Computational vascular fluid–structure interaction: methodology and application to cerebral aneurysms

A computational vascular fluid–structure interaction framework for the simulation of patient-specific cerebral aneurysm configurations is presented. A new approach for the computation of the blood vessel tissue prestress is also described. Simulations of four patient-specific models are carried out, and quantities of hemodynamic interest such as wall shear stress and wall tension are studied to examine the relevance of fluid–structure interaction modeling when compared to the rigid arterial wall assumption. We demonstrate that flexible wall modeling plays an important role in accurate prediction of patient-specific hemodynamics. Discussion of the clinical relevance of our methods and results is provided.     

Derivation of Patient Specific Pluripotent Stem Cells Using Clinically Discarded Cumulus Cells

Induced pluripotent stem cells (iPSCs) are powerful tools for basic and translational research, as well as regenerative medicine. In routine human in vitro fertilization (IVF) practices, cumulus cells (CCs) are discarded, representing a potential source of biological materials for regenerative medicine. In this study, we derived patient-specific iPSCs using CCs from human infertility clinics for the first time. The human cumulus cell derived iPSCs (hc-iPSCs) were characterized for growth, karyotype, expression of pluripotency genes, and were subjected to embryoid bodies (EBs) and teratoma assays to evaluate their differentiation capacity. Hc-iPSCs display typical iPSC characteristics, and are capable of differentiating into all germ layers in vitro and in vivo. We further show that putative primordial germ cell like cells (PGCLCs) can be derived using hc-iPSCs. Our data demonstrate the feasibility of deriving patient-specific pluripotent stem cells using CCs.     

TomoEQA: Dose verification for patient-specific quality assurance in helical tomotherapy using an exit detector

PurposeExisting phantom-less quality assurance (QA) platforms does not provide patient-specific QA for helical tomotherapy (HT). A new system, called TomoEQA, is presented to facilitate this using the leaf open time (LOT) of a binary multi-leaf collimator, as measured by an exit detector.MethodsTomoEQA was designed to provide measurement-based LOTs based on detector data and to generate a new digital imaging and communication in medicine (DICOM) dataset that includes the measured LOTs for use by secondary check platforms. To evaluate the system, 20 patient-specific QAs were performed using the program in Mobius3D software, and the results were compared to conventional phantom-based QA results.ResultsFrom our assessment, most of the differences between the planned and measured (or calculated) data, excluding one case, were within the acceptance criteria comparing with those of conventional QA. Regarding the gamma analysis, all results considered in this study were within the acceptance criteria. In addition, the developed system was performed for a failed case and showed approximately the same trends as the conventional approach.ConclusionsTomoEQA could perform patient-specific QAs of HT using Mobius3D and provide reliable patient-specific QAs results by evaluating point dose errors and 3D gamma passing rates. TomoEQA could also distinguish whether an intensity-modulated radiation therapy plan failed or not.     

Sparse Representation-Based Patient-Specific Diagnosis and Treatment for Esophageal Squamous Cell Carcinoma

Precision medicine and personalized treatment have attracted attention in recent years. However, most genetic medicines mainly target one genetic site, while complex diseases like esophageal squamous cell carcinoma (ESCC) usually present heterogeneity that involves variations of many genetic markers. Here, we seek an approach to leverage genetic data and ESCC knowledge data to forward personalized diagnosis and treatment for ESCC. First, 851 ESCC-related gene markers and their druggability were studied through a comprehensive literature analysis. Then, a sparse representation-based variable selection (SRVS) was employed for patient-specific genetic marker selection using gene expression datasets. Results showed that the SRVS method could identify a unique gene vector for each patient group, leading to significantly higher classification accuracies compared to randomly selected genes (100, 97.17, 100, 100%; permutation p values: 0.0032, 0.0008, 0.0004, and 0.0008). The SRVS also outperformed an ANOVA-based gene selection method in terms of the classification ratio. The patient-specific gene markers are targets of ESCC effective drugs, providing specific guidance for medicine selection. Our results suggest the effectiveness of integrating previous database utilizing SRVS in assisting personalized medicine selection and treatment for ESCC.     

