Effect of postnatal development on calcium currents and slow charge movement in mammalian skeletal muscle

Single- (whole-cell patch) and two-electrode voltage-clamp techniques were used to measure transient (Ifast) and sustained (Islow) calcium currents, linear capacitance, and slow, voltage-dependent charge movements in freshly dissociated fibers of the flexor digitorum brevis (FDB) muscle of rats of various postnatal ages. Peak Ifast was largest in FDB fibers of neonatal (1-5 d) rats, having a magnitude in 10 mM external Ca of 1.4 +/- 0.9 pA/pF (mean +/- SD; current normalized by linear fiber capacitance). Peak Ifast was smaller in FDB fibers of older animals, and by approximately 3 wk postnatal, it was so small as to be unmeasurable. By contrast, the magnitudes of Islow and charge movement increased substantially during postnatal development. Peak Islow was 3.6 +/- 2.5 pA/pF in FDB fibers of 1-5-d rats and increased to 16.4 +/- 6.5 pA/pF in 45-50-d-old rats; for these same two age groups, Qmax, the total mobile charge measurable as charge movement, was 6.0 +/- 1.7 and 23.8 +/- 4.0 nC/microF, respectively. As both Islow and charge movement are thought to arise in the transverse-tubular system, linear capacitance normalized by the area of fiber surface was determined as an indirect measure of the membrane area of the t-system relative to that of the fiber surface. This parameter increased from 1.5 +/- 0.2 microF/cm2 in 2-d fibers to 2.9 +/- 0.4 microF/cm2 in 44-d fibers. The increases in peak Islow, Qmax, and normalized linear capacitance all had similar time courses. Although the function of Islow is unknown, the substantial postnatal increase in its magnitude suggests that it plays an important role in the physiology of skeletal muscle.     

Molecular evolution of voltage-sensitive ion channel genes: on the origins of electrical excitability

We have analyzed nucleic acid and amino acid sequence alignments of a variety of voltage-sensitive ion channels, using several methods for phylogenetic tree reconstruction. Ancient duplications within this family gave rise to three distantly related groups, one consisting of the Na+ and Ca++ channels, another the K+ channels, and a third including the cyclic nucleotide-binding channels. A series of gene duplications produced at least seven mammalian homologues of the Drosophila Shaker K+ channel; clones of only three of these genes are available from all three mammalian species examined (mouse, rat, and human), pointing to specific genes that have yet to be recovered in one or another of these species. The Shaw-related K+ channels and the Na+ channel family have also undergone considerable expansion in mammals, relative to flies. These expansions presumably reflect the needs of the high degree of physiological and neuronal complexity of mammals. Analysis of the separate domains of the four-domain channels (Ca++ and Na+) supports their having evolved by two sequential gene duplications and implies the historical existence of a functional two-domain channel.      

Linking mosquito surveillance to dengue fever through Bayesian mechanistic modeling

Our ability to effectively prevent the transmission of the dengue virus through targeted control of its vector, Aedes aegypti, depends critically on our understanding of the link between mosquito abundance and human disease risk. Mosquito and clinical surveillance data are widely collected, but linking them requires a modeling framework that accounts for the complex non-linear mechanisms involved in transmission. Most critical are the bottleneck in transmission imposed by mosquito lifespan relative to the virus’ extrinsic incubation period, and the dynamics of human immunity. We developed a differential equation model of dengue transmission and embedded it in a Bayesian hierarchical framework that allowed us to estimate latent time series of mosquito demographic rates from mosquito trap counts and dengue case reports from the city of Vitória, Brazil. We used the fitted model to explore how the timing of a pulse of adult mosquito control influences its effect on the human disease burden in the following year. We found that control was generally more effective when implemented in periods of relatively low mosquito mortality (when mosquito abundance was also generally low). In particular, control implemented in early September (week 34 of the year) produced the largest reduction in predicted human case reports over the following year. This highlights the potential long-term utility of broad, off-peak-season mosquito control in addition to existing, locally targeted within-season efforts. Further, uncertainty in the effectiveness of control interventions was driven largely by posterior variation in the average mosquito mortality rate (closely tied to total mosquito abundance) with lower mosquito mortality generating systems more vulnerable to control. Broadly, these correlations suggest that mosquito control is most effective in situations in which transmission is already limited by mosquito abundance.     

What processes must we understand to forecast regional-scale population dynamics?

