Elemental Content of Calcium Oxalate Stones from a Canine Model of Urinary Stone Disease

One of the most common types of urinary stones formed in humans and some other mammals is composed of calcium oxalate in ordered hydrated crystals. Many studies have reported a range of metals other than calcium in human stones, but few have looked at stones from animal models such as the dog. Therefore, we determined the elemental profile of canine calcium oxalate urinary stones and compared it to reported values from human stones. The content of 19 elements spanning 7-orders of magnitude was quantified in calcium oxalate stones from 53 dogs. The elemental profile of the canine stones was highly overlapping with human stones, indicating similar inorganic composition. Correlation and cluster analysis was then performed on the elemental profile from canine stones to evaluate associations between the elements and test for potential subgrouping based on elemental content. No correlations were observed with the most abundant metal calcium. However, magnesium and sulfur content correlated with the mineral hydration form, while phosphorous and zinc content correlated with the neuter status of the dog. Inter-elemental correlation analysis indicated strong associations between barium, phosphorous, and zinc content. Additionally, cluster analysis revealed subgroups within the stones that were also based primarily on barium, phosphorous, and zinc. These data support the use of the dog as a model to study the effects of trace metal homeostasis in urinary stone disease.     

Maternal Antioxidant Levels in Pregnancy and Risk of Preeclampsia and Small for Gestational Age Birth: A Systematic Review and Meta-Analysis

Background

Oxidative stress in preeclampsia and small for gestational age (SGA) birth suggests antioxidant supplementation could prevent these conditions. However, it remains unclear whether maternal antioxidant levels are systematically lower in these pregnancies.

Objective

To conduct a systematic review of the association between maternal antioxidant levels during pregnancy and preeclampsia or SGA.

Methods

We searched PubMed, Embase, and several other databases from 1970–2013 for observational studies that measured maternal blood levels of non-enzymatic antioxidants (vitamins A, C, E, and carotenoids) during pregnancy or within 72 hours of delivery. The entire review process was done in duplicate. Study quality was assessed using the Newcastle-Ottawa Scale and additional questions. We pooled the standardized mean difference (SMD) across studies, stratified by outcome and pregnancy trimester, and investigated heterogeneity using meta-regression.

Results

We reviewed 1,882 unique citations and 64 studies were included. Most studies were small with important risk of bias. Among studies that addressed preeclampsia (n = 58) and SGA (n = 9), 16% and 66%, respectively, measured levels prior to diagnosis. The SMDs for vitamins A, C, and E were significantly negative for overall preeclampsia, but not for mild or severe preeclampsia subtypes. Significant heterogeneity was observed in all meta-analyses and most could not be explained. Evidence for lower carotenoid antioxidants in preeclampsia and SGA was limited and inconclusive. Publication bias appears likely.

Conclusions

Small, low-quality studies limit conclusions that can be drawn from the available literature. Observational studies inconsistently show that vitamins C and E or other antioxidants are lower in women who develop preeclampsia or SGA. Reverse causality remains a possible explanation for associations observed. New clinical trials are not warranted in light of this evidence; however, additional rigorous observational studies measuring antioxidant levels before clinical detection of preeclampsia and SGA may clarify whether levels are altered at a causally-relevant time of pregnancy.     

In Vitro Fracture Testing of Submicron Diameter Collagen Fibril Specimens

Mechanical testing of collagenous tissues at different length scales will provide improved understanding of the mechanical behavior of structures such as skin, tendon, and bone, and also guide the development of multiscale mechanical models. Using a microelectromechanical-systems (MEMS) platform, stress-strain response curves up to failure of type I collagen fibril specimens isolated from the dermis of sea cucumbers were obtained in vitro. A majority of the fibril specimens showed brittle fracture. Some displayed linear behavior up to failure, while others displayed some nonlinearity. The fibril specimens showed an elastic modulus of 470 ± 410 MPa, a fracture strength of 230 ± 160 MPa, and a fracture strain of 80% ± 44%. The fibril specimens displayed significantly lower elastic modulus in vitro than previously measured in air. Fracture strength/strain obtained in vitro and in air are both significantly larger than those obtained in vacuo, indicating that the difference arises from the lack of intrafibrillar water molecules produced by vacuum drying. Furthermore, fracture strength/strain of fibril specimens were different from those reported for collagenous tissues of higher hierarchical levels, indicating the importance of obtaining these properties at the fibrillar level for multiscale modeling.     

Moving from Data on Deaths to Public Health Policy in Agincourt,South Africa: Approaches to Analysing and Understanding Verbal Autopsy Findings

Background

Cause of death data are an essential source for public health planning, but their availability and quality are lacking in many parts of the world. Interviewing family and friends after a death has occurred (a procedure known as verbal autopsy) provides a source of data where deaths otherwise go unregistered; but sound methods for interpreting and analysing the ensuing data are essential. Two main approaches are commonly used: either physicians review individual interview material to arrive at probable cause of death, or probabilistic models process the data into likely cause(s). Here we compare and contrast these approaches as applied to a series of 6,153 deaths which occurred in a rural South African population from 1992 to 2005. We do not attempt to validate either approach in absolute terms.

