for TA was 78%, with response rates of 84%, 77%, and 75% observed in type I, II, and III patients respectively. Most patients received steroids, immunosuppressants, and treatment targeting the underlying causative disease. The overall long-term renal outcome rate was 77%, with type I, II, and III patients experiencing response rates of 89%, 76%, and 90%, respectively. The renal outcomes in patients receiving PE, PP, and CF were comparable, with rates of 78%, 76%, and 81%, respectively. CONCLUSIONS: This study presents compelling evidence that combination of TA with other treatments, especially immunosuppressive therapy, is a successful strategy for effectively managing severe renal involvement in CV patients. Among the TA modalities studied, including PE, PP, and CF, all demonstrated efficacy, with PE being the most frequently employed approach.

Evaluating ChatGPT's Accuracy in Responding to Patient Education Questions on Acute Kidney Injury and Continuous Renal Replacement Therapy.

INTRODUCTION: Acute kidney injury (AKI) and continuous renal replacement therapy (CRRT) are critical areas in nephrology. The effectiveness of ChatGPT in simpler, patient education-oriented questions has not been thoroughly assessed. This study evaluates the proficiency of ChatGPT 4.0 in responding to such questions, subjected to various linguistic alterations. METHODS: Eighty-nine questions were sourced from the Mayo Clinic Handbook for educating patients on AKI and CRRT. These questions were categorized as original, paraphrased with different interrogative adverbs, paraphrased resulting in incomplete sentences, and paraphrased containing misspelled words. Two nephrologists verified the questions for medical accuracy. A χ2 test was conducted to ascertain notable discrepancies in ChatGPT 4.0's performance across these formats. RESULTS: ChatGPT provided notable accuracy in handling a variety of question formats for patient education in AKI and CRRT. Across all question types, ChatGPT demonstrated an accuracy of 97% for both original and adverb-altered questions and 98% for questions with incomplete sentences or misspellings. Specifically for AKI-related questions, the accuracy was consistently maintained at 97% for all versions. In the subset of CRRT-related questions, the tool achieved a 96% accuracy for original and adverb-altered questions, and this increased to 98% for questions with incomplete sentences or misspellings. The statistical analysis revealed no significant difference in performance across these varied question types (p value: 1.00 for AKI and 1.00 for CRRT), and there was no notable disparity between the artificial intelligence (AI)'s responses to AKI and CRRT questions (p value: 0.71). CONCLUSION: ChatGPT 4.0 demonstrates consistent and high accuracy in interpreting and responding to queries related to AKI and CRRT, irrespective of linguistic modifications. These findings suggest that ChatGPT 4.0 has the potential to be a reliable support tool in the delivery of patient education, by accurately providing information across a range of question formats. Further research is needed to explore the direct impact of AI-generated responses on patient understanding and education outcomes.

Mechanical study of alisol B 23-acetate on methionine and choline deficient diet-induced nonalcoholic steatohepatitis based on untargeted metabolomics.

Alisol B 23-acetate (AB23A) has been demonstrated to have beneficial effects on nonalcoholic steatohepatitis (NASH). However, the mechanisms of AB23A on NASH remain unclear. This study aimed to investigate the mechanisms underlying the metabolic regulatory effects of AB23A on NASH. We used AB23A to treat mice with NASH, which was induced by a methionine and choline deficient (MCD) diet. We initially investigated therapeutic effect and resistance to oxidation and inflammation of AB23A on NASH. Subsequently, we performed untargeted metabolomic analyses and relative validation assessments to evaluate the metabolic regulatory effects of AB23A. AB23A reduced lipid accumulation, ameliorated oxidative stress and decreased pro-inflammatory cytokines in the liver. Untargeted metabolomic analysis found that AB23A altered the metabolites of liver. A total of 55 differential metabolites and three common changed pathways were screened among the control, model and AB23A treatment groups. Further tests validated the effects of AB23A on modulating common changed pathway-involved factors. AB23A treatment can ameliorate NASH by inhibiting oxidative stress and inflammation. The mechanism of AB23A on NASH may be related to the regulation of alanine, aspartate and glutamate metabolism, d-glutamine and d-glutamate metabolism, and arginine biosynthesis pathways.