An urgent challenge facing biologists is predicting the regional-scale population dynamics of species facing environmental change. Biologists suggest that we must move beyond predictions based on phenomenological models and instead base predictions on underlying processes. For example, population biologists, evolutionary biologists, community ecologists and ecophysiologists all argue that the respective processes they study are essential. Must our models include processes from all of these fields? We argue that answering this critical question is ultimately an empirical exercise requiring a substantial amount of data that have not been integrated for any system to date. To motivate and facilitate the necessary data collection and integration, we first review the potential importance of each mechanism for skilful prediction. We then develop a conceptual framework based on reaction norms, and propose a hierarchical Bayesian statistical framework to integrate processes affecting reaction norms at different scales. The ambitious research programme we advocate is rapidly becoming feasible due to novel collaborations, datasets and analytical tools.     

Intensified Tuberculosis Case Finding among Malnourished Children in Nutritional Rehabilitation Centres of Karnataka,India: Missed Opportunities

Background

Severe acute malnutrition (SAM) is the most serious form of malnutrition affecting children under-five and is associated with many infectious diseases including Tuberculosis (TB). In India, nutritional rehabilitation centres (NRCs) have been recently established for the management of SAM including TB. The National TB Programme (NTP) in India has introduced a revised algorithm for diagnosing paediatric TB. We aimed to examine whether NRCs adhered to these guidelines in diagnosing TB among SAM children.

Methods

A cross-sectional study involving review of records of all SAM children identified by health workers during 2012 in six tehsils (sub-districts) with NRCs (population: 1.8 million) of Karnataka, India.

Results

Of 1927 identified SAM children, 1632 (85%) reached NRCs. Of them, 1173 (72%) were evaluated for TB and 19(2%) were diagnosed as TB. Of 1173, diagnostic algorithm was followed in 460 (37%). Among remaining 763 not evaluated as per algorithm, tuberculin skin test alone was conducted in 307 (41%), chest radiography alone in 99 (13%) and no investigations in 337 (45%). The yield of TB was higher among children evaluated as per algorithm (4%) as compared to those who were not (0.3%) (OR: 15.3 [95%CI: 3.5-66.3]). Several operational challenges including non-availability of a full-time paediatrician, non-functioning X-ray machine due to frequent power cuts, use of tuberculin with suboptimal strength and difficulties in adhering to a complex diagnostic algorithm were observed.

Conclusion

This study showed that TB screening in NRCs was sub-optimal in Karnataka. Some children did not reach the NRC, while many of those who did were either not or sub-optimally evaluated for TB. This study pointed to a number of operational issues that need to be addressed if this collaborative strategy is to identify more TB cases amongst malnourished children in India.     

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.     

Prey-mediated avoidance of an intraguild predator by its intraguild prey

Intraguild (IG) predation is an important factor influencing community structure, yet factors allowing coexistence of IG predator and IG prey are not well understood. The existence of spatial refuges for IG prey has recently been noted for their importance in allowing coexistence. However, reduction in basal prey availability might lead IG prey to leave spatial refuges for greater access to prey, leading to increased IG predation and fewer opportunities for coexistence. We determined how the availability of prey affected space-use patterns of bobcats (Lynx rufus, IG prey) in relation to coyote space-use patterns (Canis latrans, IG predators). We located animals from fall 2007 to spring 2009 and estimated bobcat home ranges and core areas seasonally. For each bobcat relocation, we determined intensity of coyote use, distance to water, small mammal biomass, and mean small mammal biomass of the home range during the season the location was collected. We built generalized linear mixed models and used Akaike Information Criteria to determine which factors best predicted bobcat space use. Coyote intensity was a primary determinant of bobcat core area location. In bobcat home ranges with abundant prey, core areas occurred where coyote use was low, but shifted to areas intensively used by coyotes when prey declined. High spatial variability in basal prey abundance allowed some bobcats to avoid coyotes while at the same time others were forced into more risky areas. Our results suggest that multiple behavioral strategies associated with spatial variation in basal prey abundance likely allow IG prey and IG predators to coexist.     

Zebrafish: a model for the study of addiction genetics

Drug abuse and dependence are multifaceted disorders with complex genetic underpinnings. Identifying specific genetic correlates is challenging and may be more readily accomplished by defining endophenotypes specific for addictive disorders. Symptoms and syndromes, including acute drug response, consumption, preference, and withdrawal, are potential endophenotypes characterizing addiction that have been investigated using model organisms. We present a review of major genes involved in serotonergic, dopaminergic, GABAergic, and adrenoreceptor signaling that are considered to be directly involved in nicotine, opioid, cannabinoid, and ethanol use and dependence. The zebrafish genome encodes likely homologs of the vast majority of these loci. We also review the known expression patterns of these genes in zebrafish. The information presented in this review provides support for the use of zebrafish as a viable model for studying genetic factors related to drug addiction. Expansion of investigations into drug response using model organisms holds the potential to advance our understanding of drug response and addiction in humans.