Asperuloside alleviates cyclophosphamide-induced myelosuppression by promoting AMPK/mTOR pathway-mediated autophagy.

Cyclophosphamide (CTX) is a common anticancer chemotherapy drug, and myelosuppression is the most common serious side effect. Asperuloside (ASP), the active component of Hedyotis diffusa Willd., may have the effect of ameliorating chemotherapy-induced myelosuppression. This study aimed to explore the effect and possible mechanism of ASP on CTX-induced myelosuppression. Male SPF C57BL/6 mice were randomly divided into five groups: control group, CTX (25 mg/kg) group, CTX + granulocyte-macrophage-colony stimulating factor (GM-CSF) (5 µg/kg) group, CTX + high-dose ASP (50 mg/kg) group and CTX + low-dose ASP (25 mg/kg) group, with six mice in each group. The body weight of mice was monitored every other day, the hematopoietic progenitor cell colony number was measured by colony forming unit, and the relevant blood indicators were detected. Femoral bone marrow was observed by hematoxylin-eosin, C-kit expression was detected by immunohistochemistry, and autophagy and adenine monophosphate-activated protein kinase (AMPK)/mammalian target of rapamycin (mTOR) pathway protein expressions were detected by immunohistochemistry and western blotting (WB). Then the AMPK inhibitor dorsomorphin was used to interfere with AMPK/mTOR pathway. Results showed that ASP significantly increased the body weight of CTX-induced mice, increased the number of hematopoietic progenitor cells, the expression of white blood cells, red blood cells, platelets, GM-CSF, thrombopoietin and erythropoietin in blood, and the expression of C-kit in bone marrow. In addition, ASP further promoted the expression of Beclin1 and LC-3II/I induced by CTX, and regulated the protein expressions in the AMPK/mTOR pathway. The use of dorsomorphin inhibited the alleviation effect of ASP on CTX-induced myelosuppression and the promotion effect of ASP on autophagy. In conclusion, ASP alleviated CTX-induced myelosuppression by promoting AMPK/mTOR pathway-mediated autophagy.

Huanglian Decoction treats Henoch-Schonlein purpura nephritis by inhibiting NF-κB/NLRP3 signaling pathway and reducing renal IgA deposition.

Henoch-Schonlein purpura nephritis (HSPN) is a systemic vascular inflammatory disease. Huanglian Decoction (HLD) ameliorates renal injury in nephritis; however, the mechanism of action of HLD on HSPN has not been investigated. This study aimed to investigate the protective mechanism of HLD treatment in HSPN. The effects of HLD on HSPN biochemical indices, kidney injury and NF-κB/NLRP3 signaling pathway were analyzed by biochemical analysis, ELISA, HE and PAS staining, immunohistochemistry, immunofluorescence, and Western Blot. In addition, the effects of HLD on HSPN cells were analyzed. We found that HLD treatment significantly reduced renal tissue damage, decreased the levels of IL-17, IL-18, TNF-α, and IL-1ß, and increased the levels of TP and ALB in HSPN mice. It also inhibited the deposition of IgA, IgG, and C3 in kidney tissues and significantly decreased the expression of IκBα, p-IκBα, NLRP3, caspase-1, and IL-1ß in kidney tissues and cells. In addition, PMA treatment inhibited the above-mentioned effects of HLD. These results suggested that HLD attenuates renal injury, IgA deposition, and inflammation in HSPN mice and its mechanism of action may be related to the inhibition of the NF-κB/NLRP3 pathway.

Confirming High-Valent Iron as Highly Active Species of Water Oxidation on the Fe, V-Coupled Bimetallic Electrocatalyst: In Situ Analysis of X-ray Absorption and Mössbauer Spectroscopy.

