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We aimed to evaluate patient preferences towards three oral antihyperglycaemic therapies using conjoint analysis to determine which attributes may influence use.We used an online survey, completed by 553 US respondents with type 2 diabetes mellitus (T2DM; mean age 64 ± 9 years; 55% had cardiovascular [CV] risk; 27% had CV disease), to present hypothetical, blinded, pairwise, drug profile comparison choices, between different benefit/risk attributes and effect ranges. Attributes were derived from phase 3 trials for empagliflozin 25 mg (SGLT2 inhibitor), oral semaglutide 14 mg (GLP-1 receptor agonist) and sitagliptin 100 mg (DPP-4 inhibitor). Predicted therapy preference outcomes and relative importance of each attribute were calculated (presented as a percentage).Preference score was highest for the profile matching empagliflozin (56%), versus sitagliptin (38%; z-test, P 0.001) and oral semaglutide (6%, z-test, P 0.001). Results were overall consistent in subgroup analyses. Genital infection risk was the most important attribute (relative score: 19% [z-test, P = 0.077]). Other important attributes were fasting requirements (15%), weight reduction (15%), risk of vomiting (14%), CV benefit (12%), and risk of nausea (11%). HbA1c reduction (8%) and ability to take medication with other drugs (6%) were considered less important. While blinded to drug name/dose, respondents chose a drug profile similar to empagliflozin (41%) versus sitagliptin (31%), oral semaglutide (11%), or 'none of the options' (17%).While the drug profile comparable to empagliflozin was preferred, CV benefit was not the top patient priority. A shared physician-patient decision model and increased patient education are needed to ensure optimal use of guideline-directed T2DM therapies.

The Thrombolysis in Myocardial Infarction Risk Score for Heart Failure (HF) in Diabetes (TRS-HFThe TRS-HFIn total, HF hospitalization occurred in 193 (3.6%) patients. Based on the TRS-HFThe TRS-HF

Chronic post-thoracotomy pain (PTPS) is a frequent complication of thoracic operations. Sometimes the pain is excruciating enough to impair activities of daily living (ADL). All thoracic procedures have the potential to cause trauma to the intercostal nerves due to retractor use, chest closure techniques, and or wound healing. In our study, we analyzed the microscopic aspects of the nerves involved in the healing process, to better understand the histopathology of chronic pain.29 patients with PTPS underwent intercostal neurectomy to alleviate the symptoms. Microscopic specimens harvested during the surgeries were sent to our pathology unit for evaluation. The following data regarding the surgical procedures was collected: surgical approach, chest closure type, number of excised nerves, and time interval from previous surgery to neurectomy.A mean of 2.34±1.11 nerves were excised. Microscopy of the specimens revealed: fibrosis, hyalinization of the epineurium and perineurium, intense hyperemia of the blood capillaries, and interstitial edema. 7 cases presented with myxoid degeneration of epineurium and perineurium. In all the cases, endoneurium, myelin sheaths, and axons were interrupted. The endoneurium showed the presence of hyperemic dilated capillaries. The segmental cytoplasmic vacuolization of Schwann's cells with the total disappearance of axons was also noted. 60% of the examined specimens had intraneural myxoid degeneration, with highly dense irregular connective tissue around nerve fibers.The pathologic findings in the structure of the intercostal nerves obtained from the patients are indicative of the involvement of the wound healing mechanisms in PTPS. The negative impact of wound healing could be considered a key component in the development of intense chronic pain.

No abstract available.

