Disciplinamiento sexual : cazando brujas y ciberfeministas

El objetivo de este trabajo es analizar el fenómeno de la violencia online contra mujeres con presencia explícitamente feminista en el ciberespacio. Para dar cuenta de las estrategias de disciplinamiento sexual a las que están sometidas las mujeres, relacionamos la caza de brujas de los siglos XVI y XVII, con el ciberacoso, un creciente tipo de ciberviolencia. Abordamos nuestro objeto de estudio desde una estrategia metodológica cualitativa, a través de un estudio etnográfico de la manosfera –un conjunto de plataformas web antifeministas– de sus integrantes, y de sus técnicas de acoso; así como de los casos de ciberacoso contra Zoë Quinn y Anita Sarkeesian, ambos enmarcados en el movimiento Gamergate. Nuestros resultados finales muestran que los mecanismos digitales de disciplinamiento –amenazas de violencia física y/o sexual, y la apropiación sin consentimiento del cuerpo femenino– tienen como consecuencia la sumersión de las feministas en un estado de hipervigilancia, autocontrol y autocensura.The aim of this paper is to analyze the phenomenon of online violence against women who display an explicitly feminist presence in the virtual space. In order to report the strategies of sexual discipline to which women are subjected, we relate the witch hunt of the 16th and 17th centuries, with the phenomenon of cyberharassment, a rising form of cyberviolence. We approach our object of study from a qualitative research method, through an nethnographic study of the manosphere –a set of antifeminist websites–, of its members, and their harassment techniques; as well as the cases of cyberharassment against Zoë Quinn and Anita Sarkeesian, both framed in the Gamergate movement. Our final results show that digital mechanisms of discipline –threats of physical and/or sexual violence, and the appropriation without consent of the female body– have as a consequence the submersion of feminists in a state of hypervigilance, self-control and self-censorship

Systemic Metabolomic Changes in Blood Samples of Lung Cancer Patients Identified by Gas Chromatography Time-of-Flight Mass Spectrometry.

Lung cancer is a leading cause of cancer deaths worldwide. Metabolic alterations in tumor cells coupled with systemic indicators of the host response to tumor development have the potential to yield blood profiles with clinical utility for diagnosis and monitoring of treatment. We report results from two separate studies using gas chromatography time-of-flight mass spectrometry (GC-TOF MS) to profile metabolites in human blood samples that significantly differ from non-small cell lung cancer (NSCLC) adenocarcinoma and other lung cancer cases. Metabolomic analysis of blood samples from the two studies yielded a total of 437 metabolites, of which 148 were identified as known compounds and 289 identified as unknown compounds. Differential analysis identified 15 known metabolites in one study and 18 in a second study that were statistically different (p-values <0.05). Levels of maltose, palmitic acid, glycerol, ethanolamine, glutamic acid, and lactic acid were increased in cancer samples while amino acids tryptophan, lysine and histidine decreased. Many of the metabolites were found to be significantly different in both studies, suggesting that metabolomics appears to be robust enough to find systemic changes from lung cancer, thus showing the potential of this type of analysis for lung cancer detection

Epithelial/mesenchymal plasticity: how have quantitative mathematical models helped improve our understanding?

Phenotypic plasticity, the ability of cells to reversibly alter their phenotypes in response to signals, presents a significant clinical challenge to treating solid tumors. Tumor cells utilize phenotypic plasticity to evade therapies, metastasize, and colonize distant organs. As a result, phenotypic plasticity can accelerate tumor progression. A well-studied example of phenotypic plasticity is the bidirectional conversions among epithelial, mesenchymal, and hybrid epithelial/mesenchymal (E/M) phenotype(s). These conversions can alter a repertoire of cellular traits associated with multiple hallmarks of cancer, such as metabolism, immune evasion, invasion, and metastasis. To tackle the complexity and heterogeneity of these transitions, mathematical models have been developed that seek to capture the experimentally verified molecular mechanisms and act as ‘hypothesis-generating machines’. Here, we discuss how these quantitative mathematical models have helped us explain existing experimental data, guided further experiments, and provided an improved conceptual framework for understanding how multiple intracellular and extracellular signals can drive E/M plasticity at both the single-cell and population levels. We also discuss the implications of this plasticity in driving multiple aggressive facets of tumor progression

