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1.
The analysis of mismatch repair proteins in solid tissue is the standard of care (SoC) for the microsatellite instability (MSI) characterization in endometrial cancer (EC). Uterine aspirates (UAs) or circulating-DNA (cfDNA) samples capture the intratumor heterogeneity and provide a more comprehensive and dynamic molecular diagnosis. Thus, MSI analysis by droplet-digital PCR (ddPCR) in UAs and cfDNA can provide a reliable tool to characterize and follow-up the disease. The UAs, paraffin-embedded tumor tissue (FFPE) and longitudinal plasma samples from a cohort of 90 EC patients were analyzed using ddPCR panel and compared to the SoC. A high concordance (96.67%) was obtained between the analysis of MSI markers in UAs and the SoC. Three discordant cases were validated as unstable by ddPCR on FFPE samples. Besides, a good overall concordance (70.27%) was obtained when comparing the performance of the ddPCR assay on UAs and cfDNA in high-risk tumors. Importantly, our results also evidenced the value of MSI analysis to monitor the disease evolution. MSI evaluation in minimally invasive samples shows great accuracy and sensitivity and provides a valuable tool for the molecular characterization and follow-up of endometrial tumors, opening new opportunities for personalized management of EC.  相似文献   
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We propose a Deep learning-based weak label learning method for analyzing whole slide images (WSIs) of Hematoxylin and Eosin (H&E) stained tumor tissue not requiring pixel-level or tile-level annotations using Self-supervised pre-training and heterogeneity-aware deep Multiple Instance LEarning (DeepSMILE). We apply DeepSMILE to the task of Homologous recombination deficiency (HRD) and microsatellite instability (MSI) prediction. We utilize contrastive self-supervised learning to pre-train a feature extractor on histopathology tiles of cancer tissue. Additionally, we use variability-aware deep multiple instance learning to learn the tile feature aggregation function while modeling tumor heterogeneity. For MSI prediction in a tumor-annotated and color normalized subset of TCGA-CRC (n=360 patients), contrastive self-supervised learning improves the tile supervision baseline from 0.77 to 0.87 AUROC, on par with our proposed DeepSMILE method. On TCGA-BC (n=1041 patients) without any manual annotations, DeepSMILE improves HRD classification performance from 0.77 to 0.81 AUROC compared to tile supervision with either a self-supervised or ImageNet pre-trained feature extractor. Our proposed methods reach the baseline performance using only 40% of the labeled data on both datasets. These improvements suggest we can use standard self-supervised learning techniques combined with multiple instance learning in the histopathology domain to improve genomic label classification performance with fewer labeled data.  相似文献   
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目的 探讨开放性修复手术治疗距腓前韧带距骨侧止点撕脱骨折的临床疗效。方法 回顾性研究。纳入2017年11月—2021年4月徐州仁慈医院足踝外科确诊为距腓前韧带距骨侧止点撕脱骨折的患者4例(4足)。其中男3例、女1例,年龄15~45岁(平均30.3岁),右足2例、左足2例。患者均采用外踝前外侧小切口开放性修复手术治疗距腓前韧带的距骨侧止点撕脱骨折,术后石膏制动。观察项目:(1)记录患者骨折愈合的时间、末次随访时踝关节疼痛视觉模拟评分法(VAS)评分,美国足踝外科协会(AOFAS)踝-后足功能评分、踝关节功能评价Karlsson-Peterson评分。(2)术前及末次随访时测量距骨前移距离(ATT)、距骨倾斜角(TT)。结果 4例患者手术均顺利完成,术后均获随访8~25个月。(1)患者骨折愈合均良好,愈合时间3~5个月(平均3.8个月)。末次随访时,患者疼痛VAS评分为0~2分(平均1.3分),AOFAS踝-后足评分为89~95分(平均92.8分),Karlsson-Peterson评分为89~94分(平均91.5分);患者1例踝关节疼痛消失,其余3例仅有轻微酸胀不适,不影响日常行走。(2)末次随访时ATT为(2.4±0.3)mm、TT为2.8°±0.8°,较术前(8.4±0.8)mm和10.0°±1.4°明显改善,差异均有统计学意义(t=14.40、19.62,P值均<0.001)。结论 采用开放性小切口结合2枚锚钉修复距腓前韧带的距骨侧撕脱骨折,可有效恢复患者踝关节的稳定性。手术创伤小,操作简便,有临床推广价值。  相似文献   
