Association between Kidney Stones and CKD: A Bidirectional Mendelian Randomization Study.

BACKGROUND: Kidney stones and CKD are common disorders with a substantial interaction. Although observational studies have suggested a potential for enhanced CKD risk after prior kidney stones, the exact relationship remains ambiguous. METHODS: Shared comorbidities between two diseases were identified using unbiased screening. Genome-wide association study summary statistics were obtained from the UK Biobank (UKBB), FinnGen, and CKDGen, followed by genetic association analyses across various traits. Bidirectional Mendelian randomization (MR) analyses were performed to define causal links, complemented by multivariable MR that included the shared comorbidities including hypertension, diabetes, and obesity. Observational analyses were undertaken using cohorts from the Mayo Clinic and a UKBB subset. RESULTS: Despite identifying a total of 123 conditions as shared comorbidities, there was no significant genetic correlation between kidney stones and CKD. Unadjusted MR analysis revealed no significant association between kidney stones and CKD risk (UKBB [exposure]/FinnGen [outcome]: OR=0.97, 95% CI: 0.88∼1.06; FinnGen/UKBB: OR=1.17, 95% CI:0.98∼1.39). Kidney stones did significantly associate with a higher urinary albumin-creatinine ratio (UACR) (ß=0.014, 95% CI: 0.002∼0.025), but this association disappeared in the multivariable MR model (ß=0.009, 95% CI: -0.003∼0.020). Furthermore, in a cross-sectional analysis limited to the UKBB cohort, a robust regression model did not detect an independent association between kidney stones and UACR (ß=0.16, 95% CI: -0.04∼0.35) or eGFR (ß=0.10, 95% CI: -0.07∼0.28). Conversely, CKD associated with a diminished risk of kidney stones in multivariable MR models (UKBB/FinnGen: OR=0.77, 95% CI: 0.69∼0.87; FinnGen/UKBB: OR=0.73, 95% CI: 0.66∼0.81). Furthermore, in the Mayo Clinic cohort with available urinary biochemistries, lower eGFR was associated with lower urinary calcium excretion and urinary calcium oxalate/phosphate supersaturation. CONCLUSIONS: In this study, kidney stones were not independently associated with CKD. Conversely, CKD was associated with a lower risk of calcium kidney stones likely via changes in key urinary traits, including lower calcium excretion.

Fructose-1, 6-Bisphosphate Aldolase B Suppresses Glycolysis and Tumor Progression of Gastric Cancer.

OBJECTIVE: Gastric cancer (GC) is believed to be one of the most common digestive tract malignant tumors. However, mounting evidence indicates a link between the glycolysis and tumorigenesis, including gastric cancer. METHODS: Our research identified 5508 differently expressed mRNAs in gastric cancer. Then, the genes highly associated with tumorigenesis were identified through weighted correlation network analysis (WGCNA). Bioinformatics analysis observed that these hub genes were significantly linked to the regulation of cell cycle, drug metabolism, and glycolysis. Among these hub genes, there is a critical gene involved in glycolysis regulation, namely fructose-bisphosphate B (ALDOB). RESULTS: Analysis based on The Cancer Genome Atlas (TCGA) and three Gene Expression Omnibus (GEO) datasets revealed that ALDOB was significantly downregulated in GC compared with normal tissues. In addition, cell viability assay confirmed that ALDOB acted as a tumor suppressor. Finally, drug sensitivity analysis revealed that ALDOB increased the sensitivity of gastric cancer cells to most antitumor drugs, especially talazoparib, XAV939, and FTI-277. Our results showed that the expression of ALDOB was significantly lower in GC tissues than in normal tissues. And ALDOB significantly inhibited proliferation and migration, delayed glycolysis in GC cells. Consequently, our study suggests that ALDOB may be a potential target for the clinical treatment of gastric cancer.

[Intrinsic "self-consistent" phenomenon based on holistic view of traditional Chinese medicine].

