Effect of melatonin in reducing second-generation antipsychotic metabolic effects: A double blind controlled clinical trial

Introduction The use of second-generation atypical antipsychotics has an increasing role in the development of metabolic syndrome. However, these medications due to metabolic disorders can lead to an increased risk of cardiovascular disease and subsequently mortality as well as reduced adherence to treatment. The main objective of current study was to determine the ability of melatonin to reduce the metabolic effects of second-generation antipsychotics. Methods This double blind controlled clinical trial was conducted on 100 patients aged 18–64 years old were treated with the second-generation antipsychotics for the first time. The patients were divided randomly into two groups of 50. The case group received slow-release melatonin at a dose of 3 mg and the control group was given oral placebo at 8 p.m. Results The findings in melatonin group indicated significantly increase of HDL and decreased fasting blood sugar and systolic blood pressure, as well as had statistically significant increase in waist circumference, weight and BMI compared with placebo group. Conclusion According to the findings, it can be claimed that the addition of melatonin to atypical antipsychotics has led to a reduction in some of the metabolic effects of these drugs. In this study, HDL level was increased, and the mean systolic blood pressure and FBS were decreased in the melatonin group. Considering that these factors are contributing to cardiovascular disease as a leading cause of mortality in psychiatric patients, so the use of melatonin can reduce some of the medical effects of long-term treatment of atypical antipsychotics. © 2017 Diabetes Indi

Evaluating equality in prescribing Novel Oral Anticoagulants (NOACs) in England: the protocol of a Bayesian small area analysis

Background Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting about 1.6% of the population in England. Novel oral anticoagulants (NOACs) are approved AF treatments that reduce stroke risk. In this study, we estimate the equality in individual NOAC prescriptions with high spatial resolution in Clinical Commissioning Groups (CCGs) across England from 2014 to 2019. Methods A Bayesian spatio-temporal model will be used to estimate and predict the individual NOAC prescription trend on ‘prescription data’ as an indicator of health services utilisation, using a small area analysis methodology. The main dataset in this study is the “Practice Level Prescribing in England,” which contains four individual NOACs prescribed by all registered GP practices in England. We will use the defined daily dose (DDD) equivalent methodology, as recommended by the World Health Organization (WHO), to compare across space and time. Four licensed NOACs datasets will be summed per 1,000 patients at the CCG-level over time. We will also adjust for CCG-level covariates, such as demographic data, Multiple Deprivation Index, and rural-urban classification. We aim to employ the extended BYM2 model (space-time model) using the RStan package. Discussion This study suggests a new statistical modelling approach to link prescription and socioeconomic data to model pharmacoepidemiologic data. Quantifying space and time differences will allow for the evaluation of inequalities in the prescription of NOACs. The methodology will help develop geographically targeted public health interventions, campaigns, audits, or guidelines to improve areas of low prescription. This approach can be used for other medications, especially those used for chronic diseases that must be monitored over time

Specific heat and magnetocaloric effect in Pr1-xAgxMnO3 manganites

The magnetocaloric effect in alternating magnetic fields has been investigated in Pr1-xAgxMnO3 manganites with x=0.05-0.25. The stepwise reversal of the sign of the magnetocaloric effect has been revealed in a weakly doped sample (x=0.05) at low temperatures (~80 K). This reversal is attributed to the coexistence of the ferromagnetic and canted antiferromagnetic phases with different critical temperatures.Comment: 4 pages, 4 figure

Geographical and socioeconomic inequalities in female breast cancer incidence and mortality in Iran: A Bayesian spatial analysis of registry data

Background In Iran, trends in breast cancer incidence and mortality have generally been monitored at national level. The purpose of this study is to examine province-level disparities in age-standardised breast cancer incidence versus mortality from 2000 to 2010 and their association with socioeconomic status. Methods In this study, data from Iran’s national cancer and death registry systems, and covariates from census and household expenditure surveys were used. We estimated the age-standardised incidence and mortality rates in women aged more than 30 years for all 31 provinces in the consecutive time intervals 2000–2003, 2004–2007 and 2008–2010 using a Bayesian spatial model. Results Mean age-standardised breast cancer incidence across provinces increased over time from 15.0 per 100,000 people (95% credible interval 12.0,18.3) in 2000–2003 to 39.6 (34.5,45.1) in 2008–2010. The mean breast cancer mortality rate declined from 10.9 (8.3,13.8) to 9.9 (7.5,12.5) deaths per 100,000 people in the same period. When grouped by wealth index quintiles, provinces in the highest quintile had higher levels of incidence and mortality. In the wealthiest quintile, reductions in mortality over time were larger than those observed among provinces in the poorest quintile. Relative breast cancer mortality decreased by 16.7% in the highest quintile compared to 10.8% in the lowest quintile. Conclusions Breast cancer incidence has increased over time, with lower incidence in the poorest provinces likely driven by underdiagnoses or late-stage diagnosis. Although the reported mortality rate is still higher in wealthier provinces, the larger decline over time in these provinces indicates a possible future reversal, with the most deprived provinces having higher mortality rates. Ongoing analysis of incidence and mortality at sub-national level is crucial in addressing inequalities in healthcare systems and public health both in Iran and elsewhere

