950 resultados para human-action recognition
Resumo:
Cell-permeable small molecules that enhance the stability of the G-quadruplex (G4) DNA structures are currently among the most intensively pursued ligands for inhibition of the telomerase activity. Herein we report the design and syntheses of four novel benzimidazole carbazole conjugates and demonstrate their high binding affinity to G4 DNA. Si nuclease assay confirmed the ligand mediated G-quadruplex DNA protection. Additional evidence from Telomeric Repeat Amplification Protocol (TRAP-LIG) assay demonstrated efficient telomerase inhibition activity by the ligands. Two of the ligands showed IC50 values in the sub-micromolar range in the TRAP-LIG assay, which are the best among the benzimidazole derivatives reported so far. The ligands also exhibited cancer cell selective nuclear internalization, nuclear condensation, fragmentation, and eventually antiproliferative activity in long-term cell viability assays. Annexin V-FITC/PI staining assays confirm that the cell death induced by the ligands follows an apoptotic pathway. An insight into the mode of ligand binding was obtained from the molecular dynamics simulations.
Resumo:
Study of emotions in human-computer interaction is a growing research area. This paper shows an attempt to select the most significant features for emotion recognition in spoken Basque and Spanish Languages using different methods for feature selection. RekEmozio database was used as the experimental data set. Several Machine Learning paradigms were used for the emotion classification task. Experiments were executed in three phases, using different sets of features as classification variables in each phase. Moreover, feature subset selection was applied at each phase in order to seek for the most relevant feature subset. The three phases approach was selected to check the validity of the proposed approach. Achieved results show that an instance-based learning algorithm using feature subset selection techniques based on evolutionary algorithms is the best Machine Learning paradigm in automatic emotion recognition, with all different feature sets, obtaining a mean of 80,05% emotion recognition rate in Basque and a 74,82% in Spanish. In order to check the goodness of the proposed process, a greedy searching approach (FSS-Forward) has been applied and a comparison between them is provided. Based on achieved results, a set of most relevant non-speaker dependent features is proposed for both languages and new perspectives are suggested.
Resumo:
The specific recognition between monoclonal antibody (anti-human prostate-specific antigen, anti-hPSA) and its antigen (human prostate-specific antigen, hPSA) has promising applications in prostate cancer diagnostics and other biosensor applications. However, because of steric constraints associated with interfacial packing and molecular orientations, the binding efficiency is often very low. In this study, spectroscopic ellipsometry and neutron reflection have been used to investigate how solution pH, salt concentration and surface chemistry affect antibody adsorption and subsequent antigen binding. The adsorbed amount of antibody was found to vary with pH and the maximum adsorption occurred between pH 5 and 6, close to the isoelectric point of the antibody. By contrast, the highest antigen binding efficiency occurred close to the neutral pH. Increasing the ionic strength reduced antibody adsorbed amount at the silica-water interface but had little effect on antigen binding. Further studies of antibody adsorption on hydrophobic C8 (octyltrimethoxysilane) surface and chemical attachment of antibody on (3-mercaptopropyl)trimethoxysilane/4-maleimidobutyric acid N-hydroxysuccinimide ester-modified surface have also been undertaken. It was found that on all surfaces studied, the antibody predominantly adopted the 'flat on' orientation, and antigen-binding capabilities were comparable. The results indicate that antibody immobilization via appropriate physical adsorption can replace elaborate interfacial molecular engineering involving complex covalent attachments.
Resumo:
This paper describes a representation of the dynamics of human walking action for the purpose of person identification and classification by gait appearance. Our gait representation is based on simple features such as moments extracted from video silhouettes of human walking motion. We claim that our gait dynamics representation is rich enough for the task of recognition and classification. The use of our feature representation is demonstrated in the task of person recognition from video sequences of orthogonal views of people walking. We demonstrate the accuracy of recognition on gait video sequences collected over different days and times, and under varying lighting environments. In addition, preliminary results are shown on gender classification using our gait dynamics features.
