Assessment of Metabolic Parameters For Autism Spectrum Disorders

Autism is a brain development disorder that first appears during infancy or childhood, and generally follows a steady course without remission. Impairments result from maturation-related changes in various systems of the brain. Autism is one of the five pervasive developmental disorders (PDD), which are characterized by widespread abnormalities of social interactions and communication, and severely restricted interests and highly repetitive behavior. The reported incidence of autism spectrum disorders (ASDs) has increased markedly over the past decade. The Centre for Disease Control and Prevention has recently estimated the prevalence of ASDs in the United States at approximately 5.6 per 1000 (1 of 155 to 1 of 160) children. Several metabolic defects, such as phenylketonuria, are associated with autistic symptoms. In deciding upon the appropriate evaluation scheme a clinician must consider a host of different factors. The guidelines in this article have been developed to assist the clinician in the consideration of these factors

In vitro response from cotyledon and hypocotyls explants in tomato by inducing 6-benzylaminopurine

Differential response of tomato was evaluated by hypocotyls and cotyledon explants on 6- benzylaminopurine (BAP) containing MS media. Among the four levels (0, 1, 2 and 4 mg/l) of BAP employed in Murashige and Skoog (MS) media, 2.0 mg/l BAP was found superior in growth traits (number of shoots/explants and shoot length) and cultivars. No significant difference was noticed between cotyledon and hypocotyls explants on media having 2.0 mg/l BAP. In the same treatment, shoot length was significantly different between cotyledon and hypocotyls derived explants. No adventitious shoots was noted in the control and higher concentration of BAP containing media but theexplants turned into callus on media having 4.0 mg/l BAP

In vitro performances of hypocotyl and cotyledon explants of tomato cultivars under sodium chloride stress

A plant tissue culture technique is a good method for the evaluation and screening of plant genotypes for salt tolerance. In vitro evaluations of sodium chloride (NaCl) effects on two tomato cultivars (Pearl and Beril) were investigated with four NaCl levels (0, 25, 50 and 75 mM) using hypocotyl and cotyledon explants. The explants were cultured in MS media having 2.0 mg/l BAP along with different concentrations of NaCl. Sodium chloride stress negatively affected the growth traits and chlorophyll content. Significant differences were noticed between the cultivars followed by different NaCl levels, where the Beril responded superior than that of Pearl. The type of explant showed a difference in their response to shoots regeneration under NaCl stress, where the cotyledon explants achieved best results than hypocotyl explants.Key words: Cotyledons, hypocotyls, In vitro, salt stress, tomato

Pulmonary group 2 innate lymphoid cells: surprises and challenges

© 2019, Society for Mucosal Immunology. Group 2 innate lymphoid cells (ILC2s) are a recently described subset of innate lymphocytes with important immune and homeostatic functions at multiple tissue sites, especially the lung. These cells expand locally after birth and during postnatal lung maturation and are present in the lung and other peripheral organs. They are modified by a variety of processes and mediate inflammatory responses to respiratory pathogens, inhaled allergens and noxious particles. Here, we review the emerging roles of ILC2s in pulmonary homeostasis and discuss recent and surprising advances in our understanding of how hormones, age, neurotransmitters, environmental challenges, and infection influence ILC2s. We also review how these responses may underpin the development, progression and severity of pulmonary inflammation and chronic lung diseases and highlight some of the remaining challenges for ILC2 biology

Capacitated Center Problems with Two-Sided Bounds and Outliers

In recent years, the capacitated center problems have attracted a lot of research interest. Given a set of vertices $V$, we want to find a subset of vertices $S$, called centers, such that the maximum cluster radius is minimized. Moreover, each center in $S$ should satisfy some capacity constraint, which could be an upper or lower bound on the number of vertices it can serve. Capacitated $k$-center problems with one-sided bounds (upper or lower) have been well studied in previous work, and a constant factor approximation was obtained. We are the first to study the capacitated center problem with both capacity lower and upper bounds (with or without outliers). We assume each vertex has a uniform lower bound and a non-uniform upper bound. For the case of opening exactly $k$ centers, we note that a generalization of a recent LP approach can achieve constant factor approximation algorithms for our problems. Our main contribution is a simple combinatorial algorithm for the case where there is no cardinality constraint on the number of open centers. Our combinatorial algorithm is simpler and achieves better constant approximation factor compared to the LP approach

