Modeling heart failure in animal models for novel drug discovery and development

Introduction: When investigating drugs that treat heart diseases, it is critical when choosing an animal model for the said model to produce data that is translatable to the human patient population, while keeping in mind the principles of reduction, refinement, and replacement of the animal model in the research.

Areas covered: In this review, the authors focus on mammalian models developed to study the impact of drug treatments on human heart failure. Furthermore, the authors address human patient variability and animal model invariability as well as the considerations that need to be made regarding choice of species. Finally, the authors discuss some of the most common models for the two most prominent human heart failure etiologies; increased load on the heart and myocardial ischemia.

Expert opinion: In the authors’ opinion, the data generated by drug studies is often heavily impacted by the choice of species and the physiologically relevant conditions under which the data are collected. Approaches that use multiple models and are not restricted to small rodents but involve some verification on larger mammals or on human myocardium, are needed to advance drug discovery for the very large patient population that suffers from heart failure.     

Applying Health Belief Model to Unveil Employees’ Workplace COVID-19 Protective Behaviors: Insights for the Hospitality Industry

The overwhelming majority of the countries around the globe have witnessed severe cases of the COVID-19 outbreak. Unfortunately, many countries are still beset with such an infectious disease. Despite the fact that there is currently no specific approved cure for this deadly infection, restrictions (e.g., lockdown and border closing) are gradually eased. Meanwhile, businesses are reopening and outdoor leisure activities are about to start again based on strict health, social distancing, and hygiene rules. However, as we still have a long way to reach an ultimate treatment for such deadly virus, changing human behavior sounds the best defense in tackling this challenge till a vaccine is developed for protection against COVID-19. With this realization, using Health Belief Model as the theoretical underpinning, our study endeavors to unveil employees’ adherence to protective health behaviors (PHBs) in the hospitality industry, which is known as a people-focused, labor-intensive, and service-oriented business. This is so crucial since there is a high degree of (frequent) interaction between employees and customers in hotels. Moreover, such establishments are known as areas where customers engage in a variety of activities that make health concerns even more crucial. To achieve the objectives of this research, we used secondary data obtained from one of the largest hotel-related online communities in the world: the ‘Tales from the front desk’. Using template analysis approach, 1680 employees’ comments were examined. The results revealed that hotel employees found themselves at high risk of being infected and several obstacles that impeded their PHBs in the workplace were identified. Our study will provide momentous implications about PHBs against COVID-19 for the hospitality industry.     

Did We Get Sensorimotor Adaptation Wrong? Implicit Adaptation as Direct Policy Updating Rather than Forward-Model-Based Learning

The human motor system can rapidly adapt its motor output in response to errors. The prevailing theory of this process posits that the motor system adapts an internal forward model that predicts the consequences of outgoing motor commands and uses this forward model to plan future movements. However, despite clear evidence that adaptive forward models exist and are used to help track the state of the body, there is no definitive evidence that such models are used in movement planning. An alternative to the forward-model-based theory of adaptation is that movements are generated based on a learned policy that is adjusted over time by movement errors directly (“direct policy learning”). This learning mechanism could act in parallel with, but independent of, any updates to a predictive forward model. Forward-model-based learning and direct policy learning generate very similar predictions about behavior in conventional adaptation paradigms. However, across three experiments with human participants (N = 47, 26 female), we show that these mechanisms can be dissociated based on the properties of implicit adaptation under mirror-reversed visual feedback. Although mirror reversal is an extreme perturbation, it still elicits implicit adaptation; however, this adaptation acts to amplify rather than to reduce errors. We show that the pattern of this adaptation over time and across targets is consistent with direct policy learning but not forward-model-based learning. Our findings suggest that the forward-model-based theory of adaptation needs to be re-examined and that direct policy learning provides a more plausible explanation of implicit adaptation.SIGNIFICANCE STATEMENT The ability of our brain to adapt movements in response to error is one of the most widely studied phenomena in motor learning. Yet, we still do not know the process by which errors eventually result in adaptation. It is known that the brain maintains and updates an internal forward model, which predicts the consequences of motor commands, and the prevailing theory of motor adaptation posits that this updated forward model is responsible for trial-by-trial adaptive changes. Here, we question this view and show instead that adaptation is better explained by a simpler process whereby motor output is directly adjusted by task errors. Our findings cast doubt on long-held beliefs about adaptation.     

