Recruitment times, proliferation, and apoptosis rates during the CD8(+) T-cell response to lymphocytic choriomeningitis virus

The specific CD8(+) T-cell response during acute lymphocytic choriomeningitis virus (LCMV) infection of mice is characterized by a rapid proliferation phase, followed by a rapid death phase and long-term memory. In BALB/c mice the immunodominant and subdominant CD8(+) responses are directed against the NP118 and GP283 epitopes. These responses differ mainly in the magnitude of the epitope-specific CD8(+) T-cell expansion. Using mathematical models together with a nonlinear parameter estimation procedure, we estimate the parameters describing the rates of change during the three phases and thereby establish the differences between the responses to the two epitopes. We find that CD8(+) cell proliferation begins 1 to 2 days after infection and occurs at an average rate of 3 day(-1), reaching the maximum population size between days 5 and 6 after immunization. The 10-fold difference in expansion to the NP118 and GP283 epitopes can be accounted for in our model by a 3.5-fold difference in the antigen concentration of these epitopes at which T-cell stimulation is half-maximal. As a consequence of this 3.5-fold difference in the epitope concentration needed for T-cell stimulation, the rates of activation and proliferation of T cells specific for the two epitopes differ during the response and in combination can account for the large difference in the magnitude of the response. After the peak, during the death phase, the population declines at a rate of 0.5 day(-1), i.e., cells have an average life time of 2 days. The model accounts for a memory cell population of 5% of the peak population size by a reversal to memory of 1 to 2% of the activated cells per day during the death phase.     

Improved inference of mutation rates: I. An integral representation for the Luria-Delbrück distribution

The estimation of mutation rates is ordinarily performed using results based on the Luria-Delbrück distribution. There are certain difficulties associated with the use of this distribution in practice, some of which we address in this paper (others in the companion paper, Oprea and Kepler, Theor. Popul. Biol., 2001). The distribution is difficult to compute exactly, especially for large values of the random variable. To overcome this problem, we derive an integral representation of the Luria-Delbrück distribution that can be computed easily for large culture sizes. In addition, we introduce the usual assumption of very small probability of having a large proportion of mutants only after the generating function has been computed. Thus, we obtain information on the moments for the more general case. We examine the asymptotic behavior of this system. We find a scaling or "standardization" technique that reduces the family of distributions parameterized by three parameters (mutation rate, initial cell number, and final cell number) to a single distribution with no parameters, valid so long as the product of the mutation rate and the final culture is sufficiently large. We provide a pair of techniques for computing confidence intervals for the mutation rate. In the second paper of this series, we use the distribution derived here to find approximate distributions for the case where the cell cycle time is not well-described as an exponential random variable as is implicitly assumed by Luria-Delbrück distribution.     

Post-high-throughput screening analysis: an empirical compound prioritization scheme

An empirical scheme to evaluate and prioritize screening hits from high-throughput screening (HTS) is proposed. Negative scores are given when chemotypes found in the HTS hits are present in annotated databases such as MDDR and WOMBAT or for testing positive in toxicity-related experiments reported in TOXNET. Positive scores were given for higher measured biological activities, for testing negative in toxicity-related literature, and for good overlap when profiled against drug-related properties. Particular emphasis is placed on estimating aqueous solubility to prioritize in vivo experiments. This empirical scheme is given as an illustration to assist the decision-making process in selecting chemotypes and individual compounds for further experimentation, when confronted with multiple hits from high-throughput experiments. The decision-making process is discussed for a set of G-protein coupled receptor antagonists and validated on a literature example for dihydrofolate reductase inhibition.     

