The efficacy of DNA mixture to mixture matching

Standard practice in forensic science is to compare a person of interest’s (POI) reference DNA profile with an evidence DNA profile and calculate a likelihood ratio that considers propositions including and excluding the POI as a DNA donor. A method has recently been published that provides the ability to compare two evidence profiles (of any number of contributors and of any level of resolution) comparing propositions that consider the profiles either have a common contributor, or do not have any common contributors. Using this method, forensic analysts can provide intelligence to law enforcement by linking crime scenes when no suspects may be available. The method could also be used as a quality assurance measure to identify potential sample to sample contamination. In this work we analyse a number of constructed mixtures, ranging from two to five contributors, and with known numbers of common contributors, in order to investigate the performance of using likelihood ratios for mixture to mixture comparisons. Our findings demonstrate the ability to identify common donors in DNA mixtures with the power of discrimination depending largely on the least informative mixture of the pair being considered. The ability to match mixtures to mixtures may provide intelligence information to investigators by identifying possible links between cases which otherwise may not have been considered connected.     

Consensus summary report for CEPI/BC March 12–13, 2020 meeting: Assessment of risk of disease enhancement with COVID-19 vaccines

A novel coronavirus (CoV), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in late 2019 in Wuhan, China and has since spread as a global pandemic. Safe and effective vaccines are thus urgently needed to reduce the significant morbidity and mortality of Coronavirus Disease 2019 (COVID-19) disease and ease the major economic impact. There has been an unprecedented rapid response by vaccine developers with now over one hundred vaccine candidates in development and at least six having reached clinical trials. However, a major challenge during rapid development is to avoid safety issues both by thoughtful vaccine design and by thorough evaluation in a timely manner. A syndrome of “disease enhancement” has been reported in the past for a few viral vaccines where those immunized suffered increased severity or death when they later encountered the virus or were found to have an increased frequency of infection. Animal models allowed scientists to determine the underlying mechanism for the former in the case of Respiratory syncytial virus (RSV) vaccine and have been utilized to design and screen new RSV vaccine candidates. Because some Middle East respiratory syndrome (MERS) and SARS-CoV-1 vaccines have shown evidence of disease enhancement in some animal models, this is a particular concern for SARS-CoV-2 vaccines. To address this challenge, the Coalition for Epidemic Preparedness Innovations (CEPI) and the Brighton Collaboration (BC) Safety Platform for Emergency vACcines (SPEAC) convened a scientific working meeting on March 12 and 13, 2020 of experts in the field of vaccine immunology and coronaviruses to consider what vaccine designs could reduce safety concerns and how animal models and immunological assessments in early clinical trials can help to assess the risk. This report summarizes the evidence presented and provides considerations for safety assessment of COVID-19 vaccine candidates in accelerated vaccine development.     

Using time series analysis to forecast the health-related quality of life of post-menopausal women with non-metastatic ER+ breast cancer: A tutorial and case study

BackgroundTime series models are widely used forecasting techniques in health care for long time series and are typically built in commercial statistical packages. However, for short time series data, such as health-related quality of life (HRQoL), guidance on how to select and use appropriate time series models is lacking. This tutorial provides a step-by-step guide adopting a time series analysis framework for HRQoL forecasting.ObjectiveWe walk through a case study examining the forecasting of the effects of adjuvant endocrine therapy on the HRQoL of post-menopausal women with non-metastatic ER + breast cancer using data from the HRQoL sub-protocol of the Tamoxifen arm of the Arimidex, tamoxifen, alone or in combination (ATAC) trial.MethodsThe forecasting of HRQoL consists of four steps: 1) data extraction and accuracy check, 2) forecasting horizon definition and identification of data pattern, 3) forecasting model identification and fitting using five forecasting approaches appropriate for short time series ((i) double exponential smoothing, (ii) double moving average, (iii) fuzzy forecasting, (iv) grey forecasting, and (v) Volterra series), 4) forecasting model selection. A user-friendly visual basic for applications (VBA) Excel add-in is made available to interested users to facilitate the application of the tutorial.ResultsThe Grey method and Volterra series appeared to be good candidates to forecast the effects of adjuvant endocrine therapy on the HRQoL of post-menopausal women with non-metastatic ER + breast cancer enrolled in the ATAC trial.ConclusionIt is feasible to forecast the effects of treatments on HRQOL even when the time series is short.     

Validation of randomized controlled trial-derived models for the prediction of postintervention outcomes in chronic limb-threatening ischemia

BackgroundChronic limb-threatening ischemia (CLTI) represents the most severe form of peripheral artery disease and has a large impact on quality of life, morbidity, and mortality. Interventions are aimed at improving tissue perfusion and averting amputation and secondary cardiovascular complications with an optimal risk-benefit ratio. Several prediction models regarding postprocedural outcomes in CLTI patients have been developed on the basis of randomized controlled trials to improve clinical decision-making. We aimed to determine model performance in predicting clinical outcomes in selected CLTI cohorts.MethodsThis study validated the Bypass versus Angioplasty in Severe Ischaemia of the Leg (BASIL), Finland National Vascular registry (FINNVASC), and Prevention of Infrainguinal Vein Graft Failure (PREVENT III) models in data sets from a peripheral artery disease registry study (Athero-Express) and two randomized controlled trials of CLTI in The Netherlands, Rejuvenating Endothelial Progenitor Cells via Transcutaneous Intra-arterial Supplementation (JUVENTAS) and Percutaneous Transluminal Angioplasty and Drug-eluting Stents for Infrapopliteal Lesions in Critical Limb Ischemia (PADI). Receiver operating characteristic (ROC) curve analysis was used to calculate their predictive capacity. The primary outcome was amputation-free survival (AFS); secondary outcomes were all-cause mortality and amputation at 12 months after intervention.ResultsThe BASIL and PREVENT III models showed predictive values regarding postintervention mortality in the JUVENTAS cohort with an area under the ROC curve (AUC) of 81% and 70%, respectively. Prediction of AFS was poor to fair (AUC, 0.60-0.71) for all models in each population, with the highest predictive value of 71% for the BASIL model in the JUVENTAS population. The FINNVASC model showed the highest predictive value regarding amputation risk in the PADI population with AUC of 78% at 12 months.ConclusionsIn general, all models performed poor to fair in predicting mortality and amputation. Because the BASIL model performed best in predicting AFS, we propose use of the BASIL model to aid in the clinical decision-making process in CLTI. However, improvements in performance have to be made for any of these models to be of real additional value in clinical practice.     

