Subset Selection Procedures for Randomized Designs

Starting from the principle that there exists a randomization procedure that assigns treatments to experimental units, four subset selection rules for the problem of selecting the best treatment from a set of different treatments are proposed. Two of these are extensions of already existing subset selection procedures, which were defined for unbalanced designs, and need a separate selection constant for each individual treatment. The other two rules proposed are new and need only one selection constant for all treatments. The various procedures are compared, and illustrated by application to a plant breeding variety trial.     

On Subset Seeds for Protein Alignment

We apply the concept of subset seeds proposed in [1] to similarity search in protein sequences. The main question studied is the design of efficient seed alphabets to construct seeds with optimal sensitivity/selectivity trade-offs. We propose several different design methods and use them to construct several alphabets. We then perform a comparative analysis of seeds built over those alphabets and compare them with the standard Blastp seeding method [2], [3], as well as with the family of vector seeds proposed in [4]. While the formalism of subset seeds is less expressive (but less costly to implement) than the cumulative principle used in Blastp and vector seeds, our seeds show a similar or even better performance than Blastp on Bernoulli models of proteins compatible with the common BLOSUM62 matrix. Finally, we perform a large-scale benchmarking of our seeds against several main databases of protein alignments. Here again, the results show a comparable or better performance of our seeds versus Blastp.     

Spiders as biological controllers in the agroecosystem

In this paper, we propose a general model consisting of insects, pests and spiders interacting in an agroecosystem included in a typical homogeneous rural landscape, characterized by a continuous mosaic of cultivated land and a few small patches of grasslands and small woods bounding the fields. The model is general enough to show all the phenomena observed in the agroecosystem. The role of the spider population as a biological controller in the agroecosystem is particularly emphasized. Human intervention by means of pesticide spraying and its relationship with the biological pest controllers is also accounted for.     

Subset Selection of an Almost Best Treatment

A generalized goal using subset selection is discussed for the location parameter case. This goal is to select a non-empty subset from a set of k (k ≥ 2) treatments that contains at least one ε-best treatment with confidence level P*. For a set of treatments an ε-best treatment is defined as a treatment with location parameter on a distance less than or equal to ε(ε ≥o) from the best treatment, where best is defined as largest value of the location parameter. The efficiency of subset selection of an ε-best treatment relative to subset selection of the best treatment is investigated and is computed for some values of k and the confidence level for the Normal case as well as for the Logistic case.     

Bi-Directional SIFT Predicts a Subset of Activating Mutations

Advancements in sequencing technologies have empowered recent efforts to identify polymorphisms and mutations on a global scale. The large number of variations and mutations found in these projects requires high-throughput tools to identify those that are most likely to have an impact on function. Numerous computational tools exist for predicting which mutations are likely to be functional, but none that specifically attempt to identify mutations that result in hyperactivation or gain-of-function. Here we present a modified version of the SIFT (Sorting Intolerant from Tolerant) algorithm that utilizes protein sequence alignments with homologous sequences to identify functional mutations based on evolutionary fitness. We show that this bi-directional SIFT (B-SIFT) is capable of identifying experimentally verified activating mutants from multiple datasets. B-SIFT analysis of large-scale cancer genotyping data identified potential activating mutations, some of which we have provided detailed structural evidence to support. B-SIFT could prove to be a valuable tool for efforts in protein engineering as well as in identification of functional mutations in cancer.     

Random marginal agreement coefficients: rethinking the adjustment for chance when measuring agreement

Agreement coefficients quantify how well a set of instruments agree in measuring some response on a population of interest. Many standard agreement coefficients (e.g. kappa for nominal, weighted kappa for ordinal, and the concordance correlation coefficient (CCC) for continuous responses) may indicate increasing agreement as the marginal distributions of the two instruments become more different even as the true cost of disagreement stays the same or increases. This problem has been described for the kappa coefficients; here we describe it for the CCC. We propose a solution for all types of responses in the form of random marginal agreement coefficients (RMACs), which use a different adjustment for chance than the standard agreement coefficients. Standard agreement coefficients model chance agreement using expected agreement between two independent random variables each distributed according to the marginal distribution of one of the instruments. RMACs adjust for chance by modeling two independent readings both from the mixture distribution that averages the two marginal distributions. In other words, both independent readings represent first a random choice of instrument, then a random draw from the marginal distribution of the chosen instrument. The advantage of the resulting RMAC is that differences between the two marginal distributions will not induce greater apparent agreement. As with the standard agreement coefficients, the RMACs do not require any assumptions about the bivariate distribution of the random variables associated with the two instruments. We describe the RMAC for nominal, ordinal and continuous data, and show through the delta method how to approximate the variances of some important special cases.     

