Heatstroke-induced acute kidney injury (HS-AKI) is a serious clinical complication, with ferroptosis implicated in its pathogenesis. While heat shock factor 1 (HSF1) is a known regulator of ferroptosis, its role in HS-AKI remains unclear. Here, we demonstrated that heatstroke triggered ferroptosis-associated renal damage in mice, characterized by elevated serum creatinine, blood urea nitrogen, and tissue iron deposition, alongside transcriptomic signatures of ferroptosis and HSF1 pathway activation. Notably, HSF1 expression was transiently activated by heat stress, and simultaneously promoted the expression of heat shock proteins (HSPs), but decreased in the late phase of heat shock. Knockdown of HSF1 in renal tubular cells exacerbated HS-induced ferroptotic death. Conversely, renal-specific overexpression of HSF1 rescued heatstroke-caused deleterious phenotype in mice. Importantly, pharmacological activation of HSF1 by HSF1A attenuated oxidative stress, rectified iron dyshomeostasis, inhibited lipid peroxidation, and conferred significant protection against HS-AKI. These results identify HSF1 activation as an endogenous adaptive response that limits ferroptosis during heatstroke, positioning HSF1A as a promising therapeutic candidate for HS-AKI.

Kidney disease represents a major non-communicable disease characterized by complex pathogenesis and limited therapeutic options. Current research has revealed multiple underlying mechanisms, including ferroptosis and necroptosis, which play important roles in acute kidney injury (AKI) and chronic kidney disease (CKD). Ferroptosis is an iron-dependent form of programmed cell death caused by the accumulation of lipid reactive oxygen species and is characterized by iron ion aggregation, lipid peroxidation, and excessive oxidative stress. Necroptosis is a regulated form of necrosis mediated by RIPK1-RIPK3 and is characterized by the recruitment and phosphorylation of the pseudokinase mixed lineage kinase domain-like protein (MLKL). Ferroptosis and necroptosis play important roles in various diseases such as tissue injury, cancer, and neurodegenerative diseases. Due to the intricate architecture of the kidney, the convergence of multiple systemic pathogenic factors, and the interactive regulation of intercellular signaling pathways, renal diseases exhibit complex pathogenesis and present limited therapeutic interventions. Exploring cell death and the interactions between different forms of cell death is highly important for understanding the occurrence and development of kidney diseases and for finding new treatment strategies. Ferroptosis and necroptosis influence renal cell viability and contribute to the exacerbation of kidney injury via inflammatory responses and additional mechanisms. They share common initiating factors and intersecting signaling pathways in the context of kidney diseases, thereby synergistically intensifying the pathological progression of renal damage. This article describes the pathogenesis and pathophysiological roles of ferroptosis, necroptosis, and their interactions in kidney diseases such as AKI and CKD and elucidates the potential of inhibiting ferroptosis and necroptosis, or their combined inhibition, in the prevention and treatment of kidney diseases such as AKI and CKD.

Acute kidney disease (AKD) describes acute or subacute renal damage and/or loss of kidney function between 7 and 90 days after AKI initiation. Because there are few reports on AKD in older patients, the present study evaluated the risk factors and outcomes of AKD in older patients. A retrospective, observational, multicenter cohort study was conducted on consecutive patients (≥ 75 years) admitted to Chinese PLA General Hospital between 2007 and 2022. AKI was diagnosed on the basis of the Kidney Disease: Improving Global Outcomes (KDIGO) SCr-based criteria. AKD was defined as AKI (KDIGO stage 1 or greater) that persisted for 7 days or longer. The outcomes included short- and long-term mortality and proportion of de novo chronic kidney disease (CKD). In total, 1395 elderly patients were included in the analysis, including 1245 (89.2

