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A postal questionnaire was sent to the managers of 857 broiler farms in the UK to determine the prevalence and risk factors for wet lifter. The response rate was 75 percent. Wet litter was reported by 75 per cent (95 percent confidence interval [cl] 71.3 to 78.3) of the respondents in at least one flock during the year 2001 and 56.1 percent (95 percent cl 52.O to 60.0) of them reported that they had an outbreak of wet litter in their most recently reared flock. Wet litter occurred more often during the winter months and farms using side ventilation systems were at an increased risk (odds ratio 1.74; 95 percent cl 1.09 to 2.76). A multivariable analysis was carried out using two different definitions of wet litter as outcome variables - all cases of wet litter, and cases of wet litter associated with disease. Consistent risk factors for both outcomes were coccidiosis, feed equipment failures and the availability of separate farm clothing for each house. Cases of wet lifter associated with disease were reported by 33.7 percent (95 per cent cl 28.8 to 39.1) of the managers in their last flock and were associated with the use of hand sanitisers and broiler houses with walls made of concrete. [ABSTRACT FROM AUTHOR]

An early paper (1932) by Majorana, that has received but scant attention, is reexamined in light of later developments. This pioneering paper constructs a relativistically invariant theory of arbitrary spin particles, develops and utilizes infinite dimensional representations of the homogeneous Lorentz group, and provides a mass spectrum for elementary particles. The relevance of Majorana's approach and results to later and current research is explained. [ABSTRACT FROM AUTHOR]

Purpose: Rates of at-risk opioid use, opioid use disorder, and opioid overdose remain alarmingly high. There are medications that can be used to treat opioid use disorder, including methadone, buprenorphine, and naltrexone, although access to care remains difficult. This review seeks to provide advanced practice psychiatric nurses (APPNs) with an overview of buprenorphine prescribing, with an emphasis on novel, long-acting delivery systems., Conclusions: APPNs should be familiar with best practices regarding buprenorphine prescribing. Some patients may benefit from long-acting delivery methods, such as subdermal implants, or subcutaneous injections., Practice Implications: APPNs can reduce barriers to buprenorphine access and should be familiar with best practices related to buprenorphine prescribing., (© 2022 Wiley Periodicals LLC.)

The use of psychedelics, such as psilocybin, has emerged in recent literature as a novel therapeutic treatment for various psychiatric disorders, including substance use, depression, and anxiety. While international and domestic trials are currently underway, there is data demonstrating both the relative safety and potential efficacy of psilocybin. Psychiatric mental health nurse practitioners are essential mental health providers that may be at the forefront of delivering these new treatment modalities. Therefore, they must be aware of the psychopharmacological and psychotherapeutic tenets of psilocybin to be prepared to treat patients., (© 2021 Wiley Periodicals LLC.)

Background: The transition from high school to college can be a stressful experience for first-year university students. Peer advisors are thought to be a valuable social support resource for first-year nursing students., Purpose: The purpose of this study was to assess the perceptions and experiences of both first-year nursing students and their peer advisors in a first semester seminar course., Methodology: A cross-sectional descriptive design was used on a sample that included 108 first-year nursing students and five peer advisors., Results: The study revealed that 68% of the participating freshmen felt that the program met their nursing school expectations and 95.1% reported that the peer advisor group meetings were beneficial and met the goals of the courses, as anticipated. Students described their peer advisors as excellent communicators, accommodating, and sensitive to diversity. The course also offered peer advisors an opportunity for personal and professional growth., Conclusion: The findings of this study might help inform the academic institution's practices regarding the benefits of peer advisement program for first-year students., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Psychiatric nursing providers and their unique challenges in the face of the COVID-19 pandemic are not well-represented in the literature. Therefore, this study sought to describe mental well-being of psychiatric nurses, and sought to elucidate factors related to mental wellness during the COVID-19 pandemic. This study utilized cross-sectional survey methodology to evaluate burnout, mental wellness, COVID-related anxiety, professional fulfillment, depressive symptoms, and anxiety symptoms among psychiatric nurses. There was a total of 151 respondents. A linear regression model was employed to identify predictors of mental wellness. The final regression model included the following predictors: depressive symptoms, burnout, professional fulfillment, and educational status. These predictors together accounted for 73% of the variance for the outcome variable of mental well-being., (Copyright © 2021 Elsevier Inc. All rights reserved.)

The purpose of the current study was to evaluate changes in attitudes toward psychiatric nursing and mental health problems in a sample of nursing students after exposure to high-fidelity standardized patient (SP) simulation scenarios. This study used a quasi-experimental, single-group pre-/post-survey approach. Immediately before and after exposure to SP simulation scenarios, undergraduate nursing students completed Attitudes to Mental Illness (AMI) and the Attitudes to Psychiatry (ATP) surveys. There were significant improvements in the following ATP domains: psychiatric career choice and psychiatric teaching ( p = 0.046 and 0.007, respectively). There were no significant changes in the AMI survey, but items related to social stigma improved following the simulation. Findings of this study suggest a potential benefit of SP simulation on nursing students in developing their attitudes toward psychiatry and mental health problems. [ Journal of Psychosocial Nursing and Mental Health Services, 59 (8), 15-21.].

