Evaluation of the Triglyceride Glucose Index as a Marker of Insulin Resistance in Adults with Isolated Impaired Glucose Tolerance

Purpose: By analyzing long-term laboratory data, we aim to evaluate the relationship between the TyG and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) in the adult population with isolated impaired fasting glucose (IFG), and also to determine the cut off value of The triglyceride (TG) to glucose index (TyG) to estimate the IR in our population. Materials and Methods: In this study, data were evaluated retrospectively from medical records. Fasting glucose, lipid panel [Total cholesterol, TG, High-density lipoprotein (HDL), Low-density lipoprotein (LDL)] and insulin levels were analyzed with commercially reagents. (Roche Cobas C701, Roche Diagnostic, Germany). High-Performance Liquid Chromatography (HPLC) method was used for hemoglobin A1c (HbA1c) (Lifotronic H9, Lifotrophic Technology, China). TyG, HOMA-IR, and TG/HDLcholesterol were calculated. IR was defined as HOMA-IR ≥2.5. Results: A total of 440 subject, (controls: 230 and IFG:210), were included in our study. The average age of the subjects was 42.5±12.0 years and 44.7±10.7 years for IFG and control, respectively. Glucose, total cholesterol, TG, LDL-cholesterol, insulin, HbA1c, TG/HDL-cholesterol, HOMA-IR, and TyG were significantly higher in the IFG group (p<0.001). There was a weak but significant correlation between HOMA-IR and the TyG (r=0.210, p=0.009). In the ROC analysis, the AUC for HOMA-IR and the TyG, respectively was 0.867 (95% CI, 0.833-0.900, p<0.001) and 0.708 (95% CI, 0.659-0.758, p<0.001). Conclusions: In our study, the TyG is proposed as a relatively accurate, simple, easily accessible, and low-cost marker for IR evaluation with IFG patients. However, population-based studies with higher patient participation are needed for future studies

Pseudo-Supervised Defect Detection Using Robust Deep Convolutional Autoencoders

Robust Autoencoders separate the input image into a Signal(L) and a Noise(S) part which, intuitively speaking, roughly corresponds to a more stable background scene (L) and an undesired anomaly (or defect) (S). This property of the method provides a convenient theoretical basis for divorcing intermittent anomalies that happen to clutter a relatively consistent background image. In this paper, we illustrate the use of Robust Deep Convolutional Autoencoders (RDCAE) for defect detection, via a pseudo-supervised training process. Our method introduces synthetic simulated defects (or structured noise) to the training process, that alleviates the scarcity of true (real-life) anomalous samples. As such, we offer a pseudo-supervised training process to devise a well-defined mechanism for deciding that the defect-normal discrimination capability of the autoencoders has reached to an acceptable point at training time. The experiment results illustrate that pseudo supervised Robust Deep Convolutional Autoencoders are very effective in identifying surface defects in an efficient way, compared to state of the art anomaly detection methods

Serum neuron specific enolase and S-100B levels in hemodialysis and peritoneal dialysis patients

Objective: Neuron-specific enolase (NSE) and S-100B are brain-derived proteins, and their levels increase in brain injury. The aim of the study was to determine serum S-100B and NSE levels in patients with end-stage renal disease undergoing hemodialysis (HD) and peritoneal dialysis (PD) and to demonsrate how these levels were affected by the type of dialysis applied. Methods: The study group consisted of age- and gender-matched 20 patients undergoing HD, 26 patients undergoing continuous ambulatory PD (CAPD) and 21 healthy controls. Blood samples were obtained before and after dialysis in the HD patient group, and fasting blood samples were obtained in the CAPD and control groups. The routine biochemical parameters were measured within two hours from all serum samples. The remaining serum samples were stored at -80 °C until the day of analysis of the S-100B and NSE assays. Serum S-100B and NSE levels were measured by chemiluminescence immunoassay method. Routine biochemistry tests were measured by colorimetric method using a biochemistry analyzer. Results: Serum S-100B (0.11±0.06 ng/mL in HD, 0.13±0.09 ng/mL in CAPD and 0.05±0.03 ng/mL in controls) and NSE (12.7±5.99 ng/mL in HD, 9.26±5.52 ng/mL in CAPD and 6.82±2.36 ng/mL in controls) levels were higher in HD and CAPD groups compared to controls. S-100B and NSE levels were higher after HD compared to before HD (p<0.001). There was a weak but significant correlation between S-100B and NSE levels (r=0.290; p=0.006). Conclusion: In this study, serum S-100B and NSE levels were found to be high in patients undergoing HD and PD. Serum S-100B and NSE concentrations were higher in HD and CAPD patients. Increased S-100B and NSE levels may be associated with cerebrovascular events in patients with chronic renal failure. They may also be important markers for the determination of cerebrovascular events

