Hyperbaric oxygen suppressed tumor progression through the improvement of tumor hypoxia and induction of tumor apoptosis in A549-cell-transferred lung cancer

Tumor cells have long been recognized as a relative contraindication to hyperbaric oxygen treatment (HBOT) since HBOT might enhance progressive cancer growth. However, in an oxygen deficit condition, tumor cells are more progressive and can be metastatic. HBOT increasing in oxygen partial pressure may benefit tumor suppression. In this study, we investigated the effects of HBOT on solid tumors, such as lung cancer. Non-small cell human lung carcinoma A549-cell-transferred severe combined immunodeficiency mice (SCID) mice were selected as an in vivo model to detect the potential mechanism of HBOT in lung tumors. HBOT not only improved tumor hypoxia but also suppressed tumor growth in murine xenograft tumor models. Platelet endothelial cell adhesion molecule (PECAM-1/CD31) was significantly increased after HBOT. Immunostaining of cleaved caspase-3 was demonstrated and apoptotic tumor cells with nuclear debris were aggregated starting on the 14th-day after HBOT. In vitro, HBOT suppressed the growth of A549 cells in a time-dependent manner and immediately downregulated the expression of p53 protein after HBOT in A549 cells. Furthermore, HBOT-reduced p53 protein could be rescued by a proteasome degradation inhibitor, but not an autophagy inhibitor in A549 cells. Our results demonstrated that HBOT improved tissue angiogenesis, tumor hypoxia and increased tumor apoptosis to lung cancer cells in murine xenograft tumor models, through modifying the tumor hypoxic microenvironment. HBOT will merit further cancer therapy as an adjuvant treatment for solid tumors, such as lung cancer

Correction: Magnetoconductance modulations due to interlayer tunneling in radial superlattices

Correction for ‘Magnetoconductance modulations due to interlayer tunneling in radial superlattices’ by Yu-Jie Zhong et al., Nanoscale Horiz., 2022, 7, 168–173, https://doi.org/10.1039/D1NH00449B

Psoas Abscess Caused by Non-Typhoid Salmonella in a Patient with Severe Aplastic Anemia

The clinical spectrum of infections caused by non-typhoid Salmonella spp. includes gastroenteritis, enteric fever, bacteremia, and extraintestinal localized complications, especially in immunocompromised hosts. Here we report a patient with severe aplastic anemia developing left iliopsoas abscess caused by non-typhoid Salmonella (NTS), which was successfully treated by prolonged antibiotic treatment and repeated debridement. Our data indicate that aplastic anemia is a risk factor for infection caused by NTS

Trayectorias laborales de jóvenes trabajadores de la actividad vitivinícola : departamento Maipú, Mendoza

La presente investigación tuvo como eje los vínculos entre educación y trabajo en la vitivinicultura mendocina desde 1990 . El objetivo general fue comprender los procesos de incorporación de jóvenes de ambos sexos al mundo del trabajo y su vínculo con las estrategias de formación y los esquemas de percepción en el mercado vitivinícola mendocino desde los 90. Se analizaron e identificaron los tipos de trayectorias educativas, laborales y transiciones existentes en los jóvenes. También los condicionantes de género que operan desde la perspectiva de las mujeres jóvenes. Se buscó comprender las formas que adquieren, cómo se manifiestan y varían las perspectivas acerca del trabajo, de las exigencias laborales y las condiciones del mercado de trabajo a lo largo de las trayectorias educativas y laborales y cuáles son los principales elementos constitutivos de las trayectorias de inserción, qué factores están asociados a sus variaciones y cómo se vinculan con las expectativas y estrategias de formación de inserción laboral.Fil: Martín, María Eugenia. CONICET (Consejo Nacional de Investigaciones Científicas y Técnicas) - Universidad Nacional de CuyoFil: Zamarbide, Gabriela. Universidad Nacional de Cuy

Gene expression profiling of breast cancer survivability by pooled cDNA microarray analysis using logistic regression, artificial neural networks and decision trees