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BackgroundPatellofemoral joint cartilage defects are difficult to treat due to their unique thickness and topography.PurposeTo report the postoperative outcomes of patients age 21 and younger treated with particulated juvenile allograft cartilage (PJAC) for full-thickness cartilaginous defects of the patellofemoral joint. The primary aim was to report surgical outcomes and complication rates, as well as return to sport activity. A secondary aim was to provide objective scores of defect restoration by magnetic resonance imaging (MRI) assessment.MethodsA retrospective review of all PJAC cases conducted between 2012 and 2019 at a single tertiary care urban musculoskeletal institution was conducted. Patients 21 years old or younger with minimum clinical follow up of 1 year and postoperative MRI at a minimum of 6 months were included. Cartilage restoration by MRI was independently assessed using the International Cartilage Repair Society’s (ICRS) standardized system.ResultsThirty four patients, 36 knees, were included, with mean age 16.1 ± 3.1 years old. Return to sport rate among patients who participated in a sport preoperatively was 100%. On independent MRI assessment, two thirds of defects achieved an overall grade of normal or nearly normal, while 28 patients (78%) had majority defect fill. Primary graft failure occurred in two cases and one patient experienced a surgical complication.ConclusionRestoration of patellofemoral chondral defects in young patients with particulated juvenile allograft results in satisfactory short-term outcomes and postoperative MRI appearance, along with high rates of return to sport and low rate of complications and graft failure.What is known about the subject: Patellofemoral joint cartilage defects are difficult to treat due to their unique thickness and topography. Several cartilage restoration techniques are available, but these rarely achieve the same mechanical properties as native hyaline cartilage. PJAC is a cell-based technique that has demonstrated promise since its introduction in 2007.What this study adds to existing knowledge: This series of patients adds the largest single cohort of pediatric and adolescent patients who receive PJAC for defects of the patellofemoral joint. Surgeons treating patients in this age group should be aware of every technique, and their respective outcomes.  相似文献   
6.
随着人口老龄化,老年高血压患者的患病率逐年增加,需选择外科手术的老年高血压患者也逐渐增多。由于围手术期发生的生理性变化,血流动力学不稳定在围手术期很常见。尽管存在这种血流动力学改变频率及与其相关的潜在危害,特别是在老年人群中,但缺乏优化围手术期血压的指南。低血压与围手术期的不良结果有关,特别是肾损伤、心肌损伤和死亡率增加。个性化血压可能是老年人围手术期血压管理的关键。  相似文献   
7.
目的 观察功能性踝关节不稳(FAI)患者的足底压力分布特征。  相似文献   
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BackgroundThe aim of this study was to develop and validate a finite element (FE) model of the patellofemoral joint to analyze the biomechanics of lateral retinacular release after medial patellofemoral ligament (MPFL) reconstruction in patellar malalignment (increased tibial tubercle–trochlear groove distance (TT-TG)). We hypothesized that lateral retinacular release is not appropriate in patellar instability addressed by MPFL reconstruction due to decreased lateral stability and inappropriate adjustment in patellofemoral contact pressures.MethodsA FE in-silico model of the patellofemoral joint was developed and validated. The model was used analyze the effect of lateral retinacular release in association with MPFL reconstruction on patellofemoral contact pressures, contact area, and lateral patellar displacement during knee flexion.ResultsMPFL reconstruction alone results in restoration of patellofemoral contact pressures throughout the entire range of motion (0–90°), mimicking the results from healthy condition. The addition of the lateral retinacular release to the MPFL reconstruction resulted in significant reductions in both patellofemoral contact pressure and contact area. Lateral retinacular release resulted in more lateral patellar displacement during the mid-flexion knee range of motion.ConclusionsCombination of lateral retinacular release with MPFL reconstruction in patients with increased TT-TG is not recommended as MPFL reconstruction alone for first-line management of recurrent patellar instability offers a greater biomechanical advantage and restoration of contact forces to resemble that of the healthy knee. The presented biomechanical data outlines the effect of concomitant MPFL reconstruction and lateral retinacular release to help guide surgical planning for patients with recurrent patellar instability due to malalignment.  相似文献   
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