Ciliopathy is differentially distributed in the brain of a Bardet-Biedl syndrome mouse model

Bardet-Biedl syndrome (BBS) is a genetically heterogeneous inherited human disorder displaying a pleotropic phenotype. Many of the symptoms characterized in the human disease have been reproduced in animal models carrying deletions or knock-in mutations of genes causal for the disorder. Thinning of the cerebral cortex, enlargement of the lateral and third ventricles, and structural changes in cilia are among the pathologies documented in these animal models. Ciliopathy is of particular interest in light of recent studies that have implicated primary neuronal cilia (PNC) in neuronal signal transduction. In the present investigation, we tested the hypothesis that areas of the brain responsible for learning and memory formation would differentially exhibit PNC abnormalities in animals carrying a deletion of the Bbs4 gene (Bbs4-/-). Immunohistochemical localization of adenylyl cyclase-III (ACIII), a marker restricted to PNC, revealed dramatic alterations in PNC morphology and a statistically significant reduction in number of immunopositive cilia in the hippocampus and amygdala of Bbs4-/- mice compared to wild type (WT) littermates. Western blot analysis confirmed the decrease of ACIII levels in the hippocampus and amygdala of Bbs4-/- mice, and electron microscopy demonstrated pathological alterations of PNC in the hippocampus and amygdala. Importantly, no neuronal loss was found within the subregions of amygdala and hippocampus sampled in Bbs4-/- mice and there were no statistically significant alterations of ACIII immunopositive cilia in other areas of the brain not known to contribute to the BBS phenotype. Considered with data documenting a role of cilia in signal transduction these findings support the conclusion that alterations in cilia structure or neurochemical phenotypes may contribute to the cognitive deficits observed in the Bbs4-/- mouse mode. © 2014 Agassandian et al

Understanding implementation and feasibility of tobacco cessation in routine primary care in Nepal: a mixed methods study

Background: By 2030, 80 % of the annual 8.3 million deaths attributable to tobacco will be in low-income countries (LICs). Yet, services to support people to quit tobacco are not part of routine primary care in LICs. This study explored the challenges to implementing a behavioural support (BS) intervention to promote tobacco cessation within primary care in Nepal. Methods: The study used qualitative and quantitative methods within an action research approach in three primary health care centres (PHCCs) in two districts of Nepal. Before implementation, 21 patient interviews and two focus groups with health workers informed intervention design. Over a 6-month period, two researchers facilitated action research meetings with staff and observed implementation, recording the process and their reflections in diaries. Patients were followed up 3 months after BS to determine tobacco use (verified biochemically) and gain feedback on the intervention. A further five interviews with managers provided reflections on the process. The qualitative analysis used Normalisation Process Theory (NPT) to understand implementation. Results: Only 2 % of out-patient appointments identified the patient as a smoker. Qualitative findings highlight patients' unwillingness to admit their smoking status and limited motivation among health workers to offer the intervention. Patient-centred skills needed for BS were new to staff, who found them challenging particularly with low-literacy patients (skill set workability). Heath workers saw cessation advice and BS as an addition to their existing workload (relational integration). While there was strong policy buy-in, operationalising this through reporting and supervision was limited (contextual integration). Of the 44 patients receiving the intervention, 27 were successfully followed up after 3 months; 37 % of these had quit (verified biochemically). Conclusions: Traditionally, primary health care in LICs has focused on acute care; with increasing recognition of the need for lifestyle change, health workers must develop new skills and relationships with patients. Appropriate and regular recording, reporting, supervision and clear leadership are needed if health workers are to take responsibility for smoking cessation. The consistent implementation of these health system activities is a requirement if cessation services are to be normalised within routine primary care

HSPB1, HSPB6, HSPB7 and HSPB8 Protect against RhoA GTPase-Induced Remodeling in Tachypaced Atrial Myocytes

BACKGROUND: We previously demonstrated the small heat shock protein, HSPB1, to prevent tachycardia remodeling in in vitro and in vivo models for Atrial Fibrillation (AF). To gain insight into its mechanism of action, we examined the protective effect of all 10 members of the HSPB family on tachycardia remodeling. Furthermore, modulating effects of HSPB on RhoA GTPase activity and F-actin stress fiber formation were examined, as this pathway was found of prime importance in tachycardia remodeling events and the initiation of AF. METHODS AND RESULTS: Tachypacing (4 Hz) of HL-1 atrial myocytes significantly and progressively reduced the amplitude of Ca²⁺ transients (CaT). In addition to HSPB1, also overexpression of HSPB6, HSPB7 and HSPB8 protected against tachypacing-induced CaT reduction. The protective effect was independent of HSPB1. Moreover, tachypacing induced RhoA GTPase activity and caused F-actin stress fiber formation. The ROCK inhibitor Y27632 significantly prevented tachypacing-induced F-actin formation and CaT reductions, showing that RhoA activation is required for remodeling. Although all protective HSPB members prevented the formation of F-actin stress fibers, their mode of action differs. Whilst HSPB1, HSPB6 and HSPB7 acted via direct prevention of F-actin formation, HSPB8-protection was mediated via inhibition of RhoA GTPase activity. CONCLUSION: Overexpression of HSPB1, as well as HSPB6, HSPB7 and HSPB8 independently protect against tachycardia remodeling by attenuation of the RhoA GTPase pathway at different levels. The cardioprotective role for multiple HSPB members indicate a possible therapeutic benefit of compounds able to boost the expression of single or multiple members of the HSPB family

