Remote sensing of spectral signatures of tropospheric aerosols

With the launch of the German Aerospace Agency's (DLR) Modular Opto-electronic Scanner (MOS) sensor on board the Indian Remote Sensing satellite (IRS-P3) launched by the Indian Space Research Organization (ISRO) in March 1996, 13 channel multi-spectral data in the range of 408 to 1010nm at high radiometric resolution, precision, and with narrow spectral bands have been available for a variety of land, atmospheric and oceanic studies. We found that these data are best for validation of radiative transfer model and the corresponding code developed by one of the authors at Space Applications Centre, and called ATMRAD (abbreviated for ATMospheric RADiation). Once this model/code is validated, it can be used for retrieving information on tropospheric aerosols over ocean or land. This paper deals with two clear objectives, viz., (1) Validation of ATMRAD model/code using MOS data and synchronously measured atmospheric data, and if found performing well, then to (2) derive relationship between MOS radiances and Aerosol Optical Thickness (AOT). The data validation procedure essentially involves near-synchronous measurements of columnar aerosol optical thickness and altitude profiles of aerosol concentration using ground-based multi-filter solar radiometers and Argon-ion Lidar, respectively and computation of the top-of-the-atmosphere (TOA) radiances from a low reflecting target (near clear water reservoir in the present study) using the ATMRAD model. The results show that the model performance is satisfactory and a relationship between the spectral parameters of MOS radiances and aerosol optical thickness can be established. In this communication, we present the details of the experiments conducted, database, validation of the ATMRAD model and development of the relationship between AOT and MOS radiance

Predicting Phenotypic Diversity and the Underlying Quantitative Molecular Transitions

During development, signaling networks control the formation of multicellular patterns. To what extent quantitative fluctuations in these complex networks may affect multicellular phenotype remains unclear. Here, we describe a computational approach to predict and analyze the phenotypic diversity that is accessible to a developmental signaling network. Applying this framework to vulval development in C. elegans, we demonstrate that quantitative changes in the regulatory network can render ~500 multicellular phenotypes. This phenotypic capacity is an order-of-magnitude below the theoretical upper limit for this system but yet is large enough to demonstrate that the system is not restricted to a select few outcomes. Using metrics to gauge the robustness of these phenotypes to parameter perturbations, we identify a select subset of novel phenotypes that are the most promising for experimental validation. In addition, our model calculations provide a layout of these phenotypes in network parameter space. Analyzing this landscape of multicellular phenotypes yielded two significant insights. First, we show that experimentally well-established mutant phenotypes may be rendered using non-canonical network perturbations. Second, we show that the predicted multicellular patterns include not only those observed in C. elegans, but also those occurring exclusively in other species of the Caenorhabditis genus. This result demonstrates that quantitative diversification of a common regulatory network is indeed demonstrably sufficient to generate the phenotypic differences observed across three major species within the Caenorhabditis genus. Using our computational framework, we systematically identify the quantitative changes that may have occurred in the regulatory network during the evolution of these species. Our model predictions show that significant phenotypic diversity may be sampled through quantitative variations in the regulatory network without overhauling the core network architecture. Furthermore, by comparing the predicted landscape of phenotypes to multicellular patterns that have been experimentally observed across multiple species, we systematically trace the quantitative regulatory changes that may have occurred during the evolution of the Caenorhabditis genus

Cause-specific mortality patterns among hospital deaths in Thailand: validating routine death certification

Background: In Thailand, 35% of all deaths occur in hospitals, and the cause of death is medically certified by attending physicians. About 15% of hospital deaths are registered with nonspecific diagnoses, despite the potential for greater accuracy using information available from medical records. Further, issues arising from transcription of diagnoses from Thai to English at registration create uncertainty about the accuracy of registration data even for specified causes of death. This paper reports findings from a study to measure validity of registered diagnoses in a sample of deaths that occurred in hospitals in Thailand during 2005.Methods: A sample of 4,644 hospital deaths was selected, and for each case, medical records were reviewed. A process of medical record abstraction, expert physician review, and independent adjudication for the selection and coding of underlying causes of death was used to derive reference diagnoses. Validation characteristics were computed for leading causes of hospital deaths from registration data, and misclassification patterns were identified for registration diagnoses. Study findings were used to estimate cause-specific mortality patterns for hospital deaths in Thailand.Results: Adequate medical records were available for 3,316 deaths in the study sample. Losses to follow up were nondifferential by age, sex, and cause. Medical records review identified specific underlying causes for the majority of deaths that were originally assigned ill-defined causes as well as for those originally assigned to residual categories for specific cause groups. In comparison with registration data for the sample, we found an increase in the relative proportion of deaths in hospitals due to stroke, ischemic heart disease, transport accidents, HIV/AIDS, diabetes, liver diseases, and chronic obstructive pulmonary disease.Conclusions: Registration data on causes for deaths occurring in hospitals require periodic validation prior to their use for epidemiological research or public health policy. Procedures for death certification and coding of underlying causes of death need to be streamlined to improve reliability of registration data. Estimates of cause-specific mortality from this research will inform burden of disease estimation and guide interventions to reduce avoidable mortality in hospitals in Thailand