基于Andersen行为模型的消化道肿瘤患者支持性照顾需求现状及影响因素分析

目的调查消化道肿瘤患者的支持性照顾需求现状并分析其影响因素。方法于2019年1—10月间,采用便利抽样的方法,抽取重庆市三峡中心医院内消化道肿瘤患者共370例,采用一般资料调查表、癌症病人支持性照顾需求简明问卷(SCNS-SF34)、医院焦虑和抑郁量表(HADS)、社会网络支持量表(LSNS)进行问卷调查。以Andersen行为模型为基础,将调查内容中关于消化道肿瘤患者支持性照顾需求的影响因素分别纳入倾向性因素、使能因素和需求性因素中,构建4个线性回归模型进行分析,并检验各模型的拟合优度,采用多元线性回归分析消化道肿瘤患者支持性照顾需求的影响因素。结果共发放问卷370份,回收有效问卷365份,有效回收率为98.6%。365例消化道肿瘤患者支持性照顾需求总均分为(3.42±0.54)分,其中生理与日常生活需求>健康信息需求>照顾与支持需求>心理需求>性需求。多元线性回归分析结果显示:倾向性因素中年龄、婚姻状况,使能因素中的家庭平均月收入、疾病负担能力、社会网络支持,需求性因素中的病程、疾病分期、疼痛情况、焦虑程度、抑郁程度是消化道肿瘤患者支持性照顾需求的主要影响因素(P<0.05)。结论消化道肿瘤患者有较高的支持性照顾需求,其需求受多种因素的影响,建议临床医护人员针对不同需求患者进行针对性满足,并对不同影响因素进行综合考量并加以分类分析。     

At the intersection of science and theory: How the Nurse Role Integration Model reconciles the conflict

As more nurses embrace precision science, there is a tendency to utilize theoretical frameworks from other disciplines thus, placing nursing at risk of losing its autonomy and independence. The discipline has fallen prey to internal binary opposition, eliminating opportunities to engage in civil discourse. To explore how the roles nurses select might fit together in a theoretical framework and help nurses understand how the roles they choose to support their identity as nurses, this paper introduced a model of nursing that includes the bench scientists, the policy activists, and bedside nurses, using the Neuman Systems Model (NSM). The Nurse Role Integration Model (NRIM) espouses the basic tenets of NSM: prevention counteracts stressors from penetrating the client’s lines of defense thus, reducing stress response. Primary prevention reflects the work of the nurse bench scientists, investigating the underlying mechanisms behind pathophysiology; secondary prevention is applied nurse scientists who build upon nurse researchers’ work, identifying and testing potential interventions; tertiary prevention is nurse policy activists, the fulcrum, who leverage primary and secondary findings to argue policy change at all levels. Once policy change is adopted, bedside nurses are educated and implement the change. This lens provides an opportunity to create greater solidarity, strengthening the unity and autonomy of the discipline.     

La toma de decisiones en salud comunitaria a través del mapeo de activos en salud

This is a report about the experience on redefining the health asset mapping methodology. The aim of this experience consisted of making an analysis on health inequalities, as well as of using it as a tool in decision-making participative processes in the local administration area. Thus, a replicable procedure for all ages and groups was designed. Besides this, assets have been widely classified, in accordance with the territorial distribution, people's profiles and asset features. Both the upload of data to a geographical information system and the large amount of data gathered allowed us to enlarge the common interpretation of data and present the information in a dynamic way.     

