Probing T-cell response by sequence-based probabilistic modeling

With the increasing ability to use high-throughput next-generation sequencing to quantify the diversity of the human T cell receptor (TCR) repertoire, the ability to use TCR sequences to infer antigen-specificity could greatly aid potential diagnostics and therapeutics. Here, we use a machine-learning approach known as Restricted Boltzmann Machine to develop a sequence-based inference approach to identify antigen-specific TCRs. Our approach combines probabilistic models of TCR sequences with clone abundance information to extract TCR sequence motifs central to an antigen-specific response. We use this model to identify patient personalized TCR motifs that respond to individual tumor and infectious disease antigens, and to accurately discriminate specific from non-specific responses. Furthermore, the hidden structure of the model results in an interpretable representation space where TCRs responding to the same antigen cluster, correctly discriminating the response of TCR to different viral epitopes. The model can be used to identify condition specific responding TCRs. We focus on the examples of TCRs reactive to candidate neoantigens and selected epitopes in experiments of stimulated TCR clone expansion

The role of input noise in transcriptional regulation

Even under constant external conditions, the expression levels of genes fluctuate. Much emphasis has been placed on the components of this noise that are due to randomness in transcription and translation; here we analyze the role of noise associated with the inputs to transcriptional regulation, the random arrival and binding of transcription factors to their target sites along the genome. This noise sets a fundamental physical limit to the reliability of genetic control, and has clear signatures, but we show that these are easily obscured by experimental limitations and even by conventional methods for plotting the variance vs. mean expression level. We argue that simple, global models of noise dominated by transcription and translation are inconsistent with the embedding of gene expression in a network of regulatory interactions. Analysis of recent experiments on transcriptional control in the early Drosophila embryo shows that these results are quantitatively consistent with the predicted signatures of input noise, and we discuss the experiments needed to test the importance of input noise more generally.Comment: 11 pages, 5 figures minor correction

Mathematical explanation of the predictive power of the X-level approach reaction noise estimator method

The X-level Approach Reaction Noise Estimator (XARNES) method has been developed previously to study reaction noise in well mixed reaction volumes. The method is a typical moment closure method and it works by closing the infinite hierarchy of equations that describe moments of the particle number distribution function. This is done by using correlation forms which describe correlation effects in a strict mathematical way. The variable X is used to specify which correlation effects (forms) are included in the description. Previously, it was argued, in a rather informal way, that the method should work well in situations where the particle number distribution function is Poisson-like. Numerical tests confirmed this. It was shown that the predictive power of the method increases, i.e. the agreement between the theory and simulations improves, if X is increased. In here, these features of the method are explained by using rigorous mathematical reasoning. Three derivative matching theoremsare proven which show that the observed numerical behavior is generic to the method

A new classification method using array Comparative Genome Hybridization data, based on the concept of Limited Jumping Emerging Patterns

<p>Abstract</p> <p>Background</p> <p>Classification using aCGH data is an important and insufficiently investigated problem in bioinformatics. In this paper we propose a new classification method of DNA copy number data based on the concept of limited Jumping Emerging Patterns. We present the comparison of our limJEPClassifier to SVM which is considered the most successful classifier in the case of high-throughput data.</p> <p>Results</p> <p>Our results revealed that the classification performance using limJEPClassifier is significantly higher than other methods. Furthermore, we show that application of the limited JEP's can significantly improve classification, when strongly unbalanced data are given.</p> <p>Conclusion</p> <p>Nowadays, aCGH has become a very important tool, used in research of cancer or genomic disorders. Therefore, improving classification of aCGH data can have a great impact on many medical issues such as the process of diagnosis and finding disease-related genes. The performed experiment shows that the application of Jumping Emerging Patterns can be effective in the classification of high-dimensional data, including these from aCGH experiments.</p

Ictal Behaviors During Nonepileptic Seizures Differ in Patients with Temporal Lobe Interictal Epileptiform EEG Activity and Patients Without Interictal Epileptiform EEG Abnormalities

Purpose: Ictal behaviors during psychogenic non-epileptic seizures (NES) vary considerably among individuals, and can closely resemble common semiologies of epileptic seizures (ES). We tested the hypothesis that behaviors during NES in patients who have temporal spikes would more closely resemble behaviors during ES in patients with temporal lobe epilepsy than would behaviors during NES in patients who do not have EEG spikes. Methods: We identified 20 patients who had interictal temporal EEG spikes and EEG-video recorded NES (Study Group), 133 patients with temporal EEG spikes and recorded ES, without NES (Epileptic Group), and 24 patients with recorded NES and no epileptiform EEG abnormalities, without ES (Nonepileptic Group). Results: The hypothesis was supported with regard to ictal motor behaviors. Motionless staring or complex automatisms occurred mainly during NES in the Study Group and during ES in the Epileptic Group. In contrast, convulsive movements or flaccid falls were most common during NES in the Nonepileptic Group. Duration of unresponsiveness was longer, and there were fewer postictal states in NES both in the Study and Non-epileptic Groups. Unresponsiveness was briefer and postictal states were more consistent in ES in the Epileptic Group, however. Conclusions: Stereotyped motor activities during NES presumably represent learned behaviors. Processes underlying acquisition of ictal behaviors of NES probably differ in patients with interictal epileptiform EEG abnormalities compared to those without. Prior experiences and temporal lobe dysfunctions that are associated with epilepsy, and psychological characteristics that are unrelated to interictal epileptic dysfunctions, may determine ictal behaviors during NES.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65913/1/j.1528-1157.1998.tb01355.x.pd