BACKGROUND The COVID-19 pandemic has disrupted the health care system, limiting health care resources such as the availability of health care professionals, patient monitoring, contact tracing, and continuous surveillance. As a result of this significant burden, digital tools have become an important asset in increasing the efficiency of patient care delivery. Digital tools can help support health care institutions by tracking transmission of the virus, aiding in the screening process, and providing telemedicine support. However, digital health tools face challenges associated with barriers to accessibility, efficiency, and privacy-related ethical issues. OBJECTIVE This paper describes the study design of an open-label, noninterventional, crossover, randomized controlled trial aimed at assessing whether interactive voice response systems can screen for SARS-CoV-2 in patients as accurately as standard screening done by people. The study aims to assess the concordance and interrater reliability of symptom screening done by Amazon Alexa compared to manual screening done by research coordinators. The perceived level of comfort of patients when interacting with voice response systems and their personal experience will also be evaluated. METHODS A total of 52 patients visiting the heart failure clinic at the Royal Victoria Hospital of the McGill University Health Center, in Montreal, Quebec, will be recruited. Patients will be randomly assigned to first be screened for symptoms of SARS-CoV-2 either digitally, by Amazon Alexa, or manually, by the research coordinator. Participants will subsequently be crossed over and screened either digitally or manually. The clinical setup includes an Amazon Echo Show, a tablet, and an uninterrupted power supply mounted on a mobile cart. The primary end point will be the interrater reliability on the accuracy of randomized screening data performed by Amazon Alexa versus research coordinators. The secondary end point will be the perceived level of comfort and app engagement of patients as assessed using 5-point Likert scales and binary mode responses. RESULTS Data collection started in May 2021 and is expected to be completed in fall 2022. Data analysis is expected to be completed in early 2023. CONCLUSIONS The use of voice-based assistants could improve the provision of health services and reduce the burden on health care personnel. Demonstrating a high interrater reliability between Amazon Alexa and health care coordinators may serve future digital tools to streamline the screening and delivery of care in the context of other conditions and clinical settings. The COVID-19 pandemic occurs during the first digital era using digital tools such as Amazon Alexa for disease screening, and it represents an opportunity to implement such technology in health care institutions in the long term. CLINICALTRIAL ClinicalTrials.gov NCT04508972; https://clinicaltrials.gov/ct2/show/NCT04508972 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/41209

BACKGROUND Mobile health (mHealth) fitness applications are increasingly being used for research and physical activity promotion; however, which features facilitate and impede routine engagement, a known predictor of application retention, are not well understood. OBJECTIVE To understand facilitators and barriers in the use of mobile applications relating to physical activity promotion. METHODS We distributed a pan-Canadian online questionnaire via the behavioral research platform Prolific.co to evaluate what features associated with the use and routine engagement (i.e., daily, or weekly use) of mHealth fitness applications, and attitudes about data sharing. Binary logistic regression was used to quantify the association between these endpoints and exploratory factors such as the perceived utility of various mHealth application features. RESULTS The survey received 694 responses. Most people were women (62%), the median age was 28 (range: 18–78), and most people reported current use of an mHealth fitness application (48%). The perceived importance of personal health (OR 2.40; 95%·CI 1.34–4.50) was the factor most associated with the current use of an mHealth fitness application. The feature most associated with routine engagement was the ability to track progress toward a goal (OR 5.10, 95%·CI 2.73–9.61) while the most significant barrier was the absence of goal customization features (OR 0.44, 95%·CI 0.25–0.81). The acceptance of sharing health data for research was high (56%) and privacy concerns did not significantly affect routine engagement (OR 0.81, 95%·CI 0.40–1.77). Results were consistent across race and gender. CONCLUSIONS Our results demonstrate that mHealth applications have the potential to be scaled across populations. Optimizing applications to improve self-monitoring and personalization could increase routine engagement and thus user retention and intervention effectiveness.

This study examines the effect of environmental, social and governance risks on firm value. We analyze the extent to which environmental, social and governance related news affect tourism firms' abnormal returns using event study methodology. The results show that environmental, social and governance related news releases do not significantly affect firm value in the short-term. We further investigate the effect of environmental, social and governance risks on the value of tourism firms during the recent pandemic utilizing difference-in-differences analysis. The results provide robust evidence that sustainable business practices provide higher resilience to pandemic-like external shocks. Also, the presence of a sustainability committee mitigates the adverse effects of environmental, social and governance risks on firm value. Theoretical and practical implications are discussed.

The term metaverse signifies various things to various people. While it broadly refers to a virtual shared space at the confluence of Web 3.0, augmented reality, virtual reality, and enabling technologies such as blockchain, there is a fair bit of divergence when it comes to the implications of metaverse on important aspects of day-to-day life, be it finance, entertainment, or education. Preteens today may find it perfectly natural to spend large chunks of their playtime inside their co-created virtual ecosystems within Roblox or Minecraft, hanging out with their friends and showing off their creative sides, even accumulating virtual currencies. This behaviour, when internalised by larger groups, can potentially pave the way for other physical world interactions to be moved to the virtual arena, notably those related with education. With the elements of on-demand availability, interactive feedback, and customised delivery mechanisms, the metaverse can emerge as the go-to destination for many learners and educators alike.