Perspectives on AI-based recommendations for mask-wearing and COVID-19 vaccination for transplant recipients in the post-COVID-19 era.

In the aftermath of the COVID-19 pandemic, the ongoing necessity for preventive measures such as mask-wearing and vaccination remains particularly critical for organ transplant recipients, a group highly susceptible to infections due to immunosuppressive therapy. Given that many individuals nowadays increasingly utilize Artificial Intelligence (AI), understanding AI perspectives is important. Thus, this study utilizes AI, specifically ChatGPT 4.0, to assess its perspectives in offering precise health recommendations for mask-wearing and COVID-19 vaccination tailored to this vulnerable population. Through a series of scenarios reflecting diverse environmental settings and health statuses in December 2023, we evaluated the AI's responses to gauge its precision, adaptability, and potential biases in advising high-risk patient groups. Our findings reveal that ChatGPT 4.0 consistently recommends mask-wearing in crowded and indoor environments for transplant recipients, underscoring their elevated risk. In contrast, for settings with fewer transmission risks, such as outdoor areas where social distancing is possible, the AI suggests that mask-wearing might be less imperative. Regarding vaccination guidance, the AI strongly advocates for the COVID-19 vaccine across most scenarios for kidney transplant recipients. However, it recommends a personalized consultation with healthcare providers in cases where patients express concerns about vaccine-related side effects, demonstrating an ability to adapt recommendations based on individual health considerations. While this study provides valuable insights into the current AI perspective on these important topics, it is crucial to note that the findings do not directly reflect or influence health policy. Nevertheless, given the increasing utilization of AI in various domains, understanding AI's viewpoints on such critical matters is essential for informed decision-making and future research.

Identification of kidney-related medications using AI from self-captured pill images.

INTRODUCTION: ChatGPT, a state-of-the-art large language model, has shown potential in analyzing images and providing accurate information. This study aimed to explore ChatGPT-4 as a tool for identifying commonly prescribed nephrology medications across different versions and testing dates. METHODS: 25 nephrology medications were obtained from an institutional pharmacy. High-quality images of each medication were captured using an iPhone 13 Pro Max and uploaded to ChatGPT-4 with the query, 'What is this medication?' The accuracy of ChatGPT-4's responses was assessed for medication name, dosage, and imprint. The process was repeated after 2 weeks to evaluate consistency across different versions, including GPT-4, GPT-4 Legacy, and GPT-4.Ø. RESULTS: ChatGPT-4 correctly identified 22 out of 25 (88%) medications across all versions. However, it misidentified Hydrochlorothiazide, Nifedipine, and Spironolactone due to misreading imprints. For instance, Nifedipine ER 90 mg was mistaken for Metformin Hydrochloride ER 500 mg because 'NF 06' was misread as 'NF 05'. Hydrochlorothiazide 50 mg was confused with the 25 mg version due to imprint errors, and Spironolactone 25 mg was misidentified as Naproxen Sodium or Diclofenac Sodium. Despite these errors, ChatGPT-4 showed 100% consistency when retested, correcting misidentifications after receiving feedback on the correct imprints. CONCLUSION: ChatGPT-4 shows strong potential in identifying nephrology medications from self-captured images, though challenges with difficult-to-read imprints remain. Providing feedback improved accuracy, suggesting ChatGPT-4 could be a valuable tool in digital health for medication identification. Future research should enhance the model's ability to distinguish similar imprints and explore broader integration into digital health platforms.

Co-impacts of cation type and humic acid on migration of polystyrene microplastics in saturated porous media.

