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Eligibility of Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) modulator therapies: cohort of cystic fibrosis registry of Türkiye
No full textBackground. Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) variants are essential for determining eligibility for CFTR modulator drugs (CFTRms). In contrast to Europe and the USA, the treatment eligibility profile of cystic fibrosis (CF) patients in Türkiye is not known. In this study we aimed to determine the eligibility of CF patients in Türkiye for the CFTRms. Methods. The Cystic Fibrosis Registry of Türkiye (CFrT) data was used to determine the age of patients in the year 2021 and the genetic variants they were carrying. Age-and CFTR-variant appropriate modulator therapies were determined using the Vertex® algorithm. Results. Among a total of 1930 registered patients, CTFR gene analysis was performed on a total of 1841 (95.4%) patients. Mutations were detected in one allele in 10.7% (198 patients), and in both alleles in 79% (1455 patients) of patients. A total of 855 patients (51.7% for whom at least 1 mutation was detected) were eligible for the drugs. The most appropriate drug among genotyped patients was found to be elexacaftor/tezacaftor/ivacaftor for 486 patients (26.4%), followed by ivacaftor for 327 patients (17.7%) and lumacaftor/ivacaftor for 42 patients (2%). Conclusions. Only half of patients registered in CFrT were eligible for CFTRms, which is a significant difference from the CFTR variant profile seen in USA and Europe. However, access to treatment is hampered for some patients whose genes are not analysed. Further studies in CF populations, where rare mutations are relatively more common, will contribute to the field of CFTR modulator treatments for such rare mutations
Synthesis of Thiazole-methylsulfonyl Derivatives, X-ray Study, and Investigation of Their Carbonic Anhydrase Activities: <i>In Vitro</i> and <i>In Silico</i> Potentials
No full textThis study focused on the design, synthesis, chemical characterization, and potential inhibitory study of thiazole-methylsulfonyl derivatives against carbonic anhydrase enzymes. The synthesized compounds, with the characteristics of both the thiazole ring and methyl sulfonyl group, were synthesized through a two-step scheme, and their structures were confirmed through NMR spectroscopy and HRMS. Additionally, the structure of compound 2b was elucidated by an X-ray study. An enzyme inhibition assay was performed to assess their biological activity against carbonic anhydrases, and the compounds showed promising results against carbonic anhydrases I and II, highlighting their potential for specificity and targeted therapy. The effects of these molecules on in vitro enzyme activities were investigated by spectrophotometric methods. For this purpose, the concentrations (IC50 values) of compounds that inhibited the biological activities of carbonic anhydrase isoenzymes (hCA I and hCA II) by 50% were calculated. The IC50 values were found between 39.38-198.04 mu M (AAZ IC50 = 18.11 mu M) for hCA I and 39.16-86.64 mu M (AAZ IC50 = 20.65 mu M). Molecular docking studies have shown that compounds 2a and 2h exhibit stable interaction networks with targeted enzymes. The combinations of both studies, enzyme inhibition assay and molecular docking studies, thus enlighten the significance of these compounds for further optimization for pharmacological profiling and for developing therapeutic agents against carbonic anhydrase. Moreover, the study provides insight for future research on the synthesis of heterocyclic compounds against carbonic anhydrase for therapeutic applications
Risk Factors and Predictors of In-Hospital Mortality in Geriatric Patients with Hip Fractures: A Retrospective Study
No full textComparison performance of the CNN-based deep learning models for the distinguishing ultrasound pretreated and microwave dried jujube fruits
No full textClassifying dried fruits with economic importance and high nutritional content using novel techniques is crucial for achieving uniformity and practicality. It also plays a key role in identifying and distinguishing dried products, benefiting end consumers and the food processing industry. In this study, jujube slices were microwave-dried with and without ultrasound pretreatment at 100, 200, 300, and 600 W (watt) power. The classification models were explored based on an image data set using ConvNeXt_Tiny, ResNet-18, Densenet-121, ConvNeXt-Base, and EfficientNet-B1 deep learning models, which are widely used in the Fastai library and developed based on the transfer learning technique. Considering model accuracy and computational cost, using images with an input image size of 224*224 is efficient. Experimental results revealed that at the end of 20 iterations, the accuracy results of the models reached 95 %, 98 %, 99 %, 98 %, and 99 % for ResNet-18, ConvNeXt-Tiny, DenseNet-121, and ConvNeXt-Base and EfficientNet-B1 algorithms, respectively, and the models showed a tendency to converge. It is observed that the DenseNet-121 and EfficientNet-B1 models had the best accuracy rate. The precision, recall, and F1-score also support these results. The proposed models can potentially be used for non-invasive, effective, and rapid classification of dried fruits on the embedded system in a related application
SERS and Machine Learning-Enabled Liquid Biopsy: A Promising Tool for Early Detection and Recurrence Prediction in Acute Leukemia