The effect of education and 4-year experience in the evaluation of preanalytical process in a clinical chemistry laboratory

Preanalytical errors have an important ratios in all laboratory processes. To reduce laboratory errors, the IFCC working group on Laboratory Errors and Patient safety (WG-LEPS) developed laboratory quality indicators (QIs) for the preanalytical process. The purpose of this study is to evaluate QIs of the preanalytical process over a 4-year period and show the effect of education. In this study, Balikesir State Hospital biochemistry laboratory were retrospectively evaluated as rejected sample for four years (between 1st of January 2014 31st of December 2017). We examined QIs for preanalytical processes such as; misidentification errors (QIs-5), unintelligible test requests (QIs-6), lost-not received samples (QIs-7), incorrect container/tube (QIs-9), samples hemolyzed (QIs-10), sample clotted (QIs-11), insufficient sample volume (QIs-12), incorrect sample type (QIs-13, unsuitable transportation (QIs-14) and improperly labeled tube (QIs-15). In our hospital, regular training is given to hospital staff and laboratory staff at least twice a year for sample taking, specimen storage and transfer training, as well as laboratory staff, laboratory processes and management of improperly sample. In our study, the preanalytical process error frequency was 0.64%, 0.63%, 0.58% and 0.76% for all years respectively. It is seen that the most frequent error frequency is clotted sample (0.31, 0.32, 0.28 and 0.27 respectively). Other the most common errors was insufficient sample and incorrect container/tube (0.18, 0.15, 0.12, 0.07 and 0.18, 0.07, 0.07, 0.03, respectively). Our results were well below the optimum values recommended by IFFC-WG-LEPS. In order to achieve all these desired goals for QI, the training process must be sustainable and standardized and repeated at appropriate intervals. [Med-Science 2018; 7(4.000): 905-9

Hepatosellüler Karsinom (Hsk) Tedavisinde Kullanılmak Üzere Manyetik Alana Duyarlı ve Etken Madde İçeren Aljinat Bazlı Mikrokürelerin Geliştirilmesi ve Karakterize Edilmesi

Today, cancer is the foremost common and deadly disease in the world. One of the most important cancer types is liver cancer and occurs either by being directly involved with liver cells resulting in primary liver cancers, or by the metastasis of other cancer cells originating from different organs and reaching the liver second-hand, thus resulting in secondary liver cancer. Among the liver cancer types, especially in the primary liver cancers, the cancer type named hepatocellular carcinoma (HCC) plays the largest part and is considered to be a global health problem worldwide. Whether for the new HCC cases occurring every year or for the fact that it makes up a considerable part of diseases resulting in death, HCC has currently been divided into three fundamental stages: early, middle, and advanced. While surgical intervention or ablation can have a high success rate when treating HCC in its early stage, for patients at the middle stage transarterial characterization and chemoembolization (TACE) procedures provide both a better success in treatment and a prolonged life regiment. Within the scope of the presented thesis, a chemoembolization agent, containing a new generation drug and imaging agent used in TACE applications, is to be developed which can be visualised using a magnetic resonance imaging (MRI) machine. For this purpose, the development and evaluation of microspheres in clinical applications carried out by in vitro tests, especially of alginate based polymer structures combined with appropriate antineoplastic agents (such as Sorafenib) is the aim of this project. Additionally, super paramagnetic iron oxide nanoparticles (SPIONs), which were synthesized for the purpose of MRI imaging and therefore tracking the microspheres during the treatment process, were tested for their potential in use during treatment via hyperthermia.Kanser hastalıkları günümüzde tüm dünya genelinde en yaygın ve en ölümcül hastalıkların başında gelmektedir. Kanser hastalıklarının en önemli gruplarından birini de karaciğer kanserleri oluşturmaktadır. Karaciğer kanserleri ya doğrudan karaciğer hücreleri aracılığı ile primer karaciğer kanserleri olarak meydana gelmekte ya da diğer organlarda başlayan kanser oluşumlarının metastaz yaparak karaciğer sekonder olarak ulaşmasıyla karaciğer kanserine dönüşmektedirler. Karaciğer kanserleri arasında özellikle primer kanserlerde hepatosellüler karsinom (HSK) adı verilen (Hepatocellular Carcinom, HCC) kanser türü en büyük paya sahip olan kanser grubudur ve halihazırda tüm dünya genelinde, global bir sağlık sorunu olarak değerlendirilmektedir. Gerek her yıl görülen yeni vaka olarak ve gerekse ölüme sebep olan hastalıklar arasında oldukça önemli yer tutan HSK temel başlangıç, orta ve ileri evre şeklinde kabaca gruplandırılabilen üç temel evreye sahiptir. Başlangıç evresinde cerrahi müdahale ve ablasyon gibi tedavilerde yüksek oranda başarı elde edilirken orta evrede yer alan hastalarda transarteriyel katerizasyon ile kemoembolizasyon (TAKE) (transarterial chemoembolization, TACE) uygulamaları gerek başarılı tedavi ve gerekse yaşam süresini uzatmaya yönelik tedavi rejimlerini oluşturmaktadır. Sunulan tez kapsamında TAKE uygulamalarında kullanılan yeni nesil ilaç ve görüntüleme ajanı taşıyan manyetik rezonas (MR) görüntüleme ile yönlendirilebilen kemoembolizasyon ajanı geliştirilmesi planlanmaktadır. Bu amaçla özellikle aljinat bazlı polimer yapıları ile uygun antineoplastik ajanları (Sorafenib gibi) ile kombine tedavilerde kullanılabilecek mikrokürelerin geliştirilmesi ve in vitro testleri yapılarak klinik uygulamalara hazırlık şeklinde değerlendirmelerin yapılması hedflenmiştir. Ek olarak, MRI görüntüleme potansiyeli bulunan ve böylece tedavi sürecinde mikroküreleri takip edebilecek süper paramanyetik demir oksit nanoparçacıkları (SPION'lar), hipertermi yoluyla tedavi sırasında kullanım potansiyelleri açısından test edildi