Pursuing the leadlikeness concept in pharmaceutical research

Lipinski and others, through concepts such as drug-likeness, re-focussed drug discovery back to the principles of medicinal chemistry in the high-throughput era as key to reducing attrition. More recently, the need to go further in defining what makes a good lead has been recognised with the concept of leadlikeness. Leadlikeness implies cut-off values in the physico-chemical profile of chemical libraries such that they have reduced complexity (e.g. MW below <400) and other more restricted properties. We examine these concepts in the context of Virtual (theoretically possible), Tangible (chemically feasible) and Real (physically available) worlds of molecules. In a thought experiment, we take the HTS concept to the extreme: screening an estimated 60 million 'Global Collection' on 5000 targets and realising that perhaps millions of drug candidates might be found that could not possibly be handled in reality. Sampling of the Virtual and Tangible worlds is therefore a necessity. We show that the world of Reals is significantly under-sampled as the MW of compounds increases. This supports the design and screening of 'reduced complexity' (leadlike) compound libraries, preferably with synthetic handles available for rapid chemical iteration and detected as interesting by careful screening or biophysical assays.     

Temporal changes in the potential geographic distribution of Histiotus velatus (Chiroptera,Vespertilionidae), the “decade effect”

We investigated how the potential distribution of Histiotus velatus is affected by the addition of new records over decades (decade effect). Assuming that (1: hypothesis of the effect of the decade) the addition of new occurrence records over time increases the potential size of the species distribution; and (2: Wallacean distance hypothesis) over the years, the new points added are increasingly distant from the research centers. Considering the geographic knowledge gap of this species, our objective is to report a new record of this species and estimate its potential distribution in South America through environment niche models (ENMs). For this, we compiled records of occurrence of species, selected from 1900 to 2015. We used 19 bioclimatic variables available in the WorldClim database to estimate the potential distribution of the species, and we used three modeling algorithms: Maximum Entropy (MXT), Random Forest (RDF), and Support Vector Machine. To test the Wallacean distance hypothesis, we calculated the Euclidian distance from occurrences to bat research centers in Brazil, located using a national researchers’ information dataset (“Plataforma Lattes”). To test the hypothesis of the decade effect, we used the beta regression analysis, taking conservative and non‐conservative approaches. The results showed that the predicted area expanded and retracted with the addition of new occurrences over the decades, with an improvement in the accuracy of models. Most records are located in the southeastern region of Brazil, but algorithms predicted areas in regions where there are no records. Only the conservative approach has had a positive relationship over the decades. The distance from new points does not increase over the years of research centers.     

桂木茎枝化学成分的研究

从桂木(Artocarpus nitidus subsp.lingnanensis)茎枝中分离得到13个化合物。通过波谱分析,分别鉴定为albanin A(1)、brosimone I(2)、cycloartocarpin A(3)、artotonkin(4)、albafuran A(5)、artocarpin(6)、artogomezianone(7)、β-香树素乙酯(8)、3,4-二羟基苯甲醛(9)、3,4-二羟基苯甲酸(10)、3-甲氧基-1,2-丙二醇(11)、β-谷甾醇(12)和β-胡萝卜苷(13)。这些化合物为首次从桂木中分离得到。     

Systems chemical biology

The increasing availability of data related to genes, proteins and their modulation by small molecules has provided a vast amount of biological information leading to the emergence of systems biology and the broad use of simulation tools for data analysis. However, there is a critical need to develop cheminformatics tools that can integrate chemical knowledge with these biological databases and simulation approaches, with the goal of creating systems chemical biology.     

Temperature-Assisted Cyclic Hybridization (TACH): An Improved Method for Supercoiled DNA Hybridization

Accurate hybridization is dependent on the ratio between sequence-specific and unspecific binding. Dissociation of unspecifically bound, while maintaining specifically hybridized, nucleic acids are key steps to obtain a well-defined complex. We have developed a new method, temperature-assisted, cyclic hybridization (TACH), which increases cognate binding at the expense of unspecific hybridization. The method was used for optimizing binding of peptide nucleic acid (PNA) to supercoiled plasmids and has several advantages over previous methods: (1) it reduces the required amount of bis-PNA by three- to fourfold; (2) it results in less unspecific binding; (3) it extends cooperative hybridization, from 3 bp to 5 bp between two adjacent binding sites; and (4) it decreases the aggregation of bis-PNA. This method might be extended to other forms of hybridizations including the use of additional nucleic acids analogs, such as locked nucleic acid (LNA) and, also, to other areas where PNAs are used such as fluorescence in situ hybridization (FISH), microarrays, or in vivo plasmid delivery.