Invasion of paranasal sinuses by Aspergillus oryzae

A 24-year-old male patient receiving chemotherapy for acute promyelocytic leukemia developed fever, right periorbital swelling and mild right proptosis. A head scan showed opacification of the right maxillary and ethmoid sinuses with adjacent soft tissue swelling. Biopsy of the nasal mucosa demonstrated the typical septate hyphae of Aspergillus species which was later shown on culture to be Aspergillus oryzae. A. oryzae has only rarely been reported in human disease and there is confusion as to its precise identification and role. We would like to confirm the pathogenicity of A. oryzae with this uncommon presentation of aspergillosis and also emphasize the need to take adequate and multiple cultures in suspected cases so that the possibility of species identification will be maximized.     

Organoid models of the tumor microenvironment and their applications

A small percentage of data obtained from animal/2D culture models can be translated to humans. Therefore, there is a need to using native tumour microenvironment mimicking models to improve preclinical screening and reduce this attrition rate. For this purpose, currently, the utilization of organoids is expanding. Tumour organoids can recapitulate tumour microenvironment that is including cancer cells and non-neoplastic host components. Indeed, tumour organoids, both phenotypically and genetically, resemble the tumour tissue that originated from it. The unique properties of the tumour microenvironment can significantly affect drug response and cancer progression. In this review, we will discuss about various organoid culture strategies for modelling the tumour immune microenvironment, their applications and advantages in cancer research such as testing cancer immunotherapeutics, developing novel approaches for personalized medicine, testing drug toxicity, drug screening, study cancer initiation and progression, and we will also review the limitations of organoid culture systems.     

Bias in Markov models of disease

We examine bias in Markov models of diseases, including both chronic and infectious diseases. We consider two common types of Markov disease models: ones where disease progression changes by severity of disease, and ones where progression of disease changes in time or by age. We find sufficient conditions for bias to exist in models with aggregated transition probabilities when compared to models with state/time dependent transition probabilities. We also find that when aggregating data to compute transition probabilities, bias increases with the degree of data aggregation. We illustrate by examining bias in Markov models of Hepatitis C, Alzheimer’s disease, and lung cancer using medical data and find that the bias is significant depending on the method used to aggregate the data. A key implication is that by not incorporating state/time dependent transition probabilities, studies that use Markov models of diseases may be significantly overestimating or underestimating disease progression. This could potentially result in incorrect recommendations from cost-effectiveness studies and incorrect disease burden forecasts.     

TGF-β in progression of liver disease

Transforming growth factor-β (TGF-β) is a central regulator in chronic liver disease contributing to all stages of disease progression from initial liver injury through inflammation and fibrosis to cirrhosis and hepatocellular carcinoma. Liver-damage-induced levels of active TGF-β enhance hepatocyte destruction and mediate hepatic stellate cell and fibroblast activation resulting in a wound-healing response, including myofibroblast generation and extracellular matrix deposition. Being recognised as a major profibrogenic cytokine, the targeting of the TGF-β signalling pathway has been explored with respect to the inhibition of liver disease progression. Whereas interference with TGF-β signalling in various short-term animal models has provided promising results, liver disease progression in humans is a process of decades with different phases in which TGF-β or its targeting might have both beneficial and adverse outcomes. Based on recent literature, we summarise the cell-type-directed double-edged role of TGF-β in various liver disease stages. We emphasise that, in order to achieve therapeutic effects, we need to target TGF-β signalling in the right cell type at the right time.     

Pluripotent Stem Cells Models for Huntington＇s Disease： Prospects and Challenges

Pluripotent cellular models have shown great promise in the study of a number of neurological disorders.Several advantages of using a stem cell model include the potential for cells to derive disease relevant neuronal cell types,providing a system for researchers to monitor disease progression during neurogenesis,along with serving as a platform for drug discovery.A number of stem cell derived models have been employed to establish in vitro research models of Huntington’s disease that can be used to investigate cellular pathology and screen for drug and cell-based therapies.Although some progress has been made,there are a number of challenges and limitations that must be overcome before the true potential of this research strategy is achieved.In this article we review current stem cell models that have been reported,as well as discuss the issues that impair these studies.We also highlight the prospective application of Huntington’s disease stem cell models in the development of novel therapeutic strategies and advancement of personalized medicine.     