BACKGROUND: Microarray technology can acquire information about thousands of genes simultaneously. We analyzed published breast cancer microarray databases to predict five-year recurrence and compared the performance of three data mining algorithms of artificial neural networks (ANN), decision trees (DT) and logistic regression (LR) and two composite models of DT-ANN and DT-LR. The collection of microarray datasets from the Gene Expression Omnibus, four breast cancer datasets were pooled for predicting five-year breast cancer relapse. After data compilation, 757 subjects, 5 clinical variables and 13,452 genetic variables were aggregated. The bootstrap method, Mann–Whitney U test and 20-fold cross-validation were performed to investigate candidate genes with 100 most-significant p-values. The predictive powers of DT, LR and ANN models were assessed using accuracy and the area under ROC curve. The associated genes were evaluated using Cox regression. RESULTS: The DT models exhibited the lowest predictive power and the poorest extrapolation when applied to the test samples. The ANN models displayed the best predictive power and showed the best extrapolation. The 21 most-associated genes, as determined by integration of each model, were analyzed using Cox regression with a 3.53-fold (95% CI: 2.24-5.58) increased risk of breast cancer five-year recurrence… CONCLUSIONS: The 21 selected genes can predict breast cancer recurrence. Among these genes, CCNB1, PLK1 and TOP2A are in the cell cycle G2/M DNA damage checkpoint pathway. Oncologists can offer the genetic information for patients when understanding the gene expression profiles on breast cancer recurrence

Machine-Part cell formation through visual decipherable clustering of Self Organizing Map

Machine-part cell formation is used in cellular manufacturing in order to process a large variety, quality, lower work in process levels, reducing manufacturing lead-time and customer response time while retaining flexibility for new products. This paper presents a new and novel approach for obtaining machine cells and part families. In the cellular manufacturing the fundamental problem is the formation of part families and machine cells. The present paper deals with the Self Organising Map (SOM) method an unsupervised learning algorithm in Artificial Intelligence, and has been used as a visually decipherable clustering tool of machine-part cell formation. The objective of the paper is to cluster the binary machine-part matrix through visually decipherable cluster of SOM color-coding and labelling via the SOM map nodes in such a way that the part families are processed in that machine cells. The Umatrix, component plane, principal component projection, scatter plot and histogram of SOM have been reported in the present work for the successful visualization of the machine-part cell formation. Computational result with the proposed algorithm on a set of group technology problems available in the literature is also presented. The proposed SOM approach produced solutions with a grouping efficacy that is at least as good as any results earlier reported in the literature and improved the grouping efficacy for 70% of the problems and found immensely useful to both industry practitioners and researchers.Comment: 18 pages,3 table, 4 figure

Correction: Comparing the genomes of Helicobacter pylori clinical strain UM032 and mice-adapted derivatives

Abstract is not available in fulltext.Published versio

Global variations and time trends in the prevalence of childhood myopia, a systematic review and quantitative meta-analysis: implications for aetiology and early prevention.

The aim of this review was to quantify the global variation in childhood myopia prevalence over time taking account of demographic and study design factors. A systematic review identified population-based surveys with estimates of childhood myopia prevalence published by February 2015. Multilevel binomial logistic regression of log odds of myopia was used to examine the association with age, gender, urban versus rural setting and survey year, among populations of different ethnic origins, adjusting for study design factors. 143 published articles (42 countries, 374 349 subjects aged 1-18 years, 74 847 myopia cases) were included. Increase in myopia prevalence with age varied by ethnicity. East Asians showed the highest prevalence, reaching 69% (95% credible intervals (CrI) 61% to 77%) at 15 years of age (86% among Singaporean-Chinese). Blacks in Africa had the lowest prevalence; 5.5% at 15 years (95% CrI 3% to 9%). Time trends in myopia prevalence over the last decade were small in whites, increased by 23% in East Asians, with a weaker increase among South Asians. Children from urban environments have 2.6 times the odds of myopia compared with those from rural environments. In whites and East Asians sex differences emerge at about 9 years of age; by late adolescence girls are twice as likely as boys to be myopic. Marked ethnic differences in age-specific prevalence of myopia exist. Rapid increases in myopia prevalence over time, particularly in East Asians, combined with a universally higher risk of myopia in urban settings, suggest that environmental factors play an important role in myopia development, which may offer scope for prevention

Roadmap on biology in time varying environments

Biological organisms experience constantly changing environments, from sudden changes in physiology brought about by feeding, to the regular rising and setting of the Sun, to ecological changes over evolutionary timescales. Living organisms have evolved to thrive in this changing world but the general principles by which organisms shape and are shaped by time varying environments remain elusive. Our understanding is particularly poor in the intermediate regime with no separation of timescales, where the environment changes on the same timescale as the physiological or evolutionary response. Experiments to systematically characterize the response to dynamic environments are challenging since such environments are inherently high dimensional. This roadmap deals with the unique role played by time varying environments in biological phenomena across scales, from physiology to evolution, seeking to emphasize the commonalities and the challenges faced in this emerging area of research