Association between dietary intake of flavonoid and chronic kidney disease in US adults: Evidence from NHANES 2007-2008, 2009-2010, and 2017-2018.

BACKGROUND: Studies investigating the relationship between flavonoid intake and chronic kidney disease (CKD) are limited. This study investigated the association between daily flavonoid intake and CKD in US adults by using data for 2007-2008, 2009-2010, and 2017-2018 from the National Health and Nutrition Examination Survey (NHANES) database. METHODS: This study employed a cross-sectional design and used data from three cycles of the continuous NHANES: 2007-2008, 2009-2010, and 2017-2018. NHANES researchers collected data related to consumption of various food and beverages from participants by employing 24-h dietary recall questionnaires. CKD is defined as an estimated glomerular filtration rate of < 60 mL/min/1.73m2 or a urine albumin-to-creatinine ratio of ≥ 30 mg/g. RESULTS: The odds ratios (OR) for CKD risk in the second (Q2), third (Q3), and fourth (Q4) quartiles of total flavonoid intake, compared with that in the first (Q1) quartile, were 0.780 (95% CI: 0.600, 1.015), 0.741 (95% CI: 0.573, 0.957), and 0.716 (95% CI: 0.554, 0.925), respectively (with a P value for the trend of 0.040). According to the restricted cubic spline analysis, total flavonoid intake exhibited a non-linear relationship with CKD risk (P < 0.001). CONCLUSION: Our findings suggest that a potential J-shaped relationship was observed between total flavonoid consumption and CKD risk, with an inflection point at 69.58 mg/d. Our study indicates that a moderate intake of flavonoids may confer renal benefits which may offer novel strategies for CKD treatment.

Association between consumption of flavonol and its subclasses and chronic kidney disease in US adults: an analysis based on National Health and Nutrition Examination Survey data from 2007-2008, 2009-2010, and 2017-2018.

Background: There is little research on the relationship between flavonol consumption and chronic kidney disease (CKD). This study aimed to examine the link between flavonol consumption and the risk of CKD among US adults, using data from the 2007-2008, 2009-2010 and 2017-2018 National Health and Nutrition Examination Survey (NHANES). Methods: A cross-sectional approach was used, drawing on data from three NHANES cycles. The flavonol consumption of the participants in this study was assessed using a 48 h dietary recall interview. CKD was diagnosed based on an estimated glomerular filtration rate below 60 mL/min/1.73 m2 or a urine albumin-to-creatinine ratio of 30 mg/g or higher. Results: Compared to the lowest quartile of flavonol intake (Q1), the odds ratios for CKD were 0.598 (95% CI: 0.349, 1.023) for the second quartile (Q2), 0.679 (95% CI: 0.404, 1.142) for the third quartile (Q3), and 0.628 (95% CI: 0.395, 0.998) for the fourth quartile (Q4), with a p value for trend significance of 0.190. In addition, there was a significant trend in CKD risk with isorhamnetin intake, with the odds ratios for CKD decreasing to 0.860 (95% CI: 0.546, 1.354) in the second quartile, 0.778 (95% CI: 0.515, 1.177) in the third quartile, and 0.637 (95% CI: 0.515, 1.177) in the fourth quartile (p for trend = 0.013). Conclusion: Our analysis of the NHANES data spanning 2007-2008, 2009-2010, and 2017-2018 suggests that high consumption of dietary flavonol, especially isorhamnetin, might be linked to a lower risk of CKD in US adults. These findings offer new avenues for exploring strategies for managing CKD.

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.

[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.

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.

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.

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 article, 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.

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.

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).

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.

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.

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.

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.

Metabolic profiling identifies the significance of caffeine metabolism in CKD.

Background: With the development of chronic kidney disease (CKD), there are various changes in metabolites. However, the effect of these metabolites on the etiology, progression and prognosis of CKD remains unclear. Objective: We aimed to identify significant metabolic pathways in CKD progression by screening metabolites through metabolic profiling, thus identifying potential targets for CKD treatment. Methods: Clinical data were collected from 145 CKD participants. GFR (mGFR) was measured by the iohexol method and participants were divided into four groups according to their mGFR. Untargeted metabolomics analysis was performed via UPLC-MS/MSUPLC-MSMS/MS assays. Metabolomic data were analyzed by MetaboAnalyst 5.0, one-way ANOVA, principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA) to identify differential metabolites for further analysis. The open database sources of MBRole2.0, including KEGG and HMDB, were used to identify significant metabolic pathways in CKD progression. Results: Four metabolic pathways were classified as important in CKD progression, among which the most significant was caffeine metabolism. A total of 12 differential metabolites were enriched in caffeine metabolism, four of which decreased with the deterioration of the CKD stage, and two of which increased with the deterioration of the CKD stage. Of the four decreased metabolites, the most important was caffeine. Conclusion: Caffeine metabolism appears to be the most important pathway in the progression of CKD as identified by metabolic profiling. Caffeine is the most important metabolite that decreases with the deterioration of the CKD stage.