The Goldbeter-Koshland switch in the first-order region and its response to dynamic disorder

In their classical work (Proc. Natl. Acad. Sci. USA, 1981, 78:6840-6844), Goldbeter and Koshland mathematically analyzed a reversible covalent modification system which is highly sensitive to the concentration of effectors. Its signal-response curve appears sigmoidal, constituting a biochemical switch. However, the switch behavior only emerges in the "zero-order region", i.e. when the signal molecule concentration is much lower than that of the substrate it modifies. In this work we showed that the switching behavior can also occur under comparable concentrations of signals and substrates, provided that the signal molecules catalyze the modification reaction in cooperation. We also studied the effect of dynamic disorders on the proposed biochemical switch, in which the enzymatic reaction rates, instead of constant, appear as stochastic functions of time. We showed that the system is robust to dynamic disorder at bulk concentration. But if the dynamic disorder is quasi-static, large fluctuations of the switch response behavior may be observed at low concentrations. Such fluctuation is relevant to many biological functions. It can be reduced by either increasing the conformation interconversion rate of the protein, or correlating the enzymatic reaction rates in the network.Comment: 23 pages, 4 figures, accepted by PLOS ON

A Dominated Coupling From The Past algorithm for the stochastic simulation of networks of biochemical reactions

<p>Abstract</p> <p>Background</p> <p>In recent years, stochastic descriptions of biochemical reactions based on the Master Equation (ME) have become widespread. These are especially relevant for models involving gene regulation. Gillespie’s Stochastic Simulation Algorithm (SSA) is the most widely used method for the numerical evaluation of these models. The SSA produces exact samples from the distribution of the ME for finite times. However, if the stationary distribution is of interest, the SSA provides no information about convergence or how long the algorithm needs to be run to sample from the stationary distribution with given accuracy. </p> <p>Results</p> <p>We present a proof and numerical characterization of a Perfect Sampling algorithm for the ME of networks of biochemical reactions prevalent in gene regulation and enzymatic catalysis. Our algorithm combines the SSA with Dominated Coupling From The Past (DCFTP) techniques to provide guaranteed sampling from the stationary distribution. The resulting DCFTP-SSA is applicable to networks of reactions with uni-molecular stoichiometries and sub-linear, (anti-) monotone propensity functions. We showcase its applicability studying steady-state properties of stochastic regulatory networks of relevance in synthetic and systems biology.</p> <p>Conclusion</p> <p>The DCFTP-SSA provides an extension to Gillespie’s SSA with guaranteed sampling from the stationary solution of the ME for a broad class of stochastic biochemical networks.</p

Haptoglobin Phenotype, Preeclampsia Risk and the Efficacy of Vitamin C and E Supplementation to Prevent Preeclampsia in a Racially Diverse Population

Haptoglobin's (Hp) antioxidant and pro-angiogenic properties differ between the 1-1, 2-1, and 2-2 phenotypes. Hp phenotype affects cardiovascular disease risk and treatment response to antioxidant vitamins in some non-pregnant populations. We previously demonstrated that preeclampsia risk was doubled in white Hp 2-1 women, compared to Hp 1-1 women. Our objectives were to determine whether we could reproduce this finding in a larger cohort, and to determine whether Hp phenotype influences lack of efficacy of antioxidant vitamins in preventing preeclampsia and serious complications of pregnancy-associated hypertension (PAH). This is a secondary analysis of a randomized controlled trial in which 10,154 low-risk women received daily vitamin C and E, or placebo, from 9-16 weeks gestation until delivery. Hp phenotype was determined in the study prediction cohort (n = 2,393) and a case-control cohort (703 cases, 1,406 controls). The primary outcome was severe PAH, or mild or severe PAH with elevated liver enzymes, elevated serum creatinine, thrombocytopenia, eclampsia, fetal growth restriction, medically indicated preterm birth or perinatal death. Preeclampsia was a secondary outcome. Odds ratios were estimated by logistic regression. Sampling weights were used to reduce bias from an overrepresentation of women with preeclampsia or the primary outcome. There was no relationship between Hp phenotype and the primary outcome or preeclampsia in Hispanic, white/other or black women. Vitamin supplementation did not reduce the risk of the primary outcome or preeclampsia in women of any phenotype. Supplementation increased preeclampsia risk (odds ratio 3.30; 95% confidence interval 1.61-6.82, p<0.01) in Hispanic Hp 2-2 women. Hp phenotype does not influence preeclampsia risk, or identify a subset of women who may benefit from vitamin C and E supplementation to prevent preeclampsia