Iron (Fe)-based bimetallic oxides/hydroxides have been widely investigated for promising alkaline electrochemical oxygen evolution reactions (OERs), but it still remains argumentative whether Fe3+ or Fe4+ intermediates are highly active for efficient OER. Here, we rationally designed and prepared one Fe, V-based bimetallic composite nanosheet by employing the OER-inert V element as a promoter to completely avoid the argument of real active metals and using our recently developed one-dimensional conductive nickel phosphide (NP) as a support. The as-obtained hierarchical nanocomposite (denoted as FeVOx/NP) was evaluated as a model catalyst to gain insight into the iron-based species as highly active OER sites by performing in situ X-ray absorption spectroscopy and 57Fe Mössbauer spectroscopy measurements. It was found that the high-valent Fe4+ species can only be detected during the OER process of the FeVOx/NP nanocomposite instead of the iron counterpart itself. Together with the fact that the OER activities of both the vanadium and iron counterparts are by far worse than that of the FeVOx/NP composite, we can confirm that the high-valent Fe4+ formed are the highly active species for efficient OER. As demonstrated by density functional theory simulations, the composite of Fe and V metals is proposed to cause a decreased Gibbs free energy as well as theoretical overpotential of water oxidation with respect to its counterparts, as is responsible for its excellent OER performance with extremely low OER overpotential (290 mV at 500 mA cm-2) and extraordinary stability (1000 h at 100 mA cm-2).

Identification of region-specific amino acid signatures for doxorubicin-induced chemo brain.

Doxorubicin (DOX) is a cornerstone of chemotherapy for solid tumors and leukemias. DOX-induced cognitive impairment, termed chemo brain, has been reported in cancer survivors, whereas its mechanism remains poorly understood. Here we initially evaluated the cognitive impairments of mice treated with clinically relevant, long-term, low-dosage of DOX. Using HILIC-MS/MS-based targeted metabolomics, we presented the changes of 21 amino acids across six anatomical brain regions of mice with DOX-induced chemo brain. By mapping the altered amino acids to the human metabolic network, we constructed an amino acid-based network module for each brain region. We identified phenylalanine, tyrosine, methionine, and γ-aminobutyric acid as putative signatures of three regions (hippocampus, prefrontal cortex, and neocortex) highly associated with cognition. Relying on the reported mouse brain metabolome atlas, we found that DOX might perturb the amino acid homeostasis in multiple brain regions, similar to the changes in the aging brain. Correlation analysis suggested the possible indirect neurotoxicity of DOX that altered the brain levels of phenylalanine, tyrosine, and methionine by causing metabolic disorders in the liver and kidney. In summary, we revealed the region-specific amino acid signatures as actionable targets for DOX-induced chemo brain, which might provide safer treatment and improve the quality of life among cancer survivors.

Novel Metabolites to Improve Glomerular Filtration Rate Estimation.

INTRODUCTION: The glomerular filtration rate (GFR) is crucial for chronic kidney disease (CKD) diagnosis and therapy. Various studies have sought to recognize ideal endogenous markers to improve the estimated GFR for clinical practice. To screen out potential novel metabolites related to GFR (mGFR) measurement in CKD patients from the Chinese population, we identified more biomarkers for improving GFR estimation. METHODS: Fifty-three CKD participants were recruited from the Third Affiliated Hospital of Sun Yat-sen University in 2020. For each participant, mGFR was evaluated by utilizing the plasma clearance of iohexol and collecting serum samples for untargeted metabolomics analyses by ultrahigh-performance liquid chromatography-tandem mass spectroscopy. All participants were divided into four groups according to mGFR. The metabolite peak area data were uploaded to MetaboAnalyst 5.0 for one-way analysis of variance, principal component analysis, and partial least squares-discriminant analysis and confirmed the metabolites whose levels increased or decreased with mGFR and variable importance in projection (VIP) values >1. Metabolites were ranked by correlation with the original values of mGFR, and metabolites with a correlation coefficient >0.8 and VIP >2 were identified. RESULTS: We screened out 198 metabolites that increased or decreased with mGFR decline. After ranking by correlation with mGFR, the top 50 metabolites were confirmed. Further studies confirmed the 10 most highly correlated metabolites. CONCLUSION: We screened out the metabolites that increased or decreased with mGFR decline in CKD patients from the Chinese population, and 10 of them were highly correlated. They are potential novel metabolites to improve GFR estimation.

A Metabolomics study of metabolites associated with the glomerular filtration rate.