Stroke is a major source of morbidity and mortality worldwide, accounting for the second largest cause of mortality and the third greatest cause of disability. Stroke is frequently preceded by a transient ischemic attack (TIA). The etiologies of 20-30% of ischemic strokes are unknown, and thus are termed "cryptogenic strokes". About 25% of ischemic strokes are cardioembolic. Strokes occur at a rate of around 2% per year in individuals with heart failure with reduced ejection fraction (HFrEF), with a strong correlation between stroke risk and the degree of ventricular impairment. Furthermore, stroke risk is augmented in the absence of anticoagulation therapy. Cardioembolic strokes, when treated inadequately, have a greater predilection for recurrences than atherothrombotic strokes, both early and late in life. The role of a patent foramen ovale in strokes, specifically in "cryptogenic strokes", is a matter of concern that deserves due attention. The use of tissue-engineered heart valves and aspirin for minimizing the risk of stroke is recommended. Transthoracic echocardiography (TTE) is advantageous for assessing heart function in the acute phase of ischemic stroke. Transesophageal echocardiography (TEE) is considered the criterion standard procedure for detecting LAA thrombi. Computed tomography (CT) scans are good imaging modalities for identifying and excluding bleeding. Magnetic resonance imaging (MRI) images are by far the most effective imaging technique available for assessing the brain parenchymal state. We conducted a thorough review of the literature on the use of imaging modalities, highlighting the important contribution of TTE, TEE, CT, and MRI in the evaluation of cardioembolic stroke.

Background: Barrier Coverage in Wireless Sensors Networks has been an active research area. Maximizing number of barriers formed after initial random deployment depends on deployment strategies used. Methods: Where existing works rely on sensor relocation after initial random deployment to maximize barrier coverage, authors in this article proposed a novel Minimum Radius Algorithm (MRA), a first of its kind where no two nodes, will be deployed within the non-overlap radius (OR). Results: The simulation results of the proposed algorithm proves that, MRA outperforms its counterpart not only in the case of maximizing barrier count but also in case convergence time required by network to form barriers. Extensive simulations are carried for all network sizes to show the effectiveness of proposed algorithm. Conclusions: This work aims at proposing a pre- deployment strategy that can maximize number of barriers.

International audience; Massive animal farming for meat production poses major problems in terms of resource use, environmental impact, and biodiversity. Furthermore, excessive meat consumption has been associated with multiple deleterious health consequences. However, more and better-designed randomized trials are needed to increase the level of evidence on the health impacts of meat. Novel meat alternatives, such as plant- and cell-based meat, are much less impactful to the environment and might replace traditional animal meat in the future, but, despite promising early data, the health consequences of these novel products need further study. This manuscript focuses on the health impacts of meat over 3 main sections: 1) overview of the evidence highlighting the association of meat consumption with health; 2) novel alternatives to meat, including plant-based and cell-based alternatives; and 3) examine the rationale for randomized studies to evaluate the effects of the novel meat alternatives compared with the standard animal meat.

A first principles physics-based simulation framework that accounts for wind-over-deck (WOD) and ground effects during approach and landing of a helicopter on a ship deck is developed. The WOD velo...

Women, older patients and non-White ethnic groups experience a substantial proportion of acute coronary syndromes (ACS), although they have been historically underrepresented in ACS randomized clinical trials (RCTs). To assess the influence of sex, age and race on major adverse cardiovascular events (MACE) and on heart failure events, we studied patients with type 2 diabetes in a large post-ACS trial (EXAMINE). Differences in baseline characteristics and the respective composite endpoint of cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke (MACE) and cardiovascular death or heart failure hospitalization (HF events) were evaluated by subgroups in a cohort of post-ACS patients with diabetes, using unadjusted and adjusted Cox regression modelling. The EXAMINE trial enrolled 5380 patients with 35% aged > 65, 32% female and 27% non-White. The risk of MACE was higher in non-White compared to White patients after adjustment for potential confounding (HR = 1.35; 95% CI 1.04–1.75), but there were no significant differences by sex and age (HR = 1.03; 95% CI 0.87–1.22 for women; HR = 1.14; 95% CI 0.96–1.35 for patients ≥ 65 years). The risk of HF events was higher in non-White patients (HR = 1.56; 95% CI 1.13–2.14), and in patients aged > 65 (HR = 1.33; 95% CI 1.07–1.66) and nominally so in women (HR = 1.23; 95% CI 0.99–1.52). The additive risk of each demographic factor (women, older age and non-White race) was greater for HF events in comparison with MACE. Moreover, non-White elderly patients consistently had poorer prognosis regardless of sex. Older adults, women and non-White patients with diabetes who are post-ACS are often underrepresented in RCTs. The risk for HF events was higher in older and non-White patients, with a trend towards significance in women, whereas only non-White patients (and not women and older patients) were at higher risk for MACE. Future trials should enrich enrollment of these persons at risk.