诱导多能干细胞在心血管疾病研究和治疗中的应用

诱导多能干细胞（induced pluripotent stem cells,iPS细胞）不仅具有与胚胎干细胞（embryonic stem cell,ESC）相似的各项特性,相对于ESC,iPS细胞,尤其患者特异性iPS细胞还具有来源方便、不存在免疫排斥和伦理问题以及可以保留特定个体基因型等优点,为再生医学提供了可能的细胞来源。该文主要从心血管药物的筛选、疾病模型的建立、iPS细胞应用于心脏移植研究等方面入手,探讨了iPS细胞在心血管疾病研究和治疗中的现状和未来。     

From inverse problems in mathematical physiology to quantitative differential diagnoses

The improved capacity to acquire quantitative data in a clinical setting has generally failed to improve outcomes in acutely ill patients, suggesting a need for advances in computer-supported data interpretation and decision making. In particular, the application of mathematical models of experimentally elucidated physiological mechanisms could augment the interpretation of quantitative, patient-specific information and help to better target therapy. Yet, such models are typically complex and nonlinear, a reality that often precludes the identification of unique parameters and states of the model that best represent available data. Hypothesizing that this non-uniqueness can convey useful information, we implemented a simplified simulation of a common differential diagnostic process (hypotension in an acute care setting), using a combination of a mathematical model of the cardiovascular system, a stochastic measurement model, and Bayesian inference techniques to quantify parameter and state uncertainty. The output of this procedure is a probability density function on the space of model parameters and initial conditions for a particular patient, based on prior population information together with patient-specific clinical observations. We show that multimodal posterior probability density functions arise naturally, even when unimodal and uninformative priors are used. The peaks of these densities correspond to clinically relevant differential diagnoses and can, in the simplified simulation setting, be constrained to a single diagnosis by assimilating additional observations from dynamical interventions (e.g., fluid challenge). We conclude that the ill-posedness of the inverse problem in quantitative physiology is not merely a technical obstacle, but rather reflects clinical reality and, when addressed adequately in the solution process, provides a novel link between mathematically described physiological knowledge and the clinical concept of differential diagnoses. We outline possible steps toward translating this computational approach to the bedside, to supplement today's evidence-based medicine with a quantitatively founded model-based medicine that integrates mechanistic knowledge with patient-specific information.     

诱导多功能干细胞的影响因素

将体细胞诱导为多功能干细胞为人类的再生医学提供了一个全新的研究手段,从而可以不用损坏胚胎就能获得可用于治疗各种特殊疾病的细胞。本文比较了近年来关于生成诱导性多能干细胞(induced pluripotent stem cells,iPS细胞)的诱导方法及重编程效率,总结了这些方法的共同点;另外通过对每个不同试验过程的影响因素进行比较,归纳了影响iPS细胞重编程过程的几个因素。     

A Meta-Analysis of Chinese Herbal Medicine in Treatment of Managed Withdrawal from Heroin

Chinese herbal medicine has shown promise for heroin detoxification. This review extends a prior meta-analysis of Chinese herbal medicine for heroin detoxification, with particular attention to the time course of symptoms. Both English and Chinese databases were searched for randomized trials comparing Chinese herbal medicine to either α2-adrenergic agonists or opioid agonists for heroin detoxification. The methodological quality of each study was assessed with Jadad’s scale (1–2 = low; 3–5 = high). Meta-analysis was performed with fixed- or random-effect models in RevMan software; outcome measures assessed were withdrawal-symptoms score, anxiety, and adverse effects of treatment. Twenty-one studies (2,949 participants) were included. For withdrawal-symptoms score relieving during the 10-day observation, Chinese herbal medicine was superior to α2-adrenergic agonists in relieving opioid-withdrawal symptoms during 4–10 days (except D8) and no difference was found within the first 3 days. Compared with opioid agonists, Chinese herbal medicine was inferior during the first 3 days, but the difference became non-significant during days 4–9. Chinese herbal medicine has better effect on anxiety relieving at late stage of intervention than α2-adrenergic agonists, and no difference with opioid agonists. The incidence of some adverse effects (fatigue, dizziness) was significantly lower for Chinese herbal medicine than for α2-adrenergic agonists (sufficient data for comparison with opioid agonists were not available). Findings were robust to file-drawer effects. Our meta-analysis suggests that Chinese herbal medicine is an effective and safety treatment for heroin detoxification. And more work is needed to determine the specific effects of specific forms of Chinese herbal medicine.     