Modeling nonhomogeneous Markov processes via time transformation

Summary .   Longitudinal studies are a powerful tool for characterizing the course of chronic disease. These studies are usually carried out with subjects observed at periodic visits giving rise to panel data. Under this observation scheme the exact times of disease state transitions and sequence of disease states visited are unknown and Markov process models are often used to describe disease progression. Most applications of Markov process models rely on the assumption of time homogeneity, that is, that the transition rates are constant over time. This assumption is not satisfied when transition rates depend on time from the process origin. However, limited statistical tools are available for dealing with nonhomogeneity. We propose models in which the time scale of a nonhomogeneous Markov process is transformed to an operational time scale on which the process is homogeneous. We develop a method for jointly estimating the time transformation and the transition intensity matrix for the time transformed homogeneous process. We assess maximum likelihood estimation using the Fisher scoring algorithm via simulation studies and compare performance of our method to homogeneous and piecewise homogeneous models. We apply our methodology to a study of delirium progression in a cohort of stem cell transplantation recipients and show that our method identifies temporal trends in delirium incidence and recovery.     

Impact of the US Patent System on the Promise of Personalized Medicine

The biotechnology revolution promises unfathomable future scientific discovery. One of the potential benefits is the accelerated introduction of new diagnostics and treatments to the general public. The right medication for the right patient is the goal of personalized medicine, which directly benefits from many of biotechnology's biggest and most recent advances. The US patent system rewards innovation in medicine and other arts and sciences by granting innovators, for a period of time, the right to exclude others from using what was invented. One of the purposes of the patent system is to trade that right to exclude, and in its stead obtain the patent holder's obligation to fully and publicly disclose the essence of the innovations so that they can be improved, thus advancing the common welfare. A tension exists between personalized medicine's need for access to and use of scientific advances and the patent system's reward of exclusive use or nonuse to innovators. This tension may result in fewer diagnostic and therapeutic tools brought to the market and generally adopted. The risk seems particularly acute with respect to the diagnostic and therapeutic tools arising from genetic testing that hold specific value for a subset of the population. The judicial system has introduced ethical exceptions that overcome a patent holder's right to exclude; these judicial overrides relate to the provision of certain types of medical procedures and the development of certain types of new drugs, and not, apparently, to the use of diagnostic and therapeutic tools essential to the success of personalized medicine. A serious question exists as to whether legislative action is necessary to increase public access to genetic testing.     

Estimation in a semi-Markov transformation model

Semi-Markov and modulated renewal processes provide a large class of multi-state models which can be used for analysis of longitudinal failure time data. In biomedical applications, models of this kind are often used to describe evolution of a disease and assume that patient may move among a finite number of states representing different phases in the disease progression. Several authors proposed extensions of the proportional hazard model for regression analysis of these processes. In this paper, we consider a general class of censored semi-Markov and modulated renewal processes and propose use of transformation models for their analysis. Special cases include modulated renewal processes with interarrival times specified using transformation models, and semi-Markov processes with with one-step transition probabilities defined using copula-transformation models. We discuss estimation of finite and infinite dimensional parameters and develop an extension of the Gaussian multiplier method for setting confidence bands for transition probabilities and related parameters. A transplant outcome data set from the Center for International Blood and Marrow Transplant Research is used for illustrative purposes.     

Bioprinting technologies for disease modeling

There is a great need for the development of biomimetic human tissue models that allow elucidation of the pathophysiological conditions involved in disease initiation and progression. Conventional two-dimensional (2D) in vitro assays and animal models have been unable to fully recapitulate the critical characteristics of human physiology. Alternatively, three-dimensional (3D) tissue models are often developed in a low-throughput manner and lack crucial native-like architecture. The recent emergence of bioprinting technologies has enabled creating 3D tissue models that address the critical challenges of conventional in vitro assays through the development of custom bioinks and patient derived cells coupled with well-defined arrangements of biomaterials. Here, we provide an overview on the technological aspects of 3D bioprinting technique and discuss how the development of bioprinted tissue models have propelled our understanding of diseases’ characteristics (i.e. initiation and progression). The future perspectives on the use of bioprinted 3D tissue models for drug discovery application are also highlighted.     

In vivo therapeutic applications of cell spheroids

Spheroids are increasingly being employed to answer a wide range of clinical and biomedical inquiries ranging from pharmacology to disease pathophysiology, with the ultimate goal of using spheroids for tissue engineering and regeneration. When compared to traditional two-dimensional cell culture, spheroids have the advantage of better replicating the 3D extracellular microenvironment and its associated growth factors and signaling cascades. As knowledge about the preparation and maintenance of spheroids has improved, there has been a plethora of translational experiments investigating in vivo implantation of spheroids into various animal models studying tissue regeneration.We review methods for spheroid delivery and how they have been utilized in tissue engineering experiments. We break down efforts in this field by organ systems, discussing applications of spheroids to various animal models of disease processes and their potential clinical implications. These breakthroughs have been made possible by advancements in spheroid formation, in vivo delivery and assessment. There is unexplored potential and room for further research and development in spheroid-based tissue engineering approaches. Regenerative medicine and other clinical applications ensure this exciting area of research remains relevant for patient care.     