The fundamental principle of traditional Chinese medicine(TCM) is holism, and it is crucial for TCM to address the key issue of the "holistic view" of Chinese herbal medicine. While the overall regulatory effects of Chinese herbal medicine have been widely recognized, the holistic internal logic of individual ingredients of Chinese herbal medicines require further clarification. In order to comprehensively understand the mechanism of action of Chinese herbal medicine, this paper combined the holistic view of Chinese herbal medicine with differentiation thinking to explore the intrinsic logical relationships within Chinese herbal medicine. Starting from the perspective of the coexistence of multiple components in Chinese herbal medicine, this paper systematically examined the "self-consistent" phenomenon within single Chinese herbal medicine. This phenomenon refers to the consistent or opposing actions of various components in terms of their physical and chemical properties, pharmacokinetic effects, biological effects, flavors and properties, and TCM efficacy. The paper summarized various logical relationships of syndrome differentiation exhibited by the same Chinese herbal medicine, analyzed the underlying reasons, and focused on analyzing external factors affecting the "self-consistent" phenomenon in the efficacy of Chinese herbal medicine, aiming to better elucidate the theoretical basis of the pharmacological effects of Chinese herbal medicine, further enrich the scientific connotation of the holistic view of Chinese herbal medicine, and provide theoretical guidance for the preparation process, compatibility patterns, and formulation design of Chinese herbal medicine.

The Correlation between Ferroptosis and m6A Methylation in Patients with Acute Kidney Injury.

OBJECTIVE: The present research analyzed the correlation between N6-methyladenosine (m6A) methylation and ferroptosis associated genes (FAGs) in acute kidney injury (AKI) patients. METHODS: Bioinformatics analysis of microarray profiles (GSE30718) was performed to select differential expression genes (DEGs). FAGs are derived from systematic analysis of the aberrances and functional implications. The m6A methylation related genes were derived from the molecular characterization and clinical significance of m6A modulators. The multi-gene correlation of ferroptosis and M6A methylation modification was displayed. Then, the CIBERSORT algorithm was used to analyze the proportions of 22 immune cell infiltration. RESULTS: In total, 349 DEGs were extracted between the AKI and control samples, among which 172 genes were upregulated and 177 were downregulated. FAGs (SLC1A5, CARS, SAT1, ACSL4, NFE2L2, TFRC, and MT1G) and m6A methylation related genes (YTHDF3, WTAP, and IGF2BP3) were significantly increased in AKI patients (p < 0.05). FAGs (SAT1, ACSL4, and NFE2L2) were positively correlated with the expression level of m6A methylation genes (p < 0.05). NFE2L2 has high diagnostic value, and the level of NFE2L2 was negatively correlated with the degree of follicular helper T (TFH) cell infiltration. CONCLUSION: Our research could provide a new theoretical basis for the pathogenesis and immune mechanism of AKI.

[Rapid determination of active components in Ginkgo biloba leaves by near infrared spectroscopy combined with genetic algorithm joint extreme learning machine].

Near-infrared spectroscopy(NIRS) combined with band screening method and modeling algorithm can be used to achieve the rapid and non-destructive detection of the traditional Chinese medicine(TCM) production process. This paper focused on the ginkgo leaf macroporous resin purification process, which is the key technology of Yinshen Tongluo Capsules, in order to achieve the rapid determination of quercetin, kaempferol and isorhamnetin in effluent. The abnormal spectrum was eliminated by Mahalanobis distance algorithm, and the data set was divided by the sample set partitioning method based on joint X-Y distances(SPXY). The key information bands were selected by synergy interval partial least squares(siPLS); based on that, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA) and Monte Carlo uninformative variable(MC-UVE) were used to select wavelengths to obtain less but more critical variable data. With selected key variables as input, the quantitative analysis model was established by genetic algorithm joint extreme learning machine(GA-ELM) algorithm. The performance of the model was compared with that of partial least squares regression(PLSR). The results showed that the combination with siPLS-CARS-GA-ELM could achieve the optimal model performance with the minimum number of variables. The calibration set correlation coefficient R_c and the validation set correlation coefficient R_p of quercetin, kaempferol and isorhamnetin were all above 0.98. The root mean square error of calibration(RMSEC), the root mean square error of prediction(RMSEP) and the relative standard errors of prediction(RSEP) were 0.030 0, 0.029 2 and 8.88%, 0.041 4, 0.034 8 and 8.46%, 0.029 3, 0.027 1 and 10.10%, respectively. Compared with the PLSR me-thod, the performance of the GA-ELM model was greatly improved, which proved that NIRS combined with GA-ELM method has a great potential for rapid determination of effective components of TCM.

