An optimal strategy to model microbial growth in a multiple substrate environment

A comprehensive model is developed based on an optimal strategy describing varied microbial growth phenomenon involving sequential and simultaneous utilization of substrate. The model mimics the complex regulatory process of a cell which results in diverse growth process with the help of simple multi-variable constrained optimization, which aims at maximizing the specific cell growth. The metabolic processes of a cell are represented by simple flux balance equations. The different growth phenomenon exhibited by a microorganism are attributed to different levels of control present inside the cell. Provision is made in the model for these controls, in the form of constraints in the optimization formulation. The model prediction matches well with the experimental data of simultaneous growth of E. coli K12 on a mixture of glucose and organic acids like lactate, pyruvate, and acetate. Moreover, the model predictions are well in agreement with earlier published experimental data for the growth of E. coli K12 on other organic acids like fumarate, alpha-ketoglutarate, and succinate. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 56: 635-644, 1997.     

Propagation of extrinsic perturbation in a negatively auto-regulated pathway

The apparent precision of the output in multi-step biochemical pathways in the face of external and intrinsic perturbations is non-obvious and conceptually difficult. Using a simple three-step negatively auto-regulated model pathway, we show that the effect of perturbation at different steps of the pathway and its transmission through the network is dependent on the context (i.e., the position) of the particular reaction step in relation to the topology of the regulatory network, stoichiometry of reactions, type of nonlinearity involved in the reactions and also on the intrinsic dynamical state of the pathway variables. We delineate the qualitative and quantitative changes in the pathway dynamics for constant ('bias') and random external perturbations acting on the pathway steps locally or globally to all steps. We show that constant perturbation induces qualitative change in dynamics, whereas random fluctuations cause significant quantitative variations in the concentrations of the different variables. Thus, the dynamic response of multi-step biochemical pathways to external perturbation depends on their biochemical, topological and dynamical features.     

Cancer pattern and survival in a rural district in South India

Background: Cancer pattern data are rare and survival data are none from rural districts of India. Methods: The Dindigul Ambilikkai Cancer Registry (DACR) covering rural population of 2 millions in Dindigul district, Tamil Nadu state, South India, registered 4516 incident cancers during 2003–2006 by active case finding from 102 data sources for studying incidence pattern, of which, 1045 incident cancers registered in 2003 were followed up for estimating survival. House visits were undertaken annually for each registered case for data completion. Cancer pattern was described using average annual incidence rates and survival experience was expressed by computing observed survival by actuarial method and age-standardized relative survival (ASRS). Results: The average annual age-standardized rate per 100,000 of all cancers together was higher among women (62.6) than men (51.9) in DACR. The most common cancers among men were stomach (5.6), mouth (4.2) and esophagus (3.7). Cervical cancer (22.1) was ranked at the top among women followed by breast (10.9) and ovary (3.3). DACR incidence rates were lesser by at least two folds and 5-year survival were on par or lower than Chennai metropolitan registry for most cancers. Five-year age-standardized relative survival (%) in DACR was as follows: all cancers (29%), larynx (48), mouth (42), breast/tongue (38) and cervix (37). Conclusion: Cancer incidence was significantly lower, cancer patterns were markedly different and population-based cancer survival was lower in rural areas than urban areas thus providing valuable leads in estimating realistic cancer burden and instituting cancer control programs in India.     

Control of metallic corrosion through microbiological route

Involvement of biofilm or microorganisms in corrosion processes is widely acknowledged. Although majority of the studies on microbiologically induced corrosion (MIC) have concentrated on aerobic/anaerobic bacteria. There are numerous aerobic bacteria, which could hinder the corrosion process. The microbiologically produced exopolymers provide the structural frame work for the biofilm. These polymers combine with dissolved metal ions and form organometallic complexes. Generally heterotrophic bacteria contribute to three major processes: (i) synthesis of polymers (ii) accumulation of reserve materials like poly-beta-hydroxy butrate (iii) production of high molecular weight extracellular polysaccharides. Poly-beta-hydroxy butyrate is a polymer of D(-)beta-hydroxy butrate and has a molecular weight between 60,000 and 2,50,000. Some extracellular polymers also have higher molecular weights. It seems that higher molecular weight polymer acts as biocoating. In the present review, role of biochemistry on corrosion inhibition and possibilities of corrosion inhibition by various microbes are discussed. The role of bacteria on current demand during cathodic protection is also debated. In addition, some of the significant contributions made by CECRI in this promising area are highlighted.     

