A comparison of dorsal and heel plate foot tracking methods on lower extremity dynamics

The primary method to model ankle motion during inverse dynamic calculations of the lower limb is through the use of skin-mounted markers, with the foot modeled as a rigid segment. Motion of the foot is often tracked via the use of a marker cluster triad on either the dorsum, or heel, of the foot/shoe. The purpose of this investigation was to evaluate differences in calculated lower extremity dynamics during the stance phase of gait between these two tracking techniques. In an analysis of 7 subjects, it was found that sagittal ankle angles and sagittal ankle, hip and knee moments were strongly correlated between the two conditions, however, there was a significant difference in peak ankle plantar flexion and dorsiflexion angles. Frontal ankle angles were only moderately correlated and there was a significant difference in peak ankle eversion and inversion, resulting in moderate correlations in frontal plane moments and a significant difference in peak hip adductor moments. We demonstrate that the technique used to track the foot is an important consideration in interpreting lower extremity dynamics for clinical and research purposes.     

Effect of vegetation on density thresholds of adult desert locust gregarization from survey data in Mauritania

In the desert locust, Schistocerca gregaria (Forskål) (Orthoptera: Acrididae), the threshold density inducing the gregarization phenomenon has never been determined under natural conditions. The influence of environmental factors on this phenomenon has been studied mostly in controlled environments. Based on data collected during several years by the survey teams of the National Center for Locust Control in Mauritania, we analyzed the influence of locust density, vegetation cover, and vegetation status on the probability of observing gregarious locusts. We assumed that a probability to observe gregarious locusts of 0.5 corresponded to the density threshold of gregarization. The results showed in detail the change in the threshold of gregarization according to the cover and status of the vegetation. Low cover and dry vegetation led to a low density threshold of gregarization probably due to high probability of individuals to touch each other. Dense and green vegetation favored a high threshold of gregarization probably due to a dispersion of the individuals and a low probability of individual encounters. These findings should help the management of locusts and decision making during control operations.     

Physiological compartmental analysis of alpha-linolenic acid metabolism in adult humans

A physiological compartmental model of alpha-linolenic acid metabolism was derived from the plasma concentration-time curves for d5-18:3n-3, d5-20:5n-3, d5-22:5n-3, and d5-22:6n-3 in eight healthy subjects. Subjects received a 1-g oral dose of an isotope tracer of alpha-linolenate (d5-18:3n-3 ethyl ester) while subsisting on a rigorously controlled beef-based diet. By utilizing the Windows Simulation and Analysis Modeling program, kinetic parameters were determined for each subject. Half-lives and mean transit times of the n-3 fatty acids in the plasma were also determined. The model predicted plasma values for the n-3 fatty acids in good accordance with the measured steady state concentrations and also predicted dietary linolenic acid intake for each subject in accordance with values determined by lipid analysis of the diet. Only about 0.2% of the plasma 18:3n-3 was destined for synthesis of 20:5n-3, approximately 63% of the plasma 20:5n-3 was accessible for production of 22:5n-3, and 37% of 22:5n-3 was available for synthesis of 22:6n-3. The inefficiency of the conversion of 18:3n-3 to 20:5n-3 indicates that the biosynthesis of long-chain n-3 PUFA from alpha-linolenic acid is limited in healthy individuals. In contrast, the much greater rate of transfer of mass from the plasma 20:5n-3 compartment to 22:5n-3 suggests that dietary eicosapentaenoic acid may be well utilized in the biosynthesis of 22:6n-3 in humans.     

Data mining in proteomic mass spectrometry

Data mining application to proteomic data from mass spectrometry has gained much interest in recent years. Advances made in proteomics and mass spectrometry have resulted in considerable amount of data that cannot be easily visualized or interpreted. Mass spectral proteomic datasets are typically high dimensional but with small sample size. Consequently, advanced artificial intelligence and machine learning algorithms are increasingly being used for knowledge discovery from such datasets. Their overall goal is to extract useful information that leads to the identification of protein biomarker candidates. Such biomarkers could potentially have diagnostic value as tools for early detection, diagnosis, and prognosis of many diseases. The purpose of this review is to focus on the current trends in mining mass spectral proteomic data. Special emphasis is placed on the critical steps involved in the analysis of surface-enhanced laser desorption/ionization mass spectrometry proteomic data. Examples are drawn from previously published studies and relevant data mining terminology and techniques are exlained.     