BACKGROUND: Chronic kidney disease (CKD) is a global public health issue. The diagnosis of CKD would be considerably enhanced by discovering novel biomarkers used to determine the glomerular filtration rate (GFR). Small molecule metabolites related to kidney filtration function that might be utilized as biomarkers to measure GFR more accurately could be found via a metabolomics analysis of blood samples taken from individuals with varied glomerular filtration rates. METHODS: An untargeted metabolomics study of 145 plasma samples was performed using ultrahigh-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). The 145 samples were divided into four groups based on the patient's measured glomerular filtration rates (mGFRs) determined by the iohexol plasma clearance rate. The data were analyzed using random forest analyses and six other unique statistical analyses. Principal component analysis (PCA) was conducted using R software. RESULTS: A large number of metabolites involved in various metabolic pathways changed significantly between groups with different GFRs. These included metabolites involved in tryptophan or pyrimidine metabolism. The top 30 metabolites that best distinguished between the four groups in a random forest plot analysis included 13 amino acids, 9 nucleotides, and 3 carbohydrates. A panel of metabolites (including hydroxyaparagine, pseudouridine, C-glycosyltryptophan, erythronate, N-acetylalanine, and 7-methylguanidine) for estimating GFR was selected for future testing in targeted analyses by combining the candidate lists with the six other statistical analyses. Both hydroxyasparagine and N,N-dimethyl-proline-proline are unique biomarkers shown to be inversely associated with kidney function that have not been reported previously. In contrast, 1,5-anhydroglucitol (1,5-AG) decreases with impaired renal function. CONCLUSIONS: This global untargeted metabolomics study of plasma samples from patients with different degrees of renal function identified potential metabolite biomarkers related to kidney filtration. These novel potential metabolites provide more insight into the underlying pathophysiologic processes that may contribute to the progression of CKD, lead to improvements in the estimation of GFR and provide potential therapeutic targets to improve kidney function.

Implicit satiety goals and food-related expectations predict portion size in older adults: Findings from the BAMMBE cohort.

Portion size selection is an indicator of appetite and within younger adults, is predicted by factors such as expected satiety, liking and motivations to achieve an ideal sensation of fullness (i.e., implicit satiety goals). Currently, there is limited research available on the determinants of portion size selection within older adults. Therefore, the current study aimed to examine the relationship between individual differences in implicit satiety goals, food-related expectations, and portion size selection in older adults. Free-living older adult Singaporeans (N = 115; Nmales = 62; age: M = 66.21 years, SD = 4.78, range = 60-83 years) participated as part of the Brain, Ageing, Microbiome, Muscle, Bone, and Exercise Study (BAMMBE). Participants completed questionnaires on their subjective requirements for experiencing different states of satiety and food-related expectations (i.e., liking, how filling) as well as a computerised portion size selection task. Using a multiple regression, we found that goals to feel comfortably full (B = 3.08, SE = 1.04, t = 2.96, p = .004) and to stop hunger (B = -2.25, SE = 0.82, t = -2.75, p = .007) significantly predicted larger portion size selection (R2 = 0.24, F(4,87) = 6.74, p < .001). Larger portion sizes (R2 = 0.53, F(5,90) = 20.58, p < .001) were also predicted by greater expected satiety (B = 0.47, SE = 0.09, t = 5.15, p < .001) and lower perceptions of how filling foods are (B = -2.92, SE = 0.77, t = -3.79, p < .001) but not liking (B = -0.09, SE = 0.91, t = -0.10, p = .925) or frequency (B = -18.42, SE = 16.91, t = -1.09, p = .279) of consumption of target foods. Comparing our findings to results of studies conducted with younger adults suggests the influence of factors such as satiety related goals on portion size selection may change with ageing while the influence of other factors (e.g., expected satiety/fullness delivered by foods) may remain consistent. These findings may inform future strategies to increase/decrease portion size accordingly to ensure older adults maintain an appropriate healthy weight.

Metabolic network-based identification of plasma markers for non-small cell lung cancer.

Metabolic markers, offering sensitive information on biological dysfunction, play important roles in diagnosing and treating cancers. However, the discovery of effective markers is limited by the lack of well-established metabolite selection approaches. Here, we propose a network-based strategy to uncover the metabolic markers with potential clinical availability for non-small cell lung cancer (NSCLC). First, an integrated mass spectrometry-based untargeted metabolomics was used to profile the plasma samples from 43 NSCLC patients and 43 healthy controls. We found that a series of 39 metabolites were altered significantly. Relying on the human metabolic network assembled from Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we mapped these differential metabolites to the network and constructed an NSCLC-related disease module containing 23 putative metabolic markers. By measuring the PageRank centrality of molecules in this module, we computationally evaluated the network-based importance of the 23 metabolites and demonstrated that the metabolism pathways of aromatic amino acids and long-chain fatty acids provided potential molecular targets of NSCLC (i.e., IL4l1 and ACOT2). Combining network-based ranking and support-vector machine modeling, we further found a panel of eight metabolites (i.e., pyruvate, tryptophan, and palmitic acid) that showed a high capability to differentiate patients from controls (accuracy > 97.7%). In summary, we present a meaningful network method for metabolic marker discovery and have identified eight strong candidate metabolites for NSCLC diagnosis.

