Cerebral Palsy

PURPOSE: ‘Praneem’, a polyherbal formulation developed by us, has successfully completed Phase II efficacy study for treatment of abnormal vaginal discharge due to reproductive tract infections that act as co-factors for HPV persistence. In the present study we evaluated potential anti-HPV activity of Praneem in women infected with high risk HPV type 16. METHODS: Twenty women molecularly diagnosed positive for HPV16 infection without or with low grade squamous intraepithelial lesion (LSIL) or inflammation were assigned to receive intra-vaginal, topical application of either Praneem tablet or placebo for 30 days excluding the days of menstrual period and were evaluated for persistence of HPV infection using HPV L1 consensus and HPV type 16-specific PCR as primary outcome. RESULTS: One course of Praneem treatment resulted in elimination of HPV in 6 out of 10 (60%) cases. A repeat treatment of four patients with persisting HPV infection resulted in clearance of HPV in two additional cases resulting in an overall 80% clearance of HPV 16 as against a spontaneous clearance of 10% (1/10) seen in the placebo arm. The elimination of HPV DNA was found to be accompanied by marked improvement in clinical symptoms and cytological abnormalities of Praneem-treated patients. CONCLUSION: Our results showed for the first time that a 30-day intra-vaginal application of the Praneem can result in elimination of HPV infection from the uterine cervix.

Congenital cytomegalovirus brain infection without symptoms at birth can cause a static encephalopathy with characteristic patterns of brain abnormalities. Here we show that loss-of-function mutations in the gene encoding the RNASET2 glycoprotein lead to cystic leukoencephalopathy, an autosomal recessive disorder with an indistinguishable clinical and neuroradiological phenotype. Congenital cytomegalovirus infection and RNASET2 deficiency may both interfere with brain development and myelination through angiogenesis or RNA metabolism.

The health status of some 6,000 workers from Latvia who went to clean-up the Chernobyl Nuclear Power Plant (CNPP) site following the explosion on 26 April 1986 has been analyzed. The data on these workers have been recorded in the Latvian State Register of Occupational disease patients and people exposed to ionizing radiation due to Chernobyl NPP accident (Latvian State Register) that was established in 1994. From these data, estimates have been made of external ionizing radiation to which these workers were exposed together with observations on the impact of exposure to heavy metals (especially lead and zinc) and radioactive isotopes released during the reactor ‘meltdown’. These factors along with psycho-emotional and social-economic stresses account for a marked excess of mortality and morbidity in the group of CNPP accident clean-up workers compared with that of the non-exposed normal Latvian population adjusted for age and sex. The number of diseases or conditions in the CNPP accident clean-up workers has progressively risen from an average of 1.3 in 1986 to 10.9 in 2007. This exceeds for the Latvian population when adjusted for age and sex. The most serious conditions affect the nervous, digestive, respiratory, cardiovascular, endocrine (especially thyroid) and immunological systems. While the morbidity associated with diseases of the respiratory and digestive systems has decreased in recent years that in the other systems is increasing. In recent years, there has been an increased occurrence of cancers affecting the thyroid, prostate and stomach. Clinical and laboratory investigations suggest that surviving CNPP accident clean-up workers exhibit signs of immuno-inflammatory reactions causing premature aging with evidence of autoimmune diseases and immunological deficiencies or abnormalities. It is suggested that the CNPP accident clean-up workers may have a specific syndrome, the ‘Chernobyl post-radiation neurosomatic polypathy’, due to sustained oxidant stress injury, as a result of exposure to radiation and lead.

Objective. The study evaluated the maternal and fetal outcome in 64 pregnancies complicated by HELLP syndrome. Methods. A retrospective analysis of the medical records was performed of patients with HELLP syndrome managed at this tertiary Obstetric unit between January 1996 and December 2005, who were admitted for preeclamsia/eclampsia and had documented evidence of hemolysis, elevated liver enzymes and low platelet count. Maternal and neonatal complications were recorded and analyzed. Results. The incidence of HELLP syndrome in the study was 8.3%. Mean gestational age at delivery was 32.4 +/- 4.2 weeks and mean birth weight was 1851 +/- 810 g. Forty-two percent of the patients had deliveries <32 weeks and 28% IUGR. Respiratory distress syndrome was the main indication for NICU admissions (33.9%). The PNM rate was 20%. Maternal morbidity rate was 34%. The most common maternal complications were abruptio placentae (36.4%) and DIC (31.8%). There was no maternal death. Conclusion. Once the diagnosis of HELLP syndrome is confirmed, the management depends on several obstetric and maternal variables like gestational age, severity of laboratory abnormalities and fetal status. As soon as the maternal condition is stabilized and fetal assessment is obtained, prompt delivery of the fetus is indicated. It is not yet established whether expectant management in preterm pregnancies with HELLP syndrome would improve perinatal outcome.

Embryonic stem cells (ESCs) are endowed with the ability to generate multiple cell lineages and carry great therapeutic potentials in regenerative medicine. Future application of ESCs in human health and diseases will embark on the delineation of molecular mechanisms that define the biology of ESCs. Here, we discuss how the finite ESC components mediate the intriguing task of brain development and exhibit biomedical potentials to cure diverse neurological disorders. Birth Defects Research (Part C) 87:182-191, 2009. (c) 2009 Wiley-Liss, Inc.