The aging process of microplastics (MPs) could significantly change their physical and chemical characteristics and impact their migration behavior in soil. However, the complex effects of different cations and humic acids (HA) on the migration of aged MPs through saturated media are not clear. In this research, the migration and retention of pristine/aged PSMPs (polystyrene microplastics) under combined effects of cations (Na+, Ca2+) (ionic strength = 10 mM) and HA (0, 5, 15 mg/L) were investigated and analyzed in conjunction with the two-site kinetic retention model and DLVO theory. The findings showed that the aging process accelerated PSMPs migration under all tested conditions. Aged PSMPs were less susceptible to Ca2+ than pristine PSMPs. Under Ca2+ conditions, pristine/aged PSMPs showed higher retention than under Na+ conditions in the absence of HA. Furthermore, under Na+ conditions, the migration of aged PSMPs significantly increased at higher concentrations of HA. However, under Ca2+ conditions, the migration of aged PSMPs decreased significantly at higher concentrations of HA. In higher HA conditions, HA, Ca2+, and PSMPs interact to cause larger aggregations, resulting in the sedimentation of aged PSMPs. The DLVO calculations and two-site kinetic retention models' results showed the detention of PSMPs was irreversible under higher HA conditions (15 mg/L) with Ca2+, and aged PSMPs were more susceptible to clogging. These findings may help to understand the potential risk of migration behavior of PSMPs in the soil-groundwater environment.

Meta-analysis comparing different ultrasound detection methods to accurately assess wound healing and scar formation after caesarean section.

The accurate assessment of wound healing post-caesarean section, especially in twin pregnancies, remains a pivotal concern in obstetrics, given its implications for maternal health and recovery. Traditional methods, including conventional abdominal ultrasonography (CU), have been challenged by the advent of transvaginal ultrasonography (TU), offering potentially enhanced sensitivity and specificity. This meta-analysis directly compares the efficacy of TU and CU in evaluating wound healing and scar formation, crucial for optimizing postoperative care. Results indicate that TU is associated with significantly better outcomes in wound healing, demonstrated by lower REEDA scores (SMD = -20.56, 95% CI: [-27.34.20, -13.77], p < 0.01), and in scar formation reduction, evidenced by lower Manchester Scar Scale scores (SMD = -25.18, 95% CI: [-29.98, -20.39], p < 0.01). These findings underscore the potential of integrating TU into routine post-caesarean evaluation protocols to enhance care quality and patient recovery.

Integrating Retrieval-Augmented Generation with Large Language Models in Nephrology: Advancing Practical Applications.

The integration of large language models (LLMs) into healthcare, particularly in nephrology, represents a significant advancement in applying advanced technology to patient care, medical research, and education. These advanced models have progressed from simple text processors to tools capable of deep language understanding, offering innovative ways to handle health-related data, thus improving medical practice efficiency and effectiveness. A significant challenge in medical applications of LLMs is their imperfect accuracy and/or tendency to produce hallucinations-outputs that are factually incorrect or irrelevant. This issue is particularly critical in healthcare, where precision is essential, as inaccuracies can undermine the reliability of these models in crucial decision-making processes. To overcome these challenges, various strategies have been developed. One such strategy is prompt engineering, like the chain-of-thought approach, which directs LLMs towards more accurate responses by breaking down the problem into intermediate steps or reasoning sequences. Another one is the retrieval-augmented generation (RAG) strategy, which helps address hallucinations by integrating external data, enhancing output accuracy and relevance. Hence, RAG is favored for tasks requiring up-to-date, comprehensive information, such as in clinical decision making or educational applications. In this article, we showcase the creation of a specialized ChatGPT model integrated with a RAG system, tailored to align with the KDIGO 2023 guidelines for chronic kidney disease. This example demonstrates its potential in providing specialized, accurate medical advice, marking a step towards more reliable and efficient nephrology practices.

Chain of Thought Utilization in Large Language Models and Application in Nephrology.

