Dissociation between mitogenicity and immunogenicity of TNP- lipopolysaccharide, a T-independent antigen

Two models have been proposed to explain triggering of B cells by so-called “T-independent antigen.” Feldmann and Basten (1) proposed that the interaction of multiple repeating determinants on polymeric antigens with specific Ig receptors on the B-cell surface is sufficient to provide the signals for division of these cells and differentiation to antibody-forming cells. In contrast, coutinho et al. (2, and see review, 3) have claimed that there is only one signal, a mitogenic signal, receptors acting merely as passive focusing devices to localize the antigen on specific cells where it delivers a mitogenic signal resulting in differentiation to an antibody-producing cell. This model rests primarily on the demonstration that at high concentration all T-independent antigens they have tested are mitogenic for B cells (4-6). Compatible with this hypothesis are the observations that hydrolysis of lipopolysaccharide (LPS) to remove the ester- linked fatty acids of the mitogenic lipid A component abrogates its mitogenic (7,8) activity as well as its ability, when substituted with the TNP hapten, to induce a T-independent anti- TNP response (9). However, alkali treatment of LPS, although not changing its antigenic component (8), may also modify the molecule physically or chemically which could account for loss of immunogenic properties (10). We therefore investigated other reagents which interact with LPS in a more chemically defined manner in an effort to clarify the relationship between the mitogenic and immunogenic properties of this molecule. Polymyxin B (PB) is one of a family of cyclic peptide antibiotics which are bactericidal for most gram-negative bacteria. It prevents the lethal endotoxic activity of LPS (11, 12) and changes the physical structure of LPS (13). We report here that low doses of PB added to cultures of mouse spleen cells inhibit the mitogenic activity of TNP-LPS, a T- independent antigen, and native LPS, but do not suppress the immune response to TNP-LPS. PB interacts with TNP-LPS and LPS causing a physical change in the molecule. In addition, polymyxin-treated LPS is no longer mitogenic. These results suggest a dissociation between the mitogenic and immunogenic properties of TNP-LPS

Comparative Nephrotoxicity of Cisplatin and Nedaplatin: Mechanisms and Histopathological Characteristics

The antineoplastic platinum complexes cisplatin and its analogues are widely used in the chemotherapy of a variety of human malignancies, and are especially active against several types of cancers. Nedaplatin is a second-generation platinum complex with reduced nephrotoxicity. However, their use commonly causes nephrotoxicity due to a lack of tumor tissue selectivity. Several recent studies have provided significant insights into the molecular and histopathological events associated with nedaplatin nephrotoxicity. In this review, we summarize findings concerning the renal histopathology and molecular pathogenesis induced by antineoplastic platinum complexes, with a particular focus on the comparative nephrotoxicity of cisplatin and nedaplatin in rats

Collective Animal Behavior from Bayesian Estimation and Probability Matching

Animals living in groups make movement decisions that depend, among other factors, on social interactions with other group members. Our present understanding of social rules in animal collectives is based on empirical fits to observations and we lack first-principles approaches that allow their derivation. Here we show that patterns of collective decisions can be derived from the basic ability of animals to make probabilistic estimations in the presence of uncertainty. We build a decision-making model with two stages: Bayesian estimation and probabilistic matching.
In the first stage, each animal makes a Bayesian estimation of which behavior is best to perform taking into account personal information about the environment and social information collected by observing the behaviors of other animals. In the probability matching stage, each animal chooses a behavior with a probability given by the Bayesian estimation that this behavior is the most appropriate one. This model derives very simple rules of interaction in animal collectives that depend only on two types of reliability parameters, one that each animal assigns to the other animals and another given by the quality of the non-social information. We test our model by obtaining theoretically a rich set of observed collective patterns of decisions in three-spined sticklebacks, Gasterosteus aculeatus, a shoaling fish species. The quantitative link shown between probabilistic estimation and collective rules of behavior allows a better contact with other fields such as foraging, mate selection, neurobiology and psychology, and gives predictions for experiments directly testing the relationship between estimation and collective behavior