Proteomic risk markers for coronary heart disease and stroke: validation and mediation of randomized trial hormone therapy effects on these diseases

Background: We previously reported mass spectrometry-based proteomic discovery research to identify novel plasma proteins related to the risk of coronary heart disease (CHD) and stroke, and to identify proteins with concentrations affected by the use of postmenopausal hormone therapy. Here we report CHD and stroke risk validation studies for highly ranked proteins, and consider the extent to which protein concentration changes relate to disease risk or provide an explanation for hormone therapy effects on these outcomes. Methods: Five proteins potentially associated with CHD (beta-2 microglobulin (B2M), alpha-1-acid glycoprotein 1 (ORM1), thrombospondin-1(THBS1), complement factor D pre-protein (CFD), and insulin-like growth factor binding protein 1 (IGFBP1)) and five potentially associated with stroke (B2M, IGFBP2, IGFBP4, IGFBP6, and hemopexin (HPX)) had high discovery phase significance level ranking and an available ELISA assay, and were included in case-control validation studies within the Women’s Health Initiative (WHI) hormone therapy trials. Protein concentrations, at baseline and 1 year following randomization, were assessed for 358 CHD cases and 362 stroke cases, along with corresponding disease-free controls. Disease association, and mediation of estrogen-alone and estrogen plus progestin effects on CHD and stroke risk, were assessed using logistic regression. Results: B2M, THBS1, and CFD were confirmed (P <0.05) as novel CHD risk markers, and B2M, IGFBP2, and IGFBP4 were confirmed as novel stroke disease risk markers, while the assay for HPX proved to be unreliable. The change from baseline to 1 year in B2M was associated (P <0.05) with subsequent stroke risk, and trended similarly with subsequent CHD risk. Change from baseline to 1 year in IGFBP1 was also associated with CHD risk, and this change provided evidence of hormone therapy effect mediation. Conclusions: Plasma B2M is confirmed to be an informative risk marker for both CHD and stroke. The B2M increase experienced by women during the first year of hormone therapy trial participation conveys cardiovascular disease risk. The increase in IGFBP1 similarly conveys CHD risk, and the magnitude of the IGFBP1 increase following hormone therapy may be a mediator of hormone therapy effects. Plasma THBS1 and CFD are confirmed as CHD risk markers, and plasma IGFBP4 and IGFBP2 are confirmed as stroke risk markers. Clinical trials registration ClinicalTrials.gov identifier: NCT0000061

Moving forward with clinical proteomics

http://deepblue.lib.umich.edu/bitstream/2027.42/112773/1/12014_2007_Article_11003.pd

Distinguishing mechanisms underlying EMT tristability

Abstract Background The Epithelial-Mesenchymal Transition (EMT) endows epithelial-looking cells with enhanced migratory ability during embryonic development and tissue repair. EMT can also be co-opted by cancer cells to acquire metastatic potential and drug-resistance. Recent research has argued that epithelial (E) cells can undergo either a partial EMT to attain a hybrid epithelial/mesenchymal (E/M) phenotype that typically displays collective migration, or a complete EMT to adopt a mesenchymal (M) phenotype that shows individual migration. The core EMT regulatory network - miR-34/SNAIL/miR-200/ZEB1 - has been identified by various studies, but how this network regulates the transitions among the E, E/M, and M phenotypes remains controversial. Two major mathematical models – ternary chimera switch (TCS) and cascading bistable switches (CBS) - that both focus on the miR-34/SNAIL/miR-200/ZEB1 network, have been proposed to elucidate the EMT dynamics, but a detailed analysis of how well either or both of these two models can capture recent experimental observations about EMT dynamics remains to be done. Results Here, via an integrated experimental and theoretical approach, we first show that both these two models can be used to understand the two-step transition of EMT - E→E/M→M, the different responses of SNAIL and ZEB1 to exogenous TGF-β and the irreversibility of complete EMT. Next, we present new experimental results that tend to discriminate between these two models. We show that ZEB1 is present at intermediate levels in the hybrid E/M H1975 cells, and that in HMLE cells, overexpression of SNAIL is not sufficient to initiate EMT in the absence of ZEB1 and FOXC2. Conclusions These experimental results argue in favor of the TCS model proposing that miR-200/ZEB1 behaves as a three-way decision-making switch enabling transitions among the E, hybrid E/M and M phenotypes