[Critical quality attribute assessment of big brand traditional Chinese medicine: study on NIR field detection method of chemical properties of moisture in Tongren Niuhuang Qingxin Pills].

For the field detection problems of critical quality attribute(CQA) of moisture content in traditional Chinese medicine(TCM) manufacturing process, big brand TCM Tongren Niuhuang Qingxin Pills were used as the carrier, to establish a moisture content NIR field detection model with or without cellophane in real world production with use of near infrared(NIR) spectroscopy combined with stoichiometry. With the moisture content determined by drying method as reference value, the partial least square method(PLS) was used to analyze the correlation between the spectrum and the moisture reference value. Then the spectral pretreatment methods were screened and optimized to further improve the accuracy and stability of the model. The results showed that the best quantitative model was developed by the spectral data pretreatment of standard normal variate(SNV) with the latent variable factor number of 2 and 7 of Tongren Niuhuang Qingxin Pills with or without cellophane samples. The prediction coefficient of determination(R_(pre)~2) and standard deviation of prediction(RMSEP) of the model with cellophane samples were 0.765 7 and 0.157 2%; R_(pre)~2 and RMSEP of the model without cellophane samples were 0.772 2 and 0.207 8%. The NIR quantitative models of moisture content of Tongren Niuhuang Qingxin Pills with and without cellophane both showed good predictive performance to realize the rapid, accurate and non-destructive quantitative analysis of moisture content in such pills, and provide a method for the field quality control of the critical chemical attributes of moisture in the manufacturing of big brand TCM.

[Critical quality attribute assessment of big brand traditional Chinese medicine: modular identification of Tongren Niuhuang Qingxin Pills based on efficacy with chemical properties].

Identification of critical quality attribute(CQA) is crucial in quality control of Tongren Niuhuang Qingxin Pills(TRNHQXP). In this study, 661 active components in TRNHQXP were selected by liquid chromatography-mass spectrometry(LC-MS) and network pharmacology based on reported data and TCMSP, BATMAN-TCM, and TCMID databases, as well as mass spectrometry data, and 1 413 targets of the active components were obtained through SwissTargetPrediction. The 152 potential targets obtained from the intersection of predicted targets with 456 stroke targets underwent functional enrichment analysis by Metascape. The 27 Chinese medicinals in TRNHQXP were divided into four sets according to efficacies. Thirty-seven key targets in the blood-activating and stasis-resolving set and 41 in the tonifying set were screened out. On the basis of these potential key targets, 137 potential key CQA of TRNHQXP for stroke were reversely predicted. This study revealed the possible mechanism of TRNHQXP in treating stroke and established a modular identification method for the potential CQA of big brand traditional Chinese medicine(TCM) based on efficacies and chemical properties. Consequently, the CQA of TRNHQXP were identified by this method, which has provided a reference for the following experimental studies of CQA.

[Criticalquality attribute assessment of big brand traditional Chinese medicine: visualization method for quality control of Ginkgo Leaves Tablets based on spatial distribution uniformity].

Spatial distribution uniformity is the critical quality attribute(CQA) of Ginkgo Leaves Tablets, a variety of big brand traditional Chinese medicine. The evaluation of the spatial distribution uniformity of active pharmaceutical ingredients(APIs) in Ginkgo Leaves Tablets is important in ensuring their stable and controllable quality. In this study, hyperspectral imaging technology was used to construct the spatial distribution map of API concentration based on three prediction models, further to realize the visualization research on the spatial distribution uniformity of Ginkgo Leaves Tablets. The region of interest(ROI) was selected from each Ginkgo Leaves Tablet, with length and width of 50 pixels, and a total of 2 500 pixels. Each pixel had 288 spectral channels, and the number of content prediction data could reach 1×10~5 for a single sample. The results of the three models showed that the Partial Least Squares(PLS) model had the highest prediction accuracy, with calibration set determination coefficient R_(pre)~2 of 0.987, prediction set determination coefficient R_(pre)~2 of 0.942, root mean square error of calibration(RMSEC) of 0.160%, and root mean square error of prediction(RMSEP) of 0.588%. The classical least-squares(CLS) model had a greater prediction error, with the RMSEP of 0.867%. Multivariate Curve Resolution-Alternating Least Square(MCR-ALS) model showed the worst predictive ability among the three models, and it couldn't realize content prediction. Based on the prediction results of PLS and CLS models, the spatial distribution map of APIs concentration was obtained through three-dimensional data reconstruction. Furthermore, histogram method was used to evaluate the spatial distribution uniformity of API. The data showed that the spatial distribution of APIs in Ginkgo Leaves Tablets was relatively uniform. The study explored the feasibility of visualization of spatial distribution of Ginkgo Leaves Tablets based on three models. The results showed that PLS model had the highest prediction accuracy, and MCR-ALS model had the lowest prediction accuracy. The research results could provide a new strategy for the visualization method of quality control of Ginkgo Leaves Tablets.