Patient-specific modeling of dyssynchronous heart failure: A case study

The development and clinical use of patient-specific models of the heart is now a feasible goal. Models have the potential to aid in diagnosis and support decision-making in clinical cardiology. Several groups are now working on developing multi-scale models of the heart for understanding therapeutic mechanisms and better predicting clinical outcomes of interventions such as cardiac resynchronization therapy. Here we describe the methodology for generating a patient-specific model of the failing heart with a myocardial infarct and left ventricular bundle branch block. We discuss some of the remaining challenges in developing reliable patient-specific models of cardiac electromechanical activity, and identify some of the main areas for focusing future research efforts. Key challenges include: efficiently generating accurate patient-specific geometric meshes and mapping regional myofiber architecture to them; modeling electrical activation patterns based on cellular alterations in human heart failure, and estimating regional tissue conductivities based on clinically available electrocardiographic recordings; estimating unloaded ventricular reference geometry and material properties for biomechanical simulations; and parameterizing systemic models of circulatory dynamics from available hemodynamic measurements.     

Feasibility of reducing differences in estimated doses in nuclear medicine between a patient-specific and a reference phantom

The feasibility of reducing the differences between patient-specific internal doses and doses estimated using reference phantoms was evaluated. Relatively simple adjustments to a polygon-surface ICRP adult male reference phantom were applied to fit selected individual dimensions using the software Rhinoceros®4.0. We tested this approach on two patient-specific phantoms: the biggest and the smallest phantoms from the Helmholtz Zentrum München library. These phantoms have unrelated anatomy and large differences in body-mass-index. Three models approximating each patient’s anatomy were considered: the voxel and the polygon-surface ICRP adult male reference phantoms and the adjusted polygon-surface reference phantom. The Specific Absorbed Fractions (SAFs) for internal photon and electron sources were calculated with the Monte Carlo code EGSnrc. Employing the time-integrated activity coefficients of a radiopharmaceutical (S)-4-(3-¹⁸F-fluoropropyl)-l-glutamic acid and the calculated SAFs, organ absorbed-dose coefficients were computed following the formalism promulgated by the Committee on Medical Internal Radiation Dose. We compared the absorbed-dose coefficients between each patient-specific phantom and other models considered with emphasis on the cross-fire component. The corresponding differences for most organs were notably lower for the adjusted reference models compared to the case when reference models were employed. Overall, the proposed approach provided reliable dose estimates for both tested patient-specific models despite the pronounced differences in their anatomy. To capture the full range of inter-individual anatomic variability more patient-specific phantoms are required. The results of this test study suggest a feasibility of estimating patient-specific doses within a relative uncertainty of 25% or less using adjusted reference models, when only simple phantom scaling is applied.     

From evidence-based medicine to genomic medicine

The concept of ‘evidence-based medicine’ dates back to mid-19th century or even earlier. It remains pivotal in planning, funding and in delivering the health care. Clinicians, public health practitioners, health commissioners/purchasers, health planners, politicians and public seek formal ‘evidence’ in approving any form of health care provision. Essentially ‘evidence-based medicine’ aims at the conscientious, explicit and judicious use of the current best evidence in making decisions about the care of individual patients. It is in fact the ‘personalised medicine’ in practice. Since the completion of the human genome project and the rapid accumulation of huge amount of data, scientists and physicians alike are excited on the prospect of ‘personalised health care’ based on individual’s genotype and phenotype. The first decade of the new millennium now witnesses the transition from ‘evidence-based medicine’ to the ‘genomic medicine’. The practice of medicine, including health promotion and prevention of disease, stands now at a wide-open road as the scientific and medical community embraces itself with the rapidly expanding and revolutionising field of genomic medicine. This article reviews the rapid transformation of modern medicine from the ‘evidence-based medicine’ to ‘genomic medicine’.     