Interleukin-15 plays a central role in human kidney physiology and cancer through the γc signaling pathway

The ability of Interleukin-15 (IL-15) to activate many immune antitumor mechanisms renders the cytokine a good candidate for the therapy of solid tumors, particularly renal cell carcinoma. Although IL-15 is being currently used in clinical trials, the function of the cytokine on kidney's components has not been extensively studied; we thus investigated the role of IL-15 on normal and tumor renal epithelial cells. Herein, we analyzed the expression and the biological functions of IL-15 in normal renal proximal tubuli (RPTEC) and in their neoplastic counterparts, the renal clear cell carcinomas (RCC). This study shows that RPTEC express a functional heterotrimeric IL-15Rαβγc complex whose stimulation with physiologic concentrations of rhIL-15 is sufficient to inhibit epithelial mesenchymal transition (EMT) commitment preserving E-cadherin expression. Indeed, IL-15 is not only a survival factor for epithelial cells, but it can also preserve the renal epithelial phenotype through the γc-signaling pathway, demonstrating that the cytokine possess a wide range of action in epithelial homeostasis. In contrast, in RCC in vitro and in vivo studies reveal a defect in the expression of γc-receptor and JAK3 associated kinase, which strongly impacts IL-15 signaling. Indeed, in the absence of the γc/JAK3 couple we demonstrate the assembly of an unprecedented functional high affinity IL-15Rαβ heterodimer, that in response to physiologic concentrations of IL-15, triggers an unbalanced signal causing the down-regulation of the tumor suppressor gene E-cadherin, favoring RCC EMT process. Remarkably, the rescue of IL-15/γc-dependent signaling (STAT5), by co-transfecting γc and JAK3 in RCC, inhibits EMT reversion. In conclusion, these data highlight the central role of IL-15 and γc-receptor signaling in renal homeostasis through the control of E-cadherin expression and preservation of epithelial phenotype both in RPTEC (up-regulation) and RCC (down-regulation).     

Autophagy Limits Endotoxemic Acute Kidney Injury and Alters Renal Tubular Epithelial Cell Cytokine Expression

Sepsis related acute kidney injury (AKI) is a common in-hospital complication with a dismal prognosis. Our incomplete understanding of disease pathogenesis has prevented the identification of hypothesis-driven preventive or therapeutic interventions. Increasing evidence in ischemia-reperfusion and nephrotoxic mouse models of AKI support the theory that autophagy protects renal tubular epithelial cells (RTEC) from injury. However, the role of RTEC autophagy in septic AKI remains unclear. We observed that lipopolysaccharide (LPS), a mediator of gram-negative bacterial sepsis, induces RTEC autophagy in vivo and in vitro through TLR4-initiated signaling. We modeled septic AKI through intraperitoneal LPS injection in mice in which autophagy-related protein 7 was specifically knocked out in the renal proximal tubules (ATG7KO). Compared to control littermates, ATG7KO mice developed more severe renal dysfunction (24hr BUN 100.1mg/dl +/- 14.8 vs 54.6mg/dl +/- 11.3) and parenchymal injury. After injection with LPS, analysis of kidney lysates identified higher IL-6 expression and increased STAT3 activation in kidney lysates from ATG7KO mice compared to controls. In vitro experiments confirmed an altered response to LPS in RTEC with genetic or pharmacological impairment of autophagy. In conclusion, RTEC autophagy protects against endotoxin induced injury and regulates downstream effects of RTEC TLR4 signaling.     

Coupling historical prospection data and a remotely-sensed vegetation index for the preventative control of Desert locusts

Locusts are grasshopper species that exhibit phase polyphenism resulting in the expression of gregarious behaviors that favor the development of large devastating bands and swarms. Desert locust preventative management aims to prevent crop damage by controlling populations before they can reach high densities and form mass migrating swarms. The areas of potential gregarization for Desert locust are large and need to be physically assessed by survey teams for efficient preventative management. An ongoing challenge is to be able to guide where prospection surveys should occur depending on local meteorological and vegetation conditions. In this study, we analyzed the relationship between historical prospection data of Desert locust observations from 2005 to 2009 and spatio-temporal statistics of a vegetation index gathered by remote-sensing with the help of multiple models of logistic regression. The vegetation index was a composite Normalized Difference Vegetation Index (NDVI) given every 16 days and at 250 m spatial resolution (MOD13Q1 from MODIS satellite). The statistics extracted from this index were: (1) spatial means at different scales around the prospection point, (2) relative differences of NDVI variation through time before the prospection, and (3) large-scale summary of vegetation quantity. The multi-model framework showed that vegetation development a month and a half before the survey was amongst the best predictors of locust presence. Also, the local vegetation quantity was not enough to predict locust presence. Vegetation quantity on a scale of a few kilometers was a better predictor but varied non-linearly, reflecting specific biotope types that support Desert locust development. Using one of the best logistic regression models and NDVI data, we were able to derive a predictive model of probability of finding locusts in specific areas. This methodology should help in more efficiently focusing survey efforts on specific parts of the gregarization areas based on the predicted probability of locusts being present.