Improving accuracy of estimating glomerular filtration rate using artificial neural network: model development and validation.

BACKGROUND: The performance of previously published glomerular filtration rate (GFR) estimation equations degrades when directly used in Chinese population. We incorporated more independent variables and using complicated non-linear modeling technology (artificial neural network, ANN) to develop a more accurate GFR estimation model for Chinese population. METHODS: The enrolled participants came from the Third Affiliated Hospital of Sun Yat-sen University, China from Jan 2012 to Jun 2016. Participants with age < 18, unstable kidney function, taking trimethoprim or cimetidine, or receiving dialysis were excluded. Among the finally enrolled 1952 participants, 1075 participants (55.07%) from Jan 2012 to Dec 2014 were assigned as the development data whereas 877 participants (44.93%) from Jan 2015 to Jun 2016 as the internal validation data. We in total developed 3 GFR estimation models: a 4-variable revised CKD-EPI (chronic kidney disease epidemiology collaboration) equation (standardized serum creatinine and cystatin C, age and gender), a 9-variable revised CKD-EPI equation (additional auxiliary variables: body mass index, blood urea nitrogen, albumin, uric acid and hemoglobin), and a 9-variable ANN model. RESULTS: Compared with the 4-variable equation, the 9-variable equation could not achieve superior performance in the internal validation data (mean of difference: 5.00 [3.82, 6.54] vs 4.67 [3.55, 5.90], P = 0.5; interquartile range (IQR) of difference: 18.91 [17.43, 20.48] vs 20.11 [18.46, 21.80], P = 0.05; P30: 76.6% [73.7%, 79.5%] vs 75.8% [72.9%, 78.6%], P = 0.4), but the 9-variable ANN model significantly improve bias and P30 accuracy (mean of difference: 2.77 [1.82, 4.10], P = 0.007; IQR: 19.33 [17.77, 21.17], P = 0.3; P30: 80.0% [77.4%, 82.7%], P < 0.001). CONCLUSIONS: It is suggested that using complicated non-linear models like ANN could fully utilize the predictive ability of the independent variables, and then finally achieve a superior GFR estimation model.

Quantitative characterization of glutaminolysis in human plasma using liquid chromatography-tandem mass spectrometry.

Glutaminolysis is the metabolic pathway that lyses glutamine to glutamate, alanine, citrate, aspartate, and so on. As partially recruiting reaction steps from the tricarboxylic acid (TCA) cycle and the malate-aspartate shuttle, glutaminolysis takes essential place in physiological and pathological situations. We herein developed a sensitive, rapid, and reproducible liquid chromatography-tandem mass spectrometry method to determine the perturbation of glutaminolysis in human plasma by quantifying 13 involved metabolites in a single 20-min run. A pHILIC column with a gradient elution system consisting of acetonitrile-5 mM ammonium acetate was used for separation, while an electrospray ionization source (ESI) operated in negative mode with multiple reaction monitoring was employed for detection. The method was fully validated according to FDA's guidelines, and it generally provided good results in terms of linearity (the correlation coefficient no less than 0.9911 within the range of 0.05-800 µg/mL), intra- and inter-day precision (less than 18.38%) and accuracy (relative standard deviation between 89.24 and 113.4%), with lower limits of quantification between 0.05 and 10 µg/mL. The new analytical approach was successfully applied to analyze the plasma samples from 38 healthy volunteers and 34 patients with type 2 diabetes (T2D). Based on the great sensitivity and comprehensive capacity, the targeted analysis revealed the imperceptible abnormalities in the concentrations of key intermediates, such as iso-citrate and cis-aconitate, thus allowing us to obtain a thorough understanding of glutaminolysis disorder during T2D. Graphical abstract ᅟ.

Inhibition of MicroRNA-96 Ameliorates Cognitive Impairment and Inactivation Autophagy Following Chronic Cerebral Hypoperfusion in the Rat.