In vitro and in vivo translational models for rare liver diseases

A challenge in developing effective treatments is the modeling of the human disease using in vitro and in vivo systems. Animal models have played a critical role in the understanding of disease pathophysiology, target validation, and evaluation of novel therapeutic agents. However, as the success rate from entry into clinical testing to drug approval remains low, it is critical to have high quality and well-validated models reflective of the disease condition. Additional experimental models are being developed based on functional in vitro 3D tissue models such as organoids and 3D bioprinted tissues. Because these 3D tissue models mimic closer the architecture, cell composition and physiology of native tissues, they are now being used as screening platforms in drug discovery and development and for tissue transplant in regenerative medicine. Here we review the current state-of-art of in vitro and in vivo translational models for the development of therapies for rare diseases of the liver.     

自身免疫调节因子(AIRE)的研究进展

自身免疫调节因子(autoimmune regulator,AIRE)是一种具有转录活化潜能的DNA结合蛋白。由于AIRE基因的突变可导致自身免疫病APECED(autoimmune polyendocrinopathy—candidiasis-ectodermal dystrophy,APECED),又称自身免疫性多腺体综合征I(autoimmune polyglandular syndrome typeI,APSI)。因此,这一基因在正常生理状态下很可能对维持自身免疫耐受、控制自身免疫起着重要作用。对自身免疫耐受产生机制的揭示将为自身免疫病、超敏反应、移植排斥及肿瘤的治疗提供新的策略。本文对AIRE的基因鉴定、分子结构和生化功能、亚细胞定位、组织分布及其在自身耐受产生中的作用作一综述性介绍。     

Biobanking and public health: is a human rights approach the tie that binds?

Ethical principles guiding public health and genomic medicine are often at odds: whereas public health practice adopts collectivist principles that emphasize population-based benefits, recent advances in genomic and personalized medicine are grounded in an individualist ethic that privileges informed consent, and the balancing of individual risk and benefit. Indeed, the attraction of personalized medicine is the promise it holds out to help individuals get the “right medicine for the right problem at the right time.” Research biobanks are an effective tool in the genomic medicine toolbox. Biobanking in public health presents a unique case study to unpack some of these issues in more detail. For example, there is a long history of using banked tissue obtained under clinical diagnostic conditions for later public health uses. But despite the collectivist approach of public health, the principles applied to the ethical challenges of biobanking (e.g. informed consent, autonomy, privacy) remain individualist. We demonstrate the value of using human rights as a public health ethics framework to address this tension in biobanking by applying it to two illustrative cases.     

Inference of surface membrane factors of HIV-1 infection through functional interaction networks

Background

HIV infection affects the populations of T helper cells, dendritic cells and macrophages. Moreover, it has a serious impact on the central nervous system. It is yet not clear whether this list is complete and why specifically those cell types are affected. To address this question, we have developed a method to identify cellular surface proteins that permit, mediate or enhance HIV infection in different cell/tissue types in HIV-infected individuals. Receptors associated with HIV infection share common functions and domains and are involved in similar cellular processes. These properties are exploited by bioinformatics techniques to predict novel cell surface proteins that potentially interact with HIV.

Methodology/Principal Findings

We compiled a set of surface membrane proteins (SMP) that are known to interact with HIV. This set is extended by proteins that have direct interaction and share functional similarity. This resulted in a comprehensive network around the initial SMP set. Using network centrality analysis we predict novel surface membrane factors from the annotated network. We identify 21 surface membrane factors, among which three have confirmed functions in HIV infection, seven have been identified by at least two other studies, and eleven are novel predictions and thus excellent targets for experimental investigation.

Conclusions

Determining to what extent HIV can interact with human SMPs is an important step towards understanding patient specific disease progression. Using various bioinformatics techniques, we generate a set of surface membrane factors that constitutes a well-founded starting point for experimental testing of cell/tissue susceptibility of different HIV strains as well as for cohort studies evaluating patient specific disease progression.     