Dopamine D1 receptor agonist A68930 attenuates acute kidney injury by inhibiting NLRP3 inflammasome activation.

Renal ischemia/reperfusion (I/R) injury is a major cause of acute kidney injury (AKI), characterized by tubulointerstitial inflammation. Currently, progress in developing effective therapies to prevent or ameliorate AKI by anti-inflammation remains slow. Emerging studies have suggested that NLRP3 (the NOD-, LRR- and pyrin domain-containing 3) inflammasome plays a key role in a wide spectrum of kidney disease models including I/R injury. In this study, we investigated the renal protective effects of A68930, a specific agonist for the D-1 dopamine receptor (DRD1), which was recently recognized to downregulate NLRP3 inflammasome via DRD1 signaling. AKI was induced by renal I/R injury and A68930 was intraperitoneally injected 3 times after renal reperfusion. We showed that A68930 significantly ameliorated renal dysfunction. Meanwhile, A68930 markedly reduced macrophages and T cells infiltration, renal pro-inflammatory cytokines production (TNF-α, IL-6, IL-1ß), serum pro-inflammatory cytokine (TNF-α and IL-6) and NLRP3 inflammasome activation. Additionally, A68930 attenuated I/R-induced mitochondria injury, which was observed by transmission electron microscopy. In summary, our results demonstrated that activation of DRD1 by A68930 inhibited renal and systematic inflammation, and improved kidney function in I/R induced AKI model, which was probably related to the inhibition of the NLRP3 inflammasome activation.

Effect of hypoxia-inducible factor-prolyl hydroxylase inhibitors on anemia in patients with CKD: a meta-analysis of randomized controlled trials including 2804 patients.

Hypoxia-inducible factor-prolyl hydroxylase inhibitors (HIF-PHIs) are orally active first-in-class new generation drugs for renal anemia. This extensive meta-analysis of randomized controlled trials (RCTs) was designed to provide clear information on the efficacy and safety of HIF-PHIs on anemia in chronic kidney disease (CKD) patients. Searches included PubMed, Web of Science, Ovid MEDLINE, and Cochrane Library database up to October 2019. RCTs of patients with CKD comparing HIF-PHIs with erythropoiesis-stimulating agents (ESAs) or placebo in the treatment of anemia. The primary outcome was hemoglobin change from baseline (Hb CFB); the secondary outcomes included iron-related parameters and the occurrence of each adverse event. 26 trials in 17 articles were included, with a total of 2804 dialysis or patients with CKD. HIF-PHIs treatment produced a significant beneficial effect on Hb CFB compared with the placebo group (MD, 0.69; 95% CI, 0.36 to 1.02). However, this favored effect of HIF-PHIs treatment was not observed in subgroup analysis among trials compared with ESAs (MD, 0.06; 95% CI, -0.20 to 0.31). The significant reduction in hepcidin by HIF-PHIs was observed in all subgroups when compared with the placebo group, whereas this effect was observed only in NDD-CKD patients when compared with ESAs. HIF-PHIs increased the risk of nausea (RR, 2.20; 95% CI, 1.06 to 4.53) and diarrhea (RR, 1.75; 95% CI, 1.06 to 2.92). We conclude that orally given HIF-PHIs are at least as efficacious as ESAs treatment to correct anemia short term in patients with CKD. In addition, HIF-PHIs improved iron metabolism and utilization in patients with CKD.

