Biomedical subjects

Leonid Brodsky

Publications and source records attributed to Leonid Brodsky.

5 recordsLinked to original sources

PubMed2006

Hereditary family signature of facial expression.

Although facial expressions of emotion are universal, individual differences create a facial expression "signature" for each person; but, is there a unique family facial expression signature? Only a few family studies on the heredity of facial expressions have been performed, none of which compared the gestalt of movements in various emotional states; they compared only a few movements in one or two emotional states. No studies, to our knowledge, have compared movements of congenitally blind subjects with their relatives to our knowledge. Using two types of analyses, we show a correlation between movements of congenitally blind subjects with those of their relatives in think-concentrate, sadness, anger, disgust, joy, and surprise and provide evidence for a unique family facial expression signature. In the analysis "in-out family test," a particular movement was compared each time across subjects. Results show that the frequency of occurrence of a movement of a congenitally blind subject in his family is significantly higher than that outside of his family in think-concentrate, sadness, and anger. In the analysis "the classification test," in which congenitally blind subjects were classified to their families according to the gestalt of movements, results show 80% correct classification over the entire interview and 75% in anger. Analysis of the movements' frequencies in anger revealed a correlation between the movements' frequencies of congenitally blind individuals and those of their relatives. This study anticipates discovering genes that influence facial expressions, understanding their evolutionary significance, and elucidating repair mechanisms for syndromes lacking facial expression, such as autism.

Blindness↗

PubMed2006

Differential expression profiling of the blind subterranean mole rat Spalax ehrenbergi superspecies: bioprospecting for hypoxia tolerance.

The blind subterranean mole rat of the Spalax ehrenbergi superspecies, living underground and exposed to fluctuating oxygen and carbon dioxide levels, is an excellent model of hypoxic tolerance. Unique structural and functional adaptations of the cardiovascular and respiratory systems allow these underground mammals to survive at severely reduced oxygen tension. Elucidation of the natural variation and evolutionary changes under hypoxia within this superspecies may have biomedical applications in ischemic syndromes and cancer. In this study, we have compared expression profiles of muscle tissue at normoxic (21%) and hypoxic (3%) levels of oxygen concentration between two allospecies of the S. ehrenbergi superspecies exhibiting differential hypoxia tolerance in accordance with their ecological regimes. Profiling was performed by cross-species hybridization using a mouse cDNA array containing 15,000 gene elements. Results uncover species-specific responses to hypoxic stress among numerous genes involved in angiogenesis, apoptosis, and oxidative stress management. Among the most striking results are differential expressions of cardiac ankyrin repeat protein (Carp), activating transcription factor 3 (Atf3), LIM and cysteine-rich domains 1 (Lmcd1), cysteine and glycine-rich protein 2 (Csrp2), and ras homolog gene family, member B (RhoB). These findings support the hypothesis that allospecies of the S. ehrenbergi superspecies are variably adapted to fluctuating oxygen tension. Differences may involve specific metabolic pathways and functional adaptations at the structural and molecular levels.

Animals↗

PubMed2006

Differential gene induction by type I and type II interferons and their combination.

Type I and type II interferons (IFNs) bind to different cell surface receptors but activate overlapping signal transduction pathways. We examined the effects of a type I IFN (IFN-alphacon1) and a type II IFN (IFN-gamma1b) on gene expression in A549 cells and demonstrate that there is a common set of genes modulated by both IFNs as well as a set of genes specifically regulated by each, reflecting the activation of different signaling pathways. In particular, IFN-gamma induced many more genes of the signaling pathways, apoptosis, and cytokine interactions than did IFN-alpha. Even with genes induced by both IFNs there were distinctive quantitative differences in expression. IFN-gamma1b plays a major role in the induction and regulation of the complement pathway. Previous work has shown a synergistic antiviral and antiproliferative effect of type I and type II IFNs in cell culture and in the treatment of tumors in mice. We demonstrate that a majority of genes showed an additive effect of IFN-alphacon1 and IFN-gamma1b, but a subset of genes is synergistically induced; these include ISG20, MX2, OAS2, and other genes known to be involved in the antiviral response, TRAIL (TNFSF10) and caspases involved in apoptosis and chemokine genes RANTES, CXCL10, and CXCL11. Greater than additive transcription of some of these genes in the presence of both IFNs was confirmed by real-time kinetic RT-PCR. Elevated induction of many of these genes may be sufficient to explain the synergistic antiviral and antitumor effects of this combination of IFNs in vivo.

Antineoplastic Agents↗

PubMed2004

Identification and handling of artifactual gene expression profiles emerging in microarray hybridization experiments.

Mathematical methods of analysis of microarray hybridizations deal with gene expression profiles as elementary units. However, some of these profiles do not reflect a biologically relevant transcriptional response, but rather stem from technical artifacts. Here, we describe two technically independent but rationally interconnected methods for identification of such artifactual profiles. Our diagnostics are based on detection of deviations from uniformity, which is assumed as the main underlying principle of microarray design. Method 1 is based on detection of non-uniformity of microarray distribution of printed genes that are clustered based on the similarity of their expression profiles. Method 2 is based on evaluation of the presence of gene-specific microarray spots within the slides' areas characterized by an abnormal concentration of low/high differential expression values, which we define as 'patterns of differentials'. Applying two novel algorithms, for nested clustering (method 1) and for pattern detection (method 2), we can make a dual estimation of the profile's quality for almost every printed gene. Genes with artifactual profiles detected by method 1 may then be removed from further analysis. Suspicious differential expression values detected by method 2 may be either removed or weighted according to the probabilities of patterns that cover them, thus diminishing their input in any further data analysis.

Algorithms↗

PubMed2003

Molecular analysis of transitional cell carcinoma using cDNA microarray.

The incidence of transitional cell carcinoma (TCC), the fourth most common neoplasm diagnosed in men, is rising. Despite the development of several noninvasive diagnostic tests, none have gained full recognition by the clinicians. Gene expression profiling of tumors can identify new molecular markers for early diagnosis and disease follow-up. It also allows the classification of tumors into subclasses assisting in disease diagnosis and prognosis, as well as in treatment selection. In this paper, we employed expression profiling for molecular analysis of TCC. A TCC-derived cDNA microarray was constructed and hybridized with 19 probes from normal urothelium and TCC tissues. Hierarchical clustering analysis identified all normal urothelium samples to be tightly clustered and separated from the TCC samples, with 29 of the genes significantly induced (t-test, P<10(-5)) in noninvasive TCC compared to normal urothelium. The identified genes are involved in epithelial cells' functions, tumorigenesis or apoptosis, and could become molecular tools for noninvasive TCC diagnosis. Principal components analysis of the noninvasive and invasive TCC expression profiles further revealed sets of genes that are specifically induced in different tumor subsets, thus providing molecular fingerprints that expand the information gained from classical staging and grading.

Adult↗