The potential demand for and strategic use of an HIV-1 vaccine in Southern India

Even a modestly effective HIV-1 vaccine would be highly useful in India and could avoid millions of deaths. How should such a vaccine be introduced? Based on evidence of adoption of other vaccines in India, current levels of spending on them and coverage of prevention programs targeting both high- and low-risk groups, Seshadri, Subramaniyam, and Jha assess the potential demand for and strategic use of an HIV-1 vaccine in the four southern Indian states of Andhra Pradesh, Karnataka, Maharashtra, and Tamil Nadu. The authors also discuss potential strategies for delivery of the vaccine, prioritization for vaccination, and the political economyof such a vaccine in India. Assuming a vaccine cost of $10 a dose and including estimated delivery costs, the total cost of vaccinating 21.6 million adolescents 11-14 years of age and 1 percent of adults would be Rs. 12.25 billion (US$ 245 million). To maintain the vaccination rate in the 11-14 year old cohort, an additional 6.77 million in that age range would have to be vaccinated each year, at a vaccine cost of Rs. 3.39 billion (US$ 67.5 million). An HIV-1 vaccine will greatly reduce HIV/AIDS in India, but it will not be a panacea. There will be a continued need for effective prevention programs to guard against behavior reversals or an imperfect vaccine. Key inputs for prevention, immunization, and treatment programs such as identification of various groups that could be immunized (vulnerable groups or general populations), strengthened surveillance, capacity building, operations research, and evaluation at local levels will continue to require intensive support.Health Monitoring&Evaluation,Public Health Promotion,HIV AIDS,Disease Control&Prevention,Early Child and Children's Health,Health Monitoring&Evaluation,Adolescent Health,HIV AIDS,Primary Education,Early Child and Children's Health

A Physics-Based Approach to Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems

Given that observational and numerical climate data are being produced at ever more prodigious rates, increasingly sophisticated and automated analysis techniques have become essential. Deep learning is quickly becoming a standard approach for such analyses and, while great progress is being made, major challenges remain. Unlike commercial applications in which deep learning has led to surprising successes, scientific data is highly complex and typically unlabeled. Moreover, interpretability and detecting new mechanisms are key to scientific discovery. To enhance discovery we present a complementary physics-based, data-driven approach that exploits the causal nature of spatiotemporal data sets generated by local dynamics (e.g. hydrodynamic flows). We illustrate how novel patterns and coherent structures can be discovered in cellular automata and outline the path from them to climate data.Comment: 4 pages, 1 figure; http://csc.ucdavis.edu/~cmg/compmech/pubs/ci2017_Rupe_et_al.ht

Approximate Inference for Constructing Astronomical Catalogs from Images

We present a new, fully generative model for constructing astronomical catalogs from optical telescope image sets. Each pixel intensity is treated as a random variable with parameters that depend on the latent properties of stars and galaxies. These latent properties are themselves modeled as random. We compare two procedures for posterior inference. One procedure is based on Markov chain Monte Carlo (MCMC) while the other is based on variational inference (VI). The MCMC procedure excels at quantifying uncertainty, while the VI procedure is 1000 times faster. On a supercomputer, the VI procedure efficiently uses 665,000 CPU cores to construct an astronomical catalog from 50 terabytes of images in 14.6 minutes, demonstrating the scaling characteristics necessary to construct catalogs for upcoming astronomical surveys.Comment: accepted to the Annals of Applied Statistic

A Halotolerant Bacterium Bacillus licheniformis HSW-16 Augments Induced Systemic Tolerance to Salt Stress in Wheat Plant (Triticum aestivum)

Certain plant growth promoting bacteria can protect associated plants from harmful effects of salinity. We report the isolation and characterization of 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase bacterium Bacillus licheniformis HSW-16 capable of ameliorating salt (NaCl) stress in wheat plants. The bacterium was isolated from water of Sambhar salt lake, Rajasthan, India. The presence of ACC deaminase activity was confirmed by enzyme assay and analysis of AcdS gene, a structural gene for ACC deaminase. Inoculation of B. licheniformis HSW-16 protected wheat plants from growth inhibition caused by NaCl and increased plant growth (6-38%) in terms of root length, shoot length, fresh weight, and dry weight. Ionic analysis of plant samples showed that the bacterial inoculation decreased accumulation of Na+ content (51%), and increased K+ (68%), and Ca2+ content (32%) in plants at different concentration of NaCl. It suggested that bacterial inoculation protected plants from the effect of NaCl by decreasing level of Na+ in plants. Production of exopolysaccharide by the B. licheniformis HSW-16 can also protect from Na+ by binding this ion. Moreover, application of test isolate resulted in an increase in certain osmolytes such as total soluble sugar, total protein content and a decrease in malondialdehyde content, illustrating their role in the protection of plants. The ability of B. licheniformis HSW-16 to colonize plant root surface was examined by staining the bacterium with acridine orange followed by fluorescence microscopy and polymerase chain reaction (PCR)-based DNA fingerprinting analysis. These results suggested that B. licheniformis HSW-16 could be used as a bioinoculant to improve the productivity of plants growing under salt stress

