人类疾病动物模型是医药创新研究的前沿

人类疾病动物模型对医药研究起着支撑作用,是进行医药研究的必备工具之一.本文阐述了人类疾病动物模型在医药研究中所能发挥的作用,以及在医药研究的历史中所做出的贡献.最后,对疾病动物模型在医药创新研究中应用的前沿进行了展望.     

Modelling Directional Guidance and Motility Regulation in Cell Migration

Although cell migration is an essential process in development, how cells reach their final destination is not well understood. Secreted molecules are known to have a migratory effect, but it remains unclear whether such molecules act as directional guidance cues or as motility regulators. There is potential to use signalling molecules in new medical therapies, so it is important to identify the exact role these molecules play. This paper focuses on distinguishing between inhibitory and repulsive effects produced by signalling molecules, based on recent experiments examining the effect of Slit, a secreted protein, on the migration of neurons from the brain. The primary role of Slit, whether it is an inhibitor or repellent of neurons, is in dispute. We present population-level continuum models and recast these in terms of transition probabilities governing individual cells. Various cell-sensing strategies are considered within this framework. The models are applied to the neuronal migration experiments. To resolve the particular role of Slit, simulations of the models characterising different cell-sensing strategies are compared at the population and individual cell level, providing two complementary perspectives on the system. Difficulties and limitations in deducing cell migration rules from time-lapse imaging are discussed.     

The role of computation in modeling evolution

Artificial life uses computers and formal systems to model and explore the dynamics of evolution. A fundamental question for A-Life concerns the role of computation in these models, and how we are to interpret computer implementations that do not have actual contact with physical systems. In this paper I will discuss how models are seen to explain and predict in philosophy of science and how these ideas apply to A-Life. I will also explore how the notion of an epistemic cut, as defined by H. Pattee, can be realized in a computational model with an artificial physical world.     

Constructive realism and medicine: an approach to medical ontology

Metaphysics is an essential part of philosophy of medicine, providing the background for further methodological work. Current accounts of the ontology of particular diseases may be classified as realist or anti-realist. Because strong arguments can be marshaled by both of these positions, an approach to medical ontology that draws support from both sides of this divide would be desirable. Abstract models, as described by Ronald Giere, provide such an approach. After a review of Giere's account of mechanics, I show how abstract models can provide an account of the ontology of diseases.     

Synthetic cell biology

Synthesis of data into formal models of cellular function is rapidly becoming a necessary industry. The complexity of the interactions among cellular constituents and the quantity of data about these interactions hinders the ability to predict how cells will respond to perturbation and how they can be engineered for industrial or medical purposes. Models provide a systematic framework to describe and analyze these complex systems. In the past few years, models have begun to have an impact on mainstream biology by creating deeper insight into the design rules of cellular signal processing, providing a basis for rational engineering of cells, and for resolving debates about the root causes of certain cellular behaviors. This review covers some of the recent work and challenges in developing these "synthetic cell" models and their growing practical applications.     

Futility Determination as a Process: Problems with Medical Sovereignty, Legal Issues and the Strengths and Weakness of the Procedural Approach

Futility is not a purely medical concept. Its subjective nature requires a balanced procedural approach where competing views can be aired and in which disputes can be resolved with procedural fairness. Law should play an important role in this process. Pure medical models of futility are based on a false claim of medical sovereignty. Procedural approaches avoid the problems of such claims. This paper examines the arguments for and against the adoption of a procedural approach to futility determination.     

Gendered Difference, Violent Imagination Blood, Race, Nation

Racism, misogyny, and the propagation of politicomilitary violence are analyzed as an integral part of the construction of Western modernity. With a focus on German public culture, the author emphasizes the interplay of gender and race against the background of medical models, documenting how fears of natural disasters (women, Jews, refugees) and medical pathologies such as dirt and infection (bodily infestations) are continuously recycled to reinforce a racialist postmodern culture.     