Resumo:
The most potent steroid in human prostatic carcinoma LNCaP cells, i.e. dihydrotestosterone (DHT), has a biphasic stimulatory effect on cell proliferation. At the maximal stimulatory concentration of 0.1 nM DHT, analysis of cell kinetic parameters shows a decrease of the G0-G1 fraction with a corresponding increase of the S and G2 + M fractions. In contrast, concentrations of 1 nM DHT or higher induce a return of cell proliferation to control levels, reflected by an increase in the G0-G1 fraction at the expense of the S and especially the G2 + M fractions. Continuous labeling for 144 h with the nucleotide analogue 5'-bromodeoxyuridine shows that the percentage of cycling LNCaP cells rises more than 90% after treatment with stimulatory concentrations of DHT, whereas in control cells as well as in cells treated with high concentrations of the androgen, this value remains below 50%. Although LNCaP cells do not contain detectable estrogen receptors, the new pure steroidal antiestrogen EM-139 not only reversed the stimulation of cell proliferation and cell kinetics induced by stimulatory doses of DHT but also inhibited basal cell proliferation.
Resumo:
The authors are concerned with the development of computer systems that are capable of using information from faces and voices to recognise people's emotions in real-life situations. The paper addresses the nature of the challenges that lie ahead, and provides an assessment of the progress that has been made in the areas of signal processing and analysis techniques (with regard to speech and face), and the psychological and linguistic analyses of emotion. Ongoing developmental work by the authors in each of these areas is described.
Resumo:
T cell immune responses to central nervous system-derived and other self-antigens are commonly described in both healthy and autoimmune individuals. However, in the case of the human prion protein (PrP), it has been argued that immunologic tolerance is uncommonly robust. Although development of an effective vaccine for prion disease requires breaking of tolerance to PrP, the extent of immune tolerance to PrP and the identity of immunodominant regions of the protein have not previously been determined in humans. We analyzed PrP T cell epitopes both by using a predictive algorithm and by measuring functional immune responses from healthy donors. Interestingly, clusters of epitopes were focused around the area of the polymorphic residue 129, previously identified as an indicator of susceptibility to prion disease, and in the C-terminal region. Moreover, responses were seen to PrP peptide 121-134 containing methionine at position 129, whereas PrP 121-134 [129V] was not immunogenic. The residue 129 polymorphism was also associated with distinct patterns of cytokine response: PrP 128-141 [129M] inducing IL-4 and IL-6 production, which was not seen in response to PrP 128-141 [129V]. Our data suggest that the immunogenic regions of human PrP lie between residue 107 and the C-terminus and that, like with many other central nervous system antigens, healthy individuals carry responses to PrP within the T cell repertoire and yet do not experience deleterious autoimmune reactions.
Resumo:
In this paper, a novel video-based multimodal biometric verification scheme using the subspace-based low-level feature fusion of face and speech is developed for specific speaker recognition for perceptual human--computer interaction (HCI). In the proposed scheme, human face is tracked and face pose is estimated to weight the detected facelike regions in successive frames, where ill-posed faces and false-positive detections are assigned with lower credit to enhance the accuracy. In the audio modality, mel-frequency cepstral coefficients are extracted for voice-based biometric verification. In the fusion step, features from both modalities are projected into nonlinear Laplacian Eigenmap subspace for multimodal speaker recognition and combined at low level. The proposed approach is tested on the video database of ten human subjects, and the results show that the proposed scheme can attain better accuracy in comparison with the conventional multimodal fusion using latent semantic analysis as well as the single-modality verifications. The experiment on MATLAB shows the potential of the proposed scheme to attain the real-time performance for perceptual HCI applications.
Resumo:
DNA-dependent protein kinase (DNA-PK) has been implicated in a variety of nuclear processes including DNA double strand break repair, V(D)J recombination, and transcription. A recent study showed that DNA-PK is responsible for Ser-473 phosphorylation in the hydrophobic motif of protein kinase B (PKB/Akt) in genotoxic-stressed cells, suggesting a novel role for DNA-PK in cell signaling. Here, we report that DNA-PK activity toward PKB peptides is impaired in DNA-PK knock-out mouse embryonic fibroblast cells when compared with wild type. In addition, human glioblastoma cells expressing a mutant form of DNA-PK (M059J) displayed a lower DNA-PK activity when compared with glioblastoma cells expressing wild-type DNA- PK (M059K) when PKB peptide substrates were tested. DNA- PK preferentially phosphorylated PKB on Ser-473 when compared with its known in vitro substrate, p53. A consensus hydrophobic amino acid surrounding the Ser-473 phospho-acceptor site in PKB containing amino acids Phe at position +1 and +4 and Tyr at position -1 are critical for DNA- PK activity. Thus, these data define the specificity of DNA- PK action as a Ser-473 kinase for PKB in DNA repair signaling.