The use of antibiotics may accelerate the development of antibiotic resistance genes (ARGs) and bacteria which shade health risks to humans and animals. The emerging of ARGs in the water environment is becoming an increasing worldwide concern. Hundreds of various ARGs encoding resistance to a broad range of antibiotics have been found in microorganisms distributed not only in hospital wastewaters and animal production wastewaters, but also in sewage, wastewater treatment plants, surface water, groundwater, and even in drinking water. This review summarizes recently published information on the types, distributions, and horizontal transfer of ARGs in various aquatic environments, as well as the molecular methods used to detect environmental ARGs, including specific and multiplex PCR (polymerase chain reaction), real-time PCR, DNA sequencing, and hybridization based techniques.

Antibiotic resistance genes in water environment.

OP/nerve agents are still considered as important chemicals acting on living organisms and are widely used. They are characterized according to their action as compounds influencing cholinergic nerve transmission via inhibition of AChE. Modeling of this action and extrapolation of experimental data from animals to humans is more possible for highly toxic agents than for the OP. The symptoms of intoxication comprise nicotinic, muscarinic, and central symptoms; for some OP/nerve agents, a delayed neurotoxicity is observed. Cholinesterases (AChE and BuChE) are characterized as the main enzymes involved in the toxic effect of these compounds, including molecular forms. The activity of both enzymes (and molecular forms) is influenced by inhibitors (reversible, irreversible, and allosteric) and other factors, such as pathological states. There are different methods for cholinesterase determination; however, the most frequent is the method based on the hydrolysis of thiocholine esters and subsequent detection of free SH-group of the released thiocholine. The diagnosis of OP/nerve agent poisoning is based on anamnesis, the clinical status of the intoxicated organism, and on cholinesterase determination in the blood. For nerve agent intoxication, AChE in the red blood cell is more diagnostically important than BuChE activity in the plasma. This enzyme is a good diagnostic marker for intoxication with OP pesticides. Some other biochemical examinations are recommended, especially arterial blood gas, blood pH, minerals, and some other specialized parameters usually not available in all clinical laboratories. These special examinations are important for prognosis of the intoxication, for effective treatment, and for retrospective analysis of the agent used for exposure. Some principles of prophylaxis against OP/nerve agent poisoning comprising the administration of reversible cholinesterase inhibitors such as pyridostigmine (alone or in combination with other drugs), scavengers such as preparations of cholinesterases, some therapeutic drugs, and possible combinations are given. Basic principles of the treatment of nerve agent OP poisoning are described. They are based on the administration of anticholinergics (mostly atropine but some other anticholinergics can be recommended) as a symptomatic treatment, cholinesterase reactivators as a causal treatment (different types but without a universal reactivator against all OP/nerve agents) as the first aid and medical treatment, and anticonvulsants, preferably diazepam though some other effective benzodiazepines are available. New drugs for the treatment are under experimental study based on new approaches to the mechanism of action. Future trends in the complex research of these compounds, which is important not only for the treatment of intoxication but also for the quantitative and qualitative increase of our knowledge of toxicology, neurochemistry, neuropharmacology, clinical biochemistry, and analytical chemistry in general, are characterized.

Organophosphates⧸Nerve Agent Poisoning: Mechanism of Action, Diagnosis, Prophylaxis, And Treatment

Summary: Blastocystis is an unusual enteric protozoan parasite of humans and many animals. It has a worldwide distribution and is often the most commonly isolated organism in parasitological surveys. The parasite has been described since the early 1900s, but only in the last decade or so have there been significant advances in our understanding of Blastocystis biology. However, the pleomorphic nature of the parasite and the lack of standardization in techniques have led to confusion and, in some cases, misinterpretation of data. This has hindered laboratory diagnosis and efforts to understand its mode of reproduction, life cycle, prevalence, and pathogenesis. Accumulating epidemiological, in vivo, and in vitro data strongly suggest that Blastocystis is a pathogen. Many genotypes exist in nature, and recent observations indicate that humans are, in reality, hosts to numerous zoonotic genotypes. Such genetic diversity has led to a suggestion that previously conflicting observations on the pathogenesis of Blastocystis are due to pathogenic and nonpathogenic genotypes. Recent epidemiological, animal infection, and in vitro host-Blastocystis interaction studies suggest that this may indeed be the case. This review focuses on such recent advances and also provides updates on laboratory and clinical aspects of Blastocystis spp.

