Estimation and testing for the effect of a genetic pathway on a disease outcome using logistic kernel machine regression via logistic mixed models

Background  

Growing interest on biological pathways has called for new statistical methods for modeling and testing a genetic pathway effect on a health outcome. The fact that genes within a pathway tend to interact with each other and relate to the outcome in a complicated way makes nonparametric methods more desirable. The kernel machine method provides a convenient, powerful and unified method for multi-dimensional parametric and nonparametric modeling of the pathway effect.     

Enhanced Production of Antimicrobial Compounds by Three Salt-Tolerant Actinobacterial Strains Isolated from the Sundarbans in a Niche-Mimic Bioreactor

A novel reactor system, the rotating disk bioreactor (RDBR), was used to mimic the niche environmental conditions of three salt-tolerant estuarine actinobacteria isolated from the Sundarbans region off the Bay of Bengal, designated MS310 (99% similar in its 16S rRNA gene sequence to Streptomyces parvallus), MS3/20 and MS1/7. The RDBR, operated at a rotational speed of one revolution per day, 50% submergence of discs, aeration rate of 1.0 vvm, and with a sucrose-containing medium, faithfully mimicked the intertidal estuarine habitat of these marine isolates, and supported biofilm formation and production of antimicrobial metabolites-in particular, actinomycin D by MS310. Onset of antibiotic production by MS310 occurs at 20 h in the RDBR compared to 55 h in a conventional stirred-tank bioreactor (STBR). Furthermore, peak antimicrobial activity is attained much earlier in the RDBR with MS310 (at 45 h) than that reported with a terrestrial strain of S. parvallus grown in a STBR (at 144 h). Peak antimicrobial activity of metabolites produced by MS1/7 and MS3/20 were also attained earlier in the RDBR (at 25 and 12 h, respectively) than in a STBR (at 80 and 28 h, respectively). Antibiotic synthesis in the three isolates, in general, appears to be associated with their growth. Overall, the RDBR may be considered the preferred alternative to the STBR for production of antimicrobials by biofilm-forming estuarine bacteria for its much higher surface/volume ratio, lower costs, and easy operability.     

Weighted Estimation of the Accelerated Failure Time Model in the Presence of Dependent Censoring

Independent censoring is a crucial assumption in survival analysis. However, this is impractical in many medical studies, where the presence of dependent censoring leads to difficulty in analyzing covariate effects on disease outcomes. The semicompeting risks framework offers one approach to handling dependent censoring. There are two representative estimators based on an artificial censoring technique in this data structure. However, neither of these estimators is better than another with respect to efficiency (standard error). In this paper, we propose a new weighted estimator for the accelerated failure time (AFT) model under dependent censoring. One of the advantages in our approach is that these weights are optimal among all the linear combinations of the previously mentioned two estimators. To calculate these weights, a novel resampling-based scheme is employed. Attendant asymptotic statistical results for the estimator are established. In addition, simulation studies, as well as an application to real data, show the gains in efficiency for our estimator.     

Inhibition of IL-2 induced IL-10 production as a principle of phase-specific immunotherapy

Leishmania donovani, a protozoan parasite, inflicts a fatal disease, visceral leishmaniasis. The suppression of antileishmanial T cell responses that characterizes the disease was proposed to be due to deficiency of a T cell growth factor, IL-2. We demonstrate that during the first week after L. donovani infection, IL-2 induces IL-10 that suppresses the host-protective functions of T cells 14 days after infection. The observed suppression is concurrent with increased CD4+ glucocorticoid-induced TNF receptor+ T cells and Foxp3 expression in BALB/c mice, implicating IL-2-dependent regulatory T cell control of antileishmanial immune responses. Indeed, IL-2 and IL-10 neutralization at different time points after the infection demonstrates their distinct roles at the priming and effector phases, respectively, and establishes kinetic modulation of ongoing immune responses as a principle of a rational, phase-specific immunotherapy.     