Does SARS‐Cov‐2 invade the brain? Translational lessons from animal models

The current coronavirus disease (COVID‐19) outbreak, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), has raised the possibility of potential neurotropic properties of this virus. Indeed, neurological sequelae of SARS‐CoV‐2 infection have already been reported and highlight the relevance of considering the neurological impact of coronavirus (CoV) from a translational perspective. Animal models of SARS and Middle East respiratory syndrome, caused by structurally similar CoVs during the 2002 and 2012 epidemics, have provided valuable data on nervous system involvement by CoVs and the potential for central nervous system spread of SARS‐CoV‐2. One key finding that may unify these pathogens is that all require angiotensin‐converting enzyme 2 as a cell entry receptor. The CoV spike glycoprotein, by which SARS‐CoV‐2 binds to cell membranes, binds angiotensin‐converting enzyme 2 with a higher affinity compared with SARS‐CoV. The expression of this receptor in neurons and endothelial cells hints that SARS‐CoV‐2 may have higher neuroinvasive potential compared with previous CoVs. However, it remains to be determined how such invasiveness might contribute to respiratory failure or cause direct neurological damage. Both direct and indirect mechanisms may be of relevance. Clinical heterogeneity potentially driven by differential host immune‐mediated responses will require extensive investigation. Development of disease models to anticipate emerging neurological complications and to explore mechanisms of direct or immune‐mediated pathogenicity in the short and medium term is therefore of great importance. In this brief review, we describe the current knowledge from models of previous CoV infections and discuss their potential relevance to COVID‐19.     

基于CT三维重建技术绘制骨折地图的临床应用进展

CT三维重建技术已经广泛应用于骨折诊断及其分型。基于CT三维重建的骨折地图绘制技术,通过绘制骨折模型来直观展现骨折线的形态学,包括骨折线的起止、走行、骨折面积等。骨折地图绘制技术为骨折诊断、骨折分型、治疗方案选择、手术内固定物设计、骨折好发部位统计、骨折标准化模型制定均提供了一个全新的方法。本文将回顾目前国内外包括对于肩胛骨骨折、胫骨远端骨折、尺骨冠状突骨折、胫骨平台骨折、桡骨小头骨折、股骨转子间外侧壁骨折、髋臼四边体骨折等骨折地图的研究进展,归纳总结了以上各个骨折模型的骨折好发部位及骨折地图绘制技术在骨折分型等方面的应用,并探讨骨折地图的临床应用前景及骨折地图绘制技术存在的问题等。     

肾虚证动物模型研究进展

肾虚证动物模型一直是中医证候研究的重点,提供与人类疾病类似的肾虚证动物模型,有助于深入研究肾虚证本质及其治疗。近年来建立了不少肾虚证动物模型,然而不同的肾虚证模型特点也不尽相同。对临床常见肾虚证型,从肾阳虚、肾阴虚、肾精不足、肾气虚方面进行概述,并对其存在的不足进行思考,以期为肾虚证动物模型的构建及其证候生物学机制研究提供新思路。     

Protective effects of pharmacological therapies in animal models of multiple sclerosis: a review of studies 2014–2019

Multiple sclerosis(MS)is an inflammatory demyelinating disease of the central nervous system.The disability caused by inflammatory demyelination clinically dominates the early stages of relapsing-remitting MS and is reversible.Once there is considerable loss of axons,MS patients enter a secondary progressive stage.Disease-modifying drugs currently in use for MS suppress the immune system and reduce relapse rates but are not effective in the progressive stage.Various animal models of MS(mostly mouse and rat)have been established and proved useful in studying the disease process and response to therapy.The experimental autoimmune encephalomyelitis animal studies reviewed here showed that a chronic progressive disease can be induced by immunization with appropriate amounts of myelin oligodendrocyte glycoprotein together with mycobacterium tuberculosis and pertussis toxin in Freund's adjuvant.The clinical manifestations of autoimmune encephalomyelitis disease were prevented or reduced by treatment with certain pharmacological agents given prior to,at,or after peak disease,and the agents had protective effects as shown by inhibiting demyelination and damage to neurons,axons and oligodendrocytes.In the cuprizone-induced toxicity animal studies,the pharmacological agents tested were able to promote remyelination and increase the number of oligodendrocytes when administered therapeutically or prophylactically.A monoclonal IgM antibody protected axons in the spinal cord and preserved motor function in animals inoculated with Theiler's murine encephalomyelitis virus.In all these studies the pharmacological agents were administered singly.A combination therapy may be more effective,especially using agents that target neuroinflammation and neurodegeneration,as they may exert synergistic actions.