AMELIORATION OF ANXIOLYTIC BEHAVIOR IN INTRACEREBROVENTRICULAR COLCHICINE INJECTED RATS BY NAPROXEN

Objective: Anxiety behavior in experimental model of Alzheimer's disease (AD) in rats by intracerebroventricular (ICV) injection of colchicine isimportant to characterize this animal model, but it has not been sufficiently investigated in this animal model. The different attributes of anxietybehavior in ICV colchicine injected rats (ICIR) was studied, and the effects of naproxen, a non-steroidal anti-inflammatory drug on the anxiety statusof these AD animals were assessed since in earlier studies naproxen protected cognitive impairments and neurodegeneration in ICIR.Methods: The anxiety status was assessed in an elevated open field with a novel object in two study durations (14-day and 21-day study). Aftermeasuring the anxiety behavior in two study durations, rats were sacrificed, and blood was collected for measuring the serum corticosterone (CORT)level.Results: Anxiolytic behavior along with lower CORT level was observed in ICIR in both the 14- and 21-day studies. After p.o. administration ofdifferent doses of naproxen (5, 10, 20 mg/kg body wt.) in ICIR, this anxiolytic behavior along with low serum CORT level showed gradual recovery andeventually both the parameters attained normal level at the dose of 20 mg/kg body weight in 21-day study.Conclusion: The present study showed an anxiolytic behavior in ICIR, and which may result from the colchicine induced neurodegeneration alongwith the impaired activity of the hypothalamo-pituitary-adrenal axis. Some parameters appeared to be sensitive for determination of anxiety statusin this model.Keywords: Colchicine, Anxiolytic, Naproxen, Corticosterone, Alzheimer's disease

Hierarchical hidden Markov models with applications to BiSulfite-sequencing data

DNA methylation is an epigenetic modification with significant roles in various biological processes such as gene expression and cellular proliferation. Aberrant DNA methylation patterns compared to normal cells have been associated with a large number of human malignancies and potential cancer symptoms. In DNA methylation studies, an important objective is to detect differences between two groups under distinct biological conditions, for e.g., between cancer/ageing and normal cells. BiSulfite sequencing (BS-seq) is currently the gold standard for experimentally measuring genome-wide DNA methylation. Recent evolution in the BS-seq technologies enabled the DNA methylation profiles at single base pair resolution to be more accurate in terms of their genome coverages. The main objective of my thesis is to identify differential patterns of DNA methylation between proliferating and senescent cells. For efficient detection of differential methylation patterns, this thesis adopts the approach of Bayesian latent variable model. One such class of models is hidden Markov model (HMM) that can detect the underlying latent (hidden) structures of the model. In this thesis, I propose a family of Bayesian hierarchical HMMs for identifying differentially methylated cytosines (DMCs) and differentially methylated regions (DMRs) from BS-seq data which act as important indicators in better understanding of cancer and other related diseases. I introduce HMMmethState, a model-based hierarchical Bayesian technique for identifying DMCs from BS-seq data. My novel HMMmethState method implements hierarchical HMMs to account for spatial dependence among the CpG sites over genomic positions of BS-seq methylation data. In particular, this thesis is concerned with developing hierarchical HMMs for the differential methylation analysis of BS-seq data, within a Bayesian framework. In these models, aberrant DNA methylation is driven by two latent states: differentially methylated state and similarly methylated state, which can be interpreted as methylation status of CpG sites, that evolve over genomic positions as a first order Markov chain. I first design a (homogeneous) discrete-index hierarchical HMM in which methylated counts given the methylation status of CpG sites follow Beta-Binomial emission distribution specific to the methylation state. However, this model does not incorporate the genomic positional variations among the CpG sites, so I develop a (non-homogeneous) continuous-index hierarchical HMM, in which the transition probabilities between methylation status depend on the genomic positions of the CpG sites. This Beta-Binomial emission model however does not take into account the correlation in the methylated counts of the proliferating and senescent cells, which has been observed in the BS-seq data analysis. So, I develop a hierarchical Normal-logit Binomial emission model that induces correlation between the methylated counts of the proliferating and senescent cells. Furthermore, to perform parameter estimation for my models, I implement efficient Markov Chain Monte Carlo (MCMC) based algorithms. In this thesis, I provide an extensive study on model comparisons and adequacy of all the models using Bayesian model checking. In addition, I also show the performances of all the models using Receiver Operating Characteristics (ROC) curves. I illustrate the models by fitting them to a large BS-seq dataset and apply model selection criteria on the dataset in search of selecting the best model. In addition, I compare the performances of my methods with existing methods for detecting DMCs with competing methods. I demonstrate how the HMMmethState based algorithms outperform the existing methods in simulation studies in terms of ROC curves. I present the results of DMRs obtained using my method, i.e., the results of DMRs with the proposed HMMmethState that have been applied to the BS-seq datasets. The results of the hierarchical HMMs explain that I can certainly implement these methods under unconditioned settings to identify DMCs for high-throughput BS-seq data. The predicted DMCs can also help in understanding the phenotypic changes associated with human ageing