Knowledge acquisition, semantic text mining, and security risks in health and biomedical informatics

Computational techniques have been adopted in medi-cal and biological systems for a long time. There is no doubt that the development and application of computational methods will render great help in better understanding biomedical and biological functions. Large amounts of datasets have been produced by biomedical and biological experiments and simulations. In order for researchers to gain knowledge from origi- nal data, nontrivial transformation is necessary, which is regarded as a critical link in the chain of knowledge acquisition, sharing, and reuse. Challenges that have been encountered include: how to efficiently and effectively represent human knowledge in formal computing models, how to take advantage of semantic text mining techniques rather than traditional syntactic text mining, and how to handle security issues during the knowledge sharing and reuse. This paper summarizes the state-of-the-art in these research directions. We aim to provide readers with an introduction of major computing themes to be applied to the medical and biological research.     

Left ventricular wall stress compendium

Left ventricular (LV) wall stress has intrigued scientists and cardiologists since the time of Lame and Laplace in 1800s. The left ventricle is an intriguing organ structure, whose intrinsic design enables it to fill and contract. The development of wall stress is intriguing to cardiologists and biomedical engineers. The role of left ventricle wall stress in cardiac perfusion and pumping as well as in cardiac pathophysiology is a relatively unexplored phenomenon. But even for us to assess this role, we first need accurate determination of in vivo wall stress. However, at this point, 150 years after Lame estimated left ventricle wall stress using the elasticity theory, we are still in the exploratory stage of (i) developing left ventricle models that properly represent left ventricle anatomy and physiology and (ii) obtaining data on left ventricle dynamics. In this paper, we are responding to the need for a comprehensive survey of left ventricle wall stress models, their mechanics, stress computation and results. We have provided herein a compendium of major type of wall stress models: thin-wall models based on the Laplace law, thick-wall shell models, elasticity theory model, thick-wall large deformation models and finite element models. We have compared the mean stress values of these models as well as the variation of stress across the wall. All of the thin-wall and thick-wall shell models are based on idealised ellipsoidal and spherical geometries. However, the elasticity model's shape can vary through the cycle, to simulate the more ellipsoidal shape of the left ventricle in the systolic phase. The finite element models have more representative geometries, but are generally based on animal data, which limits their medical relevance. This paper can enable readers to obtain a comprehensive perspective of left ventricle wall stress models, of how to employ them to determine wall stresses, and be cognizant of the assumptions involved in the use of specific models.     

Symptom and Surface: Disruptive Deafness and Medieval Medical Authority

This essay examines constructions of deafness in medieval culture, exploring how deaf experience disrupts authoritative discourses in three textual genres: medical treatise, literary fiction, and autobiographical writing. Medical manuals often present deafness as a physical defect, yet they also suggest how social conditions for deaf people can be transformed in lieu of treatment protocols. Fictional narratives tend to associate deafness with sin or social stigma, but they can also imagine deaf experience with a remarkable degree of sympathy and nuance. Autobiographical writing by deaf authors most vividly challenges diagnostic models of disability, exploring generative forms of perception that deafness can foster. In tracing the disruptive force that deaf experience exerts on perceived notions of textual authority, this essay reveals how medieval culture critiqued the diagnostic power of medical practitioners. Deafness does not simply function as a symptom of an individual problem or a metaphor for a spiritual or social condition; rather, deafness is a transformative capacity affording new modes of knowing self and other.     

Left ventricular wall stress compendium

Left ventricular (LV) wall stress has intrigued scientists and cardiologists since the time of Lame and Laplace in 1800s. The left ventricle is an intriguing organ structure, whose intrinsic design enables it to fill and contract. The development of wall stress is intriguing to cardiologists and biomedical engineers. The role of left ventricle wall stress in cardiac perfusion and pumping as well as in cardiac pathophysiology is a relatively unexplored phenomenon. But even for us to assess this role, we first need accurate determination of in vivo wall stress. However, at this point, 150 years after Lame estimated left ventricle wall stress using the elasticity theory, we are still in the exploratory stage of (i) developing left ventricle models that properly represent left ventricle anatomy and physiology and (ii) obtaining data on left ventricle dynamics. In this paper, we are responding to the need for a comprehensive survey of left ventricle wall stress models, their mechanics, stress computation and results. We have provided herein a compendium of major type of wall stress models: thin-wall models based on the Laplace law, thick-wall shell models, elasticity theory model, thick-wall large deformation models and finite element models. We have compared the mean stress values of these models as well as the variation of stress across the wall. All of the thin-wall and thick-wall shell models are based on idealised ellipsoidal and spherical geometries. However, the elasticity model's shape can vary through the cycle, to simulate the more ellipsoidal shape of the left ventricle in the systolic phase. The finite element models have more representative geometries, but are generally based on animal data, which limits their medical relevance. This paper can enable readers to obtain a comprehensive perspective of left ventricle wall stress models, of how to employ them to determine wall stresses, and be cognizant of the assumptions involved in the use of specific models.     

