Emphysematous pyelonephritis with left renal vein thrombosis-case report successfully treated by conservative methods

Presently emphysematous pyelonephritis is a rare but life-threatening disease, mostly seen in patients with urinary tract obstr uc- tion and diabetes mellitus. It is characterized by the production of gas and necrosis in the renal parenchyma, collecting systems, and perinephritic tissue. Radiologically, the Huang and Tseng classification is used to categorize the severity of the disease. Our case was 49 years old female pre- senting with unconsciousness, fever and bilateral Grade 3 lower extremity eodema one week after left percutaneous nephrolithotomy procedure because of urinary tract stone. Abdominal computerized tomography scan showed renal parenchymal and perinephritic tissue necrosis with the production of gas and renal vein thrombosis which was in accordance with Huang and Tseng classification Grade 3A. We treated our patient with the appropriate antibiotic, enoxaparin sodium, strict glycemic control, and supportive treatment without any surgical intervention or nephrectomy

Keystroke dynamics based biometric identification [Tuş vuruşa dayalı biyometrik tanıma]

Biometrics based keystroke dynamics aim to perform user identification and authentication based on users' typing behaviour on digital devices. In this study, keystroke timing and regional distributions extracted from free-text are utilized to perform user identification. In order to obtain the highest representative set of attributes, attributes based on directional graph, hold time and keyboard distance have been extracted and used in different configurations. In order to process the generated feature sets more effectively, unlike the existing studies, a multilayer artificial neural network model with attention mechanism was used and 0.13% FAR and 2.5% FRR results were obtained

Annotated corpora and tools of the PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions (edition 1.0)

The PARSEME shared task aims at identifying verbal MWEs in running texts. Verbal MWEs include idioms (let the cat out of the bag), light verb constructions (make a decision), verb-particle constructions (give up), and inherently reflexive verbs (se suicider 'to suicide' in French). VMWEs were annotated according to the universal guidelines in 18 languages. The corpora are provided in the parsemetsv format, inspired by the CONLL-U format. For most languages, paired files in the CONLL-U format - not necessarily using UD tagsets - containing parts of speech, lemmas, morphological features and/or syntactic dependencies are also provided. Depending on the language, the information comes from treebanks (e.g., Universal Dependencies) or from automatic parsers trained on treebanks (e.g., UDPipe). This item contains training and test data, tools and the universal guidelines file

Dealing with the gray zones in the management of gastric cancer: The consensus statement of the Istanbul Group

The geographical location and differences in tumor biology significantly change the management of gastric cancer. The prevalence of gastric cancer ranks fifth and sixth among men and women, respectively, in Turkey. The international guidelines from the Eastern and Western countries fail to manage a considerable amount of inconclusive issues in the management of gastric cancer. The uncertainties lead to significant heterogeneities in clinical practice, lack of homogeneous data collection, and subsequently, diverse outcomes

Clinical and molecular evaluation of MEFV gene variants in the Turkish population: a study by the National Genetics Consortium

Familial Mediterranean fever (FMF) is a monogenic autoinflammatory disorder with recurrent fever, abdominal pain, serositis, articular manifestations, erysipelas-like erythema, and renal complications as its main features. Caused by the mutations in the MEditerranean FeVer (MEFV) gene, it mainly affects people of Mediterranean descent with a higher incidence in the Turkish, Jewish, Arabic, and Armenian populations. As our understanding of FMF improves, it becomes clearer that we are facing with a more complex picture of FMF with respect to its pathogenesis, penetrance, variant type (gain-of-function vs. loss-of-function), and inheritance. In this study, MEFV gene analysis results and clinical findings of 27,504 patients from 35 universities and institutions in Turkey and Northern Cyprus are combined in an effort to provide a better insight into the genotype-phenotype correlation and how a specific variant contributes to certain clinical findings in FMF patients. Our results may help better understand this complex disease and how the genotype may sometimes contribute to phenotype. Unlike many studies in the literature, our study investigated a broader symptomatic spectrum and the relationship between the genotype and phenotype data. In this sense, we aimed to guide all clinicians and academicians who work in this field to better establish a comprehensive data set for the patients. One of the biggest messages of our study is that lack of uniformity in some clinical and demographic data of participants may become an obstacle in approaching FMF patients and understanding this complex disease

PARSEME corpora annotated for verbal multiword expressions (version 1.3)

This multilingual resource contains corpora in which verbal MWEs have been manually annotated. VMWEs include idioms (let the cat out of the bag), light-verb constructions (make a decision), verb-particle constructions (give up), inherently reflexive verbs (help oneself), and multi-verb constructions (make do). This is the first release of the corpora without an associated shared task. Previous version (1.2) was associated with the PARSEME Shared Task on semi-supervised Identification of Verbal MWEs (2020). The data covers 26 languages corresponding to the combination of the corpora for all previous three editions (1.0, 1.1 and 1.2) of the corpora. VMWEs were annotated according to the universal guidelines. The corpora are provided in the cupt format, inspired by the CONLL-U format. Morphological and syntactic information, ­­­­including parts of speech, lemmas, morphological features and/or syntactic dependencies, are also provided. Depending on the language, the information comes from treebanks (e.g., Universal Dependencies) or from automatic parsers trained on treebanks (e.g., UDPipe). All corpora are split into training, development and test data, following the splitting strategy adopted for the PARSEME Shared Task 1.2. The annotation guidelines are available online: https://parsemefr.lis-lab.fr/parseme-st-guidelines/1.3 The .cupt format is detailed here: https://multiword.sourceforge.net/cupt-format