Recent studies have identified AHR as a master regulator of Wilms’ tumor suppressor gene (WT1) signaling in the developing kidney. Activation of AHR signaling by environmental chemical is associated with proteasome-mediated degradation of AHR protein, disruption of WT1 alternative splicing, and marked alterations in the regulation of genetic programs of developmental progression in the developing kidney. The complexity of genetic regulatory networks of nephrogenesis controlled by AHR-WT1 interactions will be discussed here with particular emphasis given to the biological and medical consequences that may result from deficits in nephrogenesis that compromise reserve capacity and renal function later in life. Understanding the impact of early-life environmental exposures to chemicals that disrupt AHR signaling can help minimize negative health consequences to pregnant women and their offspring. Birth Defects Research (Part C) 87:192-197, 2009. (c) 2009 Wiley-Liss, Inc.

The genomic revolution has provided the first glimpses of the architecture of regulatory networks. Combined with evolutionary information, the “network view” of life processes leads to remarkable insights into how biological systems have been shaped by various forces. This understanding is critical because biological systems, including regulatory networks, are not products of engineering but of historical contingencies. In this light, we attempt a synthetic overview of the natural history of regulatory networks operating in the development and differentiation of multicellular organisms. We first introduce regulatory networks and their organizational principles as can be deduced using ideas from the graph theory. We then discuss findings from comparative genomics to illustrate the effects of lineage-specific expansions, gene-loss, and nonprotein-coding DNA on the architecture of networks. We consider the interaction between expansions of transcription factors, and cis regulatory and more general chromatin state stabilizing elements in the emergence of morphological complexity. Finally, we consider a case study of the Notch subnetwork, which is present throughout Metazoa, to examine how such a regulatory system has been pieced together in evolution from new innovations and pre-existing components that were originally functionally distinct. Birth Defects Research (Part C) 87:143-164, 2009. (c) 2009 Wiley-Liss, Inc.

Animal development is an elaborate process programmed by genomic regulatory instructions. Regulatory genes encode transcription factors and signal molecules, and their expression is under the control of cis-regulatory modules that define the logic of transcriptional responses to the inputs of other regulatory genes. The functional linkages among regulatory genes constitute the gene regulatory networks (GRNs) that govern cell specification and patterning in development. Constructing such networks requires identification of the regulatory genes involved and characterization of their temporal and spatial expression patterns. Interactions (activation/repression) among transcription factors or signals can be investigated by large-scale perturbation analysis, in which the function of each gene is specifically blocked. Resultant expression changes are then integrated to identify direct linkages, and to reveal the structure of the GRN. Predicted GRN linkages can be tested and verified by cis-regulatory analysis. The explanatory power of the GRN was shown in the lineage specification of sea urchin endomesoderm. Acquiring such networks is essential for a systematic and mechanistic understanding of the developmental process. Birth Defects Research (Part C) 87:123-130, 2009. (c) 2009 Wiley-Liss, Inc.

An emerging research area in computational biology and biotechnology is devoted to mathematical modeling and prediction of gene-expression patterns; it nowadays requests mathematics to deeply understand its foundations. This article surveys data mining and machine learning methods for an analysis of complex systems in computational biology. It mathematically deepens recent advances in modeling and prediction by rigorously introducing the environment and aspects of errors and uncertainty into the genetic context within the framework of matrix and interval arithmetics. Given the data from DNA microarray experiments and environmental measurements, we extract nonlinear ordinary differential equations which contain parameters that are to be determined. This is done by a generalized Chebychev approximation and generalized semi-infinite optimization. Then, time-discretized dynamical systems are studied. By a combinatorial algorithm which constructs and follows polyhedra sequences, the region of parametric stability is detected. In addition, we analyze the topological landscape of gene-environment networks in terms of structural stability. As a second strategy, we will review recent model selection and kernel learning methods for binary classification which can be used to classify microarray data for cancerous cells or for discrimination of other kind of diseases. This review is practically motivated and theoretically elaborated; it is devoted to a contribution to better health care, progress in medicine, a better education, and more healthy living conditions. Birth Defects Research (Part C) 87:165-181, 2009. (c) 2009 Wiley-Liss, Inc.

The network of interacting regulatory signals within a cell comprises one of the most complex and powerful computational systems in biology. Gene regulatory networks (GRNs) play a key role in transforming the information encoded in a genome into morphological form. To achieve this feat, GRNs must respond to and integrate environmental signals with their internal dynamics in a robust and coordinated fashion. The highly dynamic nature of this process lends itself to interpretation and analysis in the language of dynamical models. Modeling provides a means of systematically untangling the complicated structure of GRNs, a framework within which to simulate the behavior of reconstructed systems and, in some cases, suites of analytic tools for exploring that behavior and its implications. This review provides a general background to the idea of treating a regulatory network as a dynamical system, and describes a variety of different approaches that have been taken to the dynamical modeling of GRNs. Birth Defects Research (Part C) 87:131-142, 2009. (c) 2009 Wiley-Liss, Inc.