The study of the electronic structures and properties of pure and transition metal-doped silicon nanoclusters: a density functional theory approach

This report presents the study of ab initio electronic structure and properties of pure and transition metal (TM = Ti, Zr and Hf)-doped silicon clusters, TM@Si(n), by using density functional theory with a polarised basis set (LanL2DZ) within the spin-polarised generalised gradient approximation for different values of n varying from 8 to 20. As the first step of the study, different optimised geometries of pure and doped clusters are calculated. These optimised clusters are then used to calculate different structural and physical parameters of the clusters, like binding energy, Highest Occupied Molecular Orbital – Lowest Unoccupied Molecular Orbital (HOMO–LUMO) gap, charge transfer, etc. In order to check the stability of the clusters, the second-order difference in the energy of the optimised structures is calculated. To study the optical behaviour of the clusters, infrared and Raman spectra are also calculated. Further calculations are also done on cation and anion clusters of both pure and doped nanoclusters to obtain their ionisation potential, electron affinity and chemical potential. An effort has been made to correlate the variation of different calculated parameters with the size of the clusters to explain the real existence and stabilities of different TM-doped clusters.     

Proceedings of the signature series event of the international society for cellular therapy: “Advancements in cellular therapies and regenerative medicine in digestive diseases,” London,United Kingdom,May 3, 2017

A summary of the First Signature Series Event, “Advancements in Cellular Therapies and Regenerative Medicine for Digestive Diseases,” held on May 3, 2017, in London, United Kingdom, is presented. Twelve speakers from three continents covered major topics in the areas of cellular therapy and regenerative medicine applied to liver and gastrointestinal medicine as well as to diabetes mellitus. Highlights from their presentations, together with an overview of the global impact of digestive diseases and a proposal for a shared online collection and data-monitoring platform tool, are included in this proceedings. Although growing evidence demonstrate the feasibility and safety of exploiting cell-based technologies for the treatment of digestive diseases, regulatory and methodological obstacles will need to be overcome before the successful implementation in the clinic of these novel attractive therapeutic strategies.     

A Statistical Approach for Testing Cross-Phenotype Effects of Rare Variants

Increasing empirical evidence suggests that many genetic variants influence multiple distinct phenotypes. When cross-phenotype effects exist, multivariate association methods that consider pleiotropy are often more powerful than univariate methods that model each phenotype separately. Although several statistical approaches exist for testing cross-phenotype effects for common variants, there is a lack of similar tests for gene-based analysis of rare variants. In order to fill this important gap, we introduce a statistical method for cross-phenotype analysis of rare variants using a nonparametric distance-covariance approach that compares similarity in multivariate phenotypes to similarity in rare-variant genotypes across a gene. The approach can accommodate both binary and continuous phenotypes and further can adjust for covariates. Our approach yields a closed-form test whose significance can be evaluated analytically, thereby improving computational efficiency and permitting application on a genome-wide scale. We use simulated data to demonstrate that our method, which we refer to as the Gene Association with Multiple Traits (GAMuT) test, provides increased power over competing approaches. We also illustrate our approach using exome-chip data from the Genetic Epidemiology Network of Arteriopathy.     

A computerized spectrophotometric instrumental system to determine the "vertical velocity" of sperm cells: a novel concept.

BACKGROUND: The presently available cell motility-analyzers measure primarily the "horizontal" velocity and there is no instrument available for "vertical" velocity measurement. This development was based on the turbidimetric method of sperm motility analysis. METHODS: Sperm was layered at the bottom of the cuvette containing buffer solution and exposed to the spectrophotometric light path at different heights to track the vertically moving sperms. The vertical movement was materialized with the development of an electromechanical up-down movement devise for the cuvette accomplished with the help of a cuvette holder-stepper motor-computer assembly. The entire system was controlled by the necessary motion control, data acquisition, and data processing software developed for cuvette movement and data analysis. RESULTS: Using goat sperm as the model a unique computer-based spectrophotometric system has been developed for the first time to determine the average "vertical" velocity of motile cells. CONCLUSIONS: Undertaking upward movement against gravity is much tougher as compared with horizontal movement. Consequently average vertical velocity is expected to be a much better identifying parameter for assessing semen and other motile cell quality. The novel instrumental system developed by us has thus the potential for immense application in human infertility clinics, animal-breeding centres, centres for conservation of endangered species, and also for research work on vertical velocity of spermatozoa and other motile cells, such as bacteria, protozoa, etc.