Assessment of Groundwater Quality by Chemometrics.

Chemometric methods were used to analyze large data sets of groundwater quality from 18 wells supplying the central drinking water system of Larissa city (Greece) during the period 2001 to 2007 (8.064 observations) to determine temporal and spatial variations in groundwater quality and to identify pollution sources. Cluster analysis grouped each year into three temporal periods (January-April (first), May-August (second) and September-December (third). Furthermore, spatial cluster analysis was conducted for each period and for all samples, and grouped the 28 monitoring Units HJI (HJI=represent the observations of the monitoring site H, the J-year and the period I) into three groups (A, B and C). Discriminant Analysis used only 16 from the 24 parameters to correctly assign 97.3% of the cases. In addition, Factor Analysis identified 7, 9 and 8 latent factors for groups A, B and C, respectively.

Assessment and modeling of routinely used biochemical laboratory data of healthy individuals and end-stage renal failure (ESRF) patients by three different chemometric methods.

BACKGROUND: In recent years, the use of biochemical markers has received increasing attention for purposes of risk assessment and clinical management in renal failure patients. Chemometric methods are often used in medical studies and there are already indications for their specific role as a tool of the medical statistics. METHODS: Three chemometric methods, discriminant analysis (DA), binary logistic regression analysis (BLRA), and cluster analysis (CA), were used for assessment and modeling of routinely used biochemical laboratory data of 18 parameters that were determined from 185 healthy individuals (HIs) and 173 end-stage renal failure (ESRF) patients. RESULTS: The above-mentioned chemometric methods were performed using the data set of 14 parameters since the rest 4 parameters did not present significant difference between healthy and patients. DA created a model using only ALB (Albumin), K (Potassium), TG (Triglyceride), and ALP (Alkaline phosphatase); BLRA model also used the above four parameters; CA classified all the cases into two clusters using the same four parameters and one more parameter, AST (aspartate aminotransferase). CONCLUSIONS: This study provides models for assessment and modeling of routinely used biochemical laboratory data, finding groups of similarity among clinical tests usually determined on HIs and ESRF patients, contributing in data mining and reducing costs.

PCR-SSCP: a method for the molecular analysis of genetic diseases.

Single strand conformation polymorphism (SSCP) is a reproducible, rapid and quite simple method for the detection of deletions/insertions/rearrangements in polymerase chain reaction amplified DNA. All the details for the use of PCR-SSCP are presented in the direction of genetic diseases (beta-thalassaemia, cystic fibrosis), optimum gel conditions, sensitivity and the latest modifications of the method, which are applied in most laboratories. This non-radioactive PCR-SSCP method can be reliably used to identify mutations in patients (beta-globin, CFTR), provided suitable controls are available. Moreover, it is widely used for mutation identification in carriers (beta-thalassaemia, cystic fibrosis), making it particularly useful in population screening.