Introduction While current guidelines currently recommend using warfarin, there is also a growing interest in the utilization of direct oral anticoagulants (DOACs) to treat left ventricular (LV) thrombus. Methods We performed a systematic search using PubMed, SCOPUS, EMBASE, Google Scholar, and ClinicalTrials.gov from inception to September 30th, 2020, for studies that had reported outcomes in patients with left ventricular thrombus treated with DOACs (PROSPERO registration number CRD42020219761) RESULTS: Twelve studies (n=867 patients) were included in the analysis. The pooled incidence of the systemic embolic events (SEE) with DOACs was 2.7%, while the thrombus resolution rate was 86.6%. The pooled incidence of overall bleeding (composite of major and minor bleeding) and major bleeding with DOACs were 5.6% and 1.1%, respectively. No significant difference was observed in terms of SEE (OR 0.81, 95% CI 0.44-1.52, p=0.54), major bleeding (OR 0.29, 95% CI 0.07-1.26, p=0.24), and failure of LV thrombus resolution (OR 0.86, 95% CI 0.28-2.58, p=0.68); while overall bleeding was significantly low in patients with LV thrombus treated with DOACs compared to vitamin K antagonists (VKAs) (OR 0.33, 95% CI 0.14-0.81, p=0.02) CONCLUSION: Our study demonstrates no significant difference in SEE, major bleeding, or failure of LV thrombus resolution between the two groups, thus demonstrating that DOACs are an efficacious and safe alternative for the treatment of LV thrombus compared to VKAs. However, further well-designed prospective trials are needed to answer important clinical questions - optimal dosing/duration of DOACs and its safety in the background of antiplatelet therapy. This article is protected by copyright. All rights reserved.

This article fills a void in the literature by investigating the impacts of royal weddings—arguably the grandest and the most iconic of public ceremonies involving royals—on destination-level brands. The direct and short-term effects of royal families and indeed the direct effect of seminal events involving the royals on destination-level accommodations and tourism service providers are more somewhat obvious. However, the more intriguing question and the one which we are more concerned with is: do royal weddings leave a more enduring legacy on the local tourism industry? The engagement announcement and the wedding date produce significant positive increases in the valuation of the home country’s tourism firms. Important managerial implications are derived in line with the long-term impact of unique events on tourism firms’ performance and the transference of brand knowledge from the destination to the companies is effective.

Aspects towards the area of array signal processing are majorly confined to two techniques, Direction of arrival (DOA) estimation and adaptive beamforming (ABF). There exist different traditional techniques for estimating the direction of incoming signals such as spectral and Eigen structure-based methods that find the direction of incoming signals. The major drawback of these techniques are that they fail to find the direction of the incoming signal in environments of low signal to noise (SNR). The maximum likelihood (ML) method has an upper hand in terms of statistical performance as compared to conventional methods and finds the direction of signal in low SNR conditions. In this article, the chicken swarm optimization (CSO) algorithm is explored for the optimization of ML function to find the direction of signals in uniform linear arrays (ULA). The algorithm is inspected with respect to the root mean square error (RMSE) and the probability of resolution (PR). Simulation results of the proposed technique prove that the ML-CSO algorithm outperforms other heuristic approaches such as the flower pollination algorithm (FPA) and other conventional techniques such as Capon, multiple signal classification (MUSIC), estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm in lower SNR environment.

The dramatic increase in the capabilities and availability of autonomous ground and aerial tools introduces safety and security challenges, particularly in protecting strategic infrastructures. In ...

Electrical hazards cause more than 300 electrocutions and 4,000 injuries in the workplace each year, disrupting lives and impacting the productivity of companies. While electrical hazards are not the leading cause of on-the-job injuries, accidents and fatalities, they are disproportionately fatal and costly. Over the past 10 years, more than 46,000 workers have been injured from on-the-job electrical hazards. These injuries are not isolated to any one industry or field of work and most could be easily avoided. Awareness of electrical hazards is critical to avoiding and preventing accidents. It is always important to ensure an employee is properly trained and qualified for a job. Not understanding the circumstances about the job can lead to accidents and injuries. Even properly qualified workers are susceptible to accidents. That’s why it’s important to make safety an integral part of the planning process for every job. Keywords: Accidents, Electrical hazards, Fatal, Injuries.

