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Biomedical subjects

S Bhavani

Publications and source records attributed to S Bhavani.

6 recordsLinked to original sources
PubMed2005

Molecular mapping of stem and leaf rust resistance in wheat.

Stem rust caused by Puccinia graminis f. sp. tritici Eriks and Henn and leaf rust caused by Puccinia triticina Rob. ex Desm. are major constraints to wheat production worldwide. In the present study, F(4)-derived SSD population, developed from a cross between Australian cultivars 'Schomburgk' and 'Yarralinka', was used to identify molecular markers linked to rust resistance genes Lr 3 a and Sr 22. A total of 1,330 RAPD and 100 ISSR primers and 33 SSR primer pairs selected ob the basis of chromosomal locations of these genes were used. The ISSR marker UBC 840(540) was found to be linked with Lr 3 a in repulsion at a distance of 6.0 cM. Markers cfa 2019 and cfa 2123 flanked Sr 22 at a distance of 5.9 cM (distal) and 6.0 cM (proximal), respectively. The use of these markers in combination would predict the presence or absence of Sr 22 in breeding populations. A previously identified PCR-based diagnostic marker STS 638 linked to Lr 20 was validated in this population. This marker showed a recombination value of 7.1 cM with Lr 20.

Australia↗
PubMed1999

Perinatal drug abuse in KK Women's and Children's Hospital.

No local figures are available in Singapore on the incidence of perinatal drug abuse and its effect on the foetus and the neonate. The objectives of this study were to determine the incidence of perinatal drug abuse and neonatal abstinence syndrome; to identify a maternal profile at high risk for substance abuse and to document the presenting features and treatment of infants with neonatal abstinence syndrome. Out of 14,690 births during the period January 1994 to December 1996, 38 (0.25%) had evidence of perinatal drug abuse. The study revealed that a high-risk maternal profile for drug abuse comprised of single mothers (52%); history of smoking (52%); no antenatal care (37%) and belonging to the Malay ethnic group (82%); and younger maternal age. Self-reporting was uncommon, occurring only in 8% and in 40% of cases, there was no known history of maternal drug addiction. The drug abused in all cases was heroin. Human immunodeficiency virus (HIV) screening was done only in a minority (21%) of the mothers and it was negative in all. Eighteen (47%) infants had evidence of neonatal abstinence syndrome with neurological manifestations being the commonest. Urine toxicology screening was positive in 26% of cases and had only 70% sensitivity and 41% positive predictive value. On follow up, default rate was high with 42% babies not attending follow up at the outpatient clinic. In conclusion, there is a need to maintain a high index of suspicion of substance abuse in those with high-risk maternal profile and their neonates should be closely watched for features of neonatal abstinence syndrome. Alternative methods of toxicology screening apart from urine need to be evaluated in order to improve the drug detection rate.

Adolescent↗
PubMed1998

Group B Streptococcal septicaemia/meningitis in neonates in a Singapore teaching hospital.

Our aims were to establish the incidence and clinical characteristics of early and late onset Group B Streptococcal (GBS) septicaemia in neonates in our hospital over a period of 1 year. Routine screening for maternal GBS was not standard practice in the hospital. GBS was isolated from high vaginal swabs (HVS) obtained antenatally or postnatally for risk factors as determined by the obstetrician or neonatologist in charge. Data obtained were analyzed separately and these did not form part of the study. By a system of clinical case review and follow-up, mail, telephone and home visits, the outcome of all 15,062 livebirths in the hospital over a 1-year period were verified and reported. Our results show a low incidence of GBS infection in neonates in the hospital: early onset disease was 0.265 per 1,000 livebirths and late onset a quarter of that. The majority of our cases of early onset GBS disease were in premature infants. Because of our low incidence, prophylaxis schedules would have to ensure an acceptably smaller number of mothers exposed to antibiotics over and above the current level and the cooperation of our obstetricians. We have devised a schedule incorporating a current PROM (prelabour premature rupture of membranes) protocol which would result in only an additional 2.2% of mothers requiring prophylactic antibiotics.

Age of Onset↗
PubMedDate not supplied

Substructure-based support vector machine classifiers for prediction of adverse effects in diverse classes of drugs.

Unforeseen adverse effects exhibited by drugs contribute heavily to late-phase failure and even withdrawal of marketed drugs. Torsade de pointes (TdP) is one such important adverse effect, which causes cardiac arrhythmia and, in some cases, sudden death, making it crucial for potential drugs to be screened for torsadogenicity. The need to tap the power of computational approaches for the prediction of adverse effects such as TdP is increasingly becoming evident. The availability of screening data including those in organized databases greatly facilitates exploration of newer computational approaches. In this paper, we report the development of a prediction method based on a support machine vector algorithm. The method uses a combination of descriptors, encoding both the type of toxicophore as well as the position of the toxicophore in the drug molecule, thus considering both the pharmacophore and the three-dimensional shape information of the molecule. For delineating toxicophores, a novel pattern-recognition method that utilizes substructures within a molecule has been developed. The results obtained using the hybrid approach have been compared with those available in the literature for the same data set. An improvement in prediction accuracy is clearly seen, with the accuracy reaching up to 97% in predicting compounds that can cause TdP and 90% for predicting compounds that do not cause TdP. The generic nature of the method has been demonstrated with four data sets available for carcinogenicity, where prediction accuracies were significantly higher, with a best receiver operating characteristics (ROC) value of 0.81 as against a best ROC value of 0.7 reported in the literature for the same data set. Thus, the method holds promise for wide applicability in toxicity prediction.

Algorithms↗