Quantifying the Effects of Prosody Modulation on User Engagement and Satisfaction in Conversational Systems

As voice-based assistants such as Alexa, Siri, and Google Assistant become ubiquitous, users increasingly expect to maintain natural and informative conversations with such systems. However, for an open-domain conversational system to be coherent and engaging, it must be able to maintain the user's interest for extended periods, without sounding boring or annoying. In this paper, we investigate one natural approach to this problem, of modulating response prosody, i.e., changing the pitch and cadence of the response to indicate delight, sadness or other common emotions, as well as using pre-recorded interjections. Intuitively, this approach should improve the naturalness of the conversation, but attempts to quantify the effects of prosodic modulation on user satisfaction and engagement remain challenging. To accomplish this, we report results obtained from a large-scale empirical study that measures the effects of prosodic modulation on user behavior and engagement across multiple conversation domains, both immediately after each turn, and at the overall conversation level. Our results indicate that the prosody modulation significantly increases both immediate and overall user satisfaction. However, since the effects vary across different domains, we verify that prosody modulations do not substitute for coherent, informative content of the responses. Together, our results provide useful tools and insights for improving the naturalness of responses in conversational systems.Comment: Published in CHIIR 2020, 4 page

Offline and Online Satisfaction Prediction in Open-Domain Conversational Systems

Predicting user satisfaction in conversational systems has become critical, as spoken conversational assistants operate in increasingly complex domains. Online satisfaction prediction (i.e., predicting satisfaction of the user with the system after each turn) could be used as a new proxy for implicit user feedback, and offers promising opportunities to create more responsive and effective conversational agents, which adapt to the user's engagement with the agent. To accomplish this goal, we propose a conversational satisfaction prediction model specifically designed for open-domain spoken conversational agents, called ConvSAT. To operate robustly across domains, ConvSAT aggregates multiple representations of the conversation, namely the conversation history, utterance and response content, and system- and user-oriented behavioral signals. We first calibrate ConvSAT performance against state of the art methods on a standard dataset (Dialogue Breakdown Detection Challenge) in an online regime, and then evaluate ConvSAT on a large dataset of conversations with real users, collected as part of the Alexa Prize competition. Our experimental results show that ConvSAT significantly improves satisfaction prediction for both offline and online setting on both datasets, compared to the previously reported state-of-the-art approaches. The insights from our study can enable more intelligent conversational systems, which could adapt in real-time to the inferred user satisfaction and engagement.Comment: Published in CIKM '19, 10 page

Laboratory-based and office-based risk scores and charts to predict 10-year risk of cardiovascular disease in 182 countries: a pooled analysis of prospective cohorts and health surveys

Background: Worldwide implementation of risk-based cardiovascular disease (CVD) prevention requires risk prediction tools that are contemporarily recalibrated for the target country and can be used where laboratory measurements are unavailable. We present two cardiovascular risk scores, with and without laboratory-based measurements, and the corresponding risk charts for 182 countries to predict 10-year risk of fatal and non-fatal CVD in adults aged 40–74 years. Methods: Based on our previous laboratory-based prediction model (Globorisk), we used data from eight prospective studies to estimate coefficients of the risk equations using proportional hazard regressions. The laboratory-based risk score included age, sex, smoking, blood pressure, diabetes, and total cholesterol; in the non-laboratory (office-based) risk score, we replaced diabetes and total cholesterol with BMI. We recalibrated risk scores for each sex and age group in each country using country-specific mean risk factor levels and CVD rates. We used recalibrated risk scores and data from national surveys (using data from adults aged 40–64 years) to estimate the proportion of the population at different levels of CVD risk for ten countries from different world regions as examples of the information the risk scores provide; we applied a risk threshold for high risk of at least 10% for high-income countries (HICs) and at least 20% for low-income and middle-income countries (LMICs) on the basis of national and international guidelines for CVD prevention. We estimated the proportion of men and women who were similarly categorised as high risk or low risk by the two risk scores. Findings: Predicted risks for the same risk factor profile were generally lower in HICs than in LMICs, with the highest risks in countries in central and southeast Asia and eastern Europe, including China and Russia. In HICs, the proportion of people aged 40–64 years at high risk of CVD ranged from 1% for South Korean women to 42% for Czech men (using a ≥10% risk threshold), and in low-income countries ranged from 2% in Uganda (men and women) to 13% in Iranian men (using a ≥20% risk threshold). More than 80% of adults were similarly classified as low or high risk by the laboratory-based and office-based risk scores. However, the office-based model substantially underestimated the risk among patients with diabetes. Interpretation: Our risk charts provide risk assessment tools that are recalibrated for each country and make the estimation of CVD risk possible without using laboratory-based measurements