Background The Thrombolysis in Myocardial Infarction Risk Score for Heart Failure in Diabetes (TRS-HFDM ) risk stratifies patients with type 2 diabetes mellitus (T2DM) and high cardiovascular risk for heart failure (HF) hospitalization. The utility of TRS-HFDM in risk stratification for HF outcomes requires further validation. Materials and methods We used data from the control group of The Action to Control Cardiovascular Risk in Diabetes Study Group (ACCORD) trial (n=5123; mean follow up 4.8 years). The TRS-HFDM includes: prior HF (2 points), atrial fibrillation (1 point), coronary artery disease (1 point), estimated glomerular filtration rate 300 mg/g; 2 point and 30-300 mg/g; 1 point). We evaluated discrimination (Harrell C index) and calibration (Nam-D Agostino calibration statistic) of TRS-HFDM for time to HF hospitalization or death due to HF. Results The mean age of participants was 62.8±6.6 years, and 38% were female. The prevalence of TRS-HFDM for 0, 1, 2, 3 and 4+ were 42.1%, 34.9%, 14.6%, 6.0%, and 2.5% respectively. Increasing TRS-HFDM corresponded to an increasing HF risk: 1.3/1000 person years (PY) (TRS-HFDM : 0) to 64.7/1000 PY (TRS-HFDM : 4+). TRS-HFDM demonstrated robust discrimination for HF outcomes (C-index 0.78). Furthermore, the score was well calibrated for HF outcomes (calibration statistic p=0.13). Similar results were seen in participants without baseline HF (C-index 0.75). Conclusion The TRS-HFDM discriminates for HF specific risk among people with T2DM. Using the TRS-HFDM to identify those who maximally benefit from therapies that reduce HF risk warrants evaluation. This article is protected by copyright. All rights reserved.

Smoothed functional (SF) algorithm estimates the gradient of the stochastic optimization problem by convolution with a smoothening kernel. This process helps the algorithm to converge to a global minimum or a point close to it. We study a two-time scale SF based gradient search algorithm with Nesterov’s acceleration for stochastic optimization problems. The main contribution of our work is to prove the convergence of this algorithm using the stochastic approximation theory. We propose a novel Lyapunov function to show the associated second-order ordinary differential equations’ (o.d.e.) stability for a non-autonomous system. We compare our algorithm with other smoothed functional algorithms such as Quasi-Newton SF, Gradient SF and Jacobi Variant of Newton SF on two different optimization problems: first, on a simple stochastic function minimization problem, and second, on the problem of optimal routing in a queueing network. Additionally, we compared the algorithms on real weather data in a weather prediction task. Experimental results show that our algorithm performs significantly better than these baseline algorithms.

Agriculture plays a vital role in the economic growth of any country. With the increase of population, frequent changes in climatic conditions and limited resources, it becomes a challenging task to fulfil the food requirement of the present population. Precision agriculture also known as smart farming have emerged as an innovative tool to address current challenges in agricultural sustainability. The mechanism that drives this cutting edge technology is machine learning (ML). It gives the machine ability to learn without being explicitly programmed. ML together with IoT (Internet of Things) enabled farm machinery are key components of the next agriculture revolution. In this article, authors present a systematic review of ML applications in the field of agriculture. The areas that are focused are prediction of soil parameters such as organic carbon and moisture content, crop yield prediction, disease and weed detection in crops and species detection. ML with computer vision are reviewed for the classification of a different set of crop images in order to monitor the crop quality and yield assessment. This approach can be integrated for enhanced livestock production by predicting fertility patterns, diagnosing eating disorders, cattle behaviour based on ML models using data collected by collar sensors, etc. Intelligent irrigation which includes drip irrigation and intelligent harvesting techniques are also reviewed that reduces human labour to a great extent. This article demonstrates how knowledge-based agriculture can improve the sustainable productivity and quality of the product.

The essential goal of any adhesive restoration is to achieve a tight and long-lasting adaptation of the restorative material to enamel and dentin. The key challenge for new dental adhesives is to be simultaneously effective on two dental substrates of conflicting nature. Some barriers must be overcome to accomplish this objective. While bonding to enamel by micromechanical interlocking of resin tags within the array of microporosities in acid-etched enamel can be reliably achieved and can effectively seal the restoration margins against leakage, bonding effectively and durably to organic and humid dentin is the most puzzling task in adhesive dentistry.

