Safety review of phenoxyethanol when used as a preservative in cosmetics

Phenoxyethanol, or 2-phenoxyethanol, has a large spectrum of antimicrobial activity and has been widely used as a preservative in cosmetic products for decades. It is effective against various Gram-negative and Gram-positive bacteria, as well as against yeasts, and has only a weak inhibitory effect on resident skin flora. According to the European Scientific Committee on Consumer Safety, phenoxyethanol is safe for all consumers \u2013 including children of all ages \u2013 when used as a preservative in cosmetic products at a maximum concentration of 1%. Adverse systemic effects have been observed in toxicological studies on animals but only when the levels of exposure were many magnitudes higher (around 200-fold higher) than those to which consumers are exposed when using phenoxyethanol-containing cosmetic products. Despite its widespread use in cosmetic products, phenoxyethanol is a rare sensitizer. It can be considered as one of the most well-tolerated preservatives used in cosmetic products

Rhus coriaria l. Fruit extract prevents UV-A-induced genotoxicity and oxidative injury in human microvascular endothelial cells

Rhus coriaria L. (sumac) is a small plant widely diffused in the Mediterranean region. Its fruit are often consumed as a spice but are also present in traditional medicine of several countries. Recently, interest in this plant has increased and many scientific works reported its beneficial effects including antioxidant and anti-inflammatory properties. Plant extracts can be successfully used against ultraviolet rays, which are able to reach and damage the human skin; however, sumac extracts were never applied to this usage. Thus, in this study, we used a macerated ethanol extract of Rhus coriaria L. dried fruit (mERC) to demonstrate its preventive role against the damage induced by ultraviolet-A rays (UV-A) on microvascular endothelial cells (HMEC-1). In vitro effects of the extract pre-treatment and UV-A exposure were evaluated in detail. The antioxidant capacity was assessed by reactive oxygen species (ROS) formation and cellular antioxidant activity measurement. Genoprotective effects of mERC were investigated as well. Our findings indicate that the extract acts as a cell cycle inhibitor or apoptosis inducer, according to the level of damage. The present work provides new insights into the usage of Rhus coriaria extracts against skin injuries

Early prediction of pathologic response to neoadjuvant therapy in breast cancer: Systematic review of the accuracy of MRI

Abstract Magnetic resonance imaging (MRI) has been proposed to have a role in predicting final pathologic response when undertaken early during neoadjuvant chemotherapy (NAC) in breast cancer. This paper examines the evidence for MRI's accuracy in early response prediction. A systematic literature search (to February 2011) was performed to identify studies reporting the accuracy of MRI during NAC in predicting pathologic response, including searches of MEDLINE, PREMEDLINE, EMBASE, and Cochrane databases. 13 studies were eligible (total 605 subjects, range 16–188). Dynamic contrast-enhanced (DCE) MRI was typically performed after 1–2 cycles of anthracycline-based or anthracycline/taxane-based NAC, and compared to a pre-NAC baseline scan. MRI parameters measured included changes in uni- or bidimensional tumour size, three-dimensional volume, quantitative dynamic contrast measurements (volume transfer constant [Ktrans], exchange rate constant [ k ep ], early contrast uptake [ECU]), and descriptive patterns of tumour reduction. Thresholds for identifying response varied across studies. Definitions of response included pathologic complete response (pCR), near-pCR, and residual tumour with evidence of NAC effect (range of response 0–58%). Heterogeneity across MRI parameters and the outcome definition precluded statistical meta-analysis. Based on descriptive presentation of the data, sensitivity/specificity pairs for prediction of pathologic response were highest in studies measuring reductions in Ktrans (near-pCR), ECU (pCR, but not near-pCR) and tumour volume (pCR or near-pCR), at high thresholds (typically >50%); lower sensitivity/specificity pairs were evident in studies measuring reductions in uni- or bidimensional tumour size. However, limitations in study methodology and data reporting preclude definitive conclusions. Methods proposed to address these limitations include: statistical comparison between MRI parameters, and MRI vs other tests (particularly ultrasound and clinical examination); standardising MRI thresholds and pCR definitions; and reporting changes in NAC based on test results. Further studies adopting these methods are warranted

The racist bodily imaginary: the image of the body-in-pieces in (post)apartheid culture

This paper outlines a reoccurring motif within the racist imaginary of (post)apartheid culture: the black body-in-pieces. This disturbing visual idiom is approached from three conceptual perspectives. By linking ideas prevalent in Frantz Fanon’s description of colonial racism with psychoanalytic concepts such as Lacan’s notion of the corps morcelé, the paper offers, firstly, an account of the black body-in-pieces as fantasmatic preoccupation of the (post)apartheid imaginary. The role of such images is approached, secondly, through the lens of affect theory which eschews a representational ‘reading’ of such images in favour of attention to their asignifying intensities and the role they play in effectively constituting such bodies. Lastly, Judith Butler’s discussion of war photography and the conditions of grievability introduces an ethical dimension to the discussion and helps draw attention to the unsavory relations of enjoyment occasioned by such images

Effetti tossicologici del particolato ultrafine emesso da impianti residenziali a biomassa : note sul progetto TOBICUP