BACKGROUND/AIMS: Chronic cerebral hypoperfusion (CCH) is a high-risk factor for vascular dementia and Alzheimer's disease. Autophagy plays a critical role in the initiation and progression of CCH. However, the underlying mechanisms remain unclear. In this study, we identified the effect of a microRNA (miR) on autophagy under CCH. METHODS: A CCH rat model was established by two-vessel occlusion (2VO). Learning and memory abilities were assessed by the Morris water maze. The protein levels of LC3, beclin-1, and mTOR were detected by western blotting and immunofluorescence assays, miR-96 expression was assessed by real-time PCR, luciferase assays were used to determine the effect of miR-96 on the 3' untranslated region (UTR) of mTOR, and the number of autophagosomes was examined by electron microscopy. RESULTS: The level of miR-96 was significantly increased in 2VO rats, and inhibition of miR-96 ameliorated the cognitive impairment induced by 2VO. Furthermore, the number of LC3- and beclin-1-positive autophagosomes was increased in 2VO rats, and was decreased after miR-96 antagomir injection. However, the protein level of mTOR was reduced in 2VO rats, and it was down-regulated by miR-96 overexpression and up-regulated by miR-96 inhibition in 2VO rats and primary culture cells. Moreover, the luciferase activity of the 3'-UTR of mTOR was suppressed by miR-96, which was relieved by mutation of the miR-96 binding sites. CONCLUSION: Our study demonstrated that miR-96 may play a key role in autophagy under CCH by regulating mTOR; therefore, miR-96 may represent a potential therapeutic target for CCH.

Discovery of Metabolite Biomarkers for Acute Ischemic Stroke Progression.

Stroke remains a major public health problem worldwide; it causes severe disability and is associated with high mortality rates. However, early diagnosis of stroke is difficult, and no reliable biomarkers are currently established. In this study, mass-spectrometry-based metabolomics was utilized to characterize the metabolic features of the serum of patients with acute ischemic stroke (AIS) to identify novel sensitive biomarkers for diagnosis and progression. First, global metabolic profiling was performed on a training set of 80 human serum samples (40 cases and 40 controls). The metabolic profiling identified significant alterations in a series of 26 metabolites with related metabolic pathways involving amino acid, fatty acid, phospholipid, and choline metabolism. Subsequently, multiple algorithms were run on a test set consisting of 49 serum samples (26 cases and 23 controls) to develop different classifiers for verifying and evaluating potential biomarkers. Finally, a panel of five differential metabolites, including serine, isoleucine, betaine, PC(5:0/5:0), and LysoPE(18:2), exhibited potential to differentiate AIS samples from healthy control samples, with area under the receiver operating characteristic curve values of 0.988 and 0.971 in the training and test sets, respectively. These findings provided insights for the development of new diagnostic tests and therapeutic approaches for AIS.

A novel liquid chromatography tandem mass spectrometry method for simultaneous determination of branched-chain amino acids and branched-chain α-keto acids in human plasma.

Branched-chain amino acids (BCAAs) and branched-chain α-keto acids (BCKAs) play significant biological roles as they are involved in protein and neurotransmitter synthesis as well as energy metabolism pathways. To routinely and accurately study the dynamics of BCAAs and BCKAs in human diseases, e.g. cerebral infarction, a novel liquid chromatography-tandem mass spectrometry (LC-MS/MS) method has been developed and validated. The plasma samples were deproteinized with acetonitrile, and then separated on a reversed phase C18 column with a mobile phase of 0.1 % formic acid (solvent A)-methanol (solvent B) using gradient elution. The detection of BCAAs and BCKAs was conducted in multiple reaction monitoring with positive/negative electrospray ionization switching mode. Biologically relevant isomers such as leucine and isoleucine were individually quantified by combining chromatographic separation and fragmentation. Good linearity (R (2) > 0.99) was obtained for all six analytes with the limits of detection from 0.1 to 0.2 µg/mL. The intra-day and inter-day accuracy ranged from 93.7 to 108.4 % and the relative standard deviation (RSD) did not exceed 15.0 %. The recovery was more than 80 % with RSD less than 14.0 %. The main improvements compared to related, state-of-the-art methods included enhanced sensitivity, enhanced separation of isomers, and reduced complexity of sample processing. Finally, the validated method was applied to analyze the plasma samples of healthy volunteers and patients suffering cerebral infarction, and significant differences in the concentration levels of BCAAs and BCKAs were observed.

