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1.
Clin Endocrinol (Oxf) ; 99(2): 174-181, 2023 08.
Artigo em Inglês | MEDLINE | ID: mdl-36971427

RESUMO

OBJECTIVE: 12,13-Dihydroxy-9Z-octadecenoic acid (12,13-diHOME) is a lipokine secreted from brown adipose tissue, and it has positive effects on dyslipidemia. Acute exercise has been shown to lead to an increase in its secretion. In this study, it was aimed to investigate the relationship of 12,13-diHOME with obesity, exercise and dyslipidaemia for the first time in the adolescent age group. DESIGN: Prospective study. PATIENTS: Twenty-eight male adolescents with obesity and the same number of age-matched healthy normal-weight male controls. MEASUREMENTS: Fasting serum glucose, insulin, lipid and 12,13-diHOME levels were measured. Cardiopulmonary exercise testing was performed in all subjects using a stress test treadmill. Peak oxygen consumption (peak VO2) and anaerobic threshold heart rate (ATHR) were measured. RESULTS: Adolescents with obesity had lower 12,13-diHOME levels than normal-weight adolescents both before and after acute exercise (p = .025 and p = .019, respectively), and after acute exercise, 12,13-diHOME levels significantly increased in both groups (p = .001 for both). 12,13-diHOME levels negatively correlated with triglyceride, total cholesterol, LDL-C, and positively correlated with HDL-C. Also, peak VO2 and ATHR levels showed positive correlation with 12,13-diHOME levels. CONCLUSION: 12,13-diHOME levels were found to be lower in adolescents with obesity than normal-weight adolescents and increased with acute exercise. Also, the close relationship of this molecule with dyslipidaemia in addition to that with obesity suggests that it has an important role in the pathophysiology of these disorders. Further molecular studies will further elucidate the role of 12,13-diHOME in obesity and dyslipidaemia.


Assuntos
Obesidade Infantil , Humanos , Masculino , Adolescente , Estudos Prospectivos , Exercício Físico , Índice de Massa Corporal
2.
J Clin Lab Anal ; 33(3): e22704, 2019 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-30390345

RESUMO

BACKGROUND: Leiomyoma, one of the most common benign tumors, causes morbidity during the reproductive years in women. The molecular pathogenesis of the disease is not clear. Leiomyomas are hormone-sensitive tumors affecting around 20%-25% of women. Gene polymorphism studies could be important and explaining in the evaluation of multifactorial diseases such as leiomyoma. Polymorphisms involving genes responsible for the synthesis and signalization of steroid hormones could be used as genetic markers for hormone-related conditions. The purpose of this study was to analyze the effect of ERα-351 XbaI A/G, ERα-397 PvuII T/C, and progesterone receptor (PGR) PROGINS polymorphisms on the development of leiomyomas. MATERIAL AND METHODS: In this study, 213 samples (103 leiomyoma patients and 110 healthy controls) participated. The ERα-351 XbaI A/G and ERα-397 PvuII T/C gene polymorphisms were analyzed using PCR-RFLP method. PGR PROGINS polymorphism was analyzed by PCR method with specific primers. RESULTS: The genotype distribution and allele frequency of the ERα-351 XbaI A/G, ERα-397 PvuII T/C, and PGR PROGINS polymorphisms were not statistically different between leiomyoma patient and control groups (p > 0.05). CONCLUSION: This study reflects that ERα and PGR PROGINS polymorphisms may not be one of the many genetic factors for leiomyoma susceptibility.


Assuntos
Leiomioma/epidemiologia , Leiomioma/genética , Polimorfismo Genético/genética , Receptores de Estrogênio/genética , Receptores de Progesterona/genética , Adulto , Estudos de Casos e Controles , Feminino , Humanos , Pessoa de Meia-Idade , Reação em Cadeia da Polimerase
3.
Endocrinol Diabetes Nutr (Engl Ed) ; 71(1): 12-18, 2024 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-38388074

RESUMO

PURPOSE: Gestational diabetes mellitus (GDM) is defined as carbohydrate intolerance that begins or is diagnosed during pregnancy. Our study aimed to establish a correlation between proinflammatory and anti-inflammatory response in order to be able to develop treatment strategies and determine early diagnosis biomarkers in the sera of cases diagnosed with GDM. Moreover, we aimed to investigate interleukin (IL), placenta-specific gene 8 protein (PLAC8) and total antioxidant capacity (TAC) in patients with GDM. METHODS: A total of 121 patients were included in the study. These were divided into four patient groups: pregnant and diagnosed with DM (P-GDM, n=30); pregnant and not diagnosed with DM (P-NGDM, n=32); non-pregnant diagnosed with DM (NP-DM, n=29) and non-pregnant and not diagnosed with DM (NPNDM, n=30). IL-10, IL-17A, IL-21, IL-33, PLAC8 and TAC determinations from patients were evaluated by ELISA (Enzyme-Linked ImmunoSorbent Assay) method. RESULTS: IL-10 and IL-33 concentrations were found to be significantly higher in P-GDM and NP-DM patient groups compared to P-NGDM and NP-NDM groups (p<0.001). The PLAC8 level in the P-GDM patient group (20.38±5.37) was determined to be significantly higher than in the P-NGDM patient group (3.41±2.17, p<0.001). TAC in the P-NGDM and NP-NDM groups (12.42±2.31 vs. 12.96±3.78, p<0.001) was determined to be significantly higher than in the P-GDM and NP-DM groups (4.8±0.52 vs. 2.21±0.71, p<0.001). DISCUSSION: The fact that the importance of PLAC8 level and TAC in the diagnosis and follow-up of GDM in pregnancy is demonstrated for the first time in this study shows that it is unique.


Assuntos
Diabetes Gestacional , Gravidez , Humanos , Feminino , Interleucina-17 , Interleucina-10 , Interleucina-33 , Antioxidantes , Interleucinas , Proteínas
4.
Stud Health Technol Inform ; 294: 866-867, 2022 May 25.
Artigo em Inglês | MEDLINE | ID: mdl-35612228

RESUMO

Radiology reports can potentially be used to detect critical cases that need immediate attention from physicians. We focus on detecting Brain Hemorrhage from Computed Tomography (CT) reports. We train a deep learning classifier and observe the effect of using different pre-trained word representations along with domain-specific fine-tuning. We have several contributions. Firstly, we report the results of a large-scale classification model for brain hemorrhage detection from Turkish radiology reports. Second, we show the effect of fine-tuning pre-trained language models using domain-specific data on the performance. We conclude that deep learning models can be used for detecting brain Hemorrhage with reasonable accuracy and fine-tuning language models using domain-specific data to improve classification performance.


Assuntos
Aprendizado Profundo , Processamento de Linguagem Natural , Humanos , Hemorragias Intracranianas , Relatório de Pesquisa , Tomografia Computadorizada por Raios X
5.
Ann Pediatr Cardiol ; 9(2): 195-6, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27212863

RESUMO

Congenital ventricular diverticulum is a rare cardiac anomaly defined as a localized protrusion of the ventricular free wall. Although, it is usually asymptomatic, complications such as embolism, infective endocarditis, and arrhythmias can occur. The diagnosis can be made by echocardiography, cardiac magnetic resonance imaging, or catheter angiography. Surgical resection is the treatment of choice in symptomatic patients, whereas the management of asymptomatic patients often represents a therapeutic dilemma. We report here, a 9-month-old patient with asymptomatic congenital left ventricular (LV) diverticulum associated with epigastric hernia.

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