TCR signaling requirements for activating T cells and for generating memory.

Over the last two decades the molecular and cellular mechanisms underlying T cell activation, expansion, differentiation, and memory formation have been intensively investigated. These studies revealed that the generation of memory T cells is critically impacted by a number of factors, including the magnitude of the inflammatory response and cytokine production, the type of dendritic cell [DC] that presents the pathogen derived antigen, their maturation status, and the concomitant provision of costimulation. Nevertheless, the primary stimulus leading to T cell activation is generated through the T cell receptor [TCR] following its engagement with a peptide MHC ligand [pMHC]. The purpose of this review is to highlight classical and recent findings on how antigen recognition, the degree of TCR stimulation, and intracellular signal transduction pathways impact the formation of effector and memory T cells.

Experimental support for the make-up hypothesis in nestling tawny owls (Strix aluco)

Body condition can affect coloration of traits used in sexual selection and parent-offspring communication by inducing rapid internal changes in pigment concentration or aggregation, thickness of collagen arrays, or blood flux. The recent "makeup hypothesis" proposes an alternative honesty-reinforcing mechanism, with behaviorally mediated deposition of substances on body surfaces ("cosmetics") generating covariation between body condition and coloration. In birds, the uropygial gland wax is actively spread on feathers using the bill and changes in its deposition rate may cause rapid changes in bill and plumage coloration. Using tawny owl nestlings, we tested 3 predictions of the makeup hypothesis, namely that 1) quantity of preen wax deposited accounts for variation in bill coloration, 2) an immune stimulation (induced by injection of a lipopolysaccharide [LPS]) impairs uropygial gland wax production, and 3) different intensities of immune stimulations (strong vs. weak stimulations induced by injections of either LPS or phytohemagglutinin [PHA], respectively) and high versus low food availabilities result in different bill colorations. We found that 1) preen wax reduced bill brightness, 2) a challenge with LPS impaired uropygial gland development, and 3) nestlings challenged with LPS had a brighter bill than PHA-injected nestlings, whereas diet manipulation had no significant effect. Altogether, these results suggest that a strong immune challenge may decrease preen wax deposition rate on the bill of nestling birds, at least by impairing gland wax production, which causes a change in bill coloration. Our study therefore highlights that cosmetic colors might signal short-term variation in immunological status.

Stable alpha-synuclein oligomers strongly inhibit chaperone activity of the Hsp70 system by weak interactions with J-domain co-chaperones.

α-Synuclein aggregation and accumulation in Lewy bodies are implicated in progressive loss of dopaminergic neurons in Parkinson disease and related disorders. In neurons, the Hsp70s and their Hsp40-like J-domain co-chaperones are the only known components of chaperone network that can use ATP to convert cytotoxic protein aggregates into harmless natively refolded polypeptides. Here we developed a protocol for preparing a homogeneous population of highly stable β-sheet enriched toroid-shaped α-Syn oligomers with a diameter typical of toxic pore-forming oligomers. These oligomers were partially resistant to in vitro unfolding by the bacterial Hsp70 chaperone system (DnaK, DnaJ, GrpE). Moreover, both bacterial and human Hsp70/Hsp40 unfolding/refolding activities of model chaperone substrates were strongly inhibited by the oligomers but, remarkably, not by unstructured α-Syn monomers even in large excess. The oligomers acted as a specific competitive inhibitor of the J-domain co-chaperones, indicating that J-domain co-chaperones may preferably bind to exposed bulky misfolded structures in misfolded proteins and, thus, complement Hsp70s that bind to extended segments. Together, our findings suggest that inhibition of the Hsp70/Hsp40 chaperone system by α-Syn oligomers may contribute to the disruption of protein homeostasis in dopaminergic neurons, leading to apoptosis and tissue loss in Parkinson disease and related neurodegenerative diseases.

Gas analysis of exhumed cadavers buried for 30 years: a case report about long time alteration.

Due to important alteration caused by long time decomposition, the gases in human bodies buried for more than a year have not been investigated. For the first time, the results of gas analysis sampled from bodies recently exhumed after 30 years are presented. Adipocere formation has prevented the bodies from too important alteration, and gaseous areas were identified. The sampling was performed with airtight syringes assisted by multi-detector computed tomography (MDCT) in those specific areas. The important amount of methane (CH4), coupled to weak amounts of hydrogen (H2) and carbon dioxide (CO2), usual gaseous alteration indicators, have permitted to confirm methanogenesis mechanism for long period of alteration. H2 and CO2 produced during the first stages of the alteration process were consumed through anaerobic oxidation by methanogenic bacteria, generating CH4.

Laser-Ultraviolet-A induced ultra weak photon emission in human skin cells: A biophotonic comparison between keratinocytes and fibroblasts

Photons participate in many atomic and molecular interactions and processes. Recent biophysical research has discovered an ultraweak radiation in biological tissues. It is now recognized that plants, animal and human cells emit this very weak biophotonic emission which can be readily measured with a sensitive photomultiplier system. UVA laser induced biophotonic emission of cultured cells was used in this report with the intention to detect biophysical changes between young and adult fibroblasts as well as between fibroblasts and keratinocytes. With suspension densities ranging from 1-8x106 cells/ml, it was evident that an increase of the UVA-laser-light induced photon emission intensity could be observed in young as well as adult fibroblastic cells. By the use of this method to determine ultraweak light emission, photons in cell suspensions in low volumes (100 mu l) could be detected, in contrast to previous procedures using quantities up to 10 ml. Moreover, the analysis has been further refined by turning off the photomultiplier system electronically during irradiation leading to the first measurements of induced light emission in the cells after less than 10 mu s instead of more than 100 milliseconds. These significant changes lead to an improvement factor up to 106 in comparison to classical detection procedures. In addition, different skin cells as fibroblasts and keratinocytes stemining from the same donor were measured using this new highly sensitive method in order to find new biophysical insight of light pathways. This is important in view to develop new strategies in biophotonics especially for use in alternative therapies.

Cluster-based active learning for compact image classification

In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer queried and sampling is focused on division of clusters showing mixed labels. The model is tested on a VHR image in a multiclass classification setting. The method clearly outperforms random sampling in a transductive setting, but cannot generalize to unseen data, since it aims at optimizing the classification of a given cluster structure.