Using Genetic Distance to Infer the Accuracy of Genomic Prediction

The prediction of phenotypic traits using high-density genomic data has many applications such as the selection of plants and animals of commercial interest; and it is expected to play an increasing role in medical diagnostics. Statistical models used for this task are usually tested using cross-validation, which implicitly assumes that new individuals (whose phenotypes we would like to predict) originate from the same population the genomic prediction model is trained on. In this paper we propose an approach based on clustering and resampling to investigate the effect of increasing genetic distance between training and target populations when predicting quantitative traits. This is important for plant and animal genetics, where genomic selection programs rely on the precision of predictions in future rounds of breeding. Therefore, estimating how quickly predictive accuracy decays is important in deciding which training population to use and how often the model has to be recalibrated. We find that the correlation between true and predicted values decays approximately linearly with respect to either F_ST or mean kinship between the training and the target populations. We illustrate this relationship using simulations and a collection of data sets from mice, wheat and human genetics.     

论＂医德＂的基本范畴

医德是医疗卫生领域精神文明建设的重要部分,也是调整医务人员与病人、医务人员之间以及与社会之间关系的行为准则。医德范畴是指人们对现代医务人员职业道德和医患关系的总结,它不仅概括了医生所应履行的职责义务,而且反映着一段时间内医患关系的本质。本文通过对医德范畴内,医生的权利和义务、责任和良心、功力和荣誉、审慎和保密四类问题的阐述,探讨当下医生在工作中应该保持何种心态,如何与患者进行沟通,以期更好地提供医疗服务。     

A Confucian View of Personhood and Bioethics

This paper focuses on Confucian formulations of personhood and the implications they may have for bioethics and medical practice. We discuss how an appreciation of the Confucian concept of personhood can provide insights into the practice of informed consent and, in particular, the role of family members and physicians in medical decision-making in societies influenced by Confucian culture. We suggest that Western notions of informed consent appear ethically misguided when viewed from a Confucian perspective.     

Medical Students’ Perceptions of Clinical Teachers as Role Model

Introduction

Role models facilitate student learning and assists in the development of professional identity. However, social organization and cultural values influence the choice of role models. Considering that the social organization and cultural values in South East Asia are different from other countries, it is important to know whether this affects the characteristics medical students look for in their role models in these societies.

Methods

A 32 item questionnaire was developed and self-administered to undergraduate medical students. Participants rated the characteristics on a three point scale (0 = not important, 1 = mildly important, 2 = very important). One way ANOVA and student''s t-test were used to compare the groups.

Results

A total of 349 (65.23%) distributed questionnaires were returned. The highest ranked themes were teaching and facilitating learning, patient care and continuing professional development followed by communication and professionalism. Safe environment and guiding personal and professional development was indicated least important. Differences were also observed between scores obtained by males and females.

Conclusion

Globally there are attributes which are perceived as essential for role models, while others are considered desirable. An understanding of the attributes which are essential and desirable for role models can help medical educators devise strategies which can reinforce those attributes within their institutions.     