Artemisinin attenuates tubulointerstitial inflammation and fibrosis via the NF-κB/NLRP3 pathway in rats with 5/6 subtotal nephrectomy.

Artemisinin (Art) is isolated from Artemisia annua L. and known as the most effective antimalaria drugs. Previous studies demonstrated that it could exert an immune-regulatory effect on autoimmune diseases. In this study, we first investigated its potential role in tubulointerstitial inflammation and fibrosis in rats with 5/6 nephrectomy. Subtotal nephrectomized (SNx) rats were orally administered Art (100 mg·kg -1 ·d - 1) for 16 weeks. Blood and urine samples were collected for biochemical examination. Kidney tissues were collected for immunohistochemistry and Western blot analyses. Ang II-induced injury of the human kidney 2 (HK-2) cells was used for in vitro study. It was shown that Art could significantly attenuate the renal function decline in SNx rats compared with control. More importantly, Art treatment significantly reduced the tubulointerstitial inflammation and fibrosis, as demonstrated by the evaluation of renal pathology. Furthermore, Art inhibited the activation of NLRP3 inflammasome and NF-κB in the kidneys. In in vitro study, Art pretreatment could significantly prevent the activation of NLRP3 inflammasome and NF-κB in Ang II-treated HK-2 cells, while BAY11-7082 (an inhibitor of NF-κB) significantly inhibited Ang II-induced NLRP3 inflammasome activation. This study suggested that Art could provide renoprotective role by attenuating the tubulointerstitial inflammation and fibrosis in SNx rats by downregulating the NF-κB/NLRP3 signaling pathway.

HIF-1α inducing exosomal microRNA-23a expression mediates the cross-talk between tubular epithelial cells and macrophages in tubulointerstitial inflammation.

Hypoxia promotes tubulointerstitial inflammation in the kidney. Although hypoxia inducible factor-1α (HIF-1α) is a master regulator of the response to hypoxia, the exact mechanisms through which HIF-1α modulates the induction of tubulointerstitial inflammation are still largely unclear. We demonstrated tubulointerstitial inflammation and increased tubular HIF-1α expression in murine models of ischemia/reperfusion injury and unilateral ureteral obstruction. Increased expression of HIF-1α in tubular epithelial cells was associated with selective shedding of microRNA-23a (miRNA-23a)-enriched exosomes in vivo and systemic inhibition of miRNA-23a prior to ischemia/reperfusion injury attenuated tubulointerstitial inflammation. In vitro, uptake of miRNA-23a-enriched exosomes by macrophages triggered their reprogramming into a pro-inflammatory state via suppression of the ubiquitin editor A20. To confirm the effect of miRNA-23a-containing exosomes on tubulointerstitial inflammation, we exposed tubular epithelial cells to hypoxic conditions to promote the release of miRNA-23a-containing exosomes. Injection of these miRNA-23a-enriched exosomes into uninjured renal parenchyma resulted in increased inflammatory infiltration in vivo. Taken together, our studies demonstrate that the HIF-1α-dependent release of miRNA-23a-enriched exosomes from hypoxic tubular epithelial cells activates macrophages to promote tubulointerstitial inflammation. Blockade of exosome-mediated miRNA-23a transfer between tubular epithelial cells and macrophages may serve as a novel therapeutic approach to ameliorate tubulointerstitial inflammation.

Bioinformatics-based discovery of the urinary BBOX1 mRNA as a potential biomarker of diabetic kidney disease.