Chain-of-thought prompting enhances the abilities of large language models (LLMs) significantly. It not only makes these models more specific and context-aware but also impacts the wider field of artificial intelligence (AI). This approach broadens the usability of AI, increases its efficiency, and aligns it more closely with human thinking and decision-making processes. As we improve this method, it is set to become a key element in the future of AI, adding more purpose, precision, and ethical consideration to these technologies. In medicine, the chain-of-thought prompting is especially beneficial. Its capacity to handle complex information, its logical and sequential reasoning, and its suitability for ethically and context-sensitive situations make it an invaluable tool for healthcare professionals. Its role in enhancing medical care and research is expected to grow as we further develop and use this technique. Chain-of-thought prompting bridges the gap between AI's traditionally obscure decision-making process and the clear, accountable standards required in healthcare. It does this by emulating a reasoning style familiar to medical professionals, fitting well into their existing practices and ethical codes. While solving AI transparency is a complex challenge, the chain-of-thought approach is a significant step toward making AI more comprehensible and trustworthy in medicine. This review focuses on understanding the workings of LLMs, particularly how chain-of-thought prompting can be adapted for nephrology's unique requirements. It also aims to thoroughly examine the ethical aspects, clarity, and future possibilities, offering an in-depth view of the exciting convergence of these areas.

A map of the spatial distribution and tumour-associated macrophage states in glioblastoma and grade 4 IDH-mutant astrocytoma.

Tumour-associated macrophages (TAMs) abundantly infiltrate high-grade gliomas and orchestrate immune response, but their diversity in isocitrate dehydrogenase (IDH)-differential grade 4 gliomas remains largely unknown. This study aimed to dissect the transcriptional states, spatial distribution, and clinicopathological significance of distinct monocyte-derived TAM (Mo-TAM) and microglia-derived TAM (Mg-TAM) clusters across glioblastoma-IDH-wild type and astrocytoma-IDH-mutant-grade 4 (Astro-IDH-mut-G4). Single-cell RNA sequencing was performed on four cases of human glioblastoma and three cases of Astro-IDH-mut-G4. Cell clustering, single-cell regulatory network inference, and gene set enrichment analysis were performed to characterize the functional states of myeloid clusters. The spatial distribution of TAM subsets was determined in human glioma tissues using multiplex immunostaining. The prognostic value of different TAM-cluster specific gene sets was evaluated in the TCGA glioma cohort. Profiling and unbiased clustering of 24,227 myeloid cells from glioblastoma and Astro-IDH-mut-G4 identified nine myeloid cell clusters including monocytes, six Mo/Mg-TAM subsets, dendritic cells, and proliferative myeloid clusters. Different Mo/Mg-TAM clusters manifest functional and transcriptional diversity controlled by specific regulons. Multiplex immunostaining of subset-specific markers identified spatial enrichment of distinct TAM clusters at peri-vascular/necrotic areas in tumour parenchyma or at the tumour-brain interface. Glioblastoma harboured a substantially higher number of monocytes and Mo-TAM-inflammatory clusters, whereas Astro-IDH-mut-G4 had a higher proportion of TAM subsets mediating antigen presentation. Glioblastomas with a higher proportion of monocytes exhibited a mesenchymal signature, increased angiogenesis, and worse patient outcome. Our findings provide insight into myeloid cell diversity and its clinical relevance in IDH-differential grade 4 gliomas, and may serve as a resource for immunotherapy development. © 2022 The Pathological Society of Great Britain and Ireland.

Investigating Genetic Factors and the Effect of Refined Multidisciplinary Clinical Management on the Quality of Life and Perceived Control Level of Breast Cancer Patients undergoing Surgery and its Morphological Diagnosis Parameters.