Data extraction from CAD model for rotational parts to be machined at turning centres

Among the most important data produced and stored is product data. CAD data forms one of many contributors to product data. Although in most circumstances CAD data can be processed within the CIM environment by integrated software components to produce information like manufacturing data, assembly data, etc., there are a significant number of cases where an external CAD resource needs to be processed. An external CAD resource comes in the form of a neutral file format such as DXF, IGES, STEP, etc. Extracting the necessary information from an exchange file to generate manufacturing parameters thus becomes an important task. In this paper we present the results of our research efforts which were intended to extract information from the defacto industry standard DXF files to determine features existing on rotational parts to be machined on turning centres, and later utilise this information in the context of a software package implemented to develop a post-processing expert system. The feature extraction module presented in this paper, forms part of that expert system, which is named ASALUS (Aslan, 1995) and is illustrated in Figure 1. ASALUS is designed to manage the life cycle of rotational parts from the design all the way to the production by performing process planning using a generative approach and applying post-processing for two different CNC lathes.Among the most important data produced and stored is product data. CAD data forms one of many contributors to product data. Although in most circumstances CAD data can be processed within the CIM environment by integrated software components to produce information like manufacturing data, assembly data, etc., there are a significant number of cases where an external CAD resource needs to be processed. An external CAD resource comes in the form of a neutral file format such as DXF, IGES, STEP, etc. Extracting the necessary information from an exchange file to generate manufacturing parameters thus becomes an important task. In this paper we present the results of our research efforts which were intended to extract information from the defacto industry standard DXF files to determine features existing on rotational parts to be machined on turning centres, and later utilize this information in the context of a software package implemented to develop a post-processing expert system. The feature extraction module presented in this paper, forms part of that expert system, which is named ASALUS (Aslan, 1995) and is illustrated in Figure 1. ASALUS is designed to manage the life cycle of rotational parts from the design all the way to the production by performing process planning using a generative approach and applying post-processing for two different CNC lathes

Forward steps in green medical laboratory practices for a sustainable future

This paper provides information on the significance of environmental sustainability and the potential benefits of implementing green laboratory processes. Sustainability is a broad concept that includes goals such as conservation of natural resources, energy efficiency, waste management, and reducing environmental footprints. Green laboratories strive to minimise environmental footprints by embedding sustainability principles into their everyday practices. This involves improvements in energy consumption, water usage, chemical waste reduction, and recycling, ultimately, as well as lower waste disposal costs. Implementing green laboratory approaches provides many benefits, such as a smaller environmental footprint, increased energy efficiency, water conservation, and cost savings. Moreover, a rational test ordering process can effectively contribute to reducing environmental impacts in medical laboratories. Rational test ordering provides cost-effectiveness and reduces the carbon footprint. Establishing a green and sustainable laboratory culture in medical laboratories requires a permanent organisation in where all personnel participate. Training of the hospital management teams, clinicians, and laboratory professionals is a vital point. Methodology and quality indicators should be defined by international and national laboratory associations within the framework of a green and sustainable laboratory plan, and data should be collected. In conclusion, adopting green laboratory practices reduces environmental impacts, saves costs, and accelerates innovation processes. Setting quality targets and rational test ordering practices are also essential for sustainability. Applying sustainability principles in laboratory workplaces is an important step towards protecting the environment and leaving a more liveable world for future generations