Biomedical subjects
Publications and source records attributed to José A Lozano.
This article reviews machine learning methods for bioinformatics. It presents modelling methods, such as supervised classification, clustering and probabilistic graphical models for knowledge discovery, as well as deterministic and stochastic heuristics for optimization. Applications in genomics, proteomics, systems biology, evolution and text mining are also shown.
Available data have led to a controversy on the relationship between human leukocyte antigen (HLA) and cutaneous malignant melanoma susceptibility or prognosis. Moreover, the influence of HLA-C on melanoma has not yet been well established. Therefore, the aim of the current study was to analyze the possible influence of the HLA system on melanoma susceptibility and prognosis in the Spanish population. For this purpose, HLA-A and HLA-B serotyping and HLA-C, HLA-DRB1, and HLA-DQB1 genotyping by polymerase chain reactions using sequence-specific oligonucleotide (PCR-SSO) and sequence-specific primer (PCR-SSP) were performed in 174 melanoma patients and 227 ethnically matched controls. The number of controls was increased up to 356 for HLA-C typing. Patients were stratified according to the histological subtypes of melanoma, sentinel lymph node status, tumor thickness, and ulceration of primary lesion. No HLA-A, HLA-B, HLA-DRB1, or HLA-DQB1 relationship with melanoma was observed for susceptibility or disease prognosis. However, the analysis of HLA-C locus showed that individuals homozygous for HLA-C(Lys80) were significantly more frequent within the patient than the control group. Remarkably, individuals homozygous for group 2 HLA-C alleles (HLA-C(Lys80)) seem to be associated with metastatic progression of melanoma. In contrast, we found a negative association between group 1 HLA-C alleles (HLA-C(Asn80)) and disease susceptibility or metastasis development. In conclusion, although an association with HLA-A, HLA-B, HLA-DRB1, or HLA-DQB1 was not demonstrated, the study of the HLA-C locus revealed that the analysis of the dimorphism at position 80 in the alpha1 helix may help to evaluate the risk and prognosis of melanoma in our population.
Eating disorders (Eds) are one of the problems with higher social repercussion in the last years. Sometimes, these clinical syndromes, which are characterized by an altered eating behavior, can have dramatic consequences. In eating disorders, one of the more critical situations, in addition to other of equal or more importance, is the patient's confrontation with food: the visual confrontation, the eating process and the repercussion on his weight. Virtual Reality (VR) technology has been used in psychology, as a therapeutic help tool for the treatment of different psychological problems, for several years now. Their helpfulness is increasingly being recognized. Some developed virtual environments (VE) and their corresponding published studies endorse the efficiency of this tool. Nevertheless, in order to increase the possibilities of success, it is very important to obtain a complete patient immersion in the VE: visual, auditory and interactive. Sometimes there are processes or actions of reality, which are difficult to simulate virtually, and simulating them coarsely would result in the patient lack of immersion in the VE, thus seriously decreasing the possibilities of success. The eating process is an example, since it consists of several steps, some of which (biting, chewing, etc.) don't have an evident virtual solution. This article shows how food and eating process have been simulated virtually in the development of a virtual environment for the treatment of eating disorders.