Contributions of mean and shape of blood pressure distribution to worldwide trends and variations in raised blood pressure: A pooled analysis of 1018 population-based measurement studies with 88.6 million participants

Background: Change in the prevalence of raised blood pressure could be due to both shifts in the entire distribution of blood pressure (representing the combined effects of public health interventions and secular trends) and changes in its high-blood-pressure tail (representing successful clinical interventions to control blood pressure in the hypertensive population). Our aim was to quantify the contributions of these two phenomena to the worldwide trends in the prevalence of raised blood pressure. Methods: We pooled 1018 population-based studies with blood pressure measurements on 88.6 million participants from 1985 to 2016. We first calculated mean systolic blood pressure (SBP), mean diastolic blood pressure (DBP) and prevalence of raised blood pressure by sex and 10-year age group from 20-29 years to 70-79 years in each study, taking into account complex survey design and survey sample weights, where relevant. We used a linear mixed effect model to quantify the association between (probittransformed) prevalence of raised blood pressure and age-group- and sex-specific mean blood pressure. We calculated the contributions of change in mean SBP and DBP, and of change in the prevalence-mean association, to the change in prevalence of raised blood pressure. Results: In 2005-16, at the same level of population mean SBP and DBP, men and women in South Asia and in Central Asia, the Middle East and North Africa would have the highest prevalence of raised blood pressure, and men and women in the highincome Asia Pacific and high-income Western regions would have the lowest. In most region-sex-age groups where the prevalence of raised blood pressure declined, one half or more of the decline was due to the decline in mean blood pressure. Where prevalence of raised blood pressure has increased, the change was entirely driven by increasing mean blood pressure, offset partly by the change in the prevalence-mean association. Conclusions: Change in mean blood pressure is the main driver of the worldwide change in the prevalence of raised blood pressure, but change in the high-blood-pressure tail of the distribution has also contributed to the change in prevalence, especially in older age groups

Cosmological phase transitions in warped space: gravitational waves and collider signatures

We study the electroweak phase transition within a 5D warped model including a scalar potential with an exponential behavior, and strong back-reaction over the metric, in the infrared. By means of a novel treatment of the superpotential formalism, we explore parameter regions that were previously inaccessible. We nd that for large enough values of the t'Hooft parameter (e.g. N = 25) the holographic phase transition occurs, and it can force the Higgs to undergo a rst order electroweak phase transition, suitable for electroweak baryogenesis. The model exhibits gravitational waves and colliders signatures. It typically predicts a stochastic gravitational wave background observable both at the Laser Interferometer Space Antenna and at the Einstein Telescope. Moreover the radion tends to be heavy enough such that it evades current constraints, but may show up in future LHC runs.The work of EM is supported by the Spanish MINEICO under Grant FPA2015-64041-C2-1-P and FIS2017-85053-C2-1-P, by the Junta de Andaluc a under Grant FQM-225, by the Basque Government under Grant IT979-16, and by the Spanish Consolider Ingenio 2010 Programme CPAN (CSD2007-00042). The research of EM is also supported by the Ram on y Cajal Program of the Spanish MINEICO, and by the Universidad del Pa s Vasco UPV/EHU, Bilbao, Spain, as a Visiting Professor. GN is supported by the Swiss National Science Foundation (SNF) under grant 200020-168988. The work of MQ is partly supported by Spanish MINEICO under Grant CICYT-FEDER-FPA2014- 55613-P and FPA2017-88915-P, by the Severo Ochoa Excellence Program of MINEICO under Grant SEV-2016-0588, and by CNPq PVE fellowship project 405559/2013-5

Single domain antibodies: promising experimental and therapeutic tools in infection and immunity

Antibodies are important tools for experimental research and medical applications. Most antibodies are composed of two heavy and two light chains. Both chains contribute to the antigen-binding site which is usually flat or concave. In addition to these conventional antibodies, llamas, other camelids, and sharks also produce antibodies composed only of heavy chains. The antigen-binding site of these unusual heavy chain antibodies (hcAbs) is formed only by a single domain, designated VHH in camelid hcAbs and VNAR in shark hcAbs. VHH and VNAR are easily produced as recombinant proteins, designated single domain antibodies (sdAbs) or nanobodies. The CDR3 region of these sdAbs possesses the extraordinary capacity to form long fingerlike extensions that can extend into cavities on antigens, e.g., the active site crevice of enzymes. Other advantageous features of nanobodies include their small size, high solubility, thermal stability, refolding capacity, and good tissue penetration in vivo. Here we review the results of several recent proof-of-principle studies that open the exciting perspective of using sdAbs for modulating immune functions and for targeting toxins and microbes