Chronic kidney disease (CKD) is an important disease affecting human health, especially in developing countries where CKD has high prevalence and mortality rates.[1] According to the latest CKD epidemiological data, the prevalence of CKD among Chinese people is 8.2%, of which 1.8% are patients with CKD stage 5 (known as end-stage renal disease [ESRD]).[2] Hemodialysis (HD) is the main treatment for ESRD patients. According to the China National Renal Data System (CNRDS), the number of people receiving HD treatment in 2022, was as high as 844,000. Although dialysis can partially replace the function of the kidneys, distant complications in dialysis patients, such as cardiovascular disease (CVD), renal bone disease, and infections, seriously affect the quality of life and prognosis. Among these conditions, CVD is the leading cause of death in dialysis patients.[3] In addition to traditional cardiovascular risk factors such as hypertension and diabetes, the development of CVD has been associated with alterations in the gut microbiota and its metabolites. HD patients and healthy subjects were varied in terms of the number and composition of the gut microbiota. In 2013, Vaziri et al[4] first reported that Firmicutes (new name, Bacillota), Proteobacteria, and Actinobacteria were significantly enriched in HD patients. Later, Wu et al[5] and Shivani et al[6] also reported similar results. Wu et al[5] reported an increased abundance of Bacillota and Proteobacteria and a decreased abundance of Bacteroidetes in HD patients compared to controls. Another study showed a relative increase in Bacillota, Actinobacteria, and Fusobacteria and a relative decrease in Bacteroidetes and Proteobacteria.[6] In a study of children with HD, the relative abundance of Bacteroidetes increased, while that of Proteobacteria decreased.[7] At the genus level, the abundance of Bacteroides increased in HD.[6] These results suggest differences in the abundance of the gut microbiota between ESRD patients who underwent HD and healthy subjects. However, little is known about the changes in the microbiota of ESRD patients before and after dialysis. He et al[8] and Luo et al[9] compared changes in the gut microbiota before and after dialysis in ESRD patients. There was increased abundance of Bifidobacteria and Lactobacillus acidophilus and decreased abundance of Escherichia coli and Enterococcus faecalis in HD patients compared to pre-dialysis ESRD patients.[8] In addition, the abundances of Blautia, Akkermansia, Coprococcus, Proteus, Pseudomonas, and Acinetobacter increased, while the abundances of Prevotella and Paraprevotella decreased in HD patients.[9] Significant alterations in the gut microbiota of HD patients are thought to be related to the uremic environment, especially the HD process itself. Some other factors specific to this population, such as alterations in diet and medication composition, are also thought to contribute. In uremia patients with renal-excretion function decreased, urea translocated into the intestinal lumen increases; urea is broken down by urease-containing bacteria into ammonia (CO[NH2]2 + H2O → CO2 + 2NH3); ammonia is further converted to NH4OH, which can damage the intestinal mucosa and cause gut microbiota dysbiosis. HD patients are unique in that they undergo dialysis at least three times a week (3–5 h each time); and the effects of vascular access, hemodynamic instability, and complications during dialysis can affect the gut microbiota. The special dietary structure of HD patients, such as low intake of dietary fiber and the restriction of potassium-, sodium-, and phosphorus-containing foods, are known to be important factors affecting the gut microbiota. Furthermore, drug interventions, such as phosphate binders, potassium binders, iron supplements, and antibiotic interventions, can cause changes in the flora. All these factors can lead to differences in the gut microbiota between HD patients and healthy people. These studies tended to include patients who were undergoing maintenance HD (dialysis for at least 3 months), who had not used antibiotics or immunosuppressants within 3 months, or who had excluded cancer.[4–6] Interestingly, even for the same bacterium, results varied in different studies, with Bacteroidetes being reduced in adult HD patients[5,6] and increasing in children with HD.[7] This can be attributed to differences in age, race, geographic location, lifestyle, primary disease, dialysis adequacy, and vascular access. A shift in the host gut environment and microbiome from a symbiotic to a dysbiotic state is associated with increased production of uremic toxins. Indoxyl sulfate (IS), p-cresol sulfate (pCS), and trimethylamine N-oxide (TMAO) accumulate in CKD patients. The IS and pCS concentrations in predialysis patients were 116 and 41 times greater than those in healthy individuals, respectively.[10] Due to the tight binding of IS and pCS to albumin, the dialysis clearance of IS and pCS was only 0.21-fold and 0.39-fold, whereas the dialysis clearance of urea and creatinine was up to 4.2-fold and 1.3-fold, respectively.[10] Serum TMAO concentrations were approximately 30-fold greater in HD patients than in healthy individuals.[11] These protein-bound uremic toxins have been shown to be important contributors to the development of CVD.[12] IS, a metabolite of tryptophanase-containing bacteria, induces endothelial dysfunction through oxidative stress, induces endothelial cell senescence through increased reactive oxygen species (ROS) and p53 activity, and is also involved in thrombosis and vascular calcification.[13]pCS, a metabolite of tyrosine, promotes ROS production by increasing nicotinamide adenine dinucleotide phosphate (NADPH) oxidase activity and is associated with impaired left ventricular diastolic function and cardiac apoptosis.[14] IS and pCS are considered markers of endothelial cell injury, and both have proinflammatory effects and are involved in vascular injury.[15] TMAO, a metabolite of cholines or trimethylamines, has been identified as a predictor of CVD and is involved in the formation of atherosclerosis. TMAO can be mediated by the inhibition of reverse cholesterol transport, the induction of the macrophage expression of scavenger receptor A (SRA) and CD36, and the promotion of foam cell formation.[16] At present, interventions to regulate gut microbiota imbalances and remove gut-derived uremic toxins include probiotics and prebiotics. The use of probiotics/prebiotics has been shown to be effective at restoring the gut microbial composition and reducing uremic toxins. However, there is a lack of clear guidelines for informing HD patients when to take these dietary supplements, as well as the types and dosages that must be taken, which can be confusing for clinicians when prescribing them to their patients. Fecal microbiota transplantation (FMT), an emerging therapy for modulating the gut microbiota, has therapeutic potential for recurrent Clostridioides difficile infections (rCDIs), inflammatory bowel disease, and gastrointestinal tract tumors.[17] However, there is a lack of basic and clinical trial-based confirmation of the efficacy of FMT in HD patients. In conclusion, there is still much work to be done on the study of intestinal microecological status in HD patients. In addition, the special and complex pathophysiological status of HD patients brings challenges to related research. Funding This research was funded by grants from the National Natural Science Foundation of China (Nos. 62271506 and61971441), the National Key R&D Program of China (No. 2021YFC1005300), and the Jinzhongzi project of Beijing Chao-yang Hospital (No. CYJZ202203). Conflicts of interest None.