综述: 诱导重编程过程中的表观遗传重塑

多能干细胞(pluripotent stem cell,PSC)是一类具有自我更新能力和多向分化潜能的细胞,具有广泛的临床应用前景．诱导性多功能干细胞(induced pluripotent stem cell,iPS cell)的获得,解决了传统方式中的细胞来源和伦理学等问题,从理论研究和应用上实现了体细胞重编程的重大突破,也为疾病发生机制研究、药物筛选、个性化药物选择、细胞治疗和再生医学等研究创造了难得的机会,从而开启了多能干细胞应用的新纪元．iPS过程中有很多问题尚未得到解决,尤其是诱导重编程的分子机制方面,这也是近年来干细胞领域研究的热点．其中如何实现表观遗传的重编程被认为是亟待解决的核心问题之一．本文结合我们的研究,主要介绍诱导重编程领域表观遗传修饰重塑机制的研究进展,并展望未来研究中大规模信息整合分析的重要性．     

Genomic medicine and neurological disease

“Genomic medicine” refers to the diagnosis, optimized management, and treatment of disease—as well as screening, counseling, and disease gene identification—in the context of information provided by an individual patient’s personal genome. Genomic medicine, to some extent synonymous with “personalized medicine,” has been made possible by recent advances in genome technologies. Genomic medicine represents a new approach to health care and disease management that attempts to optimize the care of a patient based upon information gleaned from his or her personal genome sequence. In this review, we describe recent progress in genomic medicine as it relates to neurological disease. Many neurological disorders either segregate as Mendelian phenotypes or occur sporadically in association with a new mutation in a single gene. Heritability also contributes to other neurological conditions that appear to exhibit more complex genetics. In addition to discussing current knowledge in this field, we offer suggestions for maximizing the utility of genomic information in clinical practice as the field of genomic medicine unfolds.     

外周血细胞重编程为诱导性多潜能干细胞的研究进展

诱导性多潜能干细胞(iPSCs)是指分化细胞中导入特定转录因子后逆转恢复到类似胚胎干细胞的具有自我更新、多向分化等潜能的一类细胞。诱导疾病特异性iPSCs是疾病机理、再生医学等领域的研究热点。目前,人iPSCs供体细胞主要来源于皮肤成纤维细胞,需要组织活检、体外增殖等繁琐过程。利用外周血细胞(peripheral blood cells)成功诱导iPSCs,具有取材方便、诱导快速等优点,将极大地促进iPSCs研究。该文在介绍iPSCs诱导方法的基础上,重点阐述了从小鼠B细胞、T细胞,人脐带血细胞,到人外周血细胞重编程为iPSCs的研究进展,分析了该技术的特点和可能存在的问题,并进行了前景展望。     

Reflexive Biomedicalization and Alternative Healing Systems

The utilization of alternative medical therapies and practitioners has increased dramatically in the U.S. in the last two to three decades. This trend seems paradoxical when one considers the rapid advances taking place in biomedical knowledge and technology during this same time period. Observers both inside and outside of the medical profession have attempted to explain the rising popularity of alternative medicine by proposing that it signals a growing sense of dissatisfaction and disenchantment with professional biomedical practices on the part of the lay public. This paper challenges this thesis and offers an alternative explanation, arguing that the rise of alternative medicine is a consequence of the success and expanding influence of biomedicine rather than its failure and declining authority. The argument presented draws primarily on Ulrich Beck’s “risk society” perspective and theory of “reflexive modernization,” with specific attention to his analysis of the “reflexive scientization” process. The application of this perspective allows us to understand the emergence and development of alternative medicine as an unanticipated consequence of the process of reflexive biomedicalization in the late modern era.