Tobacco consumption among adolescents in rural Wardha: Where and how tobacco control should focus its attention?

Objectives: The objectives of the present study were to study the pattern of tobacco use among rural adolescents (15-19 years) and to find out reasons for use and non use of tobacco products. Materials and Methods : In the present community-based research, triangulation of qualitative (free list, focus group discussions) and quantitative methods (survey) was undertaken. The study was carried out in surrounding 11 villages of the Kasturba Rural Health Training Centre, Anji during January 2008 where 385 adolescents were selected by simple random sampling and interviewed by house to house visits. After survey, six focus group discussions were undertaken with adolescent boys. Results: About 68.3% boys and 12.4% girls had consumed any tobacco products in last 30 days. Out of boys who had consumed tobacco, 79.2% consumed kharra, and 46.4% consumed gutka. Among boys, 51.2% consumed it due to peer pressure, 35.2% consumed tobacco as they felt better, and five percent consumed tobacco to ease abdominal complaints and dental problem. Among girls, 72% used dry snuff for teeth cleaning, 32% and 20% consumed tobacco in the form of gutka and tobacco & lime respectively. The reasons for non use of tobacco among girls were fear of cancer (59%), poor oral health (37.9%). Among non consuming boys it was fear of cancer (58.6%), poor oral health (44.8%) and fear of getting addiction (29.3%). According to FGD respondents, few adolescent boys taste tobacco by 8-10 years of age, while girls do it by 12-13 years. Peer pressure acts as a pro tobacco influence among boys who are outgoing and spend more time with their friends. They prefer to consume freshly prepared kharra which was supposed to be less strong (tej) than gutka. Tobacco is being used in treatment of some health problems. Tobacco is chewed after meals for better digestion, given to ease toothache, pain in abdomen and to induce vomiting in suicidal insecticide poisoning. Conclusion: The current consumption of any tobacco products among rural adolescents was found very high. Hence, the multi-pronged intervention strategy is needed to tackle the problem

A physics-based machine learning technique rapidly reconstructs the wall-shear stress and pressure fields in coronary arteries

With the global rise of cardiovascular disease including atherosclerosis, there is a high demand or accurate diagnostic tools that can be used during a short consultation. In view of pathology, abnormal blood flow patterns have been demonstrated to be strong predictors of atherosclerotic lesion incidence, location, progression, and rupture. Prediction of patient-specific blood flow patterns can hence enable fast clinical diagnosis. However, the current state of art for the technique is by employing 3D-imaging-based Computational Fluid Dynamics (CFD). The high computational cost renders these methods impractical. In this work, we present a novel method to expedite the reconstruction of 3D pressure and shear stress fields using a combination of a reduced-order CFD modelling technique together with non-linear regression tools from the Machine Learning (ML) paradigm. Specifically, we develop a proof-of-concept automated pipeline that uses randomised perturbations of an atherosclerotic pig coronary artery to produce a large dataset of unique mesh geometries with variable blood flow. A total of 1407 geometries were generated from seven reference arteries and were used to simulate blood flow using the CFD solver Abaqus. This CFD dataset was then post-processed using the mesh-domain common-base Proper Orthogonal Decomposition (cPOD) method to obtain Eigen functions and principal coefficients, the latter of which is a product of the individual mesh flow solutions with the POD Eigenvectors. Being a data-reduction method, the POD enables the data to be represented using only the ten most significant modes, which captures cumulatively greater than 95% of variance of flow features due to mesh variations. Next, the node coordinate data of the meshes were embedded in a two-dimensional coordinate system using the t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm. The reduced dataset for t-SNE coordinates and corresponding vector of POD coefficients were then used to train a Random Forest Regressor (RFR) model. The same methodology was applied to both the volumetric pressure solution and the wall shear stress. The predicted pattern of blood pressure, and shear stress in unseen arterial geometries were compared with the ground truth CFD solutions on 'unseen' meshes. The new method was able to reliably reproduce the 3D coronary artery haemodynamics in less than 10 seconds

A physics-based machine learning technique rapidly reconstructs the wall-shear stress and pressure fields in coronary arteries