Mobile health (mHealth) platforms can affect health behaviors but have not been rigorously tested in randomized trials.We sought to evaluate the effectiveness of a pragmatic mHealth intervention in patients with heart failure (HF) and diabetes (DM).We conducted a multicenter randomized trial in 187 patients with both HF and DM to assess an mHealth intervention to improve physical activity and medication adherence compared to usual care. The primary endpoint was change in mean daily step count from baseline through 3 months. Other outcomes included medication adherence, health-related quality of life and metabolomic profiling.The mHealth group had an increase in daily step count of 151 steps/day at 3 months, whereas the usual-care group had a decline of 162 steps/day (least squares mean between-group difference = 313 steps/day; 95% CI: 8 619; P = 0.044). Medication adherence, measured using the Voils Adherence Questionnaire, did not change from baseline to 3 months (LS-mean change -0.08 in mHealth vs -0.15 in usual care; P = 0.47). The mHealth group had an improvement in Kansas City Cardiomyopathy Questionnaire Overall Summary Score compared to the usual-care group (LS-mean difference = 5.5 points, 95% CI: 1.4, 9.6; P = 0.009). Thirteen metabolites, primarily medium- and long-chain acylcarnitines, changed differently between treatment groups from baseline to 3 months (P0.05).In patients with HF and DM, a 3-month mHealth intervention significantly improved daily physical activity, health-related quality of life and metabolomic markers of cardiovascular health but not medication adherence.Heart failure (HF) and diabetes (DM) have overlapping biological and behavioral risk factors. We conducted a multicenter randomized, clinical trial in 187 patients with both HF (regardless of ejection fraction) and DM to assess whether an mHealth intervention could improve physical activity and medication adherence. The mHealth group had an increase in mean daily step count and quality of life but not in medication adherence. Medium- and long-chain acylcarnitines changed differently in treatment groups from baseline to 3 months (P0.05). These data have important implications for designing effective lifestyle interventions in HF and DM.

The balance of microbial species in the intestine must be maintained to prevent inflammation and disease. Healthy bacteria suppress infection by pathogens and prevent disorders such as inflammatory bowel diseases (IBDs). The role of mucus in the relation between pathogens and the intestinal microbiota is poorly understood. Here, we hypothesized that healthy bacteria inhibit infection by preventing pathogens from penetrating the mucus layer and that microbial imbalance leads to inflammation by promoting the penetration of the mucosal barrier. We tested this hypothesis with an in vitro model that contains mucus, an epithelial cell layer, and resident immune cells. We found that, unlike probiotic

The objective of this article is to analyze the impact of lodging taxes on the performance of US hotels by looking at the two key market segments involved. The empirical application conducted on a sample of more than 7,000 observations corresponding to more than 100 urban submarkets from 2013 to 2018 finds that lodging taxes have a more negative effect on hotel performance (RevPar) for group bookings than for transient bookings. As groups usually have greater flexibility regarding the location of events, they can more easily choose a different destination if a tax increase is observed. To prevent this possibility hotels may be more inclined to offer discounts to groups, thereby absorbing some of the tax increase. The results obtained have relevant managerial implications, which are discussed.

Aims Among patients with acute myocardial infarction (AMI) complicated by heart failure [HF; clinical HF or left ventricular (LV) systolic dysfunction], we explored the probability of subsequent non-fatal cardiovascular (CV) events and sudden cardiac death (SCD). Methods and results The high-risk myocardial infarction (HRMI) database contains 28 771 patients with signs of HF or reduced LV ejection fraction ( Conclusion Among patients with AMI complicated by HF, SCD, compared with other causes of death, was less likely to be preceded by a non-fatal CV event. As patients are less likely to have preceding non-fatal CV events to alert the healthcare team of a possible impending SCD event, additional strategies for risk stratification for SCD are needed.

Background Incidental radiographic findings, such as adrenal nodules, are commonly identified in imaging studies and documented in radiology reports. However, patients with such findings frequently do not receive appropriate follow-up, partially due to the lack of tools for the management of such findings and the time required to maintain up-to-date lists. Natural language processing (NLP) is capable of extracting information from free-text clinical documents and could provide the basis for software solutions that do not require changes to clinical workflows. Objectives In this manuscript we present (1) a machine learning algorithm we trained to identify radiology reports documenting the presence of a newly discovered adrenal incidentaloma, and (2) the web application and results database we developed to manage these clinical findings. Methods We manually annotated a training corpus of 4,090 radiology reports from across our institution with a binary label indicating whether or not a report contains a newly discovered adrenal incidentaloma. We trained a convolutional neural network to perform this text classification task. Over the NLP backbone we built a web application that allows users to coordinate clinical management of adrenal incidentalomas in real time. Results The annotated dataset included 404 positive (9.9%) and 3,686 (90.1%) negative reports. Our model achieved a sensitivity of 92.9% (95% confidence interval: 80.9–97.5%), a positive predictive value of 83.0% (69.9–91.1)%, a specificity of 97.8% (95.8–98.9)%, and an F1 score of 87.6%. We developed a front-end web application based on the model's output. Conclusion Developing an NLP-enabled custom web application for tracking and management of high-risk adrenal incidentalomas is feasible in a resource constrained, safety net hospital. Such applications can be used by an institution's quality department or its primary care providers and can easily be generalized to other types of clinical findings.

