Respiratory phasic effects of inspiratory loading on left ventricular hemodynamics in vagotomized dogs.

Exaggerated inspiratory swings in intrathoracic pressure have been postulated to increase left ventricular (LV) afterload. These predictions are based on measurements of LV afterload by use of esophageal or lateral pleural pressure. Using direct measurements of pericardial pressure, we reexamined respiratory changes in LV afterload. In 11 anesthetized vagotomized dogs, we measured arterial pressure, LV end-systolic (ES) and end-diastolic transmural (TM) pressures, stroke volume (SV), diastolic left anterior descending blood flow (CBF-D), and coronary resistance. Dogs were studied before and while breathing against an inspiratory threshold load of -20 to -25 cmH2O compared with end expiration. Relative to end expiration, SV and LVES TM pressures decreased during inspiration and increased during early expiration, effects exaggerated during inspiratory loading. In all cases, LV afterload (LVES TM pressure) changed in parallel with SV. LV end-diastolic TM pressure did not change. CBF-D paralleled arterial pressure, and there were no changes in coronary resistance. In two dogs, regional LVES segment length paralleled calculated changes in LVES TM pressure. We conclude that 1) LV afterload decreases during early inspiration and increases during early expiration, changes secondary to those in SV; 2) changes in CBF-D are secondary to changes in perfusion pressure during the respiratory cycle; and 3) the use of esophageal or lateral pleural pressure to estimate LV surface pressure overestimates changes in LV TM pressures during respiration.     

Effects of hypoxic and CO hypoxia on isolated hearts.

Isolated perfused dog hearts were made hypoxic by respiring the support dog with low oxygen (hypoxic hypoxia) or with carbon monoxide (CO hypoxia). Each heart was exposed to both types of hypoxia, separately. Effects on coronary flow (Qt), coronary vascular resistance, cardiac oxygen consumption (Vo2), and contractility (%deltadP/dt) were studied. Two series of experiments were done. Series I: At constant perfusion pressure. As oxygen content (Cao2) was lowered from 20 to 5 vol%, Qt doubled with hypoxic hypoxia and almost tripled with CO hypoxia (P less than 0.01). Vo2 and contractility increased with both types of hypoxia. Beta-adrenergic blockade eliminated the increase in VO2 and contractility but not the difference in Qt increase between hypoxic and CO hypoxia. Series II: At constant Qt (with beta-blockade), vascular resistance decreased more with CO than hypoxic hypoxia. Finally, alpha-blockade eliminated the difference in vascular resistance and thus with complete (alpha and beta) blockade, the two types of hypoxia have the same effect and are indistinguishable.     

A Pilot Randomized Controlled Trial of a Clinic and Home‐Based Behavioral Intervention to Decrease Obesity in Preschoolers

We evaluated the efficacy of a 6‐month clinic and home‐based behavioral intervention (Learning about Activity and Understanding Nutrition for Child Health; LAUNCH) to reduce obesity in preschool children ≥95th BMI percentile compared to enhanced standard of care (Pediatrician Counseling; PC). LAUNCH was a family‐based behavioral intervention that taught parents to use child behavior management strategies to increase healthy eating and activity for their children and themselves. PC presented the same diet and activity recommendations, but was delivered in a one‐time PC session. Eighteen children aged 2–5 years (mean 4.71 ± 1.01) with an average BMI percentile of 98 (±1.60) and an overweight parent were randomized to LAUNCH or PC. Assessments were conducted at baseline, 6 months (end of LAUNCH treatment) and 12 months (6 months following LAUNCH treatment). LAUNCH showed a significantly greater decrease on the primary outcomes of child at month 6 (post‐treatment) BMI z (?0.59 ± 0.17), BMI percentile (?2.4 ± 1.0), and weight gain (?2.7 kg ± 1.2) than PC and this difference was maintained at follow‐up (month 12). LAUNCH parents also had a significantly greater weight loss (?5.5 kg ± 0.9) at month 6 and 12 (?8.0 kg ± 3.5) than PC parents. Based on the data from this small sample, an intensive intervention that includes child behavior management strategies to improve healthy eating and activity appears more promising in reducing preschool obesity than a low intensity intervention that is typical of treatment that could be delivered in primary care.     

Accounting for phenology in the analysis of animal movement

The analysis of animal tracking data provides important scientific understanding and discovery in ecology. Observations of animal trajectories using telemetry devices provide researchers with information about the way animals interact with their environment and each other. For many species, specific geographical features in the landscape can have a strong effect on behavior. Such features may correspond to a single point (eg, dens or kill sites), or to higher dimensional subspaces (eg, rivers or lakes). Features may be relatively static in time (eg, coastlines or home‐range centers), or may be dynamic (eg, sea ice extent or areas of high‐quality forage for herbivores). We introduce a novel model for animal movement that incorporates active selection for dynamic features in a landscape. Our approach is motivated by the study of polar bear (Ursus maritimus) movement. During the sea ice melt season, polar bears spend much of their time on sea ice above shallow, biologically productive water where they hunt seals. The changing distribution and characteristics of sea ice throughout the year mean that the location of valuable habitat is constantly shifting. We develop a model for the movement of polar bears that accounts for the effect of this important landscape feature. We introduce a two‐stage procedure for approximate Bayesian inference that allows us to analyze over 300 000 observed locations of 186 polar bears from 2012 to 2016. We use our model to estimate a spatial boundary of interest to wildlife managers that separates two subpopulations of polar bears from the Beaufort and Chukchi seas.     