Amygdala 14-3-3ζ as a Novel Modulator of Escalating Alcohol Intake in Mice

Alcoholism is a devastating brain disorder that affects millions of people worldwide. The development of alcoholism is caused by alcohol-induced maladaptive changes in neural circuits involved in emotions, motivation, and decision-making. Because of its involvement in these processes, the amygdala is thought to be a key neural structure involved in alcohol addiction. However, the molecular mechanisms that govern the development of alcoholism are incompletely understood. We have previously shown that in a limited access choice paradigm, C57BL/6J mice progressively escalate their alcohol intake and display important behavioral characteristic of alcohol addiction, in that they become insensitive to quinine-induced adulteration of alcohol. This study used the limited access choice paradigm to study gene expression changes in the amygdala during the escalation to high alcohol consumption in C57BL/6J mice. Microarray analysis revealed that changes in gene expression occurred predominantly after one week, i.e. during the initial escalation of alcohol intake. One gene that stood out from our analysis was the adapter protein 14-3-3ζ, which was up-regulated during the transition from low to high alcohol intake. Independent qPCR analysis confirmed the up-regulation of amygdala 14-3-3ζ during the escalation of alcohol intake. Subsequently, we found that local knockdown of 14-3-3ζ in the amygdala, using RNA interference, dramatically augmented alcohol intake. In addition, knockdown of amygdala 14-3-3ζ promoted the development of inflexible alcohol drinking, as apparent from insensitivity to quinine adulteration of alcohol. This study identifies amygdala 14-3-3ζ as a novel key modulator that is engaged during escalation of alcohol use

Neural computations underpinning the strategic management of influence in advice giving

Research on social influence has focused mainly on the target of influence (e.g., consumer and voter); thus, the cognitive and neurobiological underpinnings of the source of the influence (e.g., politicians and salesmen) remain unknown. Here, in a three-sided advice-giving game, two advisers competed to influence a client by modulating their own confidence in their advice about which lottery the client should choose. We report that advisers’ strategy depends on their level of influence on the client and their merit relative to one another. Moreover, blood-oxygenation-level-dependent (BOLD) signal in the temporo-parietal junction is modulated by adviser’s current level of influence on the client, and relative merit prediction error affects activity in medial-prefrontal cortex. Both types of social information modulate ventral striatum response. By demonstrating what happens in our mind and brain when we try to influence others, these results begin to explain the biological mechanisms that shape inter-individual differences in social conduct

Combining biophysical parameters with thermal and RGB indices using machine learning models for predicting yield in yellow rust affected wheat crop

Abstract Evaluating crop health and forecasting yields in the early stages are crucial for effective crop and market management during periods of biotic stress for both farmers and policymakers. Field experiments were conducted during 2017–18 and 2018–19 with objective to evaluate the effect of yellow rust on various biophysical parameters of 24 wheat cultivars, with varying levels of resistance to yellow rust and to develop machine learning (ML) models with improved accuracy for predicting yield by integrating thermal and RGB indices with crucial plant biophysical parameters. Results revealed that as the level of rust increased, so did the canopy temperature and there was a significant decrease in crop photosynthesis, transpiration, stomatal conductance, leaf area index, membrane stability index, relative leaf water content, and normalized difference vegetation index due to rust, and the reductions were directly correlated with levels of rust severity. The yield reduction in moderate resistant, low resistant and susceptible cultivars as compared to resistant cultivars, varied from 15.9–16.9%, 28.6–34.4% and 59–61.1%, respectively. The ML models were able to provide relatively accurate early yield estimates, with the accuracy increasing as the harvest approached. The yield prediction performance of the different ML models varied with the stage of the crop growth. Based on the validation output of different ML models, Cubist, PLS, and SpikeSlab models were found to be effective in predicting the wheat yield at an early stage (55-60 days after sowing) of crop growth. The KNN, Cubist, SLR, RF, SpikeSlab, XGB, GPR and PLS models were proved to be more useful in predicting the crop yield at the middle stage (70 days after sowing) of the crop, while RF, SpikeSlab, KNN, Cubist, ELNET, GPR, SLR, XGB and MARS models were found good to predict the crop yield at late stage (80 days after sowing). The study quantified the impact of different levels of rust severity on crop biophysical parameters and demonstrated the usefulness of remote sensing and biophysical parameters data integration using machine-learning models for early yield prediction under biotically stressed conditions