Cox-2 Plays a Vital Role in the Impaired Anxiety Like Behavior in Colchicine Induced Rat Model of Alzheimer Disease

The anxiety status is changed along with memory impairments in intracerebroventricular colchicine injected rat model of Alzheimer Disease (cAD) due to neurodegeneration, which has been indicated to be mediated by inflammation. Inducible cox-2, involved in inflammation, may have important role in the colchicine induced alteration of anxiety status. Therefore, the present study was designed to investigate the role of cox-2 on the anxiety behavior (response to novelty in an elevated open field space) of cAD by inhibiting it with three different doses (10, 20, and 30 mg) of etoricoxib (a cox-2 blocker) in two time points (14 and 21 days). The results showed anxiolytic behavior in cAD along with lower serum corticosterone level, both of which were recovered at all the doses of etoricoxib on day 21. On day 14 all of the anxiety parameters showed similar results to that of day 21 at high doses but not at 10 mg/kg body weight. Results indicate that the parameters of anxiety were dependent on neuronal circuitries that were probably sensitive to etoricoxib induced blocking of neurodegeneration. The present study showed that anxiolytic behavior in cADr is predominantly due to cox-2 mediated neuroinflammation induced neurodegeneration in the brain

An observational study of pattern of bradyarrhythmia and pacing management modality in geriatric population: A single-center 2-year analysis data

Background: Incidence of cardiac conduction disorders are escalating in the current era especially due to enhanced life expectancy in the geriatric population and better standards of medical care and coronary revascularization. Aims and Objectives: This study aimed to analyse the demographical aspect and temporal trends of permanent pacemaker (PPM) therapy in patients aged above 60 years of age from an observational 2-year retrospective data from a single-center tertiary care academic hospital. Results: Males consisted of more than two-third of the patients and complete atrioventricular block was the most common conduction pathology. Fascicular and Bundle branch blocks appeared to have a male preponderance, whereas sinus node dysfunction was found to have statistically significant association with the female cohort. Most of the patients were implanted out of admission from cardiac emergency and single chamber ventricle paced and sensed, inhibition response with rate adaptation (VVIR) mode was the predominant modality of pacing management, not found to be influenced by the age or sex of the patients. However, there was a statistical correlation noted of utilization of dual chamber Dual paced and sensed, dual inhibition with rate adaptation (DDDR) mode in patients with sick sinus pathology. Conclusion: Implantation of PPM is on the rise as a modality of bradyarrhythmia treatment in the increasing proportion of geriatric population with advanced life expectancy

Simulation scenarios.

(A) low additive noise. (B) medium additive noise. (C) large additive noise. Three levels of noise were added to the reference SPI curves (clustered vs. random) to generate subject-specific SPI curves. (TIF)</p

Kaplan–Meier curves for the overall survival probability from the NSCLC dataset, stratified using the Mantel correlation.

Subjects were classified as clustered vs. random based on the permutation test of the Mantel correlation. P-value of 0.24 indicates non-significant difference in survival probability in two groups. (TIF)</p

Simulated spatial configurations.

Two reference spatial configurations: clustered (A) and random (B) of five different cell types: CD14+, CD19+, CD4+, CD8+, and CK+. (C): Corresponding spatial entropy at multiple distance ranges for each configuration.</p

Histograms of first four FPC scores obtained from the NSCLC dataset.

FPC scores were obtained by applying FPCA on the spatial entropy curves from the NSCLC dataset. The scores were centered around 0. (TIF)</p

First five functional principal components (FPC) obtained from the NSCLC dataset.

For each FPC, the mean function is overlaid with +/- FPC score multiplying 2 standard deviations of the associated score distribution. (TIF)</p