Preclinical relevance of probiotics in type 2 diabetes: A systematic review

Type 2 diabetes (T2DM) is among the most prevalent metabolic diseases in the world and may result in several long‐term complications. The crosstalk between gut microbiota and host metabolism is closely related to T2DM. Currently, fragmented data hamper defining the relationship between probiotics and T2DM. This systematic review aimed at investigating the effects of probiotics on T2DM in animal models. We systematically reviewed preclinical evidences using PubMed/MEDLINE and Scopus databases, recovering 24 original articles published until September 27th, 2019. This systematic review was performed according to PRISMA guidelines. We included experimental studies with animal models reporting the effects of probiotics on T2DM. Studies were sorted by characteristics of publications, animal models, performed analyses, probiotic used and interventions. Bias analysis and methodological quality assessments were examined through the SYRCLE's Risk of Bias tool. Probiotics improved T2DM in 96% of the studies. Most studies (96%) used Lactobacillus strains, and all of them led to improved glycaemia. All studies used rodents as models, and male animals were preferred over females. Results suggest that probiotics have a beneficial effect in T2DM animals and could be used as a supporting alternative in the disease treatment. Considering a detailed evaluation of the reporting and methodological quality, the current preclinical evidence is at high risk of bias. We hope that our critical analysis will be useful in mitigating the sources of bias in further studies.     

量化分级模式在呼吸内科风险管理中的应用评价

目的研究量化分级模式在呼吸内科护理工作中的应用效果。方法回顾性整理该院中2016年6月-2017年12月间呼吸内科收治的患者临床数据,随机挑选出100例患者进行实验,选择2016年6月-2017年4月间的50例患者作为对照组,2017年5-12月的50例患者作为实验组,从2017年5月开始实施量化分级模式,对两组患者对护理人员的护理质量评分进行对比。结果该次研究成果显示,对照组患者的护理质量评分低于实验组,实验组护理人员在与患者沟通时,其服务态度优于对照组,并且在执行各项护理操作流程时,流程评分较对照组同时也更高,各数据对比差异有统计学意义(P<0.05)。结论在呼吸内科的日常护理中应用量化分级模式,有助于减少护理风险事件发生率,护理质量也能得到提升,改善护患之间的关系,具有良好的应用价值。     

经乙二醇诱导的改良型草酸钙肾结石果蝇模型

目的:通过一种改良方法构建果蝇草酸钙肾结石模型。方法:配制标准培养基和造模用培养基，空白对照组果蝇仅予标准培养基，而传统模型组和改良模型组分别从成虫期和幼虫期开始摄入含 0.5%乙二醇( EG)的造模用培养基。于偏光显微镜下观察并评估各组果蝇马氏管内成石情况，分别记录模型组成石率达 100%所花时间，并对成石率 100%时模型组间“ ++”和“ +++”所占比率进行比较；用傅立叶变换拉曼光谱仪鉴定模型组果蝇马氏管内结石成分。绘制各组果蝇生存曲线，并比较生存周期差异。结果:改良模型组和传统模型组分别在果蝇成虫日龄 14 d和 22 d，马氏管内成石率达到 100%。当改良模型组和传统模型组成石率均达到 100%时，两组“ ++”与“+++”所占比率分别为(40.5±4.4)%和(39.0±4.2)%，差异无统计学意义(P＞ 0.05)；拉曼位移的主峰主要集中在 1 462 cm-1、1 463 cm-1和 1 473 cm-1，说明模型组果蝇马氏管内结石成分均为草酸钙。空白对照组、传统模型组和改良模型组的最高寿命分别为 76 d、70 d和 68 d，中位生存时间分别为 35 d、30.5 d和 30 d，与空白对照组相比，模型组生存周期均显著缩短(P均＜ 0.01)，但传统模型组与改良模型组间差异无统计学意义( P＞ 0.05)。结论:改良型造模方法使果蝇在其幼虫期即摄入 0.5% EG，缩短了模型构建周期且具有可重复性，值得进一步研究推广。