Plasmacytoid dendritic cells reduce HIV production in elite controllers

HIV elite controllers (EC) are a rare group of HIV-infected patients who are able to maintain undetectable viral loads during a long period of time in the absence of antiretroviral treatment. Adaptive immunity and host genetic factors, although implicated, do not entirely explain this phenomenon. On the other hand, plasmacytoid dendritic cells (pDCs) are the principal type I interferon (IFN) producers in response to viral infection, and it is unknown whether pDCs are involved in the control of HIV infection in EC. In our study, we analyzed peripheral pDC levels and IFN-α production by peripheral blood mononuclear cells (PBMCs) in EC compared to other groups of HIV-infected patients, the ability of pDCs to reduce HIV production in vitro, and the mechanisms potentially involved. We showed preserved pDC counts and IFN-α production in EC. We also observed a higher capacity of pDCs from EC to reduce HIV production and to induce T cell apoptosis, whereas pDCs from viremic patients barely responded without previous Toll-like receptor 9 (TLR-9) stimulus. The preserved functionality of pDCs from EC to reduce viral production may be one of the mechanisms involved in the control of HIV viremia in these subjects. These results demonstrate the importance of innate immunity in HIV pathogenesis, and an understanding of pDC mechanisms would be helpful for the design of new therapies.     

Polite plurals and adjective agreement

When an agreement controller such as a subject NP is a hybrid of contrasting syntactic and semantic features, the choice of syntactic versus semantic agreement depends on both the type of agreement target and the type of agreement controller. Two types of controller are contrasted: hybrid pronouns such as polite uses of the second person plural to refer to one addressee; and hybrid common nouns such as plurale tante. In some languages the pronoun type triggers singular on a predicate adjective and plural on the verb, while the common noun type triggers plural on both adjectives and verbs. The former pattern is explained in terms of underspecification of the pronoun: it is unspecified for the Concord number feature, to which adjectives are sensitive; but it carries a number feature on its referential Index, to which finite verbs are sensitive. An Agreement Marking Principle is proposed, according to which an agreement target checks the trigger for a syntactic phi feature, assigning that feature’s semantic interpretation to the trigger denotation if no syntactic feature is found.     

Tegmento-thalamic relations in turtles

A focus of evoked potentials and the largest number of spike responses of single units to tegmental stimulation were found in immobilized turtles (Emys orbicularis), lightly anesthetized with chloralose, in the ventral region of the thalamus, which is a heterosensory zone of predominantly somatosensory modality. Incomplete separation of lateral- and medial-tegmental projections between the dorsal and ventral portions of the ventral thalamic region respectively was discovered. Tegmental stimulation, coinciding with or preceding electrodermal or photic stimulation, causes predominant depression of somatic single unit responses, but has less effect on visual responses. The possibility of comparison of tegmento-thalamic systems in reptiles and mammals is discussed.I. M. Sechenov Institute of Evolutionary Physiology and Biochemistry, Academy of Sciences of the USSR, Leningrad. Translated from Neirofiziologiya, Vol. 12, No. 2, pp. 165–174, March–April, 1980.     

Tegmento-telencephalic relations in turtles

Electrophysiological characteristics of tegmental projections in the forebrain were studied in immobilized turtles (Emys orbicularis), anesthetized with chloralose. The main zone of representation of the tegmentum is located in the striatum, where evoked responses with shorter latencies were recorded and a larger number of units responding distinctly to tegmental stimulation was concentrated than in the dorsal ventricular ridge and general cortex. At the striatal level predominance of lateral tegmental projections was found in the lateral zone and of medial tegmental projections in the medial zone of the striatum. An inhibitory action of conditioning stimulation of the tegmentum on somatic evoked potentials and single unit responses was established. An attempt was made to compare the tegmento-telencephalic system in reptiles and mammals.I. M. Sechenov Institute of Evolutionary Physiology and Biochemistry, Academy of Sciences of the USSR, Leningrad. Translated from Neirofiziologiya, Vol. 12, No. 3, pp. 255–263, May–June, 1980.     

The design of controllers for batch bioreactors

The implementation of control algorithms to batch bioreactors is often complicated by variations in process dynamics that occur during the course of fermentation. Such a wide operating range often renders the performance of fixed gain proportional-integral-differential (PID) controllers unsatisfactory. In this work, detailed studies on the control of batch fermentations are per formed. Two simple controller designs are presented with the intent to compensate for changing process dynamics. One design incorporates the concepts of static feedforward-feedback control. While this technique produces tighter control than feedback alone, it is not as successful as a controller based on gain scheduling. The gain-scheduling controller, a subclass of adaptive controllers, uses the oxygen uptake rate as an auxiliary variable to fine-tune the PID controller parameters. The control of oxygen tension in the bioreactor is used as a vehicle to convey the proposed ideas, analyses, and results. Simulation experiments indicate significant improvement in controller performance can be achieved by both of the proposed approaches even in the presence of measurement noise.