The composition of the gut microbiota varies among end-stage renal disease (ESRD) patients on the basis of their mode of renal replacement therapy (RRT), with notably more pronounced dysbiosis occurring in those undergoing hemodialysis (HD). Interventions such as dialysis catheters, unstable hemodynamics, strict dietary restrictions, and pharmacotherapy significantly alter the intestinal microenvironment, thus disrupting the gut microbiota composition in HD patients. The gut microbiota may influence HD-related complications, including cardiovascular disease (CVD), infections, anemia, and malnutrition, through mechanisms such as bacterial translocation, immune regulation, and the production of gut microbial metabolites, thereby affecting both the quality of life and the prognosis of patients. This review focuses on alterations in the gut microbiota and its metabolites in HD patients. Additionally, understanding the impact of the gut microbiota on the complications of HD could provide insights into the development of novel treatment strategies to prevent or alleviate complications in HD patients.

Diabetic nephropathy (DN), as the one of most common complications of diabetes, is generally diagnosed based on a longstanding duration, albuminuria, and decreased kidney function. Some patients with the comorbidities of diabetes and other primary renal diseases have similar clinical features to DN, which is defined as non-diabetic renal disease (NDRD). It is necessary to distinguish between DN and NDRD, considering they differ in their pathological characteristics, treatment regimes, and prognosis. Renal biopsy provides a gold standard; however, it is difficult for this to be conducted in all patients. Therefore, it is necessary to discover non-invasive biomarkers that can distinguish between DN and NDRD. In this research, the urinary exosomes were isolated from the midstream morning urine based on ultracentrifugation combined with 0.22 μm membrane filtration. Data-independent acquisition-based quantitative proteomics were used to define the proteome profile of urinary exosomes from DN (n = 12) and NDRD (n = 15) patients diagnosed with renal biopsy and Type 2 diabetes mellitus (T2DM) patients without renal damage (n = 9), as well as healthy people (n = 12). In each sample, 3372 ± 722.1 proteins were identified on average. We isolated 371 urinary exosome proteins that were significantly and differentially expressed between DN and NDRD patients, and bioinformatic analysis revealed them to be mainly enriched in the immune and metabolic pathways. The use of least absolute shrinkage and selection operator (LASSO) logistic regression further identified phytanoyl-CoA dioxygenase domain containing 1 (PHYHD1) as the differential diagnostic biomarker, the efficacy of which was verified with another cohort including eight DN patients, five NDRD patients, seven T2DM patients, and nine healthy people. Additionally, a concentration above 1.203 μg/L was established for DN based on the ELISA method. Furthermore, of the 19 significantly different expressed urinary exosome proteins selected by using the protein–protein interaction network and LASSO logistic regression, 13 of them were significantly related to clinical indicators that could reflect the level of renal function and hyperglycemic management.

