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.

Isolation and identification of nontuberculous mycobacteria from hospitalized patients and drinking water samples--examination of their correlation by chemometrics.

Nontuberculous mycobacteria (NTM) have been found to be widely dispersed in the environment and are being considered potentially pathogenic for humans and animals, while reports of their human to human transmission are absent. Water and aerosols are potential transmission modes of NTM to humans. Hospitalized patients with NTM infections were studied together with drinking water samples from their respective residence areas during 2003-2013. Cluster analysis and factor analysis were used to analyze the data matrix. A total of 367 hospitalized patients living in 30 localities in the Prefecture of Larissa were tested positive for NTM. The most frequently isolated NTM species of the 383 NTM isolates from the clinical specimens were Mycobacterium fortuitum (n = 118, 30.8 %), M. gordonae (n = 87, 22.7 %), M. peregrinum (n = 46, 12.0 %), M. chelonae (n = 11, 2.9 %), M. avium (n = 8, 2.1 %), and M. intracellulare (n = 7, 1.8 %), while 88 (23.0 %) of these isolates were not identified. It is noted that in 8 patients, M. tuberculosis was isolated simultaneously with one NTM, in 15 patients, together with two types of NTM, while in 1 patient, it was found at the same time as three different NTM. In addition, 3360 drinking water samples were collected from 30 localities and analyzed during 2010 to 2013; they were found 11.2 % NTM positive. Cluster analysis and factor analysis results confirm that NTM strains are correlated to each other in both isolated samples from patients and drinking water, while the strength of their correlation varied from weak to moderate (e.g., factor loadings ranged from 0.69 to 0.74 when all data are considered). These results provide indications that drinking water could be linked with NTM cases in humans.

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.

Application of multivariate statistical methods for groundwater physicochemical and biological quality assessment in the context of public health.

Three representative areas (lowland, semi-mountainous, and coastal) have been selected for the collection of drinking water samples, and a total number of 28 physical, chemical, and biological parameters per water sample have been determined and analyzed. The mean values of the physical and chemical parameters were found to be within the limits mentioned in the 98/83/EEC directive. The analysis of biological parameters shows that many of the water samples are inadequate for human consumption because of the presence of bacteria. Cluster analysis (CA) first was used to classify sample sites with similar properties and results in three groups of sites; discriminant analysis (DA) was used to construct the best discriminant functions to confirm the clusters determined by CA and evaluate the spatial variations in water quality. The standard mode discriminant functions, using 17 parameters, yielded classification matrix correctly assigning 96.97% of the cases. In the stepwise mode, the DA produced a classification matrix with 96.36% correct assignments using only ten parameters (EC, Cl-, NO3-, HCO3-, CO3(-2), Ca+2, Na+, Zn, Mn, and Pb). CA and factor analysis (FA) are used to characterize water quality and assist in water quality monitoring planning. CA proved that two major groups of similarity (six subclusters) between 17 physicochemical parameters are formed, and FA extracts six factors that account for 66.478% of the total water quality variation, when all samples' physicochemical data set is considered. It is noteworthy that the classification scheme obtained by CA is completely confirmed by principal component analysis.

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.

Application of chemometric methods for assessment and modelling of microbiological quality data concerning coastal bathing water in Greece.

BACKGROUND: Worldwide, the aim of managing water is to safeguard human health whilst maintaining sustainable aquatic and associated terrestrial, ecosystems. Because human enteric viruses are the most likely pathogens responsible for waterborne diseases from recreational water use, but detection methods are complex and costly for routine monitoring, it is of great interest to determine the quality of coastal bathing water with a minimum cost and maximum safety. DESIGN AND METHODS: This study handles the assessment and modelling of the microbiological quality data of 2149 seawater bathing areas in Greece over 10-year period (1997-2006) by chemometric methods. RESULTS: Cluster analysis results indicated that the studied bathing beaches are classified in accordance with the seasonality in three groups. Factor analysis was applied to investigate possible determining factors in the groups resulted from the cluster analysis, and also two new parameters were created in each group; VF1 includes E. coli, faecal coliforms and total coliforms and VF2 includes faecal streptococci/enterococci. By applying the cluster analysis in each seasonal group, three new groups of coasts were generated, group A (ultraclean), group B (clean) and group C (contaminated). CONCLUSIONS: The above analysis is confirmed by the application of discriminant analysis, and proves that chemometric methods are useful tools for assessment and modeling microbiological quality data of coastal bathing water on a large scale, and thus could attribute to effective and economical monitoring of the quality of coastal bathing water in a country with a big number of bathing coasts, like Greece. Significance for public healthThe microbiological protection of coastal bathing water quality is of great interest for the public health authorities as well as for the economy. The present study proves that this protection can be achieved by monitoring only two microbiological parameters, E. coli and faecal streptococci/enterococci instead four microbiological parameters (the two mentioned above plus Total coliforms and Faecal coliforms) that are usually monitored today. As a consequence, countries, especially those with large quantities of coastal bathing sites, can perform microbiological monitoring of their bathing waters by checking only the mentioned two parameters, thus ensuring economies of scale. Thus, funds can be used in other actions to preserve the quality of coastal water and human health. This in turn, would aid in the assessment of the quality of coastal bathing waters and provide a more timely indication of bathing water quality, hence contributing to the immediate health protection of bathers.

The prevalence of obstructive sleep apnea-hypopnea syndrome-related symptoms and their relation to airflow limitation in an elderly population receiving home care.

BACKGROUND: Both airflow limitation and obstructive sleep apnea-hypopnea syndrome (OSAHS)-related symptoms are most prevalent in the elderly population. Previous studies revealed significant associations between OSAHS-related symptoms and obstructive airway diseases in the general population. However, other studies showed that the frequency of OSAHS-related symptoms in patients with obstructive airway diseases decreases after the age of 60 and older. AIMS: To investigate the prevalence of OSAHS-related symptoms (snoring, breathing pauses, and excessive daytime sleepiness [EDS]) and their relations to airflow limitation, for people over 65 years old. METHODS: A full screening spirometry program was performed in a total of 490 aging participants (mean age 77.5 years - range 65-98) who were attending 16 home care settings in central Greece. Airflow limitation was assessed according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) spirometric criteria (FEV1/FVC <70%). The Berlin Questionnaire and the Epworth Sleepiness Scale were used to screen individuals for OSAHS-related symptoms. Bivariate associations were described using odds ratio (OR) with 95% confidence intervals (CI). RESULTS: Airflow limitation prevalence was 17.1% (male 24.2% and female 9.9%) and was strongly related to male gender and smoking status. The prevalence rates of frequent snoring, breathing pauses, and EDS were 28.1%, 12.9%, and 11.6%, respectively. However, participants with airflow limitation were less likely to report breathing pauses, frequent snoring, EDS, and obesity. Finally, frequent snoring was significantly more common in males than females. CONCLUSION: This study revealed decreased frequency of OSAHS-related symptoms in participants with airflow limitation suggesting that OSAHS-related symptoms and airflow limitation are not related in our elderly population.