Population-Level Scale-Up of Cervical Cancer Prevention Services in a Low-Resource Setting: Development,Implementation, and Evaluation of the Cervical Cancer Prevention Program in Zambia

Background

Very few efforts have been undertaken to scale-up low-cost approaches to cervical cancer prevention in low-resource countries.

Methods

In a public sector cervical cancer prevention program in Zambia, nurses provided visual-inspection with acetic acid (VIA) and cryotherapy in clinics co-housed with HIV/AIDS programs, and referred women with complex lesions for histopathologic evaluation. Low-cost technological adaptations were deployed for improving VIA detection, facilitating expert physician opinion, and ensuring quality assurance. Key process and outcome indicators were derived by analyzing electronic medical records to evaluate program expansion efforts.

Findings

Between 2006-2013, screening services were expanded from 2 to 12 clinics in Lusaka, the most-populous province in Zambia, through which 102,942 women were screened. The majority (71.7%) were in the target age-range of 25–49 years; 28% were HIV-positive. Out of 101,867 with evaluable data, 20,419 (20%) were VIA positive, of whom 11,508 (56.4%) were treated with cryotherapy, and 8,911 (43.6%) were referred for histopathologic evaluation. Most women (87%, 86,301 of 98,961 evaluable) received same-day services (including 5% undergoing same-visit cryotherapy and 82% screening VIA-negative). The proportion of women with cervical intraepithelial neoplasia grade 2 and worse (CIN2+) among those referred for histopathologic evaluation was 44.1% (1,735/3,938 with histopathology results). Detection rates for CIN2+ and invasive cervical cancer were 17 and 7 per 1,000 women screened, respectively. Women with HIV were more likely to screen positive, to be referred for histopathologic evaluation, and to have cervical precancer and cancer than HIV-negative women.

Interpretation

We creatively disrupted the ''no screening'' status quo prevailing in Zambia and addressed the heavy burden of cervical disease among previously unscreened women by establishing and scaling-up public-sector screening and treatment services at a population level. Key determinants for successful expansion included leveraging HIV/AIDS program investments, and context-specific information technology applications for quality assurance and filling human resource gaps.     

Modeling the Contributions of Basal Ganglia and Hippocampus to Spatial Navigation Using Reinforcement Learning

A computational neural model that describes the competing roles of Basal Ganglia and Hippocampus in spatial navigation is presented. Model performance is evaluated on a simulated Morris water maze explored by a model rat. Cue-based and place-based navigational strategies, thought to be subserved by the Basal ganglia and Hippocampus respectively, are described. In cue-based navigation, the model rat learns to directly head towards a visible target, while in place-based navigation the target position is represented in terms of spatial context provided by an array of poles placed around the pool. Learning is formulated within the framework of Reinforcement Learning, with the nigrostriatal dopamine signal playing the role of Temporal Difference Error. Navigation inherently involves two apparently contradictory movements: goal oriented movements vs. random, wandering movements. The model hypothesizes that while the goal-directedness is determined by the gradient in Value function, randomness is driven by the complex activity of the SubThalamic Nucleus (STN)-Globus Pallidus externa (GPe) system. Each navigational system is associated with a Critic, prescribing actions that maximize value gradients for the corresponding system. In the integrated system, that incorporates both cue-based and place-based forms of navigation, navigation at a given position is determined by the system whose value function is greater at that position. The proposed model describes the experimental results of [1], a lesion-study that investigates the competition between cue-based and place-based navigational systems. The present study also examines impaired navigational performance under Parkinsonian-like conditions. The integrated navigational system, operated under dopamine-deficient conditions, exhibits increased escape latency as was observed in experimental literature describing MPTP model rats navigating a water maze.     