Discriminating between diabetic nephropathy (DN) and non-diabetic renal disease (NDRD) can help provide more specific treatments. However, there are no ideal biomarkers for their differentiation. Thus, the aim of this study was to identify biomarkers for diagnosing and predicting the progression of DN by investigating different salivary glycopatterns. Lectin microarrays were used to screen different glycopatterns in patients with DN or NDRD. The results were validated by lectin blotting. Logistic regression and artificial neural network analyses were used to construct diagnostic models and were validated in in another cohort. Pearson's correlation analysis, Cox regression, and Kaplan-Meier survival curves were used to analyse the correlation between lectins, and disease severity and progression. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) and bioinformatics analyses were used to identify corresponding glycoproteins and predict their function. Both the logistic regression model and the artificial neural network model achieved high diagnostic accuracy. The levels of Aleuria aurantia lectin (AAL), Lycopersicon esculentum lectin (LEL), Lens culinaris lectin (LCA), Vicia villosa lectin (VVA), and Narcissus pseudonarcissus lectin (NPA) were significantly correlated with the clinical and pathological parameters related to DN severity. A high level of LCA and a low level of LEL were associated with a higher risk of progression to end-stage renal disease. Glycopatterns in the saliva could be a non-invasive tool for distinguishing between DN and NDRD. The AAL, LEL, LCA, VVA, and NPA levels could reflect the severity of DN, and the LEL and LCA levels could indicate the prognosis of DN.

Diabetic nephropathy (DN) is a major microvascular complication of both type 1 and type 2 diabetes mellitus and is the most frequent cause of end-stage renal disease with an increasing prevalence. Presently there is no non-invasive method for differential diagnosis, and an efficient target therapy is lacking. Extracellular vesicles (EV), including exosomes, microvesicles, and apoptotic bodies, are present in various body fluids such as blood, cerebrospinal fluid, and urine. Proteins in EV are speculated to be involved in various processes of disease and reflect the original cells’ physiological states and pathological conditions. This systematic review is based on urinary extracellular vesicles studies, which enrolled patients with DN and investigated the proteins in urinary EV. We systematically reviewed articles from the PubMed, Embase, Web of Science databases, and China National Knowledge Infrastructure (CNKI) database until January 4, 2022. The article quality was appraised according to the Newcastle-Ottawa Quality Assessment Scale (NOS). The methodology of samples, isolation and purification techniques of urinary EV, and characterization methods are summarized. Molecular functions, biological processes, and pathways were enriched in all retrievable urinary EV proteins. Protein-protein interaction analysis (PPI) revealed pathways of potential biomarkers. A total of 539 articles were retrieved, and 13 eligible records were enrolled in this systematic review and meta-analysis. And two studies performed mass spectrometry to obtain the proteome profile. Two of them enrolled only T1DM patients, two studies enrolled both patients with T1DM and T2DM, and other the nine studies focused on T2DM patients. In total 988 participants were enrolled, and DN was diagnosed according to UACR, UAER, or decreased GFR. Totally 579 urinary EV proteins were detected and 28 of them showed a potential value to be biomarkers. The results of bioinformatics analysis revealed that urinary EV may participate in DN through various pathways such as angiogenesis, biogenesis of EV, renin-angiotensin system, fluid shear stress and atherosclerosis, collagen degradation, and immune system. Besides that, it is necessary to report results compliant with the guideline of ISEV, in orderto assure repeatability and help for further studies. This systematic review concordance with previous studies and the results of meta-analysis may help to value the methodology details when urinary EV proteins were reported, and also help to deepen the understanding of urinary EV proteins in DN.

