A case of sudden cardiac death due to mitochondrial disease

A 25-year-old, emaciated man without medical treatment was found to have died suddenly at home by his mother. At autopsy, there were no injuries to his body, but significant circulatory insufficiency was observed. Electron microscopy revealed abnormal mitochondria in cells of the cardiac conduction system. The conduction system was filled with mitochondrial size abnormalities and mitochondrial cristae abnormalities. No notable abnormal findings were observed in other organs. Genetic examination of the blood revealed the mitochondrial pathogenetic variant m.3243A>G. Epileptic seizures, diabetic ketoacidosis, and hyperosmolar hyperglycemic state were unlikely to be the cause of sudden death. The cause of death was diagnosed as arrhythmia possibly induced by the failure of the cardiac conduction system due to mitochondrial disease. This is a rare case of sudden death caused by an accumulation of abnormal mitochondria in the cardiac conduction system.     

A Proposal for an Alternative Approach to Particle Size Method Development During Early-Stage Small Molecule Pharmaceutical Development

Particle size analysis in the pharmaceutical industry has long been a source of debate regarding how best to define measurement accuracy; the degree to which the result of a measurement or calculation conforms to the true value. Defining a “true” value for the size of a particle can be challenging as the output of its measurement will differ because of variations in measurement approaches, instrumental differences and calculation methods. Consequently, for “real” particles, a universal “true” value does not exist and accuracy is therefore not a definable characteristic. Accordingly, precision is then a measure of the ability to reproducibly achieve a measurement of unknown relevance.This article proposes, in place of accuracy, a means to define the “appropriateness” of a measurement in line with the critical quality attributes (CQA) of the material being characterized. The decision as to whether the measurement is correct should involve a link to the CQA; that is, correlation should be demonstrated, without which the measured particle size cannot be defined as a critical material attribute.Correspondingly, methods should also be able to provide sufficient precision to demonstrate discrimination relating to variation in the CQA. The benefits and challenges of this approach are discussed.     

Population Genetics Identifies Challenges in Analyzing Rare Variants

Geneticists have, for years, understood the nature of genome‐wide association studies using common genomic variants. Recently, however, focus has shifted to the analysis of rare variants. This presents potential problems for researchers, as rare variants do not always behave in the same way common variants do, sometimes rendering decades of solid intuition moot. In this paper, we present examples of the differences between common and rare variants. We show why one must be significantly more careful about the origin of rare variants, and how failing to do so can lead to highly inflated type I error. We then explain how to best avoid such concerns with careful understanding and study design. Additionally, we demonstrate that a seemingly low error rate in next‐generation sequencing can dramatically impact the false‐positive rate for rare variants. This is due to the fact that rare variants are, by definition, seen infrequently, making it hard to distinguish between errors and real variants. Compounding this problem is the fact that the proportion of errors is likely to get worse, not better, with increasing sample size. One cannot simply scale their way up in order to solve this problem. Understanding these potential pitfalls is a key step in successfully identifying true associations between rare variants and diseases.     

P-Values and Power in Orthopedic Research: Myths and Reality

The results of statistical tests in orthopedic studies are typically reported using P-values. If a P-value is smaller than the pre-determined level of significance (eg, < .05), the null hypothesis is rejected in support of the alternative. This automaticity in interpreting statistical results without consideration of the power of the study has been denounced over the years by statisticians, since it can potentially lead to misinterpretation of the study conclusions. In this paper, we review fundamental misconceptions and misinterpretations of P-values and power, along with their connection with confidence intervals, and we provide guidelines to orthopedic researchers for evaluating and reporting study results. We provide real-world orthopedic examples to illustrate the main concepts. Please visit the following https://youtu.be/bdPU4luYmF0 for videos that explain the highlights of the paper in practical terms.     