Modeling the trend of Iraqi GDP for 1970-2020

The study of economic growth indicators is of fundamental importance in estimating the effectiveness of economic development plans, as well as the great role it plays in determining appropriate economic policies in order to optimally use the factors that lead to the dynamics of growth in Iraq, especially during a certain period of time. The gross domestic product (GDP) at current prices), which is considered a part of the national accounts, which is considered as an integrated dynamic of statistics that produces in front of policy makers the possibility of determining whether the economy is witnessing a state of expansion or evaluating economic activity and its efficiency in order to reach the size of the overall economy.The research aims to determine the best and most efficient statistical model to be used in forecasting the GDP in Iraq based on time series data for the period from (1970-2020) years. Where the general trend models (Linear trend, Quadratic trend and Exponential Trend) were applied, and the three models were compared to choose the best model using some statistical criteria, including the Akiaki Information Standard (AIC) and Schwartz Standard (SBS). The results showed that the appropriate model is the Quadratic trend model, were predicting and forecasting values are close to the real values of the GDP series

Association of Plasma CD163 Concentration with De Novo–Onset Chronic Graft-versus-Host Disease

Chronic graft-versus-host disease (GVHD) is the leading cause of long-term morbidity and mortality after allogeneic hematopoietic cell transplantation. To identify prognostic plasma proteins associated with de novo– or quiescent-onset chronic GVHD (cGVHD), we performed a discovery and validation proteomic study. The total study cohort included 167 consecutive patients who had no clinical evidence of GVHD under minimum glucocorticoid administration and had available plasma samples obtained at 80 ± 14 days after transplantation. We first used high-throughput mass spectrometry to screen pooled plasma using 20 cases with subsequent cGVHD and 20 controls without it, and we identified 20 candidate proteins. We then measured 12 of the 20 candidate proteins by ELISA on the same individual samples and identified 4 proteins for further verification (LGALS3BP, CD5L, CD163, and TXN for de novo onset, and LGALS3BP and CD5L for quiescent onset). The verification cohort included 127 remaining patients. The cumulative incidence of de novo–onset cGVHD was higher in patients with higher plasma soluble CD163 concentrations at day 80 than those with lower concentrations (75% versus 40%, P = .018). The cumulative incidence of de novo– or quiescent-onset cGVHD did not differ statistically according to concentrations of the 3 other proteins at day 80. CD163 is a macrophage scavenger receptor and is elevated in oxidative conditions. These results suggest that monocyte or macrophage activation or increased oxidative stress may contribute to the pathogenesis of cGVHD

Proteomics analysis reveals a Th17-prone cell population in presymptomatic graft-versus-host disease

Gastrointestinal graft-versus-host-disease (GI-GVHD) is a life-threatening complication occurring after allogeneic hematopoietic cell transplantation (HCT), and a blood biomarker that permits stratification of HCT patients according to their risk of developing GI-GVHD would greatly aid treatment planning. Through in-depth, large-scale proteomic profiling of presymptomatic samples, we identified a T cell population expressing both CD146, a cell adhesion molecule, and CCR5, a chemokine receptor that is upregulated as early as 14 days after transplantation in patients who develop GI-GVHD. The CD4+CD146+CCR5+ T cell population is Th17 prone and increased by ICOS stimulation. shRNA knockdown of CD146 in T cells reduced their transmigration through endothelial cells, and maraviroc, a CCR5 inhibitor, reduced chemotaxis of the CD4+CD146+CCR5+ T cell population toward CCL14. Mice that received CD146 shRNA-transduced human T cells did not lose weight, showed better survival, and had fewer CD4+CD146+CCR5+ T cells and less pathogenic Th17 infiltration in the intestine, even compared with mice receiving maraviroc with control shRNA- transduced human T cells. Furthermore, the frequency of CD4+CD146+CCR5+ Tregs was increased in GI-GVHD patients, and these cells showed increased plasticity toward Th17 upon ICOS stimulation. Our findings can be applied to early risk stratification, as well as specific preventative therapeutic strategies following HCT

Risk Assessment Model for Breast Cancer in Women Using MERIT Cohort Study

https://openworks.mdanderson.org/sumexp22/1121/thumbnail.jp