With the global rise of cardiovascular disease including atherosclerosis, there is a high demand for accurate diagnostic tools that can be used during a short consultation. In view of pathology, abnormal blood flow patterns have been demonstrated to be strong predictors of atherosclerotic lesion incidence, location, progression, and rupture. Prediction of patient-specific blood flow patterns can hence enable fast clinical diagnosis. However, the current state of art for the technique is by employing 3D-imaging-based Computational Fluid Dynamics (CFD). The high computational cost renders these methods impractical. In this work, we present a novel method to expedite the reconstruction of 3D pressure and shear stress fields using a combination of a reduced-order CFD modelling technique together with non-linear regression tools from the Machine Learning (ML) paradigm. Specifically, we develop a proof-of-concept automated pipeline that uses randomised perturbations of an atherosclerotic pig coronary artery to produce a large dataset of unique mesh geometries with variable blood flow. A total of 1,407 geometries were generated from seven reference arteries and were used to simulate blood flow using the CFD solver Abaqus. This CFD dataset was then post-processed using the mesh-domain common-base Proper Orthogonal Decomposition (cPOD) method to obtain Eigen functions and principal coefficients, the latter of which is a product of the individual mesh flow solutions with the POD Eigenvectors. Being a data-reduction method, the POD enables the data to be represented using only the ten most significant modes, which captures cumulatively greater than 95% of variance of flow features due to mesh variations. Next, the node coordinate data of the meshes were embedded in a two-dimensional coordinate system using the t-distributed Stochastic Neighbor Embedding ((Formula presented.) -SNE) algorithm. The reduced dataset for (Formula presented.) -SNE coordinates and corresponding vector of POD coefficients were then used to train a Random Forest Regressor (RFR) model. The same methodology was applied to both the volumetric pressure solution and the wall shear stress. The predicted pattern of blood pressure, and shear stress in unseen arterial geometries were compared with the ground truth CFD solutions on “unseen” meshes. The new method was able to reliably reproduce the 3D coronary artery haemodynamics in less than 10 s

Recent advances on information transmission and storage assisted by noise

The interplay between nonlinear dynamic systems and noise has proved to be of great relevance in several application areas. In this presentation, we focus on the areas of information transmission and storage. We review some recent results on information transmission through nonlinear channels assisted by noise. We also present recent proposals of memory devices in which noise plays an essential role. Finally, we discuss new results on the influence of noise in memristors.Comment: To be published in "Theory and Applications of Nonlinear Dynamics: Model and Design of Complex Systems", Proceedings of ICAND 2012 (Springer, 2014

A prospective trial of tacrolimus (FK 506) in clinical heart transplantation: Intermediate-term results

Between January 1, 1989, and December 31, 1994, we have treated 122 primary heart recipients with FK 506 (group I) and 121 with cyclosporine (group II). Fifty patients in the cyclosporine (CyA) group received no lympholytic induction (CyA alone) and 71 others received lympholytic induction with either rabbit antithymocyte globulin or OKT3 (CyA+LI). The mean follow-up was longer in the FK 506 group than in the CyA groups (3.2 ± 1.3 vs 2.3 ± 1.8 years; p < 0.01). Patient survival did not differ on the basis of the type of immunosuppression used. At 3 months after transplantation, the freedom from rejection in the FK 506 group was higher than that of the CyA-alone group (47% vs 22%, p < 0.01) but similar to that of the CyA+LI group (47% vs 53%). The linearized rejection rate (episodes/100 patient-days) of the FK 506 group (0.09 episodes) was lower (p < 0.05) than that of the CyA-alone group (0.26) and the CyA+LI group (0.13). The requirement for pulsed steroids to treat rejection was less in common in the FK 506 group than in either CyA group. Eighteen patients in the CyA group had refractory rejections; all resolved with FK 506 rescue. Two patients in the FK 506 group had refractory rejection that resolved with total lymphoid irradiation (n = 1) and methotrexate therapy (n = 1). Patients receiving FK 506 had a lower risk of hypertension and required a lower dose of steroids. Although the mean serum creatinine concentration at 1 year was higher in the FK 506 group, this difference disappeared after 2 years. No patients required discontinuation of FK 506 because of its side effects. Our intermediate-term results indicate that FK 506 compares favorably with CyA as a primary immunosuppressant in heart transplantation

