新型国产二尖瓣夹合器系统的动物实验研究

通过动物实验,对一种新型国产二尖瓣夹合器系统的可行性和安全性进行评价。14只正常三元杂交系猪分为实验组10只和对照组4只,实验组植入新型二尖瓣夹合器系统,对照组行传统二尖瓣修复术。分别于术前、术后不同时间点行超声心动图检查、血液检查,术后140 d对动物安乐死取材,进行心脏及主要脏器大体、病理检查,观察植入后的情况。实验组共8只动物、对照组共4只动物达到实验终点,所有动物术中未出现夹合器脱落、心脏破裂、瓣膜损伤、顽固性心律失常、脏器栓塞、心力衰竭、死亡等严重并发症。超声显示,所有夹合器均固定在二尖瓣处,不同时间点二尖瓣平均跨瓣压差、左心室射血分数等两组间均未见具有统计学意义的差异。血液学检查,未见植入器械对肝肾功能产生明显影响。病理检查提示,夹合器周围瓣叶呈现慢性炎症、黏液样变性、少量出血,未引起二尖瓣及心脏组织损伤,未出现心脏血栓、感染,各脏器也未见血栓栓塞。动物实验结果表明,新型国产二尖瓣夹合器系统生物相容性好,能够有效固定在二尖瓣处而不引起严重的相关并发症。     

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。     

经乙二醇诱导的改良型草酸钙肾结石果蝇模型

目的:通过一种改良方法构建果蝇草酸钙肾结石模型。方法:配制标准培养基和造模用培养基，空白对照组果蝇仅予标准培养基，而传统模型组和改良模型组分别从成虫期和幼虫期开始摄入含 0.5%乙二醇( EG)的造模用培养基。于偏光显微镜下观察并评估各组果蝇马氏管内成石情况，分别记录模型组成石率达 100%所花时间，并对成石率 100%时模型组间“ ++”和“ +++”所占比率进行比较；用傅立叶变换拉曼光谱仪鉴定模型组果蝇马氏管内结石成分。绘制各组果蝇生存曲线，并比较生存周期差异。结果:改良模型组和传统模型组分别在果蝇成虫日龄 14 d和 22 d，马氏管内成石率达到 100%。当改良模型组和传统模型组成石率均达到 100%时，两组“ ++”与“+++”所占比率分别为(40.5±4.4)%和(39.0±4.2)%，差异无统计学意义(P＞ 0.05)；拉曼位移的主峰主要集中在 1 462 cm-1、1 463 cm-1和 1 473 cm-1，说明模型组果蝇马氏管内结石成分均为草酸钙。空白对照组、传统模型组和改良模型组的最高寿命分别为 76 d、70 d和 68 d，中位生存时间分别为 35 d、30.5 d和 30 d，与空白对照组相比，模型组生存周期均显著缩短(P均＜ 0.01)，但传统模型组与改良模型组间差异无统计学意义( P＞ 0.05)。结论:改良型造模方法使果蝇在其幼虫期即摄入 0.5% EG，缩短了模型构建周期且具有可重复性，值得进一步研究推广。     

Nonlinear panel data estimation via quantile regressions

We introduce a class of quantile regression estimators for short panels. Our framework covers static and dynamic autoregressive models, models with general predetermined regressors and models with multiple individual effects. We use quantile regression as a flexible tool to model the relationships between outcomes, covariates and heterogeneity. We develop an iterative simulation‐based approach for estimation, which exploits the computational simplicity of ordinary quantile regression in each iteration step. Finally, an application to measure the effect of smoking during pregnancy on birthweight completes the paper.     

Genomic data in prognostic models—what is lost in translation? The case of deletion 17p and mutant TP53 in chronic lymphocytic leukaemia

Genomic technologies are revolutionizing the practice of haematology-oncology, leading to improved disease detection, more accurate prognostication and targeted treatment decisions. These advances, however, have also introduced new clinical challenges, which include problems of prognostic underdetermination and its attendant risks of over- and undertreatment. Genomic data is generated from different technologies, from cytogenetics to next-generation sequencing, which are often interpreted interchangeably and in a binary fashion—as the presence or absence of a given chromosomal deletion or mutation—an oversimplification which may lead to mistaken prognosis. We discuss the clinical use of one such prognostic marker, represented by sequence and copy number alterations in TP53, located on chromosome 17p. Mutations in TP53 are strongly linked to poor prognosis in a variety of haematological malignancies, including chronic lymphocytic leukaemia (CLL). We review studies in CLL which utilize the 17p deletion or TP53 mutations for prognostic stratification with specific focus on the technologies used for detection, the thresholds established for clinical significance, and the clinical contexts in which these alterations are identified. The case of CLL illustrates issues arising from simplistic, binary interpretation of genetic testing and highlights the need to apply a critical lens when incorporating genomics into prognostic models.     

Powerful rare variant association testing in a copula-based joint analysis of multiple phenotypes

In genetic association studies of rare variants, the low power of association tests is one of the main challenges. In this study, we propose a new single-marker association test called C-JAMP (Copula-based Joint Analysis of Multiple Phenotypes), which is based on a joint model of multiple phenotypes given genetic markers and other covariates. We evaluated its performance and compared its empirical type I error and power with existing univariate and multivariate single-marker and multi-marker rare-variant tests in extensive simulation studies. C-JAMP yielded unbiased genetic effect estimates and valid type I errors with an adjusted test statistic. When strongly dependent traits were jointly analyzed, C-JAMP had the highest power in all scenarios except when a high percentage of variants were causal with moderate/small effect sizes. When traits with weak or moderate dependence were analyzed, whether C-JAMP or competing approaches had higher power depended on the effect size. When C-JAMP was applied with a misspecified copula function, it still achieved high power in some of the scenarios considered. In a real-data application, we analyzed sequencing data using C-JAMP and performed the first genome-wide association studies of high-molecular-weight and medium-molecular-weight adiponectin plasma concentrations. C-JAMP identified 20 rare variants with p-values smaller than 10⁻⁵, while all other tests resulted in the identification of fewer variants with higher p-values. In summary, the results indicate that C-JAMP is a powerful, flexible, and robust method for association studies, and we identified novel candidate markers for adiponectin. C-JAMP is implemented as an R package and freely available from https://cran.r-project.org/package=CJAMP .     

Animal models of spinal injury for studying back pain and SCI

IntroductionBack pain is a common ailment affecting individuals around the globe. Animal models to understand the back pain mechanism, treatment modalities, and spinal cord injury are widely researched topics worldwide. Despite the presence of several animal models on disc degeneration and Spinal Cord Injury, there is a lack of a comprehensive review.Material and methodA methodological narrative literature review was carried out for the study. A total of 1273 publications were found, out of which 763 were related to spine surgery in animals. The literature with full-text availability was selected for the review. Scale for the Assessment of Narrative Review Articles (SANRA) guidelines was used to assess the studies. Only English language publications were included which were listed on PubMed. A total of 113 studies were shortlisted (1976–2019) after internal validation scoring.ResultThe animal models for spine surgery ranged from rodents to primates. These are used to study the mechanisms of back pain as well as spinal cord injuries. The models could either be created surgically or through various means like use of electric cautery, chemicals or trauma. Genetic spine models have also been documented in which the injuries are created by genetic alterations and knock outs. Though the dorsal approach is the most common, the literature also mentions the anterior and lateral approach for spine surgery animal experiments.ConclusionThere are no single perfect animal models to represent and study human models. The selection is based on the application and the methodology. Careful selection is needed to give optimum and appropriate results.