New insights on classification, identification, and clinical relevance of Blastocystis spp.

The oral health surveys basic methods that we provide for you will be ultimate to give preference. This reading book is your chosen book to accompany you when in your free time, in your lonely. This kind of book can help you to heal the lonely and get or add the inspirations to be more inoperative. Yeah, book as the widow of the world can be very inspiring manners. As here, this book is also created by an inspiring author that can make influences of you to do more.

Oral Health Surveys: Basic Methods

Chemical composition and antimicrobial activity of the essential oils of Chrysanthemum indicum

Akarsu kopruleri buyuk taskinlar esnasinda genellikle hasar gormekte veya yikilmaktadir. Hasar nedenleri genellikle taban seviyesi alcalmasi ve kopru acikligindaki yerel oyulmalara baglanmistir. Bu konu son yillarda arastirmacilarin yogun ilgisine sahip olmakla birlikte henuz istenilen asamaya ulasilamamis ve evrensel bir yontem gelistirilememistir. Kontrol edilebilir laboratuar kosullarinda akarsu ve kopru ayaklari konularinda elde edilecek veriler, uygulamada karsilasilan sorunlarin cozumu, hidrolik etkenlerin konu uzerindeki etkisinin anlasilabilmesi icin yaygin olarak kullanilmaktadir. Son yillarda, hesaplamali akiskanlar dinamigi esaslarina dayanan sayisal modeller bu gibi problemlerin cozumunde ve bu verilerin degerlendirilmesinde alternatif araclar olmaktadirlar. Bu calismada, dikdortgen, silindir ve trapez geometriye sahip kopru kenar ayagi civarindaki hiz dagilimini incelemek icin FLOW- 3D bilgisayar programi vasitasiyla 3 boyutlu sayisal modelleme yapilmistir. Modelleme sonucu bulunan sayisal sonuclar daha once yapilmis deneysel sonuclarla karsilastirilmistir.

/pdf/farkli-geometrilerdeki-kopru-kenar-ayaklari-etrafindaki-hiz-2b4s17augv.pdf

Farklı geometrilerdeki köprü kenar ayakları etrafındaki hız dağılımının sayısal incelenmesi

Water resources managers can benefit from accurate prediction of the availability of groundwater. Ground water is a major source of water in Turkey for irrigation, water supply and industrial uses. The ground water level fluctuations depend on several factors such as rainfall, temperature, pumping etc.  In this study, Hatay Amik Plain, Kumlu region was evaluated using Autoregressive (AR) and Support Vektor Machines (SVMs) methods.  The monthly groundwater level was used the previous years data belonging to the Kumlu region. DOI: https://doi.org/10.3846/enviro.2017.093

/pdf/groundwater-level-prediction-using-support-vektor-machines-3zikgthpm9.pdf

Groundwater Level Prediction Using Support Vektor Machines and Autoregressive (AR) Modelss