How does endothelial cell injury start? The role of endothelin in systemic sclerosis

A considerable amount of research time has been invested in studies aimed at elucidating pathogenic processes in systemic sclerosis (SSc). Despite this, major challenges for biomedical science remain, such as identification of the key factors that determine susceptibility to SSc, and elucidation of the precise nature of the initiating event that causes endothelial cell injury and ultimately brings about the biological cascade(s) that lead to the pathologic vascular changes. Involved factors are likely to include genetic perturbations, environmental cues, tissue injury, infection and hypoxia/oxidative stress. As important as determining the initiating events are the identification and characterization of key factors that are functionally important in driving vascular disease progression, because these factors are potential targets for therapeutic intervention. This article reviews the role of endothelin as an example of a pleiotropic mediator with effects on various aspects of SSc pathogenesis, such as inflammation, vasculopathy and tissue remodelling.     

Detailed Analysis of the African Green Monkey Model of Nipah Virus Disease

Henipaviruses are implicated in severe and frequently fatal pneumonia and encephalitis in humans. There are no approved vaccines or treatments available for human use, and testing of candidates requires the use of well-characterized animal models that mimic human disease. We performed a comprehensive and statistically-powered evaluation of the African green monkey model to define parameters critical to disease progression and the extent to which they correlate with human disease. African green monkeys were inoculated by the intratracheal route with 2.5×10⁴ plaque forming units of the Malaysia strain of Nipah virus. Physiological data captured using telemetry implants and assessed in conjunction with clinical pathology were consistent with shock, and histopathology confirmed widespread tissue involvement associated with systemic vasculitis in animals that succumbed to acute disease. In addition, relapse encephalitis was identified in 100% of animals that survived beyond the acute disease phase. Our data suggest that disease progression in the African green monkey is comparable to the variable outcome of Nipah virus infection in humans.     

Neuroendocrine immunity in patients with Alzheimer's disease: toward translational epigenetics

The emerging domain of epigenetics in molecular medicine finds application for a variety of patient populations. Here, we present fundamental neuroendocrine immune evidence obtained in patients with senile dementia of the Alzheimer's type (sDAT), and discuss the implications of these data from the viewpoint of translational epigenetics of Alzheimer's disease. We followed 18 subjects with mild sDAT treated with acetylcholinesterase inhibitors, and 10 control subjects matched for age in a repeated measure design every six months for 18 months. We monitored psychosocial profile (Mini-Mental State Examination, Functional Assessment Staging, Independence in Activities of Daily Living, Depression, Profile of Moods States) in parallel to immunophenotypic parameters of T cell subpopulations by flow cytometry. Based on change in the mini-mental state score at entry and at 18 months, patients with sDAT were assigned to a "fast progression" (delta greater than 2 points) or to a "slow progression" group (delta less than or equal to 2 points). The change in circulating activated T cells (CD3+Dr+) with time in patients with sDAT was significantly inversely correlated with the change in time in natural killer (NK) cytotoxic activity to cortisol modulation in these patients, which was greater in patients with fast progression, compared to slow progression sDAT. These data indicate underlying neuroendocrine immune processes during progression of sDAT. Our observations suggest that psychoimmune measures such as those we have monitored in this study provide relevant information about the evolving physiological modulation in patients with sDAT during progression of Alzheimer's disease, and point to new or improved translational epigenetic treatment interventions.     

Tolerance and Autoimmunity

Long-lasting tolerance can be produced by prenatal or perinatal exposure to foreign antigens. Self-tolerance results from embryonic exposure to antigens of the host itself. Several mechanisms that contribute to self-tolerance have been described. They include clonal deletion, anergy, and active suppression. A failure in these mechanisms may lead to autoimmune disease. Some important human diseases are associated with autoimmunity, and immunomethods are regularly employed for their diagnosis. In the future immunomethods will prove to be valuable for the identification of subjects at risk of developing autoimmune disease, thereby permitting preventive interventions.     

Transposon Mediated Integration of Plasmid DNA into the Subventricular Zone of Neonatal Mice to Generate Novel Models of Glioblastoma

An urgent need exists to test the contribution of new genes to the pathogenesis and progression of human glioblastomas (GBM), the most common primary brain tumor in adults with dismal prognosis. New potential therapies are rapidly emerging from the bench and require systematic testing in experimental models which closely reproduce the salient features of the human disease. Herein we describe in detail a method to induce new models of GBM with transposon-mediated integration of plasmid DNA into cells of the subventricular zone of neonatal mice. We present a simple way to clone new transposons amenable for genomic integration using the Sleeping Beauty transposon system and illustrate how to monitor plasmid uptake and disease progression using bioluminescence, histology and immuno-histochemistry. We also describe a method to create new primary GBM cell lines. Ideally, this report will allow further dissemination of the Sleeping Beauty transposon system among brain tumor researchers, leading to an in depth understanding of GBM pathogenesis and progression and to the timely design and testing of effective therapies for patients.