Prime movers : mechanochemistry of mitotic kinesins

Mitotic spindles are self-organizing protein machines that harness teams of multiple force generators to drive chromosome segregation. Kinesins are key members of these force-generating teams. Different kinesins walk directionally along dynamic microtubules, anchor, crosslink, align and sort microtubules into polarized bundles, and influence microtubule dynamics by interacting with microtubule tips. The mechanochemical mechanisms of these kinesins are specialized to enable each type to make a specific contribution to spindle self-organization and chromosome segregation

Natural gaits of the non-pathological flat foot and high-arched foot

There has been a controversy as to whether or not the non-pathological flat foot and high-arched foot have an effect on human walking activities. The 3D foot scanning system was employed to obtain static footprints from subjects adopting a half-weight-bearing stance. Based upon their footprints, the subjects were divided into two groups: the flat-footed and the high-arched. The plantar pressure measurement system was used to measure and record the subjects' successive natural gaits. Two indices were proposed: distribution of vertical ground reaction force (VGRF) of plantar and the rate of the footprint areas. Using these two indices to compare the natural gaits of the two subject groups, we found that (1) in stance phase, there is a significant difference (p<0.01) in the distributions of VGRF of plantar; (2) in a stride cycle, there is also a significant difference (p<0.01) in the rates of the footprint areas. Our analysis suggests that when walking, the VGRF of the plantar brings greater muscle tension to the flat-footed while a smaller rate of the footprint areas brings greater stability to the high-arched.Comment: 8 pages, 4 figure

Essential versus accessory aspects of cell death: recommendations of the NCCD 2015

Cells exposed to extreme physicochemical or mechanical stimuli die in an uncontrollable manner, as a result of their immediate structural breakdown. Such an unavoidable variant of cellular demise is generally referred to as ‘accidental cell death’ (ACD). In most settings, however, cell death is initiated by a genetically encoded apparatus, correlating with the fact that its course can be altered by pharmacologic or genetic interventions. ‘Regulated cell death’ (RCD) can occur as part of physiologic programs or can be activated once adaptive responses to perturbations of the extracellular or intracellular microenvironment fail. The biochemical phenomena that accompany RCD may be harnessed to classify it into a few subtypes, which often (but not always) exhibit stereotyped morphologic features. Nonetheless, efficiently inhibiting the processes that are commonly thought to cause RCD, such as the activation of executioner caspases in the course of apoptosis, does not exert true cytoprotective effects in the mammalian system, but simply alters the kinetics of cellular demise as it shifts its morphologic and biochemical correlates. Conversely, bona fide cytoprotection can be achieved by inhibiting the transduction of lethal signals in the early phases of the process, when adaptive responses are still operational. Thus, the mechanisms that truly execute RCD may be less understood, less inhibitable and perhaps more homogeneous than previously thought. Here, the Nomenclature Committee on Cell Death formulates a set of recommendations to help scientists and researchers to discriminate between essential and accessory aspects of cell death

RGD-avidin–biotin pretargeting to αvβ3 integrin enhances the proapoptotic activity of TNFα related apoptosis inducing ligand (TRAIL)

Recombinant TNF-related apoptosis-inducing ligand (TRAIL) is considered a powerful and selective inducer of tumor cell death. We hypothesize that TRAIL’s potential as anticancer agent can be enhanced further by promoting its accumulation in tumor tissue. For this purpose, we developed TRAIL complexes that bind to angiogenic endothelial cells. We employed an avidin–biotin pretargeting approach, in which biotinylated TRAIL interacted with RGD-equipped avidin. The assembled complexes killed tumor cells (Jurkat T cells) via apoptosis induction. Furthermore, we demonstrated that the association of the RGD-avidin-TRAIL complex onto endothelial cells enhanced the tumor cell killing activity. Endothelial cells were not killed by TRAIL nor its derived complexes. Our approach can facilitate the enrichment of TRAIL onto angiogenic blood vessels, which may enhance intratumoral accumulation. Furthermore, it offers a versatile technology for the complexation of targeting ligands with therapeutic recombinant proteins and by this a novel way to enhance their specificity and activity

Small molecule sensitization to TRAIL is mediated via nuclear localization, phosphorylation and inhibition of chaperone activity of Hsp27

10.1038/cddis.2013.413Cell Death and Disease410