The purpose of this study is to investigate the genetic factors and the effect of refined multidisciplinary clinical management on the quality of life and perceived control level of breast cancer patients undergoing surgery and its morphological diagnosis parameters. Breast cancer, as the most common cancer in women, requires screening, early diagnosis, prognosis, response to treatment, and choosing the appropriate treatment method. In this study, we introduced the genes involved in breast cancer BRCA1 and BRCA2 and the molecular techniques of its diagnosis. From October 2016 to July 2021, 400 patients with breast cancer were selected from the glandular surgery department of Xingtai Third Hospital. According to the method of random number table, they were divided into an observation group and a control group, with 200 cases in each group. The control group adopted the routine management scheme, while the observation group adopted the multidisciplinary refined clinical management scheme based on the control group. The quality of life, perception control level, negative psychology, upper limb lymphedema, and satisfaction with the nursing of the two groups were compared after 3 months of intervention. The results showed the scores and total scores of the quality-of-life scale for breast cancer in the observation group were higher than those in the control group (P<0.05). The scores of perceived experience and control effectiveness in the observation group were higher than those in the control group (P<0.05). The scores of the Hamilton Anxiety Scale and Hamilton Depression Scale in the observation group were lower than those in the control group (P<0.05). After nursing, the improvement of upper limb edema in the observation group was better than that in the control group (P<0.05). Nursing satisfaction in the observation group (84.50%) was higher than that in the control group (66.50%) (P<0.05). Also, the results of this research showed the multidisciplinary refined clinical management plan for breast cancer patients can effectively improve the quality of life, improve the level of perceived control, reduce negative psychology, improve the degree of upper limb edema, and increase patient satisfaction.

Characteristics of intestinal microbiota in children with idiopathic short stature: a cross-sectional study.

Idiopathic short stature (ISS) accounts for more than 70% of childhood short stature cases, with an undefined etiology and pathogenesis, leading to limited treatment. However, recent studies have shown that intestinal microbiota may be associated with ISS. This study aimed to characterize the intestinal microbiota in children with ISS, effect of treatment with growth hormones, and association between specific bacterial species and ISS. This study enrolled 55 children, comprising 40 diagnosed with ISS at Jinhua Hospital, Zhejiang University, and 15 healthy controls. The subjects with ISS were divided into the untreated ISS group (UISS group, 22 children who had not been treated with recombinant human growth hormone [rhGH]), treated ISS group (TISS group, 18 children treated with rhGH for 1 year), and control group (NC group, 15 healthy children). High-throughput sequencing was used to determine the intestinal microbiota characteristics. Higher abundances of Bacteroides, Prevotella, Alistipes, Parabacteroides, Agathobacter and Roseburia were found in the UISS and TISS groups than in the control group, whereas Bifidobacterium, Subdoligranulum, and Romboutsia were less abundant. The composition of intestinal microbiota in the UISS and TISS groups was almost identical, except for Prevotella. The TISS group had significantly lower levels of Prevotella than did the UISS group, which were closer to those of the NC group. Receiver operating characteristic curve analysis revealed that the abundances of Prevotella, Bifidobacterium, Bacteroides, and Subdoligranulum were effective in differentiating between the UISS and NC groups. CONCLUSION: Alterations in intestinal microbiota may be associated with ISS. Specific bacterial species, such as Prevotella, may be potential diagnostic markers for ISS. WHAT IS KNOWN: • ISS is associated with the GH-IGF-1 axis. • Recent studies indicated an association between the GH-IGF-1 axis and intestinal microbiota. WHAT IS NEW: • Children with ISS showed alterations in intestinal microbiota, with a relative increase in the abundance of gut inflammation-related bacteria. • The relative abundances of Prevotella, Bacteroides, Bifidobacterium, and Subdoligranulum may serve as potential diagnostic markers.

Efficacy of extracorporeal plasma therapy for adult native kidney patients with Primary FSGS: a Systematic review.