Multisensory Oddity Detection as Bayesian Inference

A key goal for the perceptual system is to optimally combine information from all the senses that may be available in order to develop the most accurate and unified picture possible of the outside world. The contemporary theoretical framework of ideal observer maximum likelihood integration (MLI) has been highly successful in modelling how the human brain combines information from a variety of different sensory modalities. However, in various recent experiments involving multisensory stimuli of uncertain correspondence, MLI breaks down as a successful model of sensory combination. Within the paradigm of direct stimulus estimation, perceptual models which use Bayesian inference to resolve correspondence have recently been shown to generalize successfully to these cases where MLI fails. This approach has been known variously as model inference, causal inference or structure inference. In this paper, we examine causal uncertainty in another important class of multi-sensory perception paradigm – that of oddity detection and demonstrate how a Bayesian ideal observer also treats oddity detection as a structure inference problem. We validate this approach by showing that it provides an intuitive and quantitative explanation of an important pair of multi-sensory oddity detection experiments – involving cues across and within modalities – for which MLI previously failed dramatically, allowing a novel unifying treatment of within and cross modal multisensory perception. Our successful application of structure inference models to the new ‘oddity detection’ paradigm, and the resultant unified explanation of across and within modality cases provide further evidence to suggest that structure inference may be a commonly evolved principle for combining perceptual information in the brain

Learning automata with side-effects

Automata learning has been successfully applied in the verification of hardware and software. The size of the automaton model learned is a bottleneck for scalability, and hence optimizations that enable learning of compact representations are important. This paper exploits monads, both as a mathematical structure and a programming construct, to design and prove correct a wide class of such optimizations. Monads enable the development of a new learning algorithm and correctness proofs, building upon a general framework for automata learning based on category theory. The new algorithm is parametric on a monad, which provides a rich algebraic structure to capture non-determinism and other side-effects. We show that this allows us to uniformly capture existing algorithms, develop new ones, and add optimizations

Membrane-Anchored HIV-1 N-Heptad Repeat Peptides Are Highly Potent Cell Fusion Inhibitors via an Altered Mode of Action

Peptide inhibitors derived from HIV-gp41 envelope protein play a pivotal role in deciphering the molecular mechanism of HIV-cell fusion. According to accepted models, N-heptad repeat (NHR) peptides can bind two targets in an intermediate fusion conformation, thereby inhibiting progression of the fusion process. In both cases the orientation towards the endogenous intermediate conformation should be important. To test this, we anchored NHR to the cell membrane by conjugating fatty acids with increasing lengths to the N- or C-terminus of N36, as well as to two known N36 mutants; one that cannot bind C-heptad repeat (CHR) but can bind NHR (N36 MUTe,g), and the second cannot bind to either NHR or CHR (N36 MUTa,d). Importantly, the IC50 increased up to 100-fold in a lipopeptide-dependent manner. However, no preferred directionality was observed for the wild type derived lipopeptides, suggesting a planar orientation of the peptides as well as the endogenous NHR region on the cell membrane. Furthermore, based on: (i) specialized analysis of the inhibition curves, (ii) the finding that N36 conjugates reside more on the target cells that occupy the receptors, and (iii) the finding that N36 MUTe,g acts as a monomer both in its soluble form and when anchored to the cell membrane, we suggest that anchoring N36 to the cell changes the inhibitory mode from a trimer which can target both the endogenous NHR and CHR regions, to mainly monomeric lipopetides that target primarily the internal NHR. Besides shedding light on the mode of action of HIV-cell fusion, the similarity between functional regions in the envelopes of other viruses suggests a new approach for developing potent HIV-1 inhibitors

Cue Integration in Categorical Tasks: Insights from Audio-Visual Speech Perception

Previous cue integration studies have examined continuous perceptual dimensions (e.g., size) and have shown that human cue integration is well described by a normative model in which cues are weighted in proportion to their sensory reliability, as estimated from single-cue performance. However, this normative model may not be applicable to categorical perceptual dimensions (e.g., phonemes). In tasks defined over categorical perceptual dimensions, optimal cue weights should depend not only on the sensory variance affecting the perception of each cue but also on the environmental variance inherent in each task-relevant category. Here, we present a computational and experimental investigation of cue integration in a categorical audio-visual (articulatory) speech perception task. Our results show that human performance during audio-visual phonemic labeling is qualitatively consistent with the behavior of a Bayes-optimal observer. Specifically, we show that the participants in our task are sensitive, on a trial-by-trial basis, to the sensory uncertainty associated with the auditory and visual cues, during phonemic categorization. In addition, we show that while sensory uncertainty is a significant factor in determining cue weights, it is not the only one and participants' performance is consistent with an optimal model in which environmental, within category variability also plays a role in determining cue weights. Furthermore, we show that in our task, the sensory variability affecting the visual modality during cue-combination is not well estimated from single-cue performance, but can be estimated from multi-cue performance. The findings and computational principles described here represent a principled first step towards characterizing the mechanisms underlying human cue integration in categorical tasks