随着我国老龄化进程的加快,老年医学的重要性日益凸显,老年科患者中肿瘤患者占据了较大比例,亟需专业的老年肿瘤学医生来保障老年肿瘤患者的健康.我国老年学专科化起步较晚,老年肿瘤学是一个年轻的学科,同时具备扎实的肿瘤学以及老年医学专科知识及丰富实践经验的医生非常少.重视老年肿瘤学青年医师的培养对于老年肿瘤学的发展具有重大意义.在培养过程中,应当施行具有针对性的专业培养模式,鼓励青年医生参加多学科合作讨论.强化整合医疗思维,扎实共病管理,实践缓和医疗.制定合理的培训制度,注重培养过程及结果考核,全面提高老年肿瘤学青年医生的综合素质.

Second-line treatment options for advanced/metastatic non-small cell lung cancer (NSCLC) patients are limited. We aimed to evaluate the efficacy and safety of docetaxel/sodium cantharidinate combination vs. either agent alone as second-line treatment for advanced/metastatic NSCLC patients with wild-type or unknown EGFR status. A randomized, open-label, phase III study was performed at 12 institutions. Patients with failure of first-line platinum regimens were randomized to receive either single-agent sodium cantharivsdinate (SCA) or single-agent docetaxel (DOX) or docetaxel/sodium cantharidinate combination (CON). The primary endpoints were centrally confirmed progression-free survival (PFS) and overall survival (OS). The secondary endpoints were objective response rate (ORR), disease control rate (DCR), quality of life (QoL) and toxicity. A total of 148 patients were enrolled in our study between October 2016 and March 2020. After a median follow-up time of 8.02 months, no significant difference was observed among the three groups in ORR (SCA vs. DOX vs. CON: 6.00% vs. 8.33% vs. 10.00%, respectively; p=0.814) and DCR (74.00% vs. 52.00% vs. 62.50%, respectively; p=0.080). In additional, the mOS was significantly higher in the CON group, compared with the single-agent groups (7.27 vs. 5.03 vs. 9.83 months, respectively; p=0.035), while no significant differences were observed in terms of PFS (2.7 vs. 2.9 vs. 3.1 months, respectively; p=0.740). There was no significant difference in the baseline QoL scores between the three groups (p>0.05); after treatment, life quality in SCA and CON group was significantly better than that in the DOX group (p<0.05). Furthermore, the incidence of adverse events (AEs) in the SCA group was significantly lower (46.00 vs. 79.17 vs. 25.00%, respectively; p=0.038) and the incidence of grade ≥3 AEs was also significantly lower in the SCA group compared with the DOX and CON groups (10.00 vs. 82.00 vs. 30.00%, respectively; p=0.042). Single-agent SCA and single-agent DOX has similar therapeutic efficacy in the second-line treatment of advanced/metastatic NSCLC with wild-type or unknown EGFR status, but single-agent SCA has fewer AEs and better QoL. Also, SCA plus DOX can significantly improve OS and exerted a significant synergistic effect, with good safety and tolerance profile.

With the development of the aging population, the concept of elderly co-morbidity management has been widely used. Based on the basic concept of co-morbidity management, the authors discussed how to apply the concept into the development and teaching practice of geriatric oncology. It is important to improve the teachers' understanding of the concept of geriatric co-morbidity management. In order to lay the foundation for better solving the elderly cancer specialty diseases, diversified teaching methods and educational technologies should be adopted to cultivate students' thinking of co-morbidity management; the continuing education of co-morbidity management should be actively carried out for young doctors.