PURPOSE: This study aimed to assess efficacy of extracorporeal plasma therapy (EPT), including plasmapheresis (PE), immunoadsorption (IA), low-density lipoprotein apheresis (LDL-A), and lymphocytapheresis (LCAP) for adult native kidney patients with primary focal segmental glomerulosclerosis (FSGS). METHODS: A literature search was conducted using MEDLINE, EMBASE and Cochrane Databases through August 2022. Studies that reported outcomes of EPT in adult native kidneys with primary FSGS were enrolled. RESULTS: 18 studies with 104 therapy-resistant or refractory primary native FSGS patients were identified. Overall EPT response rate was 56%, with long-term benefit of 46%. Of the 101 non-hemodialysis (HD) patients, 54% achieved remission, with 30% complete remission (CR) and 23% partial remission (PR). Of 31 patients with PE, response rate was 65%; CR and PR rates were 27% and 37% in 30 non-HD patients. Of 61 patients with LDL-A, the response rate was 54%; CR and PR rates were 41% and 3% in 29 non-HD patients. Of 10 patients with IA, response rate was 40%. Of 2 patients with LCAP, 1 achieved CR, and one developed renal failure. All 3 HD patients showed increase in urine output and gradual decrease in urine protein excretion following PE (n = 1) or LDL-A (n = 2). 2 of 3 HD patients ultimately discontinued dialysis. CONCLUSION: EPT with immunosuppressive therapy showed benefit in some patients with refractory primary FSGS, and PE appeared to have a higher response rate.

Distinct clinical profiles and post-transplant outcomes among kidney transplant recipients with lower education levels: uncovering patterns through machine learning clustering.

BACKGROUND: Educational attainment significantly influences post-transplant outcomes in kidney transplant patients. However, research on specific attributes of lower-educated subgroups remains underexplored. This study utilized unsupervised machine learning to segment kidney transplant recipients based on education, further analyzing the relationship between these segments and post-transplant results. METHODS: Using the OPTN/UNOS 2017-2019 data, consensus clustering was applied to 20,474 kidney transplant recipients, all below a college/university educational threshold. The analysis concentrated on recipient, donor, and transplant features, aiming to discern pivotal attributes for each cluster and compare post-transplant results. RESULTS: Four distinct clusters emerged. Cluster 1 comprised younger, non-diabetic, first-time recipients from non-hypertensive younger donors. Cluster 2 predominantly included white patients receiving their first-time kidney transplant either preemptively or within three years, mainly from living donors. Cluster 3 included younger re-transplant recipients, marked by elevated PRA, fewer HLA mismatches. In contrast, Cluster 4 captured older, diabetic patients transplanted after prolonged dialysis duration, primarily from lower-grade donors. Interestingly, Cluster 2 showcased the most favorable post-transplant outcomes. Conversely, Clusters 1, 3, and 4 revealed heightened risks for graft failure and mortality in comparison. CONCLUSIONS: Through unsupervised machine learning, this study proficiently categorized kidney recipients with lesser education into four distinct clusters. Notably, the standout performance of Cluster 2 provides invaluable insights, underscoring the necessity for adept risk assessment and tailored transplant strategies, potentially elevating care standards for this patient cohort.

Satellite Interference Source Direction of Arrival (DOA) Estimation Based on Frequency Domain Covariance Matrix Reconstruction.

Direction of arrival (DOA) estimation is an effective method for detecting various active interference signals during the satellite navigation process. It can be utilized for both interference detection and anti-interference applications. This paper proposes a DOA estimation algorithm for satellite interference sources based on frequency domain covariance matrix reconstruction (FDCMR) to address various types of active interference that may occur in the satellite navigation positioning process. This algorithm can estimate the DOA of coherent signals from multiple frequency points under low signal-to-noise ratio (SNR) conditions. The signals received from the array are transformed from the time domain to the frequency domain using a fast Fourier transform (FFT). The data corresponding to the frequency point of the target signal is extracted from the signal in the frequency domain. The frequency domain covariance matrix of the received array signals is reconstructed by utilizing its covariance matrix property. The spatial spectrum search method is used for the final DOA estimation. Simulation experiments have shown that the proposed algorithm performs well in the DOA estimation under low SNR conditions and also resolves coherency. Moreover, the algorithm's effectiveness is verified through comparison with three other algorithms. Finally, the algorithm's applicability is validated through simulations of various interference scenarios.