Study of mast cell density, distribution and morphology in skin lesions of leprosy

Background: Mast cells are found at all levels of dermis, grouped around blood vessels, nerves and appendages. An increase in the mast cell number has been reported in various cutaneous diseases. Mast cells respond to diverse range of stimuli like neuronal impulses, allergens, antigens, hormones, cytokines from T cells and keratinocytes and thus play a role in manifestation of dermatological disorders. The objective was to study mast cell density in various subsets of Hansen’s disease and analyse whether the distribution and density vary amongst the subsets. Methods: A total of 60 skin biopsies diagnosed as leprosy were included in this study. 10 control slides were also studied for mast cell density and distribution. Histopathological diagnosis was made on the biopsy and mast cell density and distribution was assessed on toluidine blue stained sections and compared with those of controls. Results: All the subsets of Hansen’s disease studied showed an increase in the number of mast cells. The highest mean mast cell count was noted in lepromatous leprosy (66/mm2), followed by erythema nodosum leprosum (42.6/mm2) and borderline lepromatous leprosy (40.8/mm2). The mean mast cell count showed progressive increase over the immunological spectrum of tuberculoid leprosy to lepromatous leprosy. The mast cells showed spindle and ovoid morphology in all the lesions (active) while round morphology was seen in controls. Conclusion: Tissue mast cell number, distribution and morphology vary depending on the degree of activation in different leprosy lesions. This may have a bearing on the diagnosis and management

The Maximal U(1)LU(1)_L Inverse Seesaw from d=5d=5 Operator and Oscillating Asymmetric Sneutrino Dark Matter

The maximal $U(1)_L$ supersymmetric inverse seesaw mechanism (M$L$SIS) provides a natural way to relate asymmetric dark matter (ADM) with neutrino physics. In this paper we point out that, M$L$SIS is a natural outcome if one dynamically realizes the inverse seesaw mechanism in the next-to minimal supersymmetric standard model (NMSSM) via the dimension-five operator $(N)^2S^2/M_*$, with $S$ the NMSSM singlet developing TeV scale VEV; it slightly violates lepton number due to the suppression by the fundamental scale $M_*$, thus preserving $U(1)_L$ maximally. The resulting sneutrino is a distinguishable ADM candidate, oscillating and favored to have weak scale mass. A fairly large annihilating cross section of such a heavy ADM is available due to the presence of singlet.Comment: journal versio

Listen to genes : dealing with microarray data in the frequency domain

Background: We present a novel and systematic approach to analyze temporal microarray data. The approach includes normalization, clustering and network analysis of genes. Methodology: Genes are normalized using an error model based uniform normalization method aimed at identifying and estimating the sources of variations. The model minimizes the correlation among error terms across replicates. The normalized gene expressions are then clustered in terms of their power spectrum density. The method of complex Granger causality is introduced to reveal interactions between sets of genes. Complex Granger causality along with partial Granger causality is applied in both time and frequency domains to selected as well as all the genes to reveal the interesting networks of interactions. The approach is successfully applied to Arabidopsis leaf microarray data generated from 31,000 genes observed over 22 time points over 22 days. Three circuits: a circadian gene circuit, an ethylene circuit and a new global circuit showing a hierarchical structure to determine the initiators of leaf senescence are analyzed in detail. Conclusions: We use a totally data-driven approach to form biological hypothesis. Clustering using the power-spectrum analysis helps us identify genes of potential interest. Their dynamics can be captured accurately in the time and frequency domain using the methods of complex and partial Granger causality. With the rise in availability of temporal microarray data, such methods can be useful tools in uncovering the hidden biological interactions. We show our method in a step by step manner with help of toy models as well as a real biological dataset. We also analyse three distinct gene circuits of potential interest to Arabidopsis researchers