Impact of Chemical Endocrine Disruptors and Hormone Modulators on the Endocrine System

There is growing concern regarding the health and safety issues of endocrine-disrupting chemicals (EDCs). Long-term exposure to EDCs has alarming adverse health effects through both hormone-direct and hormone-indirect pathways. Non-chemical agents, including physical agents such as artificial light, radiation, temperature, and stress exposure, are currently poorly investigated, even though they can seriously affect the endocrine system, by modulation of hormonal action. Several mechanisms have been suggested to explain the interference of EDCs with hormonal activity. However, difficulty in quantifying the exposure, low standardization of studies, and the presence of confounding factors do not allow the establishment of a causal relationship between endocrine disorders and exposure to specific toxic agents. In this review, we focus on recent findings on the effects of EDCs and hormone system modulators on the endocrine system, including the thyroid, parathyroid glands, adrenal steroidogenesis, beta-cell function, and male and female reproductive function

Neural Attentive Session-based Recommendation

Given e-commerce scenarios that user profiles are invisible, session-based recommendation is proposed to generate recommendation results from short sessions. Previous work only considers the user's sequential behavior in the current session, whereas the user's main purpose in the current session is not emphasized. In this paper, we propose a novel neural networks framework, i.e., Neural Attentive Recommendation Machine (NARM), to tackle this problem. Specifically, we explore a hybrid encoder with an attention mechanism to model the user's sequential behavior and capture the user's main purpose in the current session, which are combined as a unified session representation later. We then compute the recommendation scores for each candidate item with a bi-linear matching scheme based on this unified session representation. We train NARM by jointly learning the item and session representations as well as their matchings. We carried out extensive experiments on two benchmark datasets. Our experimental results show that NARM outperforms state-of-the-art baselines on both datasets. Furthermore, we also find that NARM achieves a significant improvement on long sessions, which demonstrates its advantages in modeling the user's sequential behavior and main purpose simultaneously.Comment: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. arXiv admin note: text overlap with arXiv:1511.06939, arXiv:1606.08117 by other author

Equatorial Kelvin waves as revealed by EOS Microwave Limb Sounder observations and European Centre for Medium-Range Weather Forecasts analyses: Evidence for slow Kelvin waves of zonal wave number 3

[1] Temperature and ozone observations from the Microwave Limb Sounder (MLS) on the EOS Aura satellite are used to study equatorial wave activity in the autumn of 2005. In contrast to previous observations for the same season in other years, the temperature anomalies in the middle and lower tropical stratosphere are found to be characterized by a strong wave-like eastward progression with zonal wave number equal to 3. Extended empirical orthogonal function (EOF) analysis reveals that the wave 3 components detected in the temperature anomalies correspond to a slow Kelvin wave with a period of 8 days and a phase speed of 19 m/s. Fluctuations associated with this Kelvin wave mode are also apparent in ozone profiles. Moreover, as expected by linear theory, the ozone fluctuations observed in the lower stratosphere are in phase with the temperature perturbations, and peak around 20–30 hPa where the mean ozone mixing ratios have the steepest vertical gradient. A search for other Kelvin wave modes has also been made using both the MLS observations and the analyses from one experiment where MLS ozone profiles are assimilated into the European Centre for Medium-Range Weather Forecasts (ECMWF) data assimilation system via a 6-hourly 3D var scheme. Our results show that the characteristics of the wave activity detected in the ECMWF temperature and ozone analyses are in good agreement with MLS data

The Coupled Model Intercomparison Project (CMIP)

The Coupled Model Intercomparison Project (CMIP) was established to study and intercompare climate simulations made with coupled ocean-atmosphere-cryosphere-land GCMs. There are two main phases (CMIP1 and CMIP2), which study, respectively, 1) the ability of models to simulate current climate, and 2) model simulations of climate change due to an idealized change in forcing (a 1% per year CO2 increase). Results from a number of CMIP projects were reported at the first CMIP Workshop held in Melbourne, Australia, in October 1998. Some recent advances in global coupled modeling related to CMIP were also reported. Presentations were based on preliminary unpublished results. Key outcomes from the workshop were that 1) many observed aspects of climate variability are simulated in global coupled models including the North Atlantic oscillation and its linkages to North Atlantic SSTs, El Niño-like events, and monsoon interannual variability; 2) the amplitude of both high- and low-frequency global mean surface temperature variability in many global coupled models is less than that observed, with the former due in part to simulated ENSO in the models being generally weaker than observed, and the latter likely to be at least partially due to the uncertainty in the estimates of past radiative forcing; 3) an El Niño-like pattern in the mean SST response with greater surface warming in the eastern equatorial Pacific than the western equatorial Pacific is found by a number of models in global warming climate change experiments, but other models have a more spatially uniform or even a La Niña-like, response; 4) flux adjustment, by definition, improves the simulation of mean present-day climate over oceans, does not guarantee a drift-free climate, but can produce a stable base state in some models to enable very long term (1000 yr and longer) integrations-in these models it does not appear to have a major effect on model processes or model responses to increasing CO2; and 5) recent multicentury integrations show that a stable surface climate can be attained without flux adjustment (though still with some systematic simulation errors)

Comparing Smartphone Speech Recognition and Touchscreen Typing for Composition and Transcription

International audienceRuan et al. found transcribing short phrases with speech recognition nearly 200% faster than typing on a smartphone. We extend this comparison to a novel composition task, using a protocol that enables a controlled comparison with transcription. Results show that both composing and transcribing with speech is faster than typing. But, the magnitude of this difference is lower with composition, and speech has a lower error rate than keyboard during composition, but not during transcription. When transcribing, speech outperformed typing in most NASA-TLX measures, but when composing, there were no significant differences between typing and speech for any measure except physical demand