Background The EXAMINE trial tested the efficacy and safety of alogliptin, an inhibitor of dipeptidyl peptidase 4, compared with placebo in 5380 patients with type 2 diabetes and a recent acute coronary syndrome. Because alogliptin is cleared by the kidney, patients were stratified according to screening renal function within two independently randomized strata: (1) estimated glomerular filtration rate (eGFR) ≥ 60 ml/min/1.73m2 and (2) eGFR 2. We aim to assess the efficacy and safety of alogliptin vs. placebo according to the renal function strata. Methods Cox-proportional hazard models with an interaction term by renal function strata were used. The primary endpoint was a composite of cardiovascular death, nonfatal myocardial infarction (MI), or nonfatal stroke. Results Patient characteristics were balanced within each renal function strata. In total, 3946 patients were randomized within the eGFR ≥ 60 stratum, and 1434 patients within the eGFR p = 0.014. Cardiovascular death: eGFR ≥ 60 HR = 0.61, 95%CI, 0.42–0.88, and eGFR p = 0.013. Non-fatal MI: eGFR ≥ 60 HR = 0.86, 95%CI, 0.66–1.13, and eGFR p = 0.013. Conclusions Alogliptin may benefit patients with eGFR ≥ 60, but may be detrimental to patients with eGFR 2. These hypothesis-generating findings require further validation to assess the potential benefit and risk of alogliptin across the renal function spectrum among patients with type 2 diabetes and a recent acute coronary syndrome. Trial registration ClinicalTrials.gov, NCT00968708

Responding to concerns about the potential for increased risk of adverse cardiovascular outcomes, specifically myocardial infarction, associated with certain glucose-lowering therapies, the US Food and Drug Administration and the Committee for Medicinal Products for Human Use of the European Medicines Agency issued guidance to the pharmaceutical industry in 2008. Glucose-lowering therapies were granted regulatory approval primarily from smaller studies that have demonstrated reductions in glycated hemoglobin concentration. Such studies were overall underpowered and of insufficient duration to show any effect on cardiovascular outcomes. The 2008 guidance aimed to ensure the cardiovascular safety of new glucose-lowering therapies to treat patients with type 2 diabetes mellitus. This resulted in a plethora of new cardiovascular outcome trials, most designed primarily as placebo-controlled noninferiority trials, but with many also powered for superiority. Several of these outcome trials demonstrated cardiovascular benefits of the newer agents, resulting in the first-ever cardiovascular protection indications for glucose-lowering therapies. Determining whether the guidance continues to have value in its current form is critically important as we move forward after the first decade of implementation. In February 2018, a think tank comprising representatives from academia, industry, and regulatory agencies convened to consider the guidance in light of the findings of the completed cardiovascular outcome trials. The group made several recommendations for future regulatory guidance and for cardiovascular outcome trials of glucose-lowering therapies. These recommendations include requiring only the 1.3 noninferiority margin for regulatory approval, conducting trials for longer durations, considering studying glucose-lowering therapies as first-line management of type 2 diabetes mellitus, considering heart failure or kidney outcomes within the primary outcome, considering head-to-head active comparator trials, increasing the diversity of patients enrolled, evaluating strategies to streamline registries and the study of unselected populations, and identifying ways to improve translation of trial results to general practice.

Dysfunction of the intestinal mucus barrier causes disorders such as ulcerative colitis and Crohn’s disease. The function of this essential barrier may be affected by the periodically changing luminal environment. We hypothesized that the pH and ion concentration in mucus control its porosity, molecular permeability, and the penetration of microbes. To test this hypothesis, we developed a scalable method to extract porcine small intestinal mucus (PSIM). The aggregation and porosity of PSIM were determined using rheometry, spectrophotometry, and microscopy. Aggregation of PSIM at low pH increased both the elastic (G′) and viscous (G″) moduli, and it slowed the transmigration of pathogenic Salmonella. Molecular transport was dependent on ion concentration. At moderate concentrations, many microscopic aggregates (2–5 μm in diameter) impeded diffusion. At higher concentrations, PSIM formed aggregate islands, increasing both porosity and diffusion. This in vitro model could lead to a better understanding of mucus barrier functions and improve the treatment of intestinal diseases.

