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Pētījuma mērķis bija novērtēt Engures ekoreģiona (Rīgas līča rietumu piekrastes) sedimentu kvalitāti, izmantojot sedimentu ekotoksicitātes testus. Lai noteiktu bioloģiskās atbildes reakcijas uz dažāda veida stresoriem, kā testorganismi pielietotas sānpeldes Monoporeia affinis and Pontogammarus robustoides, un izvēlēti biomarķieri (AChE, GST, GR, CAT, MT), kas noteikti gliemenēs Macoma balthica. Engures ekoreģionu varētu uzskatīt par nepiesārņotu rajonu, jo tā sedimentus raksturo salīdzinoši zemas smago metālu koncentrācijas. Engures ekoreģiona sedimentu ekotoksicitātes testu rezultāti neuzrādīja statistiski būtisku (>20% mirstība) toksisko efektu. Testorganismu izdzīvotība bija robežās no 83 līdz 100% un norādīja uz labu testēto sedimentu kvalitāti. Biomarķieru atbildes reakcijas neuzrādīja būtiskas atšķirības starp stacijām un gadiem. Lai gan integrētais biomarķieru indekss uzrādīja lielāku gliemeņu M. balhtica stresu Mērsraga stacijā, biomarķiera MT aktivitāte liecināja par smago metālu paaugstinātu piesārņojumu Engures stacijā. Kopumā smago metālu koncentrācijas, ekotoksicitātes testu un biomarķieru aktivitātes rezultāti norāda, ka Engures ekoreģiona sedimentu kvalitāte ir samērā homogēna un nav pakļauta būtiskai antropogēnai ietekmei.

Exhaled Air Analysis in Patients with Different Lung Diseases Using Artificial Odour Sensors Sniffing breath to diagnose a disease has been practiced by doctors since ancient times. Nowadays, electronic noses are successfully used in the food, textile and perfume industry as well as for air pollution control. The aim of this study was to test whether exhaled breath analysed by an artificial nose could identify and discriminate between different lung diseases. A total of 76 individuals were tested: 25 bronchial asthma, 19 lung cancer, 10 pneumonia, 6 chronic obstructive pulmonary disease (COPD) patients and 16 healthy volunteers. Exhaled air was collected in plastic bags and immediately analysed using an electronic nose instrument (9185, Nordic Sensors AB) containing 14 different odour sensors. Multifactor logistic regression analysis was used to determine correlation between the amplitudes of sensor responses and the clinical diagnoses of patients and to calculate sensitivity and specificity of the method for each diagnosis. For diagnostics of asthma the sensitivity was found to be 84% and specificity — 86%. For lung cancer, the sensitivity was 74% and specificity, 95%; for pneumonia 90% and 98%, but for COPD, 33% and 97%, respectively. We conclude that an artificial nose is able to discriminate among different lung diseases with sufficiently good accuracy. This method may be further developed to implement it in clinical medicine for express diagnostics of acute and chronic lung diseases.

First Detection of Vancomycin Resistant Enterococcus faecium in Latvia Enterococci have become one of the most important nosocomial pathogens in advanced treatment facilities. Though they are not considered as very pathogenic bacteria, their high levels of antimicrobial resistance are the subject of major concern. Particularly epidemiologically important are vancomycin-resistant enterococci (VRE) due to high risk of transmission of vancomycin resistance genes to staphylococci. We describe the first outbreak of VRE in a Latvian multidisciplinary hospital.