No full textAcute leukemia (AL), classified as acute myeloid leukemia (AML) and acute lymphocytic leukemia (ALL), is a hematologic malignancy caused by the uncontrolled proliferation of leucocytes in the bone marrow. Early detection of AL is crucial for clinical treatment. Detection methods of AL are currently blood tests, bone marrow tests, imaging, and spinal fluid tests. However, these tests have drawbacks, such as high cost and time consumption. Liquid biopsy using biological fluids such as blood or serum is an emerging technique for noninvasive cancer detection and monitoring. Surface-enhanced Raman spectroscopy (SERS), which enhanced Raman signals by the interaction of plasmonic nanostructures with the analyte, is a highly sensitive and specific detection method with simple sample preparation that has been used in combination with machine learning techniques to analyze liquid biopsy. In this study, we developed a SERS-based liquid biopsy approach that enables accurate classification of AML and ALL subtypes and the prediction of disease recurrence. SERS spectra of serum samples from 24 healthy individuals, 43 AML patients, and 18 ALL patients were obtained using an Ag-based SERS substrate and clustered using hierarchical cluster analysis (HCA). The spectra were then classified using three commonly used classifiers, namely, support vector machine (SVM), random forest (RF), and k-nearest neighbor (kNN). Our findings demonstrate that the RF classifier has the highest accuracy values, with 96.1, 95.5, and 98.5% for classifying three groups and predicting the recurrence of AML and ALL, respectively. The combination of SERS-based serum analysis with machine learning algorithms represents a remarkable advancement in the realm of hematological disease diagnostics, particularly for AML and ALL. This approach not only facilitates the precise differentiation of disease subtypes but also introduces the novel capability of prognosticating disease recurrence
Postgraduate Theses on Coaching Practice in Special Education: A Systematic Review Study
No full textApplication of a modular polycarbonate and GRP beam system for enhanced wind resistance in low-cost greenhouse construction
No full textModern agricultural practices frequently involve controlling critical growth parameters, including humidity, temperature, and light exposure. Before selecting the proper growth system, some variables must be considered, such as the properties of the place where products are grown, environmental factors, the equipment used, and the workforce. Besides being easily installable, the plastic material applied in the greenhouse construction does not pose any chemical threat to the plant cover. The modular system, constructed from glass-fiber reinforced polyester (GRP) rods, showed superior wind resistance and ease of installation, improving vegetable production in adverse climates. According to the results, the GRP rod with a mean of 6.730 kN was the most durable material. The test results also showed that the beam system (0.993 kN) and the SP3 module (0.920 kN) were very similar regarding the durability of materials. The greatest results in terms of resistance duration were found in the beam system (26.50 s). This means 3 times more resistance for the connected materials of the greenhouse. In addition, the GRP material is 86.84 % lighter than traditional galvanized iron-framed systems. According to the results of the study, the low specific gravity of the polymer (1.2 g.cm-3) as compared to the weight of the galvanized iron (7 g.cm-3) provides a significant reduction in the loads in the greenhouse, and this, in turn, reduces the shear force in the columns caused by the dynamic load (wind load). This study used a newly developed SP3 module and GRP rods to build a portable greenhouse
Recent Advances in Polymer Electrolyte Membrane Water Electrolyzer Stack Development Studies: A Review
No full textPolymer electrolyte membrane water electrolyzers have significant advantages over other electrolyzers, such as compact design, high efficiency, low gas permeability, fast response, high-pressure operation (up to 200 bar), low operating temperature (20-80 degrees C), lower power consumption, and high current density. Moreover, polymer electrolyte membrane water electrolyzers are a promising technology for sustainable hydrogen production due to their easy adaptability to renewable energy sources. However, the cost of expensive electrocatalysts and other construction equipment must be reduced for the widespread usage of polymer electrolyte membrane water electrolyzer technology. In this review, recent improvements made in developing the polymer electrolyte membrane water electrolyzer stack are summarized. First, we present a brief overview of the working principle of polymer electrolyte membrane water electrolyzers. Then, we discuss the components of polymer electrolyte membrane water electrolyzers (base materials such as membranes, gas diffusion layers, electrocatalysts, and bipolar plates) and their particular functions. We also provide an overview of polymer electrolyte membrane water electrolyzer's material technology, production technology, and commercialization issues. We finally present recent advancements of polymer electrolyte membrane water electrolyzer stack developments and their recent developments under different operating conditions