Evapotranspiration is an important parameter to be considered in hydrology. In the design of water structures, accurate estimation of the amount of evapotranspiration allows for safer designs. Thus, maximum efficiency can be obtained from the structure. In order to accurately estimate evapotranspiration, the parameters affecting evapotranspiration should be well known. There are many factors that affect evapotranspiration. Some of these can be listed as temperature, humidity in the atmosphere, wind speed, pressure and water depth. In this study, models were created for the estimation of the daily evapotranspiration amount by using the simple membership functions and fuzzy rules generation technique (fuzzy-SMRGT), multivariate regression (MR), artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS) and support vector regression (SMOReg) methods. Model results were compared with each other and traditional regression calculations. The ET amount was calculated empirically using the Penman-Monteith (PM) method which was taken as a reference equation. In the created models, daily air temperature (T), wind speed (WS), solar radiation (SR), relative humidity (H) and evapotranspiration (ET) data were obtained from the station near Lake Lewisville (Texas, USA). The coefficient of determination (R2), root mean square error (RMSE) and average percentage error (APE) were used to compare the model results. According to the performance criteria, the best model was obtained by Q-MR (quadratic-MR), ANFIS and ANN methods. The R2, RMSE, APE values of the best models were 0,991, 0,213, 18,881% for Q-MR; 0,996; 0,103; 4,340% for ANFIS and 0,998; 0,075; 3,361% for ANN, respectively. The Q-MR, ANFIS and ANN models had slightly better performance than the MLR, P-MR and SMOReg models.

A comparative study on daily evapotranspiration estimation by using various artificial intelligence techniques and traditional regression calculations.

Introduction: Aims: HPV-DNA testing is widely used throughout the world and today is an important part of cervical cancer screening programs. In this study, it was aimed the investigation of the presence and typing of HPV-DNA by using real time polyme- rase chain reaction (PCR) in the cervical samples of women with risk factors in terms of HPV and the evaluation of compliance of identified HPV types with results of cervical smear. Methods: HPV-DNA results were analyzed between January 2009 and December 2012 retrospectively. Results: HPV-DNA detection rate was 48% at the cervical samples. The positive samples were described HPV-16 in 26.5%, HPV-18 in 5.5%, non-HPV-16-18 (HPV-31, HPV-35, HPV-59) in 40%, potential HR-HPV (HPV-66) in 1.5% and LR-HPV (HPV-6, HPV-11) in 27.5%. In the cytological examination, %15 (n: 54) samples were evaluated as positive for intraepithelial lesion. These was determined as ASCUS (Atypical Squamous Cells of Undetermined Significance) in 18% (n: 10), LSIL (Low-grade Intraepithelial Lesion) in 50% (n: 27), HSIL (High-grade intraepithelial lesion) in 30% (n: 16), squamous cell carcinoma in 2% samples. In the samples that intraepitelyal lesion was positive but undetermined HPV-DNA, 5 samples were identified as ASCUS and 13 samples were LSIL. Cytological abnormality was found in the 23.4% of 128 detected samples to HR-HPV and potential HR-HPV; in 12.2% of 49 detected samples to LR-HPV and in 9.3% of 194 undetected samples to HPV-DNA. In the samples with cytological abnormality, HPV types were listed HPV-16, non-HPV 16-18, LR-HPV, HPV-18 and potential HR-HPV, respectively, in the samples that cytologi- cal abnormality was not found, HPV types were non-HPV-16-18, LR-HPV, HPV-16, HPV-18 and potential HR-HPV. Coclusion: Non-HPV-16-18 were monitored as the most common type and HPV-16 was third of frequency in cytological abnormality negative group; non-HPV-16-18 and HPV-16 were monitored close proportions of each other in cytological abnormality positive group. These isolates were accompany to preinvasive lesions.

Mustafa Demirci

Papers

Farklı geometrilerdeki köprü kenar ayakları etrafındaki hız dağılımının sayısal incelenmesi

Groundwater Level Prediction Using Support Vektor Machines and Autoregressive (AR) Modelss

A comparative study on daily evapotranspiration estimation by using various artificial intelligence techniques and traditional regression calculations.

The investigation and typing of human papillomavirus by molecular microbo- logical method and evaluation of cytological results in cervical smears

Coupling of stabilized total Lagrangian and weakly compressible SPH models for challenging fluid–elastic structure interaction problems