Aims To develop a risk model for sudden cardiac death (SCD) in high‐risk acute myocardial infarction (AMI) survivors. Methods and results Data from the Effect of Carvedilol on Outcome After Myocardial Infarction in Patients With Left Ventricular Dysfunction trial (CAPRICORN) and the Valsartan in Acute Myocardial Infarction Trial (VALIANT) were used to create a SCD risk model (with non‐SCD as a competing risk) in 13 202 patients. The risk model was validated in the Eplerenone Post‐AMI Heart Failure Efficacy and Survival Study (EPHESUS). The rate of SCD was 3.3 (95% confidence interval 3.0–3.5) per 100 person‐years over a median follow‐up of 2.0 years. Independent predictors of SCD included age > 70 years; heart rate ≥ 70 bpm; smoking; Killip class III/IV; left ventricular ejection fraction ≤30%; atrial fibrillation; history of prior myocardial infarction, heart failure or diabetes; estimated glomerular filtration rate

This research work has been completed by concentrating on the structure of inserts for foot orthosis fabricated by utilizing rapid prototyping technology. Thermoplastic elastomer and thermoplastic polyurethane are the most commonly used materials that are being used in customized three-dimensional printed orthotic insoles, which are comfortable and prevent the user in many foot disorders. Thermo-softening viscoelastic polymers, explicitly Filaflex and Ninjaflex, have been printed by utilizing Flash Forge three-dimensional printers to evaluate the mechanical properties of specimens with alterations of the percentage rate fill-up design replicas. The results are compared on the basis of hardness test, flexural/bending test, and tensile test using Durometer and Universal Testing Machine (UTM). It has also been observed that the most significant effecting factor is infill density.

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A facile solvothermal synthesis approach for chemical composition control in ternary Bi-S-I systems is reported by simply controlling the sulfide concentration. We demonstrate the application of these bismuth-based ternary mixed-anion compounds as high capacity anode materials in rechargeable batteries. Cells utilising Bi

Asynchronously replicated primary-backup databases are commonly deployed to improve availability and offload read-only transactions. To both apply replicated writes from the primary and serve read-only transactions, the backups implement a cloned concurrency control protocol. The protocol ensures read-only transactions always return a snapshot of state that previously existed on the primary. This compels the backup to exactly copy the commit order resulting from the primary's concurrency control. Existing cloned concurrency control protocols guarantee this by limiting the backup's parallelism. As a result, the primary's concurrency control executes some workloads with more parallelism than these protocols. In this paper, we prove that this parallelism gap leads to unbounded replication lag, where writes can take arbitrarily long to replicate to the backup and which has led to catastrophic failures in production systems. We then design C5, the first cloned concurrency protocol to provide bounded replication lag. We implement two versions of C5: Our evaluation in MyRocks, a widely deployed database, demonstrates C5 provides bounded replication lag. Our evaluation in Cicada, a recent in-memory database, demonstrates C5 keeps up with even the fastest of primaries., Comment: 14 pages, 12 figures

Biopolymer networks are common in biological systems from the cytoskeleton of individual cells to collagen in the extracellular matrix. The mechanics of these systems under applied strain can be explained in some cases by a phase transition from soft to rigid states. For collagen networks, it has been shown that this transition is critical in nature and it is predicted to exhibit diverging fluctuations near a critical strain that depends on the network's connectivity and structure. Whereas prior work focused mostly on shear deformation that is more accessible experimentally, here we study the mechanics of such networks under an applied bulk or isotropic extension. We confirm that the bulk modulus of subisostatic fiber networks exhibits similar critical behavior as a function of bulk strain. We find different non-mean-field exponents for bulk as opposed to shear. We also confirm a similar hyperscaling relation to what previously found for shear., 5 pages, 4 figures

While the dynamics of dimers and polymer chains in a viscous solvent is well understood within the celebrated Rouse model, the effect of an external magnetic field on the dynamics of a charged chain is much less understood. Here, we generalize the Rouse model for a charged dimer to include the effect of an external magnetic field. Our analytically solvable model allows a fundamental insight into the magneto-generated dynamics of the dimer in the overdamped limit as induced by the Lorentz force. Surprisingly, for a dimer of oppositely charged particles, we find an enormous enhancement of the dynamics of the dimer center, which exhibits even a transient superballistic behavior. This is highly unusual in an overdamped system for there is neither inertia nor any internal or external driving. We attribute this to a significant translation and rotation coupling due to the Lorentz force. We also find that magnetic field reduces the mobility of a dimer along its orientation and its effective rotational diffusion coefficient. In principle, our predictions can be tested by experiments with colloidal particles and complex plasmas.