Abstract: Between 1999 and 2017, nearly 400,000 individuals died from opioid-related overdoses in the United States. Nurse practitioners (NPs) can be instrumental in providing care for those with opioid use disorders (OUDs) but must be adequately prepared to do so. Currently, there is limited evidence regarding how NP programs are preparing their graduates to address opioid use. The purpose of this study was to evaluate how NP programs have addressed the opioid epidemic within their curricula, and to evaluate barriers to and facilitators of curricular modifications. Electronic surveys were distributed to all 444 NP program directors in the United States. The survey consisted of 10 questions and inquired about curricular modifications made in regard to OUDs, barriers and facilitators of such modifications, and perceived importance of addressing the opioid epidemic within NP programs. A total of 130 (29.3%) of program directors responded to the survey. Of the program directors who responded, 89 (76.1%) reported that curricular modifications were made to address OUDs. Barriers to curricular modification included limited time, lack of faculty expertise or confidence, and stigma in regard to opioid use. Facilitators included faculty champions, availability of external educational resources, student interest, and financial incentives. Nurse practitioners can treat patients with OUDs, mitigating significant barriers to care reported in light of the opioid epidemic. Graduate NP programs should assure that curricula adequately cover opioid use and related management., Competing Interests: Competing interests: The authors report no conflicts of interest., (Copyright © 2020 American Association of Nurse Practitioners.)

This work proposes a pattern mining approach to learn event detection models from complex multivariate temporal data, such as electronic health records. We present Recent Temporal Pattern mining, a novel approach for efficiently finding predictive patterns for event detection problems. This approach first converts the time series data into time-interval sequences of temporal abstractions. It then constructs more complex time-interval patterns backward in time using temporal operators. We also present the Minimal Predictive Recent Temporal Patterns framework for selecting a small set of predictive and non-spurious patterns. We apply our methods for predicting adverse medical events in real-world clinical data. The results demonstrate the benefits of our methods in learning accurate event detection models, which is a key step for developing intelligent patient monitoring and decision support systems.

Aim: Numerous genes are known to cause dilated cardiomyopathy (DCM). However, until now technological limitations have hindered elucidation of the contribution of all clinically relevant disease genes to DCM phenotypes in larger cohorts. We now utilized next-generation sequencing to overcome these limitations and screened all DCM disease genes in a large cohort., Methods and Results: In this multi-centre, multi-national study, we have enrolled 639 patients with sporadic or familial DCM. To all samples, we applied a standardized protocol for ultra-high coverage next-generation sequencing of 84 genes, leading to 99.1% coverage of the target region with at least 50-fold and a mean read depth of 2415. In this well characterized cohort, we find the highest number of known cardiomyopathy mutations in plakophilin-2, myosin-binding protein C-3, and desmoplakin. When we include yet unknown but predicted disease variants, we find titin, plakophilin-2, myosin-binding protein-C 3, desmoplakin, ryanodine receptor 2, desmocollin-2, desmoglein-2, and SCN5A variants among the most commonly mutated genes. The overlap between DCM, hypertrophic cardiomyopathy (HCM), and channelopathy causing mutations is considerably high. Of note, we find that >38% of patients have compound or combined mutations and 12.8% have three or even more mutations. When comparing patients recruited in the eight participating European countries we find remarkably little differences in mutation frequencies and affected genes., Conclusion: This is to our knowledge, the first study that comprehensively investigated the genetics of DCM in a large-scale cohort and across a broad gene panel of the known DCM genes. Our results underline the high analytical quality and feasibility of Next-Generation Sequencing in clinical genetic diagnostics and provide a sound database of the genetic causes of DCM., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2014. For permissions please email: journals.permissions@oup.com.)

Improving the performance of classifiers using pattern mining techniques has been an active topic of data mining research. In this work we introduce the recent temporal pattern mining framework for finding predictive patterns for monitoring and event detection problems in complex multivariate time series data. This framework first converts time series into time-interval sequences of temporal abstractions. It then constructs more complex temporal patterns backwards in time using temporal operators. We apply our framework to health care data of 13,558 diabetic patients and show its benefits by efficiently finding useful patterns for detecting and diagnosing adverse medical conditions that are associated with diabetes.

We present a study on how to predict new emerging trends in the biomedical domain based on textual data. We thereby propose a way of anticipating the transformation of arbitrary information into ground truth knowledge by predicting the inclusion of new terms into the MeSH ontology. We also discuss the preparation of a dataset for the evaluation of emerging trend prediction algorithms that is based on PubMed abstracts and related MeSH terms. The results suggest that early prediction of emerging trends is possible.