BACKGROUND: Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease (ESKD) in the world. Emerging evidence has shown that urinary mRNAs may serve as early diagnostic and prognostic biomarkers of DKD. In this article, we aimed to first establish a novel bioinformatics-based methodology for analyzing the "urinary kidney-specific mRNAs" and verify their potential clinical utility in DKD. METHODS: To select candidate mRNAs, a total of 127 Affymetrix microarray datasets of diabetic kidney tissues and other tissues from humans were compiled and analyzed using an integrative bioinformatics approach. Then, the urinary expression of candidate mRNAs in stage 1 study (n = 82) was verified, and the one with best performance moved on to stage 2 study (n = 80) for validation. To avoid potential detection bias, a one-step Taqman PCR assay was developed for quantification of the interested mRNA in stage 2 study. Lastly, the in situ expression of the selected mRNA was further confirmed using fluorescent in situ hybridization (FISH) assay and bioinformatics analysis. RESULTS: Our bioinformatics analysis identified sixteen mRNAs as candidates, of which urinary BBOX1 (uBBOX1) levels were significantly upregulated in the urine of patients with DKD. The expression of uBBOX1 was also increased in normoalbuminuric diabetes subjects, while remained unchanged in patients with urinary tract infection or bladder cancer. Besides, uBBOX1 levels correlated with glycemic control, albuminuria and urinary tubular injury marker levels. Similar results were obtained in stage 2 study. FISH assay further demonstrated that BBOX1 mRNA was predominantly located in renal tubular epithelial cells, while its expression in podocytes and urothelium was weak. Further bioinformatics analysis also suggested that tubular BBOX1 mRNA expression was quite stable in various types of kidney diseases. CONCLUSIONS: Our study provided a novel methodology to identify and analyze urinary kidney-specific mRNAs. uBBOX1 might serve as a promising biomarker of DKD. The performance of the selected urinary mRNAs in monitoring disease progression needs further validation.

Urinary Exosomes and Exosomal CCL2 mRNA as Biomarkers of Active Histologic Injury in IgA Nephropathy.

IgA nephropathy (IgAN) features variable renal pathology and a heterogeneous clinical course. Our aim was to search noninvasive biomarkers from urinary exosomes for IgAN patients; membrane nephropathy and minimal change disease were included as other glomerulopathy controls. Transmission electron microscopy and nanoparticle tracking analysis confirmed the size and morphology characteristic of urinary exosomes. Exosome markers (Alix and CD63) as well as renal cell markers [aquaporin 2 (AQP2) and nephrin] were detected, which indicate the renal origin of urinary exosomes. Exosome excretion was increased markedly in IgAN patients compared with controls and correlated with levels of proteinuria and tubular injury. More important, urinary exosome excretion correlated with greater histologic activity (mesangial hypercellularity, crescents, and endocapillary hypercellularity). Profiling of the inflammation-related mRNA revealed that exosomal chemokine (C-C motif) ligand 2 (CCL2) was up-regulated in IgAN patients. In a validation study, CCL2 was exclusively highly expressed in IgAN patients compared with healthy controls as well as minimal change disease and membrane nephropathy patients. Also, a correlation between exosomal CCL2 and estimated glomerular filtration rate levels was found in IgAN. Exosomal CCL2 was correlated with tubulointerstitial inflammation and C3 deposition. High CCL2 levels at the time of renal biopsy were associated with subsequent deterioration in renal function. Thus, urinary exosomes and exosomal CCL2 mRNA are promising biomarkers reflecting active renal histologic injury and renal function deterioration in IgAN.

Urinary Biomarkers of Renal Fibrosis.

Renal fibrosis is the common pathological pathway of progressive CKD. The commonly used biomarkers in clinical practice are not optimal to detect injury or predict prognosis. Therefore, it is crucial to develop novel biomarkers to allow prompt intervention. Urine serves as a valuable resource of biomarker discovery for kidney diseases. Owing to the rapid development of omics platforms and bioinformatics, research on novel urinary biomarkers for renal fibrosis has proliferated in recent years. In this chapter, we discuss the current status and provide basic knowledge in this field. We present novel promising biomarkers including tubular injury markers, proteins related to activated inflammation/fibrosis pathways, CKD273, transcriptomic biomarkers, as well as metabolomic biomarkers. Furthermore, considering the complex nature of the pathogenesis of renal fibrosis, we also highlight the combination of biomarkers to further improve the diagnostic and prognostic performance.

Exosomal CCL2 from Tubular Epithelial Cells Is Critical for Albumin-Induced Tubulointerstitial Inflammation.

