Logical Concurrency Control from Sequential Proofs

We are interested in identifying and enforcing the isolation requirements of a concurrent program, i.e., concurrency control that ensures that the program meets its specification. The thesis of this paper is that this can be done systematically starting from a sequential proof, i.e., a proof of correctness of the program in the absence of concurrent interleavings. We illustrate our thesis by presenting a solution to the problem of making a sequential library thread-safe for concurrent clients. We consider a sequential library annotated with assertions along with a proof that these assertions hold in a sequential execution. We show how we can use the proof to derive concurrency control that ensures that any execution of the library methods, when invoked by concurrent clients, satisfies the same assertions. We also present an extension to guarantee that the library methods are linearizable or atomic

Energy-dependent quenching adjusts the excitation diffusion length to regulate photosynthetic light harvesting

An important determinant of crop yields is the regulation of photosystem II (PSII) light harvesting by energy-dependent quenching (qE). However, the molecular details of excitation quenching have not been quantitatively connected to the PSII yield, which only emerges on the 100 nm scale of the grana membrane and determines flux to downstream metabolism. Here, we incorporate excitation dissipation by qE into a pigment-scale model of excitation transfer and trapping for a 200 nm x 200 nm patch of the grana membrane. We demonstrate that single molecule measurements of qE are consistent with a weak-quenching regime. Consequently, excitation transport can be rigorously coarse-grained to a 2D random walk with an excitation diffusion length determined by the extent of quenching. A diffusion-corrected lake model substantially improves the PSII yield determined from variable chlorophyll fluorescence measurements and offers an improved model of PSII for photosynthetic metabolism.Comment: 19 pages, 4 figures, 3 supplementary figure

Iodine status during pregnancy in India and related neonatal and infant outcomes

Objective: To document iodine status in Indian pregnancies, associations with maternal diet and demographics, and offspring developmental measures. Design: Longitudinal study following mothers through pregnancy and offspring up to 24 months. Setting: Rural health-care centre (Vadu) and urban antenatal clinic (Pune) in the Maharashtra region of India. Subjects: Pregnant mothers at 17 (n 132) and 34 weeks’ (n 151) gestation and their infants from birth to the age of 24 months. Results: Median urinary iodine concentration (UIC) was 203 and 211 μg/l at 17 and 34 weeks of pregnancy, respectively (range 26–800 μg/l). Using the UIC distribution adjusted for within-person variation, extreme UIC quartiles were compared for predictors and outcomes. There was no correlation between UIC at 17 and 34 weeks, but 24 % of those with UIC in the lowest quartile at 17 weeks had UIC in the same lowest quartile at 34 weeks. Maternal educational, socio-economic status and milk products consumption (frequency) were different between the lowest and highest quartile of UIC at 34 weeks. Selected offspring developmental outcomes differed between the lowest and highest UIC quartiles (abdominal circumference at 24 months, subscapular and triceps skinfolds at 12 and 24 months). However, UIC was only a weak predictor of subscapular skinfold at 12 months and of triceps skinfold at 24 months. Conclusions: Median UIC in this pregnant population suggested adequate dietary provision at both gestational stages studied. Occasional high results found in spot samples may indicate intermittent consumption of iodine-rich foods. Maternal UIC had limited influence on offspring developmental outcomes

Heterogeneities in EGF receptor density at the cell surface can lead to concave up scatchard plot of EGF binding

AbstractThe mechanism responsible for the concave up nature of the Scatchard plot of epidermal growth factor (EGF) binding on EGF receptor (EGFR) has been a controversial issue for more than a decade. Past efforts to mechanistically simulate the concave up nature of the Scatchard plot of EGF binding have shown that negative cooperativity in EGF binding on an EGFR dimer or inclusion of some external site or binding event can describe this behavior. However, herein we show that heterogeneity in the density of EGFR due to localization in certain regions of the plasma membrane, which has been experimentally reported, can also lead to concave up shape of the Scatchard plot of the EGF binding on EGFR

Iterative approach to model identification of biological networks

BACKGROUND: Recent advances in molecular biology techniques provide an opportunity for developing detailed mathematical models of biological processes. An iterative scheme is introduced for model identification using available system knowledge and experimental measurements. RESULTS: The scheme includes a state regulator algorithm that provides estimates of all system unknowns (concentrations of the system components and the reaction rates of their inter-conversion). The full system information is used for estimation of the model parameters. An optimal experiment design using the parameter identifiability and D-optimality criteria is formulated to provide "rich" experimental data for maximizing the accuracy of the parameter estimates in subsequent iterations. The importance of model identifiability tests for optimal measurement selection is also considered. The iterative scheme is tested on a model for the caspase function in apoptosis where it is demonstrated that model accuracy improves with each iteration. Optimal experiment design was determined to be critical for model identification. CONCLUSION: The proposed algorithm has general application to modeling a wide range of cellular processes, which include gene regulation networks, signal transduction and metabolic networks

Computational modeling reveals molecular details of epidermal growth factor binding

BACKGROUND: The ErbB family of receptors are dysregulated in a number of cancers, and the signaling pathway of this receptor family is a critical target for several anti-cancer drugs. Therefore a detailed understanding of the mechanisms of receptor activation is critical. However, despite a plethora of biochemical studies and recent single particle tracking experiments, the early molecular mechanisms involving epidermal growth factor (EGF) binding and EGF receptor (EGFR) dimerization are not as well understood. Herein, we describe a spatially distributed Monte Carlo based simulation framework to enable the simulation of in vivo receptor diffusion and dimerization. RESULTS: Our simulation results are in agreement with the data from single particle tracking and biochemical experiments on EGFR. Furthermore, the simulations reveal that the sequence of receptor-receptor and ligand-receptor reaction events depends on the ligand concentration, receptor density and receptor mobility. CONCLUSION: Our computer simulations reveal the mechanism of EGF binding on EGFR. Overall, we show that spatial simulation of receptor dynamics can be used to gain a mechanistic understanding of receptor activation which may in turn enable improved cancer treatments in the future

Conservation of fish genetic resources: An introduction to state fishes of India.

Over exploitation, habitat destruction, introduction of exotic species and pollution has led to the loss of native germplasm. Biodiversity conservation is very important to preserve species and also to safeguard the local interest and the cultural attachment of people to certain species. Several species from India are already extinct and many are endangered, threatened or listed in diff erent categories based on their natural presence. The estimated current extinction rate is very high, ranging between 1000-10000 times the natural rate . Hence, appropriate strategies for biodiversity conservation management are required