25-Hydroxyvitamin D in the Range of 20 to 100 ng/mL and Incidence of Kidney Stones

Objectives. Increasing 25-hydroxyvitamin D serum levels can prevent a wide range of diseases. There is a concern about increasing kidney stone risk with vitamin D supplementation. We used GrassrootsHealth data to examine the relationship between vitamin D status and kidney stone incidence.Methods. The study included 2012 participants followed prospectively for a median of 19 months. Thirteen individuals self-reported kidney stones during the study period. Multivariate logistic regression was applied to assess the association between vitamin D status and kidney stones.Results. We found no statistically significant association between serum 25-hydroxyvitamin D and kidney stones (P = .42). Body mass index was significantly associated with kidney stone risk (odds ratio = 3.5; 95% confidence interval = 1.1, 11.3).Conclusions. We concluded that a serum 25-hydroxyvitamin D level of 20 to 100 nanograms per milliliter has no significant association with kidney stone incidence.An issue of possible concern related to the use of vitamin D supplementation is a reported increase in risk of kidney stones.1 Mounting evidence indicates that a 25-hydroxyvitamin D (25[OH]D) serum level in the range of 40 to 60 nanograms per milliliter (ng/mL) is needed for substantial reduction in risk of a wide range of diseases including breast cancer,2 colorectal cancer,3 multiple sclerosis,4 and type 1 diabetes.5,6 However, few people can achieve 25(OH)D in the range higher than 40 ng/mL without supplementation.7GrassrootsHealth is a nonprofit public health research organization that runs a large population cohort study of participants who reach and sustain, if desired, a 25(OH)D serum level of their choice and tracking subsequent health outcomes. GrassrootsHealth has assembled a database that includes information on serum 25(OH)D concentrations, demographic characteristics, and health status measures. These data include values from 5552 individuals with daily supplemental intakes averaging 3600 international units (IU) per day and an average 25(OH)D level of 45 ng/mL, which is higher than the ranges found in most other cohorts.2,4In this study we investigated whether serum 25(OH)D concentration in the range of 20 to 100 ng/mL was associated with incidence of kidney stones in all participants who provided data at 2 or more sampling times.     

A miniature quantitative PCR device for directly monitoring a sample processing on a microfluidic rapid DNA system

We report a microfluidic device and measurement method to perform real-time PCR (or qPCR) in a miniaturized configuration for on-chip implementation using reaction volumes of less than 20 μL. The qPCR bioreactor is designed as a module to be embedded in an automated sample-in/profile-out system for rapid DNA biometrics or human identification. The PCR mixture is excited with a 505 nm diode-pumped solid-state laser (DPSSL) and the fluorescence build-up is measured using optical fibers directly embedded to the sidewalls of the microfluidic qPCR bioreactor. We discuss manufacturing and operating parameters necessary to adjust the internal surface conditions and temperature profiles of the bioreactor and to optimize the yield and quality of the PCR reaction for the amplification of 62 bp hTERT intron fragments using the commercial Quantifiler® kit (Life Technologies, Carlsbad, CA) commonly accepted for genotyping analysis. We designed a microfluidic device suitable for continuously processing a specimen by efficiently mixing the reagents from the kit to a set volume of DNA template on chip. Our approach relies on a calibration curve for the specific device using control DNA. We successfully applied this method to determine the concentration of genomic DNA extracted from a buccal swab on separate microfluidic devices which are operated upstream the qPCR device and perform buccal swab lysis and buccal DNA extraction. A precise correlation between the amount determined on chip and that obtained using a commercial cycler is demonstrated.     

Hubs disruption in mesial temporal lobe epilepsy. A resting‐state fMRI study on a language‐and‐memory network

Mesial temporal lobe epilepsy (mTLE) affects the brain networks at several levels and patients suffering from mTLE experience cognitive impairment for language and memory. Considering the importance of language and memory reorganization in this condition, the present study explores changes of the embedded language‐and‐memory network (LMN) in terms of functional connectivity (FC) at rest, as measured with functional MRI. We also evaluate the cognitive efficiency of the reorganization, that is, whether or not the reorganizations support or allow the maintenance of optimal cognitive functioning despite the seizure‐related damage. Data from 37 patients presenting unifocal mTLE were analyzed and compared to 48 healthy volunteers in terms of LMN‐FC using two methods: pairwise correlations (region of interest [ROI]‐to‐ROI) and graph theory. The cognitive efficiency of the LMN‐FC reorganization was measured using correlations between FC parameters and language and memory scores. Our findings revealed a large perturbation of the LMN hubs in patients. We observed a hyperconnectivity of limbic areas near the dysfunctional hippocampus and mainly a hypoconnectivity for several cortical regions remote from the dysfunctional hippocampus. The loss of FC was more important in left mTLE (L‐mTLE) than in right (R‐mTLE) patients. The LMN‐FC reorganization may not be always compensatory and not always useful for patients as it may be associated with lower cognitive performance. We discuss the different connectivity patterns obtained and conclude that interpretation of FC changes in relation to neuropsychological scores is important to determine cognitive efficiency, suggesting the concept of “connectome” would gain to be associated with a “cognitome” concept.     

Multi‐scale network regression for brain‐phenotype associations

Brain networks are increasingly characterized at different scales, including summary statistics, community connectivity, and individual edges. While research relating brain networks to behavioral measurements has yielded many insights into brain‐phenotype relationships, common analytical approaches only consider network information at a single scale. Here, we designed, implemented, and deployed Multi‐Scale Network Regression (MSNR), a penalized multivariate approach for modeling brain networks that explicitly respects both edge‐ and community‐level information by assuming a low rank and sparse structure, both encouraging less complex and more interpretable modeling. Capitalizing on a large neuroimaging cohort (n = 1, 051) , we demonstrate that MSNR recapitulates interpretable and statistically significant connectivity patterns associated with brain development, sex differences, and motion‐related artifacts. Compared to single‐scale methods, MSNR achieves a balance between prediction performance and model complexity, with improved interpretability. Together, by jointly exploiting both edge‐ and community‐level information, MSNR has the potential to yield novel insights into brain‐behavior relationships.