Albuminuria is a key instigator of tubulointerstitial inflammation associated with CKD, but the mechanism through which filtered albumin propagates renal injury remains unclear. In this study, we explored the role in this process of exosome mRNA released from tubular epithelial cells (TECs). Compared with control mice, acute and chronic kidney injury models had more exosomes containing inflammatory cytokine mRNA, particularly the chemokine CCL2, in kidneys and urine. In vitro stimulation of TECs with BSA recapitulated this finding. Notably, the internalization of purified TEC exosomes by cultured macrophages increased if TECs were exposed to BSA. Macrophage internalization of exosomes from BSA-treated TECs led to an enhanced inflammatory response and macrophage migration, but CCL2 silencing in TECs prevented these effects. Using a GFP-CCL2 fusion mRNA construct, we observed direct transfer of CCL2 mRNA from TEC exosomes to macrophages. Mice subjected to tail vein injection of purified BSA-treated TEC exosomes developed tubular injury with renal inflammatory cell infiltration. However, injection of exosomes from BSA-treated CCL2-deficient TECs induced less severe kidney inflammation. Finally, in patients with IgA nephropathy, the increase of proteinuria correlated with augmented urinary excretion of exosomes with exaggerated expression of CCL2 mRNA. Moreover, the level of CCL2 mRNA in urinary exosomes correlated closely with levels of renal interstitial macrophage infiltration in these patients. Our studies demonstrate that the increasing release of exosomes that transfer CCL2 mRNA from TECs to macrophages constitutes a critical mechanism of albumin-induced tubulointerstitial inflammation.

[Research of hospital preparations based on QbD concept: whole process optimization strategy of gynecological antipruritic lotion].

The stable quality of hospital preparations is the basis for their clinical efficacy. Gynecological antipruritic prescription is widely used in gynecology clinics of Chinese medicine hospitals. Therefore,in this study,the production process of gynecological antipruritic lotion was optimized based on the concept of quality by design( QbD). The production process of the gynecological antipruritic lotion was developed to ensure its process stability and reliable quality,and enhance its clinical applicability. With total amount of matrine and oxymatrine used as the critical quality attribute( CQA) of the production process,parameter levels were designed based on production practice of hospital preparations,and Plackett-Burman and Box-Behnken experiments were used to optimize the water extraction and alcohol precipitation process of antipruritic lotion based on CQA of intermediates and final product. The soaking time,the first extraction time,and the second extraction time were determined as the critical process parameters( CPPs) of the production process. The optimal preparation process was as follows: water volume of 8 times,soaking for 0. 5 h,extraction for 2 times,the first extraction for 30 min,the second extraction for 56 min,alcohol concentration of 50%,and alcohol precipitation for 3 h. Furthermore,the design space was established based on the binomial regress model between CPPs and CQA,so as to set the optimization target and risk range; and the control space was displayed by overlay plot. The results of three repeated experiments in the control space showed that the relative standard deviation( RSD) of CQA was 4. 70%,and the similarity of chromatogram for gynecological antipruritic lotion was 0. 978,0. 974,and 0. 998,respectively. The above results indicated that the operation in the control space can guarantee the quality and stability of gynecological antipruritic lotion,suitable for practical application.

Integrative Bioinformatics Analysis Provides Insight into the Molecular Mechanisms of Chronic Kidney Disease.

BACKGROUND/AIMS: Chronic kidney disease (CKD) is a worldwide public health problem. Regardless of the underlying primary disease, CKD tends to progress to end-stage kidney disease, resulting in unsatisfactory and costly treatment. Its common pathogenesis, however, remains unclear. The aim of this study was to provide an unbiased catalog of common gene-expression changes of CKD and reveal the underlying molecular mechanism using an integrative bioinformatics approach. METHODS: We systematically collected over 250 Affymetrix microarray datasets from the glomerular and tubulointerstitial compartments of healthy renal tissues and those with various types of established CKD (diabetic kidney disease, hypertensive nephropathy, and glomerular nephropathy). Then, using stringent bioinformatics analysis, shared differentially expressed genes (DEGs) of CKD were obtained. These shared DEGs were further analyzed by the gene ontology (GO) and pathway enrichment analysis. Finally, the protein-protein interaction networks(PINs) were constructed to further refine our results. RESULTS: Our analysis identified 176 and 50 shared DEGs in diseased glomeruli and tubules, respectively, including many transcripts that have not been previously reported to be involved in kidney disease. Enrichment analysis also showed that the glomerular and tubulointerstitial compartments underwent a wide range of unique pathological changes during chronic injury. As revealed by the GO enrichment analysis, shared DEGs in glomeruli were significantly enriched in exosomes. By constructing PINs, we identified several hub genes (e.g. OAS1, JUN, and FOS) and clusters that might play key roles in regulating the development of CKD. CONCLUSION: Our study not only further reveals the unifying molecular mechanism of CKD pathogenesis but also provides a valuable resource of potential biomarkers and therapeutic targets.

