Alternative Physical Activation Program to Improve School Performance

One of the problems affecting children in Mexico is the lack of systematic physical activity which influences school performance For this reason the objective was to determine the effect of an alternative physical activation program to improve school performance This was a quantitative study based on a pre-experimental design The participants were N 134 made up of n 64 boys and n 70 girls the average age was 9 4 1 01 Normality tests were applied as well as Student s t-test to compare the results of Bimesters II and IV the confidence level was 95 with a significance value of p 0 05 The most significant results found were in Mathematics p 0 000 in the second and sixth grades Better progress was obtained with the alternative physical activation program to improve school performance the alternative program was used for 40 sessions with a duration of 45 minutes in advance of the school day In conclusion the alternative physical activation program to improve school performance can have a beneficial effect in the subjects of Mathematics Civic Education and Histor

Improved personalized survival prediction of patients with diffuse large B-cell Lymphoma using gene expression profiling

BACKGROUND: Thirty to forty percent of patients with Diffuse Large B-cell Lymphoma (DLBCL) have an adverse clinical evolution. The increased understanding of DLBCL biology has shed light on the clinical evolution of this pathology, leading to the discovery of prognostic factors based on gene expression data, genomic rearrangements and mutational subgroups. Nevertheless, additional efforts are needed in order to enable survival predictions at the patient level. In this study we investigated new machine learning-based models of survival using transcriptomic and clinical data. METHODS: Gene expression profiling (GEP) of in 2 different publicly available retrospective DLBCL cohorts were analyzed. Cox regression and unsupervised clustering were performed in order to identify probes associated with overall survival on the largest cohort. Random forests were created to model survival using combinations of GEP data, COO classification and clinical information. Cross-validation was used to compare model results in the training set, and Harrel's concordance index (c-index) was used to assess model's predictability. Results were validated in an independent test set. RESULTS: Two hundred thirty-three and sixty-four patients were included in the training and test set, respectively. Initially we derived and validated a 4-gene expression clusterization that was independently associated with lower survival in 20% of patients. This pattern included the following genes: TNFRSF9, BIRC3, BCL2L1 and G3BP2. Thereafter, we applied machine-learning models to predict survival. A set of 102 genes was highly predictive of disease outcome, outperforming available clinical information and COO classification. The final best model integrated clinical information, COO classification, 4-gene-based clusterization and the expression levels of 50 individual genes (training set c-index, 0.8404, test set c-index, 0.7942). CONCLUSION: Our results indicate that DLBCL survival models based on the application of machine learning algorithms to gene expression and clinical data can largely outperform other important prognostic variables such as disease stage and COO. Head-to-head comparisons with other risk stratification models are needed to compare its usefulness

Familial hypercholesterolaemia in children and adolescents from 48 countries: a cross-sectional study

Background: Approximately 450 000 children are born with familial hypercholesterolaemia worldwide every year, yet only 2·1% of adults with familial hypercholesterolaemia were diagnosed before age 18 years via current diagnostic approaches, which are derived from observations in adults. We aimed to characterise children and adolescents with heterozygous familial hypercholesterolaemia (HeFH) and understand current approaches to the identification and management of familial hypercholesterolaemia to inform future public health strategies. Methods: For this cross-sectional study, we assessed children and adolescents younger than 18 years with a clinical or genetic diagnosis of HeFH at the time of entry into the Familial Hypercholesterolaemia Studies Collaboration (FHSC) registry between Oct 1, 2015, and Jan 31, 2021. Data in the registry were collected from 55 regional or national registries in 48 countries. Diagnoses relying on self-reported history of familial hypercholesterolaemia and suspected secondary hypercholesterolaemia were excluded from the registry; people with untreated LDL cholesterol (LDL-C) of at least 13·0 mmol/L were excluded from this study. Data were assessed overall and by WHO region, World Bank country income status, age, diagnostic criteria, and index-case status. The main outcome of this study was to assess current identification and management of children and adolescents with familial hypercholesterolaemia. Findings: Of 63 093 individuals in the FHSC registry, 11 848 (18·8%) were children or adolescents younger than 18 years with HeFH and were included in this study; 5756 (50·2%) of 11 476 included individuals were female and 5720 (49·8%) were male. Sex data were missing for 372 (3·1%) of 11 848 individuals. Median age at registry entry was 9·6 years (IQR 5·8-13·2). 10 099 (89·9%) of 11 235 included individuals had a final genetically confirmed diagnosis of familial hypercholesterolaemia and 1136 (10·1%) had a clinical diagnosis. Genetically confirmed diagnosis data or clinical diagnosis data were missing for 613 (5·2%) of 11 848 individuals. Genetic diagnosis was more common in children and adolescents from high-income countries (9427 [92·4%] of 10 202) than in children and adolescents from non-high-income countries (199 [48·0%] of 415). 3414 (31·6%) of 10 804 children or adolescents were index cases. Familial-hypercholesterolaemia-related physical signs, cardiovascular risk factors, and cardiovascular disease were uncommon, but were more common in non-high-income countries. 7557 (72·4%) of 10 428 included children or adolescents were not taking lipid-lowering medication (LLM) and had a median LDL-C of 5·00 mmol/L (IQR 4·05-6·08). Compared with genetic diagnosis, the use of unadapted clinical criteria intended for use in adults and reliant on more extreme phenotypes could result in 50-75% of children and adolescents with familial hypercholesterolaemia not being identified. Interpretation: Clinical characteristics observed in adults with familial hypercholesterolaemia are uncommon in children and adolescents with familial hypercholesterolaemia, hence detection in this age group relies on measurement of LDL-C and genetic confirmation. Where genetic testing is unavailable, increased availability and use of LDL-C measurements in the first few years of life could help reduce the current gap between prevalence and detection, enabling increased use of combination LLM to reach recommended LDL-C targets early in life

Clinical significance of CD56 expression in patients with acute promyelocytic leukemia treated with all-trans retinoic acid and anthracycline-based regimens

The expression of CD56 antigen in acute promyelocytic leukemia (APL) blasts has been associated with short remission duration and extramedullary relapse. We investigated the clinical significance of CD56 expression in a large series of patients with APL treated with all-trans retinoic acid and anthracycline-based regimens. Between 1996 and 2009, 651 APL patients with available data on CD56 expression were included in 3 subsequent trials (PETHEMA LPA96 and LPA99 and PETHEMA/HOVON LPA2005). Seventy-two patients (11%) were CD56(+) ( expression of CD56 in >= 20% leukemic promyelocytes). CD56(+) APL was significantly associated with high white blood cell counts; low albumin levels; BCR3 isoform; and the coexpression of CD2, CD34, CD7, HLA-DR, CD15, and CD117 antigens. For CD56(+) APL, the 5-year relapse rate was 22%, compared with a 10% relapse rate for CD56(+) APL (P = .006). In the multivariate analysis, CD56 expression retained the statistical significance together with the relapse-risk score. CD56(+) APLalso showed a greater risk of extramedullary relapse (P <.001). In summary, CD56 expression is associated with the coexpression of immaturity-associated and T-cell antigens and is an independent adverse prognostic factor for relapse in patients with APL treated with all-trans-retinoic acid plus idarubicin-derived regimens. This marker may be considered for implementing risk-adapted therapeutic strategies in APL. The LPA2005 trial is registered at http://www.clinicaltrials.govasNCT00408278. (Blood. 2011;117(6):1799-1805