A randomised controlled trial linking mental health inpatients to community smoking cessation supports: A study protocol

<p>Abstract</p> <p>Background</p> <p>Mental health inpatients smoke at higher rates than the general population and are disproportionately affected by tobacco dependence. Despite the advent of smoke free policies within mental health hospitals, limited systems are in place to support a cessation attempt post hospitalisation, and international evidence suggests that most smokers return to pre-admission smoking levels following discharge. This protocol describes a randomised controlled trial that will test the feasibility, acceptability and efficacy of linking inpatient smoking care with ongoing community cessation support for smokers with a mental illness.</p> <p>Methods/Design</p> <p>This study will be conducted as a randomised controlled trial. 200 smokers with an acute mental illness will be recruited from a large inpatient mental health facility. Participants will complete a baseline survey and will be randomised to either a multimodal smoking cessation intervention or provided with hospital smoking care only. Randomisation will be stratified by diagnosis (psychotic, non-psychotic). Intervention participants will be provided with a brief motivational interview in the inpatient setting and options of ongoing smoking cessation support post discharge: nicotine replacement therapy (NRT); referral to Quitline; smoking cessation groups; and fortnightly telephone support. Outcome data, including cigarettes smoked per day, quit attempts, and self-reported 7-day point prevalence abstinence (validated by exhaled carbon monoxide), will be collected via blind interview at one week, two months, four months and six months post discharge. Process information will also be collected, including the use of cessation supports and cost of the intervention.</p> <p>Discussion</p> <p>This study will provide comprehensive data on the potential of an integrated, multimodal smoking cessation intervention for persons with an acute mental illness, linking inpatient with community cessation support.</p> <p>Trial Registration</p> <p>Australian and New Zealand Clinical Trials Registry ANZTCN: <a href="http://www.anzctr.org.au/ACTRN12609000465257.aspx">ACTRN12609000465257</a></p

Physical principles for scalable neural recoding

Simultaneously measuring the activities of all neurons in a mammalian brain at millisecond resolution is a challenge beyond the limits of existing techniques in neuroscience. Entirely new approaches may be required, motivating an analysis of the fundamental physical constraints on the problem. We outline the physical principles governing brain activity mapping using optical, electrical, magnetic resonance, and molecular modalities of neural recording. Focusing on the mouse brain, we analyze the scalability of each method, concentrating on the limitations imposed by spatiotemporal resolution, energy dissipation, and volume displacement. Based on this analysis, all existing approaches require orders of magnitude improvement in key parameters. Electrical recording is limited by the low multiplexing capacity of electrodes and their lack of intrinsic spatial resolution, optical methods are constrained by the scattering of visible light in brain tissue, magnetic resonance is hindered by the diffusion and relaxation timescales of water protons, and the implementation of molecular recording is complicated by the stochastic kinetics of enzymes. Understanding the physical limits of brain activity mapping may provide insight into opportunities for novel solutions. For example, unconventional methods for delivering electrodes may enable unprecedented numbers of recording sites, embedded optical devices could allow optical detectors to be placed within a few scattering lengths of the measured neurons, and new classes of molecularly engineered sensors might obviate cumbersome hardware architectures. We also study the physics of powering and communicating with microscale devices embedded in brain tissue and find that, while radio-frequency electromagnetic data transmission suffers from a severe power–bandwidth tradeoff, communication via infrared light or ultrasound may allow high data rates due to the possibility of spatial multiplexing. The use of embedded local recording and wireless data transmission would only be viable, however, given major improvements to the power efficiency of microelectronic devices

Effect of age, sex and gender on pain sensitivity: A narrative review

© 2017 Eltumi And Tashani. Introduction: An increasing body of literature on sex and gender differences in pain sensitivity has been accumulated in recent years. There is also evidence from epidemiological research that painful conditions are more prevalent in older people. The aim of this narrative review is to critically appraise the relevant literature investigating the presence of age and sex differences in clinical and experimental pain conditions. Methods: A scoping search of the literature identifying relevant peer reviewed articles was conducted on May 2016. Information and evidence from the key articles were narratively described and data was quantitatively synthesised to identify gaps of knowledge in the research literature concerning age and sex differences in pain responses. Results: This critical appraisal of the literature suggests that the results of the experimental and clinical studies regarding age and sex differences in pain contain some contradictions as far as age differences in pain are concerned. While data from the clinical studies are more consistent and seem to point towards the fact that chronic pain prevalence increases in the elderly findings from the experimental studies on the other hand were inconsistent, with pain threshold increasing with age in some studies and decreasing with age in others. Conclusion: There is a need for further research using the latest advanced quantitative sensory testing protocols to measure the function of small nerve fibres that are involved in nociception and pain sensitivity across the human life span. Implications: Findings from these studies should feed into and inform evidence emerging from other types of studies (e.g. brain imaging technique and psychometrics) suggesting that pain in the older humans may have unique characteristics that affect how old patients respond to intervention

Metabolic comorbidities of adrenal insufficiency: Focus on steroid replacement therapy and chronopharmacology.

Adrenal insufficiency (AI) is characterized by higher mortality and morbidity compared with the general population. Conventional replacement steroid therapy, currently recommended for the treatment of AI, is associated with increased frequency of metabolic comorbidities due to daily overexposure. By contrast, dual-release hydrocortisone is associated with a decreased risk of metabolic comorbidities, providing an adequate release of hydrocortisone and mimicking the physiological profile of cortisol. These favorable effects are due to a reduced daily steroid exposure that does not affect the expression of the clock genes which are involved in metabolic pathways and are regulated by the normal physiological circadian rhythm of endogenous cortisol. This narrative review focuses on the possible metabolic comorbidities of AI due to steroid replacement therapy, which evaluates the effects of conventional and novel drugs with attention to chronopharmacology