Downregulation of MTHFD2 Inhibits Proliferation and Enhances Chemosensitivity in Hepatocellular Carcinoma via PI3K/AKT Pathway.

BACKGROUND: Despite the substantial impact of methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) on cancer progression, its significance in the regulation of hepatocellular carcinoma (HCC) cell proliferation and chemosensitivity remains poorly defined. METHODS: We evaluated MTHFD2 expression in a total of 95 HCC tissues by immunohistochemistry and analyzed the association of MTHFD2 with clinicopathologic features. qRT-PCR and Western blotting were conducted to verify MTHFD2 expression levels. Bioinformatics analysis such as gene set enrichment analysis (GSEA) and kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis were used to predict the signaling pathways involved in MTHFD2. In addition, to investigate the anti-tumor effects of MTHFD2 knockdown, Cell Counting Kit-8 (CCK-8) and EdU assays were used. RESULTS: We found that MTHFD2 was frequently upregulated in HCC, and the combination of increased expression of MTHFD2 and Ki67 was associated with poor HCC prognosis. MTHFD2 knockdown significantly inhibited HCC cell proliferation and effectively sensitized HCC cells to sorafenib and lenvatinib. PI3K/AKT pathway was involved in MTHFD2-mediated modulation of proliferation and chemosensitivity. CONCLUSIONS: These findings indicate that MTHFD2 plays an important role in proliferation and chemosensitivity of HCC, indicating that it may serve as a novel pharmacological target for improving HCC therapy.

[Spatial scale effects of landscape patterns on non-point source pollution: A case study of Taizi River Basin in Northeast China]. / éžç‚¹æºæ±¡æŸ“å¯¹æ™¯è§‚æ ¼å±€å“åº”çš„ç©ºé—´å°ºåº¦æ•ˆåº”­­ä»¥ä¸œåŒ—太子河流域为例.

River water quality is influenced by natural processes and human activities. Multi-scale landscape patterns can affect river water quality by altering the generation and transport processes of pollutants at different spatial scales. Taking Taizi River Basin in Northeast China as an example, we analyzed the relationship between landscape patterns and non-point source pollution in rivers based on water quality monitoring data and land use data by using correlation analysis and redundancy analysis methods. We aimed to determine the key spatial scales for the responses of landscape patterns to non-point source pollution and identify the key landscape indices influencing river non-point source pollution. The results showed that water quality of Taizi River Basin had seasonal differences, with better water quality during the flood season than non-flood season. Spatially, total nitrogen (TN) and total phosphorus (TP) were higher at the confluence points of tributaries and downstream areas. The impact of landscape patterns on non-point source pollution was stronger during the non-flood season than the flood season, while the influence on TN was stronger than on TP. At the spatial scale of within 500 m buffer zone during the flood season and at the sub-watershed scale during the non-flood season, landscape patterns showed the highest explanatory power for the variations of TN and TP. At the type level, built-up land, cropland, and bare land were positively correlated with TN and TP, while forest was negatively correlated with TN and TP, which were the key types influencing non-point source pollution. At the landscape level, patch density, percentage of like adjacencies, and contagion index were key indicators affecting watershed water quality. Lower patch density was associated with better connectivity and aggregation of "sink" landscapes, leading to better purification effects on TN, but more pronounced retention effects on TP. Conversely, higher landscape diversity and denser pattern of multiple types would cause the deterioration of water quality. Our results suggested that rational allocation of landscape types within the watershed and riparian buffer zones, appropriately enriching landscape diversity, and optimizing landscape aggregation and connectivity would be effective measures for improving water quality and achieving sustainable ecological management.