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.

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.

Association between recovery/occurrence of metabolic syndrome and rapid estimated glomerular filtration rate decline in middle-aged and older populations: evidence from the China Health and Retirement Longitudinal Study.

OBJECTIVES: Few studies have explored correlations between metabolic syndrome (MetS) alterations and renal deterioration in longitudinal cohorts. We aim to investigate associations between MetS recovery/development and rapid estimated glomerular filtration rate (eGFR) decline in the China Health and Retirement Longitudinal Study (CHARLS). DESIGN: Longitudinal cohort study. SETTING: This study is a secondary analysis of CHARLS. PARTICIPANTS: After excluding individuals with age <45 years old, eGFR <60 mL/min/1.73 m2 and clinician-reported malignant tumour, heart disease, stroke or kidney disease at baseline, 4142 participants with complete data were selected from the CHARLS during the 4-year follow-up period (2011-2015). OUTCOME MEASURES: MetS were measured at 2011 and 2015 in CHARLS. A rapid eGFR decline was defined as an average annual eGFR decline of >3 mL/min/1.73 m2. The associations between rapid eGFR decline and MetS recovery/development were analysed using multivariable adjusted logistic models. RESULTS: According to MetS baseline status and follow-up, participants were divided into four groups: (1) 2460 (59.4%) in the MetS-free group, (2) 361 (8.7%) in the MetS-developed group, (3) 499 (12.0%) in the MetS recovery group and (4) 822 (19.8%) in the MetS chronic group. When compared with the MetS chronic group, the multivariable adjusted OR of rapid eGFR decline in the MetS recovery group was 0.64 (OR: 0.64; 95% CI 0.45 to 0.90, p=0.01). In contrast, when compared with the MetS-free group, the multivariable adjusted OR of rapid eGFR decline in the MetS-developed group was 1.00 (OR: 1.00; 95% CI 0.73 to 1.38, p=0.98). CONCLUSIONS: Over the 4-year follow-up period, we found that MetS recovery was associated with a reduced risk of rapid eGFR decline in middle-aged and older adults, while MetS occurrence was not related to rapid eGFR decline. Recovery from MetS appeared to protect against a rapid decline in eGFR.

Identification of Metabolite Markers Associated with Kidney Function.

Background: Chronic kidney disease (CKD) is a global public health problem. Identifying new biomarkers that can be used to calculate the glomerular filtration rate (GFR) would greatly improve the diagnosis and understanding of CKD at the molecular level. A metabolomics study of blood samples derived from patients with widely divergent glomerular filtration rates could potentially discover small molecule metabolites associated with varying kidney function. Methods: Using ultrahigh-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), serum was analyzed from 53 participants with a spectrum of measured GFR (by iohexol plasma clearance) ranging from normal to severe renal insufficiency. An untargeted metabolomics assay (N » 214) was conducted at the Calibra-Metabolon Joint Laboratory. Results: From a large number of metabolomics-derived metabolites, the top 30 metabolites correlated to increasing renal insufficiency according to mGFR were selected by the random forest method. Significant differences in metabolite profiles with increasing stages of CKD were observed. Combining candidate lists from six other unique statistical analyses, six novel, potential metabolites that were reproducibly strongly associated with mGFR were selected, including erythronate, gulonate, C-glycosyltryptophan, N-acetylserine, N6-carbamoylthreonyladenosine, and pseudouridine. In addition, hydroxyasparagine were strongly associated with mGFR and CKD, which were unique to this study. Conclusions: Global metabolite profiling of serum yielded potentially valuable biomarkers of different stages of CKD. Additionally, these potential biomarkers might provide insight into the underlying pathophysiologic processes that contribute to the progression of CKD as well as improve GFR estimation.

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.