Study on the short-term effects of increased alcohol and cigarette consumption in healthy young men's seminal quality

Many studies have reported a negative impact of lifestyle factors on testicular function, spermatozoa parameters and pituitary-gonadal axis. However, conclusions are difficult to draw, since studies in the general population are rare. In this study we intended to address the early and late short-term impact of acute lifestyle alterations on young men's reproductive function. Thirty-six healthy male students, who attended the Portuguese academic festivities, provided semen samples and answered questionnaires at three time-points. The consumption of alcohol and cigarette increased more than 8 and 2 times, respectively, during the academic festivities and resulted in deleterious effects on semen quality: one week after the festivities, a decrease on semen volume, spermatozoa motility and normal morphology was observed, in parallel with an increase on immotile spermatozoa, head and midpiece defects and spermatozoa oxidative stress. Additionally, three months after the academic festivities, besides the detrimental effect on volume, motility and morphology, a negative impact on spermatozoa concentration was observed, along with a decrease on epididymal, seminal vesicles and prostate function. This study contributed to understanding the pathophysiology underlying semen quality degradation induced by acute lifestyle alterations, suggesting that high alcohol and cigarette consumption are associated with decreased semen quality in healthy young men.publishe

Genotoxicity of metal oxide nanomaterials: review of recent data and discussion of possible mechanisms

Nanotechnology has rapidly entered into human society, revolutionized many areas, including technology, medicine and cosmetics. This progress is due to the many valuable and unique properties that nanomaterials possess. In turn, these properties might become an issue of concern when considering potentially uncontrolled release to the environment. The rapid development of new nanomaterials thus raises questions about their impact on the environment and human health. This review focuses on the potential of nanomaterials to cause genotoxicity and summarizes recent genotoxicity studies on metal oxide/silica nanomaterials. Though the number of genotoxicity studies on metal oxide/silica nanomaterials is still limited, this endpoint has recently received more attention for nanomaterials, and the number of related publications has increased. An analysis of these peer reviewed publications over nearly two decades shows that the test most employed to evaluate the genotoxicity of these nanomaterials is the comet assay, followed by micronucleus, Ames and chromosome aberration tests. Based on the data studied, we concluded that in the majority of the publications analysed in this review, the metal oxide (or silica) nanoparticles of the same core chemical composition did not show different genotoxicity study calls (i.e. positive or negative) in the same test, although some results are inconsistent and need to be confirmed by additional experiments. Where the results are conflicting, it may be due to the following reasons: (1) variation in size of the nanoparticles; (2) variations in size distribution; (3) various purities of nanomaterials; (4) variation in surface areas for nanomaterials with the same average size; (5) differences in coatings; (6) differences in crystal structures of the same types of nanomaterials; (7) differences in size of aggregates in solution/media; (8) differences in assays; (9) different concentrations of nanomaterials in assay tests. Indeed, due to the observed inconsistencies in the recent literature and the lack of adherence to appropriate, standardized test methods, reliable genotoxicity assessment of nanomaterials is still challenging

Suitable waves for bender element tests: Interpretations, errors and modelling aspects

© 2016, Technical University of Budapest. All rights reserved.Extensive research on bender element tests has been carried out by many researchers, but precise guidelines for carrying out such tests have not yet been established. It is often recommended that, when using a particular bender element test for the first time on a particular soil to determine its small strain dynamic properties, several methods should be tried and the results compared in order to improve confidence in the results obtained. Demonstrated use of relatively easy analytical models for investigating different scenarios of bender element testing is another aspect that should be further looked into. This paper presents laboratory experiments and dynamic finite element analyses to determine a suitable wave for use in bender element tests in the laboratory to measure small strain shear stiffness (Gmax). The suitability of a distorted sine wave over a continuous sine wave for tests is observed from laboratory experiments and dynamic finite element analyses. The use of simple finite element models for assessing a number of aspects in relation to bender element testing is demonstrated

Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations Differ (Abstract Reprint)

Counterfactual explanations have emerged as a popular solution for the eXplainable AI (XAI) problem of elucidating the predictions of black-box deep-learning systems because people easily understand them, they apply across different problem domains and seem to be legally compliant. Although over 100 counterfactual methods exist in the XAI literature, each claiming to generate plausible explanations akin to those preferred by people, few of these methods have actually been tested on users (∼7%). Even fewer studies adopt a user-centered perspective; for instance, asking people for their counterfactual explanations to determine their perspective on a “good explanation”. This gap in the literature is addressed here using a novel methodology that (i) gathers human-generated counterfactual explanations for misclassified images, in two user studies and, then, (ii) compares these human-generated explanations to computationally-generated explanations for the same misclassifications. Results indicate that humans do not “minimally edit” images when generating counterfactual explanations. Instead, they make larger, “meaningful” edits that better approximate prototypes in the counterfactual class. An analysis based on “explanation goals” is proposed to account for this divergence between human and machine explanations. The implications of these proposals for future work are discussed