Abstract Background Patients with both diabetes mellitus (DM) and kidney disease could have diabetic nephropathy (DN) or non-diabetic renal disease (NDRD). IgA nephropathy (IgAN) and membranous nephropathy (MN) are the major types of NDRD. No ideal noninvasive diagnostic model exists for differentiating them. Our study sought to construct diagnostic models for these diseases and to identify noninvasive biomarkers that can reflect the severity and prognosis of DN. Methods The diagnostic models were constructed using logistic regression analysis and were validated in an external cohort by receiver operating characteristic curve analysis method. The associations between these microRNAs and disease severity and prognosis were explored using Pearson correlation analysis, Cox regression, Kaplan–Meier survival curves, and log-rank tests. Results Our diagnostic models showed that miR-95-3p, miR-185-5p, miR-1246, and miR-631 could serve as simple and noninvasive tools to distinguish patients with DM, DN, DM with IgAN, and DM with MN. The areas under the curve of the diagnostic models for the four diseases were 0.995, 0.863, 0.859, and 0.792, respectively. The miR-95-3p level was positively correlated with the estimated glomerular filtration rate (p < 0.001) but was negatively correlated with serum creatinine (p < 0.01), classes of glomerular lesions (p < 0.05), and scores of interstitial and vascular lesions (p < 0.05). However, the miR-631 level was positively correlated with proteinuria (p < 0.001). A low miR-95-3p level and a high miR-631 level increased the risk of progression to end-stage renal disease (p = 0.002, p = 0.011). Conclusions These four microRNAs could be noninvasive tools for distinguishing patients with DN and NDRD. The levels of miR-95-3p and miR-631 could reflect the severity and prognosis of DN.

Netrin-1,an axon guidance factor,and its receptor UNC5B play important roles in axonal development and angiogenesis.This study examined netrin-1 and UNC5B expression in kidneys with diabetic kidney disease (DKD) and investigated their roles in angiogenesis.Netrin-1 and UNC5B were upregulated in streptozotocininduced DKD Wistar rats,and their expression was compared with that in healthy controls.However,exogenous netrin-1 in UNC5B-depleted human renal glomerular endothelial cells (HRGECs) inhibited cell migration and tubulogenesis.This effect was likely associated with SRC pathway deactivation.Netrin-1 treatment also eliminated the pro-angiogenic effects of exogenous VEGF-165 on UNC5B-silenced HRGECs.These results indicate that UNC5B antagonizes netrin-1 and that UNC5B upregulation contributes partly to enhancing angiogenesis in DKD.Therefore,introducing exogenous netrin-1 and depleting endogenous UNC5B are potential strategies for reducing the incidence of early angiogenesis and mitigating kidney injury in DKD.

Mitochondrial injury and endoplasmic reticulum (ER) stress are considered to be the key mechanisms of renal ischemia-reperfusion (I/R) injury. Mitochondria are membrane-bound organelles that form close physical contact with a specific domain of the ER, known as mitochondrial-associated membranes. The close physical contact between them is mainly restrained by ER-mitochondria tethering complexes, which can play an important role in mitochondrial damage, ER stress, lipid homeostasis, and cell death. Several ER-mitochondria tethering complex components are involved in the process of renal I/R injury. A better understanding of the physical and functional interaction between ER and mitochondria is helpful to further clarify the mechanism of renal I/R injury and provide potential therapeutic targets. In this review, we aim to describe the structure of the tethering complex and elucidate its pivotal role in renal I/R injury by summarizing its role in many important mechanisms, such as mitophagy, mitochondrial fission, mitochondrial fusion, apoptosis and necrosis, ER stress, mitochondrial substance transport, and lipid metabolism.

长QT综合征(long QT syndrome,LQTS)又称复极延迟综合征,是指在心电图上表现为QT间期延长,临床上表现为心悸、晕厥且易产生恶性室性心律失常甚至心脏性猝死的一组综合征.LQTS根据病因可分为遗传性QT间期延长综合征和获得性QT间期延长综合征2种.12导联心电图QT间期延长(女性QTc>460 ms,男性QTc>450 ms)是LQTS的主要心电图特征,但并不是每次检查均会出现QT间期延长.因此,充分测量QT间期及多次复查心电图对LQTS诊断尤为重要.本文介绍间歇性QTc延长的LQTS 1例,并对其分型、机制及治疗进行讨论.