Combinative predictive effect of left ventricular mass index, ratio of HDL and CRP for progression of chronic kidney disease in non-dialysis patient.

PURPOSE: This current study scrutinized the association among left ventricular mass index (LVMI), ratio of high-density lipoprotein (HDL) and C-reactive protein (CRP), and renal function. Furthermore, we examined the predictive effects of left ventricular mass index and HDL/CRP on progression of non-dialysis chronic kidney disease. METHODS: We enrolled adult patients with chronic kidney disease (CKD) who were not receiving dialysis and obtained follow-up data on them. We extracted and compared data between different groups. To investigate the relationship between left ventricular mass index (LVMI), high-density lipoprotein (HDL)/C-reactive protein (CRP) levels, and CKD, we employed linear regression analysis, Kaplan-Meier analysis, and Cox proportional hazards regression analysis. RESULTS: Our study enrolled a total of 2351 patients. Compared with those in the non-progression group, subjects in the CKD progression group had lower ln(HDL/CRP) levels (- 1.56 ± 1.78 vs. - 1.14 ± 1.77, P < 0.001) but higher left ventricular mass index (LVMI) values (115.45 ± 29.8 vs. 102.8 ± 26.31 g/m2, P < 0.001). Moreover, after adjusting for demographic factors, ln(HDL/CRP) was found to be positively associated with estimated glomerular filtration rate (eGFR) (B = 1.18, P < 0.001), while LVMI was negatively associated with eGFR (B = - 0.15, P < 0.001). In the end, we found that both LVH (HR = 1.53, 95% CI 1.15 to 2.05, P = 0.004) and lower ln(HDL/CRP) (HR = 1.46, 95% CI 1.08 to 1.96, P = 0.013) independently predicted CKD progression. Notably, the combined predictive power of these variables was stronger than either variable alone (HR = 1.98, 95% CI 1.5 to 2.62, P < 0.001). CONCLUSION: Our study findings indicate that in pre-dialysis patients, both HDL/CRP and LVMI are associated with basic renal function and are independently correlated with CKD progression. These variables may serve as predictors for CKD progression, and their combined predictive power is stronger than that of either variable alone.

[Effects of Ziyin Liangxue Formula Combined with Prednisone on Immune Function and ST2/IL-33 Pathway in Mice with Immune Thrombocytopenia].

OBJECTIVE: To investigate the effects of Ziyin Liangxue formula combined with prednisone on immune function and the ST2/IL-33 pathway in mice with immune thrombocytopenia. METHODS: In 40 BALB/c mice, 32 were constructed as immune thrombocytopenia mouse models by antiplatelet serum injection. After successful modeling, the mice were randomly divided into model group, Ziyin Liangxue formula group (0.2 ml/10 g), prednisone group (0.2 ml/10 g), and Ziyin Liangxue formula + prednisone group (0.2 ml/10 g), 8 mice in each group, and the other 8 mice were set as control group. The drugs were administered by gavage at the dose, and the model group and control group were given equal amounts of saline by gavage once a day for 2 weeks of continuous intervention. Blood samples and spleen tissues were collected, the peripheral platelet count was measured by automatic hematology analyzer, the pathological changes in spleen tissue was observed by HE staining, the levels of serum transforming growth factor (TGF)-ß, interleukin (IL)-17, and peripheral blood thrombopoietin (TPO) were detected by enzyme-linked immunosorbent assay (ELISA), the expression of IL-33, sST2, and ST2 in spleen tissue was detected by Western blot, and the cell counts of peripheral blood Th17 and Treg were detected by flow cytometry. RESULTS: Compared with the control group, the number of platelets, the level of TPO, TGF-ß, and Treg cells were significantly decreased (P <0.05), while the level of IL-17, Th17 cells, and the expression of IL-33, sST2, and ST2 protein were significantly increased in the model group (P <0.01). Compared with the model group, the number of platelets, the level of TPO, TGF-ß, and Treg cells were significantly increased (P <0.05), while the level of IL-17, Th17 cells, and the expression of IL-33, sST2, and ST2 protein were significantly decreased in the Ziyin Liangxue formula + prednisone group (P <0.01). CONCLUSION: Ziyin Liangxue formula + prednisone can effectively regulate Th17/Treg balance, thus effectively improve immune thrombocytopenia, and the mechanism may be related to the regulation of ST2/IL-33 signaling pathway.

