1.Intron 4 VNTR (4a/b) Polymorphism of the Endothelial Nitric Oxide Synthase Gene Is Associated with Breast Cancer in Mexican Women.
Ramiro RAMIREZ-PATINO ; Luis Eduardo FIGUERA ; Ana Maria PUEBLA-PEREZ ; Jorge Ivan DELGADO-SAUCEDO ; Maria Magdalena LEGAZPI-MACIAS ; Rocio Patricia MARIAUD-SCHMIDT ; Adriana RAMOS-SILVA ; Itzae Adonai GUTIERREZ-HURTADO ; Liliana GOMEZ FLORES-RAMOS ; Guillermo Moises ZUNIGA-GONZALEZ ; Martha Patricia GALLEGOS-ARREOLA
Journal of Korean Medical Science 2013;28(11):1587-1594
The endothelial nitric oxide synthase (eNOS) gene plays an important role in several biological functions. Polymorphisms of the eNOS gene have been associated with cancer. It has been suggested that the VNTR 4 a/b polymorphism may affect the expression of eNOS and contributes to tumor promotion in the mammary gland. We examined the role of the eNOS4 a/b polymorphism by comparing the genotypes of 281 healthy Mexican women with the genotypes of 429 Mexican women with breast cancer (BC). The observed genotype frequencies for control and BC patients were 0.6% and 0.7% for a/a (polymorphic); 87% and 77% for a/a (wild type); and 12% and 22% for a/b respectively. We found that the odds ratio (OR) was 1.9, with a 95% confidence interval (95%CI) of 1.29-2.95, P = 0.001 for genotypes a/a-a/b, b/c. The association was also evident when comparing the distribution of the a/a-a/b genotypes in patients with high levels of glutamate-oxaloacetate transaminase (SGOT) (OR, 1.93; 95% CI, 1.14-3.28; P = 0.015); undergoing menopause with high levels of SGOT (OR, 2.0; 95% CI, 1.1-3.84); and with high levels of glutamic-pyruvic transaminase (SGPT) (OR, 3.5; 95% CI, 1.56-8.22). The genotypes a/a-a/b are associated with BC susceptibility in the analyzed samples from the Mexican population.
Adult
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Alanine Transaminase/*blood
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Aspartate Aminotransferases/*blood
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Breast Neoplasms/*blood/*genetics
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Female
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Gene Frequency
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Genetic Predisposition to Disease
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Genotype
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Humans
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Mexico
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Middle Aged
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Nitric Oxide/biosynthesis/metabolism
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Nitric Oxide Synthase Type III/*genetics
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Polymorphism, Single Nucleotide
2.Artificial Intelligence in Andrology: From Semen Analysis to Image Diagnostics
Ramy Abou GHAYDA ; Rossella CANNARELLA ; Aldo E. CALOGERO ; Rupin SHAH ; Amarnath RAMBHATLA ; Wael ZOHDY ; Parviz KAVOUSSI ; Tomer AVIDOR-REISS ; Florence BOITRELLE ; Taymour MOSTAFA ; Ramadan SALEH ; Tuncay TOPRAK ; Ponco BIROWO ; Gianmaria SALVIO ; Gokhan CALIK ; Shinnosuke KURODA ; Raneen Sawaid KAIYAL ; Imad ZIOUZIOU ; Andrea CRAFA ; Nguyen Ho Vinh PHUOC ; Giorgio I. RUSSO ; Damayanthi DURAIRAJANAYAGAM ; Manaf AL-HASHIMI ; Taha Abo-Almagd Abdel-Meguid HAMODA ; Germar-Michael PINGGERA ; Ricky ADRIANSJAH ; Israel Maldonado ROSAS ; Mohamed ARAFA ; Eric CHUNG ; Widi ATMOKO ; Lucia ROCCO ; Haocheng LIN ; Eric HUYGHE ; Priyank KOTHARI ; Jesus Fernando Solorzano VAZQUEZ ; Fotios DIMITRIADIS ; Nicolas GARRIDO ; Sheryl HOMA ; Marco FALCONE ; Marjan SABBAGHIAN ; Hussein KANDIL ; Edmund KO ; Marlon MARTINEZ ; Quang NGUYEN ; Ahmed M. HARRAZ ; Ege Can SEREFOGLU ; Vilvapathy Senguttuvan KARTHIKEYAN ; Dung Mai Ba TIEN ; Sunil JINDAL ; Sava MICIC ; Marina BELLAVIA ; Hamed ALALI ; Nazim GHERABI ; Sheena LEWIS ; Hyun Jun PARK ; Mara SIMOPOULOU ; Hassan SALLAM ; Liliana RAMIREZ ; Giovanni COLPI ; Ashok AGARWAL ;
The World Journal of Men's Health 2024;42(1):39-61
Artificial intelligence (AI) in medicine has gained a lot of momentum in the last decades and has been applied to various fields of medicine. Advances in computer science, medical informatics, robotics, and the need for personalized medicine have facilitated the role of AI in modern healthcare. Similarly, as in other fields, AI applications, such as machine learning, artificial neural networks, and deep learning, have shown great potential in andrology and reproductive medicine. AI-based tools are poised to become valuable assets with abilities to support and aid in diagnosing and treating male infertility, and in improving the accuracy of patient care. These automated, AI-based predictions may offer consistency and efficiency in terms of time and cost in infertility research and clinical management. In andrology and reproductive medicine, AI has been used for objective sperm, oocyte, and embryo selection, prediction of surgical outcomes, cost-effective assessment, development of robotic surgery, and clinical decision-making systems. In the future, better integration and implementation of AI into medicine will undoubtedly lead to pioneering evidence-based breakthroughs and the reshaping of andrology and reproductive medicine.