Estimation of disease prevalence, true positive rate, and false positive rate of two screening tests when disease verification is applied on only screen-positives: a hierarchical model using multi-center data

Objectives: A model is proposed to estimate and compare cervical cancer screening test properties for third world populations when only subjects with a positive screen receive the gold standard test. Two fallible screening tests are compared, VIA and VILI. Methods: We extend the model of Berry et al. [1] to the multi-site case in order to pool information across sites and form better estimates for prevalences of cervical cancer, the true positive rates (TPRs), and false positive rates (FPRs). For 10 centers in five African countries and India involving more than 52,000 women, Bayesian methods were applied when gold standard results for subjects who screened negative on both tests were treated as missing. The Bayesian methods employed suitably correct for the missing screen negative subjects. The study included gold standard verification for all cases, making it possible to validate model-based estimation of accuracy using only outcomes of women with positive VIA or VILI result (ignoring verification of double negative screening test results) with the observed full data outcomes. Results: Across the sites, estimates for the sensitivity of VIA ranged from 0.792 to 0.917 while for VILI sensitivities ranged from 0.929 to 0.977. False positive estimates ranged from 0.056 to 0.256 for VIA and 0.085 to 0.269 for VILI. The pooled estimates for the TPR of VIA and VILI are 0.871 and 0.968, respectively, compared to the full data values of 0.816 and 0.918. Similarly, the pooled estimates for the FPR of VIA and VILI are 0.134 and 0.146, respectively, compared to the full data values of 0.144 and 0.146. Globally, we found VILI had a statistically significant higher sensitivity but no statistical difference for the false positive rates could be determined. Conclusion: Hierarchical Bayesian methods provide a straight forward approach to estimate screening test properties, prevalences, and to perform comparisons for screening studies where screen negative subjects do not receive the gold standard test. The hierarchical model with random effects used to analyze the sites simultaneously resulted in improved estimates compared to the single-site analyses with improved TPR estimates and nearly identical FPR estimates to the full data outcomes. Furthermore, higher TPRs but similar FPRs were observed for VILI compared to VIA.     

Education and cancer incidence in a rural population in south India

Background: Population-based studies describing the association between education and cancer incidence has not yet been reported from India. Methods: Information on the educational attainment of 4417 cancer cases aged 14 years and above, diagnosed during 2003–2006 in Dindigul district, Tamil Nadu, India, was obtained from the Dindigul Ambilikkai Cancer Registry, which registers invasive cancer cases by active methods from 102 data sources. Population distribution by 5-year age groups and for four educational levels namely no education, education ≤5 years, 6–12 years and >12 years, was obtained from census data. Standardized rate ratios based on age-standardized rates were calculated to study cancer risks for different educational levels. Results: Men and women with no education had higher overall cancer incidence rates compared to the educated population. The risk of cervix, mouth, esophagus, stomach and lung cancers were inversely associated with higher levels of education whereas a high incidence of breast cancer was observed with increasing educational levels. The standardized rate ratio of cervical cancer 0.32 (95% CI: 0.19–0.52) and of breast cancer was 6.08 (95% CI: 1.81–20.48) for women with more than 12 years of education compared to those with no education. There was paucity of cases in the highest education level for most cancers. Conclusion: With more and more women in rural India becoming educated, one could foresee breast cancer becoming more frequent even in rural areas of India in future.     

Structural Properties of Gene Regulatory Networks: Definitions and Connections

The study of gene regulatory networks is a significant problem in systems biology. Of particular interest is the problem of determining the unknown or hidden higher level regulatory signals by using gene expression data from DNA microarray experiments. Several studies in this area have demonstrated the critical aspect of the network structure in tackling the network modelling problem. Structural analysis of systems has proved useful in a number of contexts, viz., observability, controllability, fault diagnosis, sparse matrix computations etc. In this contribution, we formally define structural properties that are relevant to Gene Regulatory Networks. We explore the structural implications of certain quantitative methods and explain completely the connections between the identifiability conditions and structural criteria of observability and distinguishability. We illustrate these concepts in case studies using representative biologically motivated network examples. The present work bridges the quantitative modelling methods with those based on the structural analysis.