Overexpression of CPE-ΔN predicts poor prognosis in colorectal cancer patients.

Carboxypeptidase E (CPE) is one of the most important carboxypeptidases involved in biosynthesis of numerous peptide hormones and neurotransmitters and has an important role in endocrine regulation. A splice variant of CPE (CPE-ΔN) has been detected and the mechanism of CPE-ΔN action in tumorigenesis has been studied in many different cancers. The aim of this study was to examine CPE-ΔN expression in human colorectal cancer (CRC) and to evaluate its possible use as a potential prognostic marker. Two hundred nineteen primary colorectal tumors and corresponding normal tissues were included in the study. We have analyzed CPE-ΔN isoform expression by qRT-PCR and Western blot in 219 CRC patients. Correlations between CPE-ΔN mRNA expression and clinicopathological variables were determined with chi-square tests. Survival probabilities were determined using Kaplan-Meier analysis, and univariate and multivariate analyses of the prognostic factors were performed with a Cox regression model. Our results show that CPE-ΔN is overexpressed in colorectal tumor tissue and that high CPE-ΔN mRNA expression is closely correlated with tumor differentiation, pT classification, pN classification, tumor recurrence, and lymph node metastasis (P = 0.042, 0.036, 0.031, 0.006, and 0.008, respectively). However, no correlation was observed between CPE-ΔN expression and age, gender, tumor localization, gross features, and the tumor size. In addition, patients with high CPE-ΔN expression had a significantly shorter survival (P < 0.001, logrank test). Tumor differentiation, gross feature, pT classification, pN classification, tumor recurrence, lymph node metastasis, and CPE-ΔN status were significantly associated with poor prognosis after performing a univariate Cox survival analysis. High CPE-ΔN expression was also identified as an independent prognostic factor using a multivariate analysis (P = 0.011). Based on these results, we can conclude that CPE-ΔN expression might be a potential prognostic marker for colorectal cancer patients.

Association of uric acid with the decline in estimated glomerular filtration rate in middle-aged and elderly populations: evidence based on the China Health and Retirement Longitudinal Study.

OBJECTIVE: Whether uric acid (UA) has an effect on renal function remains controversial. We aimed to investigate the association between serum UA with the decline in estimated glomerular filtration rate (eGFR) in middle-aged and elderly populations in the China Health and Retirement Longitudinal Study (CHARLS). DESIGN: Longitudinal cohort study. SETTING: This was a second analysis of a public dataset (CHARLS). PARTICIPANTS: In this study, 4538 middle-aged and elderly individuals were screened after removing individuals younger than 45 years old, with kidney disease, malignant tumour and missing values. OUTCOME MEASURES: Blood tests were performed both in 2011 and 2015. Decline in eGFR was defined as an eGFR decrease of more than 25% or deterioration of the eGFR stage during the 4-year follow-up period. Logistic models corrected for multiple covariables were used to analyse the association of UA with the decline in eGFR. RESULTS: The median (IQR) concentrations of serum UA grouped by quartiles were 3.1 (0.6), 3.9 (0.3), 4.6 (0.4) and 5.7 (1.0) mg/dL, respectively. After multivariable adjustment, the OR of the decline in eGFR was higher for quartile 2 (3.5-<4.2 mg/dL: OR 1.44; 95% CI 1.07 to 1.64; p<0.01), quartile 3 (4.2-<5.0 mg/dL: OR 1.72; 95% CI 1.36 to 2.18; p<0.001) and quartile 4 (≥5.0 mg/dL: OR 2.04; 95% CI 1.58 to 2.63; p<0.001) when compared with quartile 1 (<3.5 mg/dL), and the p value for the trend was <0.001. CONCLUSIONS: Over a 4-year follow-up period, we found that elevated UA was associated with a decline in eGFR in the middle-aged and elderly individuals with normal renal function.

Mapping Topsoil Total Nitrogen Using Random Forest and Modified Regression Kriging in Agricultural Areas of Central China.