刺果甘草全基因组Survey及叶绿体基因组特征分析＊

目的 基于基因组Survey分析对刺果甘草Glycyrrhiza pallidiflora Maxim.基因组大小和杂合率进行估计，并通过叶绿体基因组序列特征对其在甘草属Glycyrrhiza L.中的系统发育位置进行研究。方法 使用二代测序技术对刺果甘草进行测序，采用K-mer方法对测序reads进行分析，估算刺果甘草基因组大小和杂合率，使用生物信息学方法进行叶绿体基因组组装、注释和系统发育分析。结果 Survey分析结果显示其基因组大小约为577.82 Mb，杂合度约为0.31%，重复序列比例约为53.72%。叶绿体基因组长度为127，267 bp，不具有典型的四分体结构，总GC含量为34.32%，包含110个基因，其中76个蛋白质编码基因，30个tRNA基因和4个rRNA基因。系统发育分析表明，刺果甘草与圆果甘草G. squamulosa Franch.亲缘较接近。结论 刺果甘草存在低杂合和重复序列较多的特点，为了更好地对全基因组进行序列拼接和组装，可尝试采用三代测序结合二代测序的分析策略进行基因组组装；刺果甘草叶绿体全基因组比对和系统发育分析，为后续开展甘草属遗传多样性研究和分子鉴定标记筛选提供了重要依据。     

Effect of Race and Ethnicity on Risk of Radiotherapy Toxicity and Implications for Radiogenomics

AimsPatient factors affect the risk of radiotherapy toxicity, but many are poorly defined. Studies have shown that race affects cancer incidence, survival, drug response, molecular pathways and epigenetics. Effects on radiosensitivity and radiotherapy toxicity are not well studied. The aim of the present study was to identify the effects of race and ethnicity on the risk of radiotherapy toxicity.Materials and methodsA systematic review was carried out of PubMed, Ovid Medline and Ovid Embase with no year limit. PRISMA 2020 guidelines were followed. Two independent assessors reviewed papers.ResultsOf 607 papers screened, 46 fulfilled the inclusion criteria. Papers were published between 1996 and 2021 and involved 30–28,354 individuals (median 433). Most involved patients with prostate (33%), breast (26%) and lung (9%) cancer. Both early and late toxicities were studied. Some studies reported a higher risk of toxicity in White men with prostate cancer compared with other races and ethnicities. For breast cancer patients, some reported an increased risk of toxicity in White women compared with other race and ethnic groups. In general, it was difficult to draw conclusions due to insufficient reporting and analysis of race and ethnicity in published literature.ConclusionsReporting of race and ethnicity in radiotherapy studies must be harmonised and improved and frameworks are needed to improve the quality of reporting. Further research is needed to understand how ancestral heritage might affect radiosensitivity and risk of radiotherapy toxicity.     

Sample size re-estimation for clinical trials with longitudinal negative binomial counts including time trends

In some diseases, such as multiple sclerosis, lesion counts obtained from magnetic resonance imaging (MRI) are used as markers of disease progression. This leads to longitudinal, and typically overdispersed, count data outcomes in clinical trials. Models for such data invariably include a number of nuisance parameters, which can be difficult to specify at the planning stage, leading to considerable uncertainty in sample size specification. Consequently, blinded sample size re-estimation procedures are used, allowing for an adjustment of the sample size within an ongoing trial by estimating relevant nuisance parameters at an interim point, without compromising trial integrity. To date, the methods available for re-estimation have required an assumption that the mean count is time-constant within patients. We propose a new modeling approach that maintains the advantages of established procedures but allows for general underlying and treatment-specific time trends in the mean response. A simulation study is conducted to assess the effectiveness of blinded sample size re-estimation methods over fixed designs. Sample sizes attained through blinded sample size re-estimation procedures are shown to maintain the desired study power without inflating the Type I error rate and the procedure is demonstrated on MRI data from a recent study in multiple sclerosis.     

Tumour volume distribution can yield information on tumour growth and tumour control

BackgroundIt is shown that tumour volume distributions can yield information on two aspects of cancer research: tumour induction and tumour control.Materials and methodsFrom the hypothesis that the intrinsic distribution of breast cancer volumes follows an exponential distribution, firstly the probability density function of tumour growth time was deduced via a mathematical transformation of the probability density functions of tumour volumes. In a second step, the distribution of tumour volumes was used to model the variation of the clonogenic cell number between patients in order to determine tumour control probabilities for radiotherapy patients.ResultsDistribution of lag times, i.e. the time from the appearance of the first fully malignant cell until a clinically observable cancer, can be used to deduce the probability of tumour induction as a function of patient age. The integration of the volume variation with a Poisson-TCP model results in a logistic function which explains population-averaged survival data of radiotherapy patients.ConclusionsThe inclusion of tumour volume distributions into the TCP formalism enables a direct link to be deduced between a cohort TCP model (logistic) and a TCP model for individual patients (Poisson). The TCP model can be applied to non-uniform tumour dose distributions.