The interplay of intrinsic and extrinsic bounded noises in genetic networks

After being considered as a nuisance to be filtered out, it became recently clear that biochemical noise plays a complex role, often fully functional, for a genetic network. The influence of intrinsic and extrinsic noises on genetic networks has intensively been investigated in last ten years, though contributions on the co-presence of both are sparse. Extrinsic noise is usually modeled as an unbounded white or colored gaussian stochastic process, even though realistic stochastic perturbations are clearly bounded. In this paper we consider Gillespie-like stochastic models of nonlinear networks, i.e. the intrinsic noise, where the model jump rates are affected by colored bounded extrinsic noises synthesized by a suitable biochemical state-dependent Langevin system. These systems are described by a master equation, and a simulation algorithm to analyze them is derived. This new modeling paradigm should enlarge the class of systems amenable at modeling. We investigated the influence of both amplitude and autocorrelation time of a extrinsic Sine-Wiener noise on: $(i)$ the Michaelis-Menten approximation of noisy enzymatic reactions, which we show to be applicable also in co-presence of both intrinsic and extrinsic noise, $(ii)$ a model of enzymatic futile cycle and $(iii)$ a genetic toggle switch. In $(ii)$ and $(iii)$ we show that the presence of a bounded extrinsic noise induces qualitative modifications in the probability densities of the involved chemicals, where new modes emerge, thus suggesting the possibile functional role of bounded noises

A Genome-Wide Analysis of Promoter-Mediated Phenotypic Noise in Escherichia coli

Gene expression is subject to random perturbations that lead to fluctuations in the rate of protein production. As a consequence, for any given protein, genetically identical organisms living in a constant environment will contain different amounts of that particular protein, resulting in different phenotypes. This phenomenon is known as “phenotypic noise.” In bacterial systems, previous studies have shown that, for specific genes, both transcriptional and translational processes affect phenotypic noise. Here, we focus on how the promoter regions of genes affect noise and ask whether levels of promoter-mediated noise are correlated with genes' functional attributes, using data for over 60% of all promoters in Escherichia coli. We find that essential genes and genes with a high degree of evolutionary conservation have promoters that confer low levels of noise. We also find that the level of noise cannot be attributed to the evolutionary time that different genes have spent in the genome of E. coli. In contrast to previous results in eukaryotes, we find no association between promoter-mediated noise and gene expression plasticity. These results are consistent with the hypothesis that, in bacteria, natural selection can act to reduce gene expression noise and that some of this noise is controlled through the sequence of the promoter region alon

The Effect of Performance-Based Financial Incentives on Improving Patient Care Experiences: A Statewide Evaluation

Patient experience measures are central to many pay-for-performance (P4P) programs nationally, but the effect of performance-based financial incentives on improving patient care experiences has not been assessed. The study uses Clinician &amp; Group CAHPS data from commercially insured adult patients (n = 124,021) who had visits with 1,444 primary care physicians from 25 California medical groups between 2003 and 2006. Medical directors were interviewed to assess the magnitude and nature of financial incentives directed at individual physicians and the patient experience improvement activities adopted by groups. Multilevel regression models were used to assess the relationship between performance change on patient care experience measures and medical group characteristics, financial incentives, and performance improvement activities. Over the course of the study period, physicians improved performance on the physician-patient communication (0.62 point annual increase, p &lt; 0.001), care coordination (0.48 point annual increase, p &lt; 0.001), and office staff interaction (0.22 point annual increase, p = 0.02) measures. Physicians with lower baseline performance on patient experience measures experienced larger improvements (p &lt; 0.001). Greater emphasis on clinical quality and patient experience criteria in individual physician incentive formulas was associated with larger improvements on the care coordination (p &lt; 0.01) and office staff interaction (p &lt; 0.01) measures. By contrast, greater emphasis on productivity and efficiency criteria was associated with declines in performance on the physician communication (p &lt; 0.01) and office staff interaction (p &lt; 0.001) composites. In the context of statewide measurement, reporting, and performance-based financial incentives, patient care experiences significantly improved. In order to promote patient-centered care in pay for performance and public reporting programs, the mechanisms by which program features influence performance improvement should be clarified