This work summarises the main findings of the TOBICUP (Toxicity of BIomass Combustion generated Ultrafine Particles) project. The project has investigated the physio-chemical features and toxicological response of ultrafine particles (UFPs) from biomass-fuelled domestic stoves. Experimental determinations consider both UFP samples collected at the stack of wood log and pellet stoves and environmental samples collected at a site where biomass burning for domestic heating is the main source of airborne UFPs. Results for the stack samples show that combustion in pellet stoves is more complete, producing UFPs that determine toxicological responses per unit input energy less relevant compared with wood log stoves. Results for the environmental samples show a larger contribution from domestic heating to airborne UFPs in wintertime, traced by the higher content of levoglucosan and potassium than in summertime. However,toxicological response are influenced by the different reactivity of the atmosphere at seasonal level: in wintertime, genotoxic effects prevail due to the larger concentration of PAH and levoglucosan; in summertime, pro-inflammatory effects are more relevant due to the higher degree of oxidation of UFPs, favoured by the stronger photochemical processes occurring in the warm season

Age-related decline in RACK-1 expression in human leukocytes is correlated to plasma levels of dehydroepiandrosterone

Aging is associated with remodeling of the immune system, contributing to increased incidence of infections, autoimmune diseases, and cancer among the elderly. Alterations in several signal transduction pathways have been reported to play an important role in immunosenescence. We show that peripheral blood leukocytes obtained from old donors ((greater-than or equal to)65 years) have a significantly reduced expression of receptor for activated C kinase 1 (RACK-1), a protein required for protein kinase C (PKC)-(beta) signaling, as compared with young donors ((less-than or equal to)40 years), both in males and females. The decline in RACK-1 immunoboth in reactivity was age-related (Spearman correlation, r=-0.278, P=0.012). All leukocyte subpopulations, namely lympho-monocytes, granulocytes, and B and T cells, showed a similar defect. We also observed a direct correlation between circulating dehydroepiandrosterone (DHEA) and RACK-1 expression in leukocytes (Spearman correlation, r=0.388, P=0.001). Furthermore, in vitro treatment with DHEA resulted in increased RACK-1 expression in leukocytes and lymphocyte proliferation, confirming the role of this hormone in the modulation of its expression and immune functions. A relevant consequence of RACK-1-reduced expression was the observation that release of tumor necrosis factor (alpha) following lipopolysaccharide challenge and mitogen-induced lymphocye proliferation, which involves PKC-(beta) activation, was significantly reduced in elderly subjects. Overall, our findings contribute to the understanding of the complex process of immunosenescence and identify age-related loss in immunological responses as partially associated with decreased RACK-1 expression. (copyright) Society for Leukocyte Biology

Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980–2015

Quantification of stillbirth risk has potential to support clinical decision-making. Studies that have attempted to quantify stillbirth risk have been hampered by small event rates, a limited range of predictors that typically exclude obstetric history, lack of validation, and restriction to a single classifier (logistic regression). Consequently, predictive performance remains low, and risk quantification has not been adopted into antenatal practice. The study population consisted of all births to women in Western Australia from 1980 to 2015, excluding terminations. After all exclusions there were 947,025 livebirths and 5,788 stillbirths. Predictive models for stillbirth were developed using multiple machine learning classifiers: regularised logistic regression, decision trees based on classification and regression trees, random forest, extreme gradient boosting (XGBoost), and a multilayer perceptron neural network. We applied 10-fold cross-validation using independent data not used to develop the models. Predictors included maternal socio-demographic characteristics, chronic medical conditions, obstetric complications and family history in both the current and previous pregnancy. In this cohort, 66% of stillbirths were observed for multiparous women. The best performing classifier (XGBoost) predicted 45% (95% CI: 43%, 46%) of stillbirths for all women and 45% (95% CI: 43%, 47%) of stillbirths after the inclusion of previous pregnancy history. Almost half of stillbirths could be potentially identified antenatally based on a combination of current pregnancy complications, congenital anomalies, maternal characteristics, and medical history. Greatest sensitivity is achieved with addition of current pregnancy complications. Ensemble classifiers offered marginal improvement for prediction compared to logistic regression

Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980–2015

Quantification of stillbirth risk has potential to support clinical decision-making. Studies that have attempted to quantify stillbirth risk have been hampered by small event rates, a limited range of predictors that typically exclude obstetric history, lack of validation, and restriction to a single classifier (logistic regression). Consequently, predictive performance remains low, and risk quantification has not been adopted into antenatal practice. The study population consisted of all births to women in Western Australia from 1980 to 2015, excluding terminations. After all exclusions there were 947,025 livebirths and 5,788 stillbirths. Predictive models for stillbirth were developed using multiple machine learning classifiers: regularised logistic regression, decision trees based on classification and regression trees, random forest, extreme gradient boosting (XGBoost), and a multilayer perceptron neural network. We applied 10-fold cross-validation using independent data not used to develop the models. Predictors included maternal socio-demographic characteristics, chronic medical conditions, obstetric complications and family history in both the current and previous pregnancy. In this cohort, 66% of stillbirths were observed for multiparous women. The best performing classifier (XGBoost) predicted 45% (95% CI: 43%, 46%) of stillbirths for all women and 45% (95% CI: 43%, 47%) of stillbirths after the inclusion of previous pregnancy history. Almost half of stillbirths could be potentially identified antenatally based on a combination of current pregnancy complications, congenital anomalies, maternal characteristics, and medical history. Greatest sensitivity is achieved with addition of current pregnancy complications. Ensemble classifiers offered marginal improvement for prediction compared to logistic regression