AI applications to medical images: From machine learning to deep learning

PurposeArtificial intelligence (AI) models are playing an increasing role in biomedical research and healthcare services. This review focuses on challenges points to be clarified about how to develop AI applications as clinical decision support systems in the real-world context.MethodsA narrative review has been performed including a critical assessment of articles published between 1989 and 2021 that guided challenging sections.ResultsWe first illustrate the architectural characteristics of machine learning (ML)/radiomics and deep learning (DL) approaches. For ML/radiomics, the phases of feature selection and of training, validation, and testing are described. DL models are presented as multi-layered artificial/convolutional neural networks, allowing us to directly process images. The data curation section includes technical steps such as image labelling, image annotation (with segmentation as a crucial step in radiomics), data harmonization (enabling compensation for differences in imaging protocols that typically generate noise in non-AI imaging studies) and federated learning. Thereafter, we dedicate specific sections to: sample size calculation, considering multiple testing in AI approaches; procedures for data augmentation to work with limited and unbalanced datasets; and the interpretability of AI models (the so-called black box issue). Pros and cons for choosing ML versus DL to implement AI applications to medical imaging are finally presented in a synoptic way.ConclusionsBiomedicine and healthcare systems are one of the most important fields for AI applications and medical imaging is probably the most suitable and promising domain. Clarification of specific challenging points facilitates the development of such systems and their translation to clinical practice.     

Modelling an outbreak of an emerging pathogen

To illustrate the usefulness of mathematical models to the microbiology and medical communities, we explain how to construct and apply a simple transmission model of an emerging pathogen. We chose to model, as a case study, a large (>8,000 reported cases) on-going outbreak of community-acquired meticillin-resistant Staphylococcus aureus (CA-MRSA) in the Los Angeles County Jail. A major risk factor for CA-MRSA infection is incarceration. Here, we show how to design a within-jail transmission model of CA-MRSA, parameterize the model and reconstruct the outbreak. The model is then used to assess the severity of the outbreak, predict the epidemiological consequences of a catastrophic outbreak and design effective interventions for outbreak control.     

Taming the complexity of protein folding

Protein folding is an important problem in structural biology with significant medical implications, particularly for misfolding disorders like Alzheimer's disease. Solving the folding problem will ultimately require a combination of theory and experiment, with theoretical models providing a comprehensive view of folding and experiments grounding these models in reality. Here we review progress towards this goal over the past decade, with an emphasis on recent theoretical advances that are empowering chemically detailed models of folding and the new results these technologies are providing. In particular, we discuss new insights made possible by Markov state models (MSMs), including the role of non-native contacts and the hub-like character of protein folded states.     

Modeling the mechanisms of acute hepatitis B virus infection

Mathematical models have been used to understand the factors that govern infectious disease progression in viral infections. Here we focus on hepatitis B virus (HBV) dynamics during the acute stages of the infection and analyze the immune mechanisms responsible for viral clearance. We start by presenting the basic model used to interpret HBV therapy studies conducted in chronically infected patients. We then introduce additional models to study acute infection where immune responses presumably play an important role in determining whether the infection will be cleared or become chronic. We add complexity incrementally and explain each step of the modeling process. Finally, we validate the model against experimental data to determine how well it represents the biological system and, consequently, how useful are its predictions. In particular, we find that a cell-mediated immune response plays an important role in controlling the virus after the peak in viral load.     

Force Transduction by the Microtubule-Bound Dam1 Ring

The coupling between the depolymerization of microtubules (MTs) and the motion of the Dam1 ring complex is now thought to play an important role in the generation of forces during mitosis. Our current understanding of this motion is based on a number of detailed computational models. Although these models realize possible mechanisms for force transduction, they can be extended by variation of any of a large number of poorly measured parameters and there is no clear strategy for determining how they might be distinguished experimentally. Here we seek to identify and analyze two distinct mechanisms present in the computational models. In the first, the splayed protofilaments at the end of the depolymerizing MT physically prevent the Dam1 ring from falling off the end, and in the other, an attractive binding secures the ring to the microtubule. Based on this analysis, we discuss how to distinguish between competing models that seek to explain how the Dam1 ring stays on the MT. We propose novel experimental approaches that could resolve these models for the first time, either by changing the diffusion constant of the Dam1 ring (e.g., by tethering a long polymer to it) or by using a time-varying load.