Propuesta de un plan estratégico de negocios para una agencia de viajes de turismo gay, enfocada al sector ejecutivo.

Tesis (Licenciatura en Turismo), Instituto Politécnico Nacional, EST, 2008, 4 archivo PDF, ( 561 pàginas). tesis.ipn.m

Methotrexate-induced epidermal necrosis in a child with osteosarcoma

Methotrexate is a folic acid antagonist used to treat psoria-sis, rheumatoid arthritis and neoplasms. It is renally excreted unchanged, at levels of about 90% within 24 hours. Several risk factors for intoxication have been described, including folate deficiency, liver cirrhosis, renal failure or the use of me-dications such as sulfonamides, salicylate and nonsteroidal anti-inflammatory drugs. Adverse cutaneous reactions such as photosensitivity, alopecia, urticaria, mucositis, erythe-ma, desquamation, Stevens-Johnson syndrome (SJS) or toxic epidermal necrolysis (TEN) are well known. Methotrexate epidermal necrosis (MEN) should also be considered because of its severity, its similarity to TEN and the importance of rapidly administering appropriate treatment. Some cases of MEN have been reported in psoriasis patients, in whom the occurrence with an underlying skin disease has been found to be more common

Clinical characterization of data-driven diabetes subgroups in Mexicans using a reproducible machine learning approach

Introduction Previous reports in European populations demonstrated the existence of five data-driven adult-onset diabetes subgroups. Here, we use self-normalizing neural networks (SNNN) to improve reproducibility of these data-driven diabetes subgroups in Mexican cohorts to extend its application to more diverse settings.Research design and methods We trained SNNN and compared it with k-means clustering to classify diabetes subgroups in a multiethnic and representative population-based National Health and Nutrition Examination Survey (NHANES) datasets with all available measures (training sample: NHANES-III, n=1132; validation sample: NHANES 1999–2006, n=626). SNNN models were then applied to four Mexican cohorts (SIGMA-UIEM, n=1521; Metabolic Syndrome cohort, n=6144; ENSANUT 2016, n=614 and CAIPaDi, n=1608) to characterize diabetes subgroups in Mexicans according to treatment response, risk for chronic complications and risk factors for the incidence of each subgroup.Results SNNN yielded four reproducible clinical profiles (obesity related, insulin deficient, insulin resistant, age related) in NHANES and Mexican cohorts even without C-peptide measurements. We observed in a population-based survey a high prevalence of the insulin-deficient form (41.25%, 95% CI 41.02% to 41.48%), followed by obesity-related (33.60%, 95% CI 33.40% to 33.79%), age-related (14.72%, 95% CI 14.63% to 14.82%) and severe insulin-resistant groups. A significant association was found between the SLC16A11 diabetes risk variant and the obesity-related subgroup (OR 1.42, 95% CI 1.10 to 1.83, p=0.008). Among incident cases, we observed a greater incidence of mild obesity-related diabetes (n=149, 45.0%). In a diabetes outpatient clinic cohort, we observed increased 1-year risk (HR 1.59, 95% CI 1.01 to 2.51) and 2-year risk (HR 1.94, 95% CI 1.13 to 3.31) for incident retinopathy in the insulin-deficient group and decreased 2-year diabetic retinopathy risk for the obesity-related subgroup (HR 0.49, 95% CI 0.27 to 0.89).Conclusions Diabetes subgroup phenotypes are reproducible using SNNN; our algorithm is available as web-based tool. Application of these models allowed for better characterization of diabetes subgroups and risk factors in Mexicans that could have clinical applications