Emerging Machine Learning Techniques for Modelling Cellular Complex Systems in Alzheimer's Disease.

We live in the big data era in the biomedical field, where machine learning has a very important contribution to the interpretation of complex biological processes and diseases, since it has the potential to create predictive models from multidimensional data sets. Part of the application of machine learning in biomedical science is to study and model complex cellular systems such as biological networks. In this context, the study of complex diseases, such as Alzheimer's diseases (AD), benefits from established methodologies of network science and machine learning as they offer algorithmic tools and techniques that can address the limitations and challenges of modeling and studying cellular AD-related networks.

Handling the Cellular Complex Systems in Alzheimer's Disease Through a Graph Mining Approach.

In the last two decades, the medical sciences have changed their approach to pathogenesis as well as to the diagnosis and treatment of complex human diseases. The main reason for this change is the explosive development of biomedical technology and research, which produces a huge amount of information and data which are generated at an increasing rate. Toward this direction is the pathway analysis, a thriving research area of systems biology tools and methodologies which aim to unravel the inherent complexity of high-throughput biological data produced by the advent of omics technologies.

Extramedullary Leukemia, Presenting at the Cervix of the Uterus.

Extramedullary relapse of leukemia is encountered more often than in the past. The reason is that leukemia survival rates increase with improved treatment schemes. We present a rare case of involvement of the cervix of the uterus in an adult B Acute Lymphocytic Leukemia (B-ALL) survivor.

Biomarkers as a Different Approach in Prevention and Treatment of Drug Addiction (Preliminary Study).

Unlabelled: Drug addiction is a chronic relapsing disorder and a burden to society and individuals. The toxicity induced by drugs related with addiction may trigger dysfunction and death of cells of the central nervous system. The study of alterations of proteins and biomarkers in buccal cells would be beneficial in understanding drug addiction, as the buccal mucosa is of ectodermal origin such as the central nervous system.

Immunocytochemical expression of a panel of markers in pleural effusions from patients with primary lung adenocarcinoma.

Introduction: This study's principal objective was to evaluate the critical role of the application of immunocytochemistry to a novel panel of diagnostic markers for the accurate detection of the source of malignancies in pleural effusions of lung adenocarcinoma.

Materials And Methods: In 40 effusion smears from lung adenocarcinoma, the expression of the E-cadherin, a-catenin, Thyroid Transcription Factor (TTF-1), Epidermal Growth Factor Receptor (EGFR), p53, caspase 9 and 3, Bax and Bcl-2 was examined by immunocytochemistry.

Results: All cases showed positive immunoreactivity of tumour cells to caspase 3 (42,5%), caspase 9 (40%), Bcl-2 (30%), Bax (40%), p53 (55%), E-cadherin (82,5%), a-catenin (80%), TTF-1 (87,5%) and EGFR (62,5%).