Single cell preparations of Mycobacterium tuberculosis damage the mycobacterial envelope and disrupt macrophage interactions

For decades, investigators have studied the interaction o

Salt Tolerance Mechanisms in Perennial Fodder Grasses

Salinity stress is one of the most damaging stresses in crop plants. It reduces the productivity of the soil and makes it unsuitable for crop cultivation. Fodder crops are considered the best alternative in such uncultivable land. Using salinity-affected land for pasture development is the best alternative to utilize such lands. However, the extent of salinity tolerance varies among different grass species. In this study, Pearl millet Napier hybrids (PMN hybrid) and guinea grass varieties were studied for salinity tolerance in artificially created saline soils in the ratio of 13:7:1:2 (NaCl: Na2SO4: MgCl: CaSO4, respectively) to understand the salinity tolerance mechanisms existing in perennial fodder grasses. Morphologically, the plant height increased in saline-tolerant PMN hybrid varieties, creating more space in nonphotosynthetic tissues to store accumulated salts away from photosynthetic tissues. Whereas in guinea grass tolerant varieties, tiller number increased under salinity. The fresh weight was highest under salinity in the PMN hybrids. In contrast, dry weight was high in control (no salt) plants, implying more water accumulation in PMN hybrids under salinity to dilute the concentration of salts absorbed by the plant. In Guinea grass, varieties like DGG1 had lower leaf succulence than control and high salt excretion through leaf hairs. Tissue tolerance in PMN hybrids was less compared to guinea grass. Membrane stability was maintained in saline-tolerant varieties. The double bond index increased in tolerant PMN hybrid varieties under salinity compared to control, implying fatty acid remodelling for maintaining the stability of membranes under salinity. Fodder grasses adopt various saline tolerance mechanisms based on their growth habit and morphology

Improved Precision Measurement of the Casimir Force

We report an improved precision measurement of the Casimir force. The force is measured between a large Al coated sphere and flat plate using an Atomic Force Microscope. The primary experimental improvements include the use of smoother metal coatings, reduced noise, lower systematic errors and independent measurement of surface separations. Also the complete dielectric spectrum of the metal is used in the theory. The average statistical precision remains at the same 1% of the forces measured at the closest separation

Complete roughness and conductivity corrections for the recent Casimir force measurement

We consider detailed roughness and conductivity corrections to the Casimir force in the recent Casimir force measurement employing an Atomic Force Microscope. The roughness of the test bodies-a metal plate and a sphere- was investigated with the Atomic Force Microscope and the Scanning Electron Microscope respectively. It consists of separate crystals of different heights and a stochastic background. The amplitude of roughness relative to the zero roughness level was determined and the corrections to the Casimir force were calculated up to the fourth order in a small parameter (which is this amplitude divided by the distance between the two test bodies). Also the corrections due to finite conductivity were found up to the fourth order in relative penetration depth of electromagnetic zero point oscillations into the metal. The theoretical result for the configuration of a sphere above a plate taking into account both corrections is in excellent agreement with the measured Casimir force

Bistability versus Bimodal Distributions in Gene Regulatory Processes from Population Balance

In recent times, stochastic treatments of gene regulatory processes have appeared in the literature in which a cell exposed to a signaling molecule in its environment triggers the synthesis of a specific protein through a network of intracellular reactions. The stochastic nature of this process leads to a distribution of protein levels in a population of cells as determined by a Fokker-Planck equation. Often instability occurs as a consequence of two (stable) steady state protein levels, one at the low end representing the “off” state, and the other at the high end representing the “on” state for a given concentration of the signaling molecule within a suitable range. A consequence of such bistability has been the appearance of bimodal distributions indicating two different populations, one in the “off” state and the other in the “on” state. The bimodal distribution can come about from stochastic analysis of a single cell. However, the concerted action of the population altering the extracellular concentration in the environment of individual cells and hence their behavior can only be accomplished by an appropriate population balance model which accounts for the reciprocal effects of interaction between the population and its environment. In this study, we show how to formulate a population balance model in which stochastic gene expression in individual cells is incorporated. Interestingly, the simulation of the model shows that bistability is neither sufficient nor necessary for bimodal distributions in a population. The original notion of linking bistability with bimodal distribution from single cell stochastic model is therefore only a special consequence of a population balance model

A2ML1 and otitis media : novel variants, differential expression, and relevant pathways

A genetic basis for otitis media is established, however, the role of rare variants in disease etiology is largely unknown. Previously a duplication variant within A2ML1 was identified as a significant risk factor for otitis media in an indigenous Filipino population and in US children. In this report exome and Sanger sequencing was performed using DNA samples from the indigenous Filipino population, Filipino cochlear implantees, US probands, Finnish, and Pakistani families with otitis media. Sixteen novel, damaging A2ML1 variants identified in otitis media patients were rare or low-frequency in population-matched controls. In the indigenous population, both gingivitis and A2ML1 variants including the known duplication variant and the novel splice variant c.4061 + 1 G>C were independently associated with otitis media. Sequencing of salivary RNA samples from indigenous Filipinos demonstrated lower A2ML1 expression according to the carriage of A2ML1 variants. Sequencing of additional salivary RNA samples from US patients with otitis media revealed differentially expressed genes that are highly correlated with A2ML1 expression levels. In particular, RND3 is upregulated in both A2ML1 variant carriers and high-A2ML1 expressors. These findings support a role for A2ML1 in keratinocyte differentiation within the middle ear as part of otitis media pathology and the potential application of ROCK inhibition in otitis media.Peer reviewe

Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex

The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders

Subcortical brain volume, regional cortical thickness, and cortical surface area across disorders: findings from the ENIGMA ADHD, ASD, and OCD Working Groups

Objective Attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. We aimed to directly compare all three disorders. The ENIGMA consortium is ideally positioned to investigate structural brain alterations across these disorders. Methods Structural T1-weighted whole-brain MRI of controls (n=5,827) and patients with ADHD (n=2,271), ASD (n=1,777), and OCD (n=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. We examined subcortical volume, cortical thickness and surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults using linear mixed-effects models adjusting for age, sex and site (and ICV for subcortical and surface area measures). Results We found no shared alterations among all three disorders, while shared alterations between any two disorders did not survive multiple comparisons correction. Children with ADHD compared to those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller ICV than controls and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared to adult controls and other clinical groups. No OCD-specific alterations across different age-groups and surface area alterations among all disorders in childhood and adulthood were observed. Conclusion Our findings suggest robust but subtle alterations across different age-groups among ADHD, ASD, and OCD. ADHD-specific ICV and hippocampal alterations in children and adolescents, and ASD-specific cortical thickness alterations in the frontal cortex in adults support previous work emphasizing neurodevelopmental alterations in these disorders

Quantifying farm-to-fork greenhouse gas emissions for five dietary patterns across Europe and North America: A pooled analysis from 2009 to 2020

Dietary patterns are inherently related to greenhouse (GHG) emissions via agricultural practices and food production systems. As the global population is predicted to increase from 8 billion (current) to 9.6 billion by 2050 added pressure will be placed on existing agricultural systems, resulting in increased GHG emissions thus exacerbating climate change. Therefore, there is an urgent need to understand present-day dietary patterns to shift to sustainable and healthy diets to mitigate GHG emissions and meet future climate targets. However, no review or pooled analyses of dietary pattern emissions from a farm-to-fork perspective has been undertaken to date. The current study sought to i) identify the current dietary habits within high-income regions from 2009 to 2020 and ii) quantify the GHG emissions associated with these dietary patterns via a global systematised review and pooled analysis. Twenty-three peer-reviewed studies were identified through online bibliographic databases. Dietary patterns are being examined based on fixed inclusion/exclusion criteria. Five dietary patterns were identified in the review with their mean GHG emissions: high-protein diets (5.71 CO2eq kg person −1 day −1), omnivorous diet (4.83 CO2eq kg person −1 day −1), lacto-ovo-vegetarian/pescatarian diet (3.86 CO2eq kg person −1 day −1), recommended diet (3.68 CO2eq kg person −1 day −1), and the vegan diet (2.34 CO2eq kg person −1 day −1). The lacto-ovo-vegetarian/pescatarian diet was associated with significantly lower emissions than both the omnivorous and high-protein dietary patterns, with -22% and -41% GHG emissions, respectively. The high-protein dietary pattern exhibited significantly higher GHG emissions than other dietary patterns. Geographically, significant statistical differences (p = 0.001) were only reported for the omnivorous diet between North America and Europe. Findings reveal that GHG emissions vary based on dietary patterns and have the potential to be reduced by shifting dietary patterns, which benefits the environment by lessening one of the drivers of climate change

CONSTRICTOR: constraint modification provides insight into design of biochemical networks.

Advances in computational methods that allow for exploration of the combinatorial mutation space are needed to realize the potential of synthetic biology based strain engineering efforts. Here, we present Constrictor, a computational framework that uses flux balance analysis (FBA) to analyze inhibitory effects of genetic mutations on the performance of biochemical networks. Constrictor identifies engineering interventions by classifying the reactions in the metabolic model depending on the extent to which their flux must be decreased to achieve the overproduction target. The optimal inhibition of various reaction pathways is determined by restricting the flux through targeted reactions below the steady state levels of a baseline strain. Constrictor generates unique in silico strains, each representing an "expression state", or a combination of gene expression levels required to achieve the overproduction target. The Constrictor framework is demonstrated by studying overproduction of ethylene in Escherichia coli network models iAF1260 and iJO1366 through the addition of the heterologous ethylene-forming enzyme from Pseudomonas syringae. Targeting individual reactions as well as combinations of reactions reveals in silico mutants that are predicted to have as high as 25% greater theoretical ethylene yields than the baseline strain during simulated exponential growth. Altering the degree of restriction reveals a large distribution of ethylene yields, while analysis of the expression states that return lower yields provides insight into system bottlenecks. Finally, we demonstrate the ability of Constrictor to scan networks and provide targets for a range of possible products. Constrictor is an adaptable technique that can be used to generate and analyze disparate populations of in silico mutants, select gene expression levels and provide non-intuitive strategies for metabolic engineering