Methods and Findings

The InterVA probabilistic model was applied to a series of 6,153 deaths which had previously been reviewed by physicians. Physicians used a total of 250 cause-of-death codes, many of which occurred very rarely, while the model used 33. Cause-specific mortality fractions, overall and for population subgroups, were derived from the model''s output, and the physician causes coded into comparable categories. The ten highest-ranking causes accounted for 83% and 88% of all deaths by physician interpretation and probabilistic modelling respectively, and eight of the highest ten causes were common to both approaches. Top-ranking causes of death were classified by population subgroup and period, as done previously for the physician-interpreted material. Uncertainty around the cause(s) of individual deaths was recognised as an important concept that should be reflected in overall analyses. One notably discrepant group involved pulmonary tuberculosis as a cause of death in adults aged over 65, and these cases are discussed in more detail, but the group only accounted for 3.5% of overall deaths.

Conclusions

There were no differences between physician interpretation and probabilistic modelling that might have led to substantially different public health policy conclusions at the population level. Physician interpretation was more nuanced than the model, for example in identifying cancers at particular sites, but did not capture the uncertainty associated with individual cases. Probabilistic modelling was substantially cheaper and faster, and completely internally consistent. Both approaches characterised the rise of HIV-related mortality in this population during the period observed, and reached similar findings on other major causes of mortality. For many purposes probabilistic modelling appears to be the best available means of moving from data on deaths to public health actions. Please see later in the article for the Editors'' Summary     

p27 phosphorylation by Src regulates inhibition of cyclin E-Cdk2

The kinase inhibitor p27Kip1 regulates the G1 cell cycle phase. Here, we present data indicating that the oncogenic kinase Src regulates p27 stability through phosphorylation of p27 at tyrosine 74 and tyrosine 88. Src inhibitors increase cellular p27 stability, and Src overexpression accelerates p27 proteolysis. Src-phosphorylated p27 is shown to inhibit cyclin E-Cdk2 poorly in vitro, and Src transfection reduces p27-cyclin E-Cdk2 complexes. Our data indicate that phosphorylation by Src impairs the Cdk2 inhibitory action of p27 and reduces its steady-state binding to cyclin E-Cdk2 to facilitate cyclin E-Cdk2-dependent p27 proteolysis. Furthermore, we find that Src-activated breast cancer lines show reduced p27 and observe a correlation between Src activation and reduced nuclear p27 in 482 primary human breast cancers. Importantly, we report that in tamoxifen-resistant breast cancer cell lines, Src inhibition can increase p27 levels and restore tamoxifen sensitivity. These data provide a new rationale for Src inhibitors in cancer therapy.     

Targeted deletion of AIF decreases mitochondrial oxidative phosphorylation and protects from obesity and diabetes

Type-2 diabetes results from the development of insulin resistance and a concomitant impairment of insulin secretion. Recent studies place altered mitochondrial oxidative phosphorylation (OxPhos) as an underlying genetic element of insulin resistance. However, the causative or compensatory nature of these OxPhos changes has yet to be proven. Here, we show that muscle- and liver-specific AIF ablation in mice initiates a pattern of OxPhos deficiency closely mimicking that of human insulin resistance, and contrary to current expectations, results in increased glucose tolerance, reduced fat mass, and increased insulin sensitivity. These results are maintained upon high-fat feeding and in both genetic mosaic and ubiquitous OxPhos-deficient mutants. Importantly, the effects of AIF on glucose metabolism are acutely inducible and reversible. These findings establish that tissue-specific as well as global OxPhos defects in mice can counteract the development of insulin resistance, diabetes, and obesity.     

A high-fat, ketogenic diet induces a unique metabolic state in mice

Ketogenic diets have been used as an approach to weight loss on the basis of the theoretical advantage of a low-carbohydrate, high-fat diet. To evaluate the physiological and metabolic effects of such diets on weight we studied mice consuming a very-low-carbohydrate, ketogenic diet (KD). This diet had profound effects on energy balance and gene expression. C57BL/6 mice animals were fed one of four diets: KD; a commonly used obesogenic high-fat, high-sucrose diet (HF); 66% caloric restriction (CR); and control chow (C). Mice on KD ate the same calories as mice on C and HF, but weight dropped and stabilized at 85% initial weight, similar to CR. This was consistent with increased energy expenditure seen in animals fed KD vs. those on C and CR. Microarray analysis of liver showed a unique pattern of gene expression in KD, with increased expression of genes in fatty acid oxidation pathways and reduction in lipid synthesis pathways. Animals made obese on HF and transitioned to KD lost all excess body weight, improved glucose tolerance, and increased energy expenditure. Analysis of key genes showed similar changes as those seen in lean animals placed directly on KD. Additionally, AMP kinase activity was increased, with a corresponding decrease in ACC activity. These data indicate that KD induces a unique metabolic state congruous with weight loss.