Background. This meta-analysis was performed to obtain a more comprehensive estimation of the role of the single nucleotide polymorphism (SNP) rs2241766 in the ADIPOQ gene in the occurrence of diabetic kidney disease (DKD). Methods. Relevant studies were identified from digital databases such as Embase, PubMed, Medline, Cochrane Library, Google Scholar, WanFang, and Chinese National Knowledge Infrastructure (CNKI). Odds ratios (ORs) with their corresponding 95% confidence intervals (95% CIs) were pooled by means of fixed- or random-effects models. Interstudy heterogeneity was examined using the Q test and I2 statistic, and sensitivity analysis was implemented to test the statistical stability of the overall estimates. Begg’s funnel plot and Egger’s test were applied to inspect potential publication bias among the included studies. Results. The overall ORs reflected a positive correlation between the ADIPOQ rs2241766 polymorphism and susceptibility to DKD in the GG vs. TT and GG vs. TT+TG comparisons (OR=1.51, 95%CI=1.16−1.95; OR=1.43, 95%CI=1.11−1.85). After stratification analyses by ethnicity and disease type, a similar trend was also revealed in the Caucasian and African subgroups as well as in the type 2 diabetes mellitus (T2DM) subgroup. Conclusion. The ADIPOQ rs2241766 polymorphism may be associated with an increased risk of DKD, especially in Caucasian and African populations as well as in T2DM patients.

BACKGROUND:The 2017 high blood pressure (BP) clinical practice guideline reported by the American College of Cardiology/American Heart Association put forward new categories of BP. This study aimed to assess the applicability of the new guideline in a nondialysis chronic kidney disease (CKD) population.METHODS:This is a nationwide, multicenter, cross-sectional study with a large sample. A total of 8927 nondialysis CKD patients in 61 tertiary hospitals in all 31 provinces, municipalities and autonomous regions of China (except Hong Kong, Macao and Taiwan) were analyzed. The categories of BP were defined as normal BP (<120/80 mmHg), elevated BP [systolic BP (SBP) 120-130 and diastolic BP (DBP) <80 mmHg], and Stage 1 (SBP 130-139 or DBP 80-89 mmHg) and Stage 2 (SBP ≥140 or DBP ≥90 mmHg) hypertension. The prevalence and control of hypertension were estimated using a new definition, and the association between the main target organs' injury and new categories of BP was analyzed.RESULTS:The prevalence, awareness and treatment of hypertension in nondialysis CKD patients were 79.8, 72.4 and 68.3%, respectively. Approximately 11.9% had BP <130/80 mmHg and 6.6% had BP <120/80 mmHg. Subgroups by categories of BP had significant differences in age, sex, body mass index category, primary cause and CKD stage (P < 0.001). After multivariable adjustment, only Stage 2 hypertension was associated with decreased renal function [odds ratio (OR) 2.4, 95% confidence interval (CI) 1.9-3.0, P < 0.001], cardiovascular disease (OR 2.0, 95% CI 1.3-3.1, P = 0.001) and cerebrovascular disease (OR 2.7, 95% CI 1.2-5.8, P = 0.015).CONCLUSIONS:Using the new definition of hypertension, the higher prevalence and lower control of hypertension were shown in nondialysis CKD participants. More studies are necessary to confirm the applicability of new categories of BP in CKD population because only Stage 2 hypertension showed statistical association with the main target organs' injury.