Accurate understanding of spatial distribution and variability of soil total nitrogen (TN) is critical for the site-specific nitrogen management. Based on 4337 newly obtained soil observations and 33 covariates, this study applied the random forest (RF) algorithm and modified regression kriging (RF combined with residual kriging: RFK, hereafter) model to spatially predict and map topsoil TN content in agricultural areas of Henan Province, central China. According to the RFK prediction, topsoil TN content ranged from 0.52 to 1.81 g kg-1, and the farmland with the topsoil TN contents of 1.00-1.23 g kg-1 and 0.80-1.23 g kg-1 accounted for 48.2% and 81.2% of the total farmland area, respectively. Spatially, the topsoil TN in the study area was generally higher in the west and lower in the east. By using the Boruta variable selection algorithm, soil organic matter (SOM) and available potassium contents in topsoil, nitrogen deposition, average annual precipitation, livestock discharges, and topsoil pH were identified as the main factors driving the spatial distribution and variation of soil TN in the study area. The RF and RFK models used showed the expected performance and achieved acceptable TN prediction accuracy. In comparison, RFK performed slightly better than the RF model. The R2 and RMSE achieved by the RFK model were improved by 4.5% and 4.5%, respectively, compared with that by the RF model. However, the results suggest that RFK was inferior to the RF model in quantifying prediction uncertainty and thus may have a slight disadvantage in model reliability.

Predictive Effect of System Inflammation Response Index for Progression of Chronic Kidney Disease in Non-Dialyzing Patient.

Purpose: Scant research has been conducted on the interplay between the systemic inflammation response index (SIRI) and chronic kidney disease (CKD). The present study endeavors to meticulously scrutinize the association between SIRI and renal function. Additionally, we aim to assess its efficacy in predicting the progression of CKD in non-dialysis patients. Patients and Methods: Adult patients with CKD who were not undergoing dialysis were enrolled, and follow-up data were obtained. Data from distinct groups were extracted and meticulously compared. A comprehensive analytical approach was adopted, including logistic regression analysis, Kaplan-Meier analysis, Cox proportional hazards regression analysis, and subgroup analysis. Results: Our study included 1420 patients, with a mean age of 61 ± 17 years, and 63% were male. 244 (17.2%) patients experienced the progression of CKD. As the level of ln(SIRI) increased, patients tended to be older, with a higher proportion of males, and increased prevalence rates of hypertension, stroke, heart failure, and progression of CKD. Additionally, the levels of baseline creatinine and C-reactive protein were elevated, while the levels of estimated glomerular filtration rate and hemoglobin decreased. Upon adjusting for demographic and biochemical variables, logistic regression analysis indicated that ln(SIRI) was independently associated with advanced CKD in pre-dialysis patients (OR=1.59, 95% CI: 1.29-1.95, P<0.001). Moreover, Cox proportional-hazard analysis revealed that ln(SIRI) independently predicted CKD progression (HR: 1.3, 95% CI: 1.07-1.59, P=0.009). Conducting a subgroup analysis, we observed significant interactions between ln(SIRI) levels and gender (p<0.001), age (p=0.046), and hypertension (p=0.028) in relation to the progression of CKD. Conclusion: Our study's findings demonstrate a significant association between SIRI and fundamental renal function, and independently establish a correlation between SIRI and the progression of CKD in pre-dialysis patients. These observations suggest that SIRI holds promise as a potential predictor for CKD progression.

Active Reconfigurable Intelligent Surface Enhanced Internet of Medical Things.

The incredible potentiality of reconfigurable intelligent surface (RIS) in addressing power supply and obstacle environment of Internet of Medical Things (IoMT) has been capturing our interest. Considering the nettlesome "double-fading" effect introduced by passive RIS, we investigate an active RIS-enhanced IoMT system in this paper, where the wireless power transfer (WPT) from power station (PS) to IoMT devices and the wireless information transfer (WIT) from IoMT devices to the access point (AP) are both implemented with the assistance of active RIS. Aiming to maximize the sum throughput of the considered IoMT system, a joint design of time schedules and reflecting coefficient matrices of the active RIS is proposed. Trapped by the non-convex and obstinate optimization problem, we explore the semi-definite programming (SDP) relaxation and successive convex approximation (SCA) techniques based on alternating optimization (AO) algorithm. Simulation results verify our solution approach to the intractable optimization problem and showcase the boosted spectrum and energy efficiency of the active RIS-enhanced IoMT system.