Propylthiouracil Is Teratogenic in Murine Embryos

Background: Hyperthyroidism during pregnancy is treated with the antithyroid drugs (ATD) propylthiouracil (PTU) and methimazole (MMI). PTU currently is recommended as the drug of choice during early pregnancy. Yet, despite widespread ATD use in pregnancy, formal studies of ATD teratogenic effects have not been performed. Methods: We examined the teratogenic effects of PTU and MMI during embryogenesis in mice. To span different periods of embryogenesis, dams were treated with compounds or vehicle daily from embryonic day (E) 7.5 to 9.5 or from E3.5 to E7.5. Embryos were examined for gross malformations at E10.5 or E18.5 followed by histological and micro-CT analysis. Influences of PTU on gene expression levels were examined by RNA microarray analysis. Results: When dams were treated from E7.5 to E9.5 with PTU, neural tube and cardiac abnormalities were observed at E10.5. Cranial neural tube defects were significantly more common among the PTU-exposed embryos than those exposed to MMI or vehicle. Blood in the pericardial sac, which is a feature indicative of abnormal cardiac function and/or abnormal vasculature, was observed more frequently in PTU-treated than MMI-treated or vehicle-treated embryos. Following PTU treatment, a total of 134 differentially expressed genes were identified. Disrupted genetic pathways were those associated with cytoskeleton remodeling and keratin filaments. At E 18.5, no gross malformations were evident in either ATD group, but the number of viable PTU embryos per dam at E18.5 was significantly lower from those at E10.5, indicating loss o

Population mechanics: A mathematical framework to study T cell homeostasis

Unlike other cell types, T cells do not form spatially arranged tissues, but move independently throughout the body. Accordingly, the number of T cells in the organism does not depend on physical constraints imposed by the shape or size of specific organs. Instead, it is determined by competition for interleukins. From the perspective of classical population dynamics, competition for resources seems to be at odds with the observed high clone diversity, leading to the so-called diversity paradox. In this work we make use of population mechanics, a non-standard theoretical approach to T cell homeostasis that accounts for clone diversity as arising from competition for interleukins. The proposed models show that carrying capacities of T cell populations naturally emerge from the balance between interleukins production and consumption. These models also suggest remarkable functional differences in the maintenance of diversity in naïve and memory pools. In particular, the distribution of memory clones would be biased towards clones activated more recently, or responding to more aggressive pathogenic threats. In contrast, permanence of naïve T cell clones would be determined by their affinity for cognate antigens. From this viewpoint, positive and negative selection can be understood as mechanisms to maximize naïve T cell diversity

Adaptive Evolution and the Birth of CTCF Binding Sites in the Drosophila Genome

Changes in the physical interaction between cis-regulatory DNA sequences and proteins drive the evolution of gene expression. However, it has proven difficult to accurately quantify evolutionary rates of such binding change or to estimate the relative effects of selection and drift in shaping the binding evolution. Here we examine the genome-wide binding of CTCF in four species of Drosophila separated by between ~2.5 and 25 million years. CTCF is a highly conserved protein known to be associated with insulator sequences in the genomes of human and Drosophila. Although the binding preference for CTCF is highly conserved, we find that CTCF binding itself is highly evolutionarily dynamic and has adaptively evolved. Between species, binding divergence increased linearly with evolutionary distance, and CTCF binding profiles are diverging rapidly at the rate of 2.22% per million years (Myr). At least 89 new CTCF binding sites have originated in the Drosophila melanogaster genome since the most recent common ancestor with Drosophila simulans. Comparing these data to genome sequence data from 37 different strains of Drosophila melanogaster, we detected signatures of selection in both newly gained and evolutionarily conserved binding sites. Newly evolved CTCF binding sites show a significantly stronger signature for positive selection than older sites. Comparative gene expression profiling revealed that expression divergence of genes adjacent to CTCF binding site is significantly associated with the gain and loss of CTCF binding. Further, the birth of new genes is associated with the birth of new CTCF binding sites. Our data indicate that binding of Drosophila CTCF protein has evolved under natural selection, and CTCF binding evolution has shaped both the evolution of gene expression and genome evolution during the birth of new genes