Background: Immunoglobulin A nephropathy (IgAN) is the most common pathological type of glomerular disease. Kidney biopsy, the gold standard for IgAN diagnosis, has not been routinely applied in hospitals worldwide due to its invasion nature. Thus, we aim to establish a non-invasive diagnostic model and determine markers to evaluate disease severity by analyzing the serological parameters and pathological stages of patients with IgAN. Methods: A total of 272 biopsy-diagnosed IgAN inpatients and 518 non-IgA nephropathy inpatients from the Department of Nephrology of Chinese People's Liberation Army General Hospital were recruited for this study. Routine blood examination, blood coagulation testing, immunoglobulin-complement testing, and clinical biochemistry testing were conducted and pathological stages were analyzed according to Lee grading system. The serological parameters and pathological stages were analyzed. The receiver operating characteristic (ROC) analysis was performed to estimate the diagnostic value of the clinical factors. Logistic regression was as used to establish the diagnostic model. Results: There were 15 significantly different serological parameters between the IgAN and non-IgAN groups (all P< 0.05). The ROC analysis was performed to measure the diagnostic value for IgAN of these parameters and the results showed that the area under the ROC curve (AUC) of total protein (TP), total cholesterol (TC), fibrinogen (FIB), D-dimer (D2), immunoglobulin A (IgA), and immunoglobulin G (IgG) were more than 0.70. The AUC of the "TC+ FIB + D2 + IgA + age" combination was 0.86, with a sensitivity of 85.98% and a specificity of 73.85%. Pathological grades of l,ll,lll, lV, and V accounted for 2.21%, 17.65%, 62.50%, 11.76%, and 5.88%, respectively, with grade III being the most prevalent. The levels of urea nitrogen (UN) (13.57 +/- 5.95 vs. 6.06 +/- 3.63, 5.92 +/- 2.97, 5.41 +/- 1.73, and 8.41 +/- 3.72 mmol/L, respectively) and creatinine (Cr) (292.19 +/- 162.21 vs. 80.42 +/- 24.75, 103.79 +/- 72.72, 96.41 +/- 33.79, and 163.04 +/- 47.51 mu mol/L, respectively) were significantly higher in grade V than in the other grades, and the levels of TP (64.45 +/- 7.56, 67.16 +/- 6.94, 6122 +/- 8.56, and 61.41 +/- 10.86 vs. 37.47 +/- 5.6 mgjd, respectively), direct bilirubin (DB) (2.34 +/- 1.23, 2.58 +/- 1.40, 1.91 +/- 0.97, and 1.81 +/- 1.44 vs. 0.74 +/- 0.57 mu mol/L, respectively), and IgA (310.35 +/- 103.78, 318.48+107.54, 292.58 +/- 81.85, and 323.29 +/- 181.67 vs. 227.17 +/- 68.12 g/L, respectively) were significantly increased in grades II-V compared with grade I (all P < 0.05). Conclusion: The established diagnostic model that combined multiple factors (TC, FIB, D2, IgA, and age) might be used for IgAN non-invasive diagnosis. TP, DB, IgA, Cr, and UN have the potential to be used to evaluate IgAN disease severity.

BACKGROUND:Accurate estimation of the glomerular filtration rate (GFR) and staging of chronic kidney disease (CKD) are important. Currently, there is no research on the differences in several estimated GFR equations for staging CKD in a large sample of centenarians. Thus, this study aimed to investigate the differences in CKD staging with the most commonly used equations and to analyze sources of discrepancy. METHODS:A total of 966 centenarians were enrolled in this study from June 2014 to December 2016 in Hainan province, China. The GFR with the Modification of Diet in Renal Disease (MDRD), Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Berlin Initiative Study 1 (BIS1) equations were estimated. Agreement between these equations was investigated with the κ statistic and Bland-Altman plots. Sources of discrepancy were investigated by partial correlation analysis. RESULTS:The κ values of the MDRD and CKD-EPI equations, MDRD and BIS1 equations, and CKD-EPI and BIS1 equations were 0.610, 0.253, and 0.381, respectively. Serum creatinine (Scr) explained 10.96%, 41.60% and 17.06% of the variability in these three comparisons, respectively. Serum uric acid (SUA) explained 3.65% and 5.43% of the variability in the first 2 comparisons, respectively. Gender was associated with significant differences in these 3 comparisons (P < 0.001). CONCLUSIONS:The strengths of agreement between the MDRD and CKD-EPI equations were substantial, but those between the MDRD and BIS1 equations and the CKD-EPI and BIS1 equations were fair. The difference in CKD staging of the first 2 comparisons strongly depended on Scr, SUA and gender, and that of CKD-EPI and BIS1 equations strongly depended on Scr and gender. The incidence at various stages of CKD staging was quite different. Thus, a new equation that is more suitable for the elderly needs to be built in the future.