Association of urinary citrate excretion, pH, and net gastrointestinal alkali absorption with diet, diuretic use, and blood glucose concentration

Urinary citrate (Ucit) protects against urinary stone formation. Acid base status and diet influence Ucit. However, the effect of demographics, diet, and glucose metabolism on Ucit excretion, urinary pH (U‐pH) and net gastrointestinal alkali absorption (NAA) are not known. Twenty‐four hour urine samples, blood glucose, creatinine, and cystatin C were obtained from non‐Hispanic white sibships in Rochester, MN (n = 446; 64.5 ± 9 years; 58% female). Diet was assessed by a food frequency questionnaire. The impact of blood glucose, demographics and dietary elements on Ucit excretion, U‐pH, and NAA were evaluated in bivariate and multivariable models and interaction models that included age, sex, and weight. NAA significantly associated with Ucit and U‐pH. In multivariate models Ucit increased with age, weight, eGFRCys, and blood glucose, but decreased with loop diuretic and thiazide use. U‐pH decreased with serum creatinine, blood glucose, and dietary protein but increased with dietary potassium. NAA was higher in males and increased with age, weight, eGFRCys and dietary potassium. Significant interactions were observed for Ucit excretion with age and blood glucose, weight and eGFRCys, and sex and thiazide use. Blood glucose had a significant and independent effect on U‐pH and also Ucit. This study provides the first evidence that blood glucose could influence urinary stone risk independent of urinary pH, potentially providing new insight into the association of obesity and urinary stone disease.This study demonstrated that blood glucose had a significant and independent effect on urinary pH and also urinary citrate. Thus it provides the first evidence that blood glucose could influence urinary stone risk independent of urinary pH, potentially providing new insight into the association of obesity and urinary stone disease.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138855/1/phy213411.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138855/2/phy213411_am.pd

Key influence of sex on urine volume and osmolality

Abstract Background Demographics influence kidney stone risk and the type of stone that is more likely to form. Common kidney stone risk factors include having a low urine volume and a high urine concentration. The goal of the current study was to evaluate the effect of demographics on urinary concentration and osmole excretion. Methods Twenty-four-hour urine samples were collected from non-Hispanic white sibships in Rochester, MN. Height, weight, blood pressure, serum creatinine, and cystatin C were measured. Diet was assessed using the Viocare food frequency questionnaire. Effects of demographics and dietary elements on urine osmolality and volume were evaluated in bivariate and multivariable models, as well as models that included dietary interactions with age, sex, and weight. Results Samples were available from 709 individuals (mean age 66 ± 9 years, 59 % female). Across the age spectrum, males had higher urine osmolality (~140 mOsm/kg, p < 0.0001) and total osmole excretion (~270 mOsm, p < 0.0001) compared to females. For any given urine volume, males had a consistently higher urine osmolality (~140 mOsm/kg, p < 0.0001). In multivariable models, urine osmolality declined with age and water intake and remained higher in males than females. Urine osmolality positively associated with weight and animal protein intake. Higher urine volume associated with larger water intake. An interaction revealed that greater body weight was associated with larger changes in urine osmolality as oxalate intake increased (p = 0.04). Conclusion Data from this study support the hypothesis that there are sex differences in thirst and vasopressin action. This trend in urine concentration is also consistent with known epidemiologic patterns of urinary stone disease risk.http://deepblue.lib.umich.edu/bitstream/2027.42/117280/1/13293_2016_Article_63.pd

A Multi-staged Feature-Attentive Network for Fashion Clothing Classification and Attribute Prediction

In the visual fashion clothing analysis, many researchers are attracted with the success of deep learning concepts. In this work, we introduce a multi-staged feature-attentive network to attain clothing category classification and attribute prediction. The proposed network in this work brings out a landmark-independent structure, whereas the existing landmark-dependent structures take up a lot of manpower for landmark annotation and also suffers from inter- and intra-individual variability. Our focus on this work is intensifying feature extraction by incorporating low-level and high-level feature fusion within fashion network. We are aiming on multi-level contextual features which utilise spatial and channel-wise information to create contextual feature supervision. Further, we enclose a semi-supervised learning approach to escalate fashion clothes analysis that utilises knowledge sharing among labelled and unlabelled data. To the best of our knowledge, this is the first attempt to investigate the semi-supervised learning in fashion clothing analysis by adopting multitask architecture which simultaneously study the clothing categories as well as its attributes. We evaluated the proposed approach on large-scale DeepFashion-C dataset while unlabelled dataset obtained from six publicly available fashion datasets. Experimental results show that the proposed architectures for supervised and semi-supervised learning entailing deep convolutional neural network outperforms many state-of-the-art techniques considerably, in fashion clothing analysis

Additional file 1: Table S1. of Key influence of sex on urine volume and osmolality

Bivariate associations for variables that did not pass stepwise linear model selection criteria. Figure S1. Analysis of biological sex on variability in urine osmolality (A) and urine volume (B). (DOCX 50 kb

Polymorphisms in Renal Ammonia Metabolism Genes Correlate With 24-Hour Urine pH

Urine pH is critical for net acid and solute excretion, but the genetic factors that contribute to its regulation are incompletely understood. Methods: We tested the association of single nucleotide polymorphisms (SNPs) from 16 genes related to ammonia (NH3) metabolism (15 biological candidates selected a priori, 1 selected from a previous genome-wide association study analysis) to that of 24-hour urine pH in 2493 individuals of European descent across 2 different cohorts using linear regression, adjusting for age, sex, and body mass index. Results: Of 2871 total SNPs in these genes, 13 SNPs in ATP6V0A4 (a4 subunit of hydrogen− adenosine triphosphatase), SLC9A3 (sodium/hydrogen exchanger, isoform 3), and RHCG (Rhesus C glycoprotein), and 12 SNPs from insulin-like growth factor binding protein 7 (IGFBP7) had a meta-analysis P value <0.01 in the joint analysis plus a consistent direction of effect and at a least suggestive association (P < 0.1) in both cohorts. The maximal effect size (in pH units) for each additional minor allele of the identified SNPs was −0.13 for IGFBP7, −0.08 for ATP6V0A4, 0.06 for RHCG, and −0.06 for SLC9A3; SNP rs34447434 in IGFBP7 had the lowest meta-analysis P value (P = 7.1 × 10−8). After adjusting for net alkali absorption, urine pH remained suggestively associated with multiple SNPs in IGFBP, 1 SNP in ATP6V0A4, and a new SNP in GLS (phosphate-dependent glutaminase). Discussion: Overall, these findings suggest that variants in common genes involved in ammonia metabolism may substantively contribute to basal urine pH regulation. These variations might influence the likelihood of developing disease conditions associated with altered urine pH, such as uric acid or calcium phosphate kidney stones