Combination of a Proteomics Approach and Reengineering of Meso Scale Network Models for Prediction of Mode-of-Action for Tyrosine Kinase Inhibitors

In drug discovery, the characterisation of the precise modes of action (MoA) and of unwanted off-target effects of novel molecularly targeted compounds is of highest relevance. Recent approaches for identification of MoA have employed various techniques for modeling of well defined signaling pathways including structural information, changes in phenotypic behavior of cells and gene expression patterns after drug treatment. However, efficient approaches focusing on proteome wide data for the identification of MoA including interference with mutations are underrepresented. As mutations are key drivers of drug resistance in molecularly targeted tumor therapies, efficient analysis and modeling of downstream effects of mutations on drug MoA is a key to efficient development of improved targeted anti-cancer drugs. Here we present a combination of a global proteome analysis, reengineering of network models and integration of apoptosis data used to infer the mode-of-action of various tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia (CML) cell lines expressing wild type as well as TKI resistance conferring mutants of BCR-ABL. The inferred network models provide a tool to predict the main MoA of drugs as well as to grouping of drugs with known similar kinase inhibitory activity patterns in comparison to drugs with an additional MoA. We believe that our direct network reconstruction approach, demonstrated on proteomics data, can provide a complementary method to the established network reconstruction approaches for the preclinical modeling of the MoA of various types of targeted drugs in cancer treatment. Hence it may contribute to the more precise prediction of clinically relevant on- and off-target effects of TKIs.     

Identification of clinically relevant protein targets in prostate cancer with 2D-DIGE coupled mass spectrometry and systems biology network platform

Prostate cancer (PCa) is the most common type of cancer found in men and among the leading causes of cancer death in the western world. In the present study, we compared the individual protein expression patterns from histologically characterized PCa and the surrounding benign tissue obtained by manual micro dissection using highly sensitive two-dimensional differential gel electrophoresis (2D-DIGE) coupled with mass spectrometry. Proteomic data revealed 118 protein spots to be differentially expressed in cancer (n = 24) compared to benign (n = 21) prostate tissue. These spots were analysed by MALDI-TOF-MS/MS and 79 different proteins were identified. Using principal component analysis we could clearly separate tumor and normal tissue and two distinct tumor groups based on the protein expression pattern. By using a systems biology approach, we could map many of these proteins both into major pathways involved in PCa progression as well as into a group of potential diagnostic and/or prognostic markers. Due to complexity of the highly interconnected shortest pathway network, the functional sub networks revealed some of the potential candidate biomarker proteins for further validation. By using a systems biology approach, our study revealed novel proteins and molecular networks with altered expression in PCa. Further functional validation of individual proteins is ongoing and might provide new insights in PCa progression potentially leading to the design of novel diagnostic and therapeutic strategies.     

Interaction of CheY2 and CheY2-P with the cognate CheA kinase in the chemosensory-signalling chain of Sinorhizobium meliloti

An unusual regulatory mechanism involving two response regulators, CheY1 and CheY2, but no CheZ phosphatase, operates in the chemotactic signalling chain of Sinorhizobium meliloti . Active CheY2-P, phosphorylated by the cognate histidine kinase, CheA, is responsible for flagellar motor control. In the absence of any CheZ phosphatase activity, the level of CheY2-P is quickly reset by a phospho-transfer from CheY2-P first back to CheA, and then to CheY1, which acts as a phosphate sink. In studying the mechanism of this phosphate shuttle, we have used GFP fusions to show that CheY2, but not CheY1, associates with CheA at a cell pole. Cross-linking experiments with the purified proteins revealed that both CheY2 and CheY2-P bind to an isolated P2 ligand-binding domain of CheA, but CheY1 does not. The dissociation constants of CheA–CheY2 and CheA–CheY2-P indicated that both ligands bind with similar affinity to CheA. Based on the NMR structures of CheY2 and CheY2-P, their interactions with the purified P2 domain were analysed. The interacting surface of CheY2 comprises its C-terminal β4-α4-β5-α5 structural elements, whereas the interacting surface of CheY2-P is shifted towards the loop connecting β5 and α5. We propose that the distinct CheY2 and CheY2-P surfaces interact with two overlapping sites in the P2 domain that selectively bind either CheY2 or CheY2-P, depending on whether CheA is active or inactive.