Kinetics of Surface Enrichment: A Molecular Dynamics Study

We use molecular dynamics (MD) to study the kinetics of surface enrichment (SE) in a stable homogeneous mixture (AB), placed in contact with a surface which preferentially attracts A. The SE profiles show a characteristic double-exponential behavior with two length scales: \xi_-, which rapidly saturates to its equilibrium value, and \xi_+, which diverges as a power-law with time (\xi_+ \sim t^\theta). We find that hydrodynamic effects result in a crossover of the growth exponent from \theta \simeq 0.5 to \theta \simeq 1.0. There is also a corresponding crossover in the growth dynamics of the SE-layer thickness.Comment: 20 pages, 6 figures, Published in J. Chem. Phys. (Research Highlights

Hepatotoxicity of Microcystis aeruginosa Strains Growing as Blooms in Certain Eutrophic Ponds

Critical assessment of five eutrophicated ponds of Varanasi city (India) revealed the presence of heavy blooms of cyanobacteria consisting mainly of Microcystis aeruginosa. Crude aqueous extracts of blooms as well as laboratory grown M. aeruginosa isolated from three ponds, namely Lakshmikund, Durgakund and Adityanagar showed toxicity in mouse bioassay test. Crude aqueous extracts from these samples caused death of test mice within 1h of administration (i.p.) with a LD50 of 60 mg/kg body weight and the treated animals showed clinical signs of hepatotoxicity. However such an effect was not associated with the blooms from Laatbhairov and Surajkund ponds suggesting that not all strains of M. aeruginosa are toxic. Based on spectral properties (?max 230 nm), and comparison with standard microcystin-LR, the toxin is tentatively identified as microcystin-LR. The purified toxin caused death of test mice within 40 min of its administration with a LD50 of 100 µg/ kg body weight and induced gross morphological and functional changes in liver. A 1.55 fold increase in liver weight accompanied by deep red coloration most probably due to hemorrhage and blood pooling suggested the hepatotoxic properties of the toxin. Hepatotoxicity was also evident from the drastic increase (up to 2.5 fold) in activity of serum enzymes such as glutamate pyruvate transaminase/alanine aminotransferase (GPT/ALT), lactate dehydrogenase (LDH) and alkaline phosphatase (APase) following toxin treatment. ^14C-labelling experiments demonstrated maximum accumulation (~15%) of ^14C- toxin after 20 min. of toxin administration. Appreciable level of toxin was also detected in water of four ponds. In conclusion these results clearly demonstrate that microcystin-producing blooms of M. aeruginosa are common in eutrophicated ponds of Varanasi city but not all ponds harbour toxic blooms

Local Causal States and Discrete Coherent Structures

Coherent structures form spontaneously in nonlinear spatiotemporal systems and are found at all spatial scales in natural phenomena from laboratory hydrodynamic flows and chemical reactions to ocean, atmosphere, and planetary climate dynamics. Phenomenologically, they appear as key components that organize the macroscopic behaviors in such systems. Despite a century of effort, they have eluded rigorous analysis and empirical prediction, with progress being made only recently. As a step in this, we present a formal theory of coherent structures in fully-discrete dynamical field theories. It builds on the notion of structure introduced by computational mechanics, generalizing it to a local spatiotemporal setting. The analysis' main tool employs the \localstates, which are used to uncover a system's hidden spatiotemporal symmetries and which identify coherent structures as spatially-localized deviations from those symmetries. The approach is behavior-driven in the sense that it does not rely on directly analyzing spatiotemporal equations of motion, rather it considers only the spatiotemporal fields a system generates. As such, it offers an unsupervised approach to discover and describe coherent structures. We illustrate the approach by analyzing coherent structures generated by elementary cellular automata, comparing the results with an earlier, dynamic-invariant-set approach that decomposes fields into domains, particles, and particle interactions.Comment: 27 pages, 10 figures; http://csc.ucdavis.edu/~cmg/compmech/pubs/dcs.ht

The Rise and Fall of HIV in High-Prevalence Countries: A Challenge for Mathematical Modeling

Several countries with generalized, high-prevalence HIV epidemics, mostly in sub-Saharan Africa, have experienced rapid declines in transmission. These HIV epidemics, often with rapid onsets, have generally been attributed to a combination of factors related to high-risk sexual behavior. The subsequent declines in these countries began prior to widespread therapy or implementation of any other major biomedical prevention. This change has been construed as evidence of behavior change, often on the basis of mathematical models, but direct evidence for behavior changes that would explain these declines is limited. Here, we look at the structure of current models and argue that the common "fixed risk per sexual contact" assumption favors the conclusion of substantial behavior changes. We argue that this assumption ignores reported non-linearities between exposure and risk. Taking this into account, we propose that some of the decline in HIV transmission may be part of the natural dynamics of the epidemic, and that several factors that have traditionally been ignored by modelers for lack of precise quantitative estimates may well hold the key to understanding epidemiologic trends