Electrolipolysis associated with aerobic activity does not reduce subcutaneous adipose tissue of the abdominal region of young women: A randomized clinical trial

ObjectiveTo analyze the effects of electrolysis, through a medium frequency current, associated to aerobic physical activity in the body composition of young women.MethodsThe study was composed of 34 sedentary women (24.35 ± 4.43 years, 71.30 ± 7.08 kg, 1.61 ± 0.06 m, 27.31 ± 1.67 kg/m2) which were evaluated for their anthropometric measures and body composition. The volunteers were randomly assigned to two group: Electrolyphysis plus Aerobic Exercise (gEEA): 17 volunteers were submitted to the application, for 60 min , of the Aussie current, followed by aerobic physical activity (77% of HRmax) on the trampoline for 40 min, through video-lessons of Jump; and Aerobic Exercise group (gEA): 17 volunteers performed only physical activity following the same parameters mentioned above. Each group performed its protocols twice weekly, for 5 weeks, totaling 10 sessions. For the data analysis, measures repeated ANOVA was performed to compare the means of the variables analyzed before and after the treatment protocols using the SPSS - 21.0 software, adopting a p ≤ 0.05.ResultsAlthough gEEA decreased suprailiac skinfold (p = 0.04), abdominal skinfold (p = 0.03) and circumference at umbilical scar (p = 0.02) in an intragroup analysis, these means differences in anthropometric measures were not important between-groups (p > 0.05). Furthermore, there were no effect of treatment on body composition (p > 0.05).ConclusionTo this studied condition, our results suggested that application of medium frequency electrolysis did not enhance the losses on anthropometric measures and body composition.     

治伤巴布剂对大鼠急性软组织损伤模型P38MAPK、AKT信号通路的影响＊

目的 观察治伤巴布剂对急性软组织损伤（acute soft tissue injury， ASTI）模型p38丝裂原活化蛋白激酶（mitogen-activated protein kinase，MAPK）、丝/苏氨酸蛋白激酶（AKT）信号通路的影响，探讨治伤巴布剂干预ASTI的可能作用机制。方法 将40只雄性SD大鼠按照随机数字表法分为正常对照组、模型对照组、治伤巴布剂组、p38MAPK信号通路抑制剂组、AKT信号通路抑制剂组，每组8只。除正常对照组外，其余四组均予以左侧后肢小腿ASTI造模。造模成功后，治伤巴布剂组于标记部位立即予治伤巴布剂（修剪成1.5x3cm大小）外敷，并用胶布固定；其余四组均予等剂量赋形剂（修剪成1.5×3 cm大小）外敷处理，胶布固定；持续外敷，共持续24 h。p38MAPK信号通路抑制剂组在造模前30 min予腹腔注射p38MAPK信号通路抑制剂SB203580（400 μg/kg/天）1次；AKT信号通路抑制剂组在造模前30 min予腹腔注射AKT信号通路抑制剂perifosine（20 mg/kg/天）1次。分别于0（造模前）、2h、4h、8h、12h、24h测量受伤小腿肌肉处的周长，并计算肌肉肿胀率（muscle swelling rate，MSR）。24 h药物干预结束后，采用颈椎脱臼法处死大鼠。后将左侧后肢小腿损伤中心部位进行取材，分成三份。一部分用于观察组织病理学形态变化；一部分用于逆转录聚合酶链反应（RT-PCR）检测核因子-κB（nuclear factor kappa-B，NF-κB）p65 mRNA、肿瘤坏死因子-α（TNF-α）mRNA、白细胞介素-1β（IL-1β）mRNA表达水平；剩下部分用酶联免疫吸附试验（ELISA）法检测骨骼肌组织TNF-α、IL-1β含量水平及蛋白质免疫印迹（Western-blot）法测定p38MAPK、AKT、NF-κB p65、核因子抑制蛋白α（inhibitor kappa B alpha， IκBα）表达水平。结果 与正常对照组相比，模型对照组MSR显著增加（P<0.01）；病理形态学上，骨骼肌组织可见大面积肌细胞排列紊乱，肌细胞变性坏死，间质内可见红细胞聚集及大量炎症细胞浸润；骨骼肌组织TNF-α、IL-1β含量水平显著升高（P<0.01）；磷酸化p38MAPK（p-p38）/总p38MAPK（t-p38），磷酸化-AKT（p-AKT）/总-AKT（t-AKT）明显升高（P<0.01），NF-κB p65及NF-κB p65mRNA表达水平明显升高（P<0.01）。与模型对照组相比，治伤巴布剂组MSR在治疗第8 h、12 h、24 h显著下降（P<0.01），且在治疗第24 h，其MSR较p38MAPK、AKT信号通路抑制剂组下降更明显（P<0.05）；病理学评分显著下降（P<0.01），且较p38MAPK、AKT信号通路抑制剂组下降更显著（P<0.05）；骨骼肌组织TNF-α、IL-1β含量水平明显下降（P<0.01），且较p38MAPK、AKT信号通路抑制剂组更显著（P<0.05）；p-p38/t-p38及p-AKT/t-AKT明显下降（P<0.01），NF-κB p65及NF-κB p65 mRNA表达水平显著下降（P<0.01），且较p38MAPK、AKT信号通路抑制剂组在降低NF-κB p65及NF-κB p65 mRNA相对表达值方面更显著（P<0.01）。结论 治伤巴布剂可能同时对p38MAPK、AKT信号通路产生了一定的抑制作用，引起NF-κB活性下调，NF-κB p65蛋白的表达下调，进而引起骨骼肌组织TNF-α、IL-1β炎性细胞因子含量水平下调，减轻ASTI炎症反应，从而改善ASTI。     

Intraabdominal and retroperitoneal soft-tissue sarcomas – Surgical treatment and outcomes

BackgroundIntraabdominal and retroperitoneal sarcomas (IaRS) are malignant connective tissue tumors. Surgical resection is often the only curative treatment. The primary objective was to report the mid-term outcomes following contemporary treatment protocols and identify prognostic factors.MethodsA retrospective review of consecutive patients (n = 107) with IaRS treated at single center from 2013 until 2018 was conducted. Histological diagnosis, tumor grade, perioperative complications, mortality, and long-time survival were registered and retrieved from patient records. Primary and recurrent tumors were analyzed separately.ResultsA total of 107 patients were identified. Median follow-up time was 3.5 years. Thirty-day mortality was 3.4% and 90-day mortality was 5.6% for all tumors. The major complication rate was 18%. The 5-year estimated survival for primary and recurrent tumors was 55.4% and 48.4%, respectively. Multifocal disease was evident in 32% of the patient cohort, and 58% of patients in the recurrent group. Multivariate analysis for survival revealed a hazard ratio (HR) of 3.1 (95% CI 1.68–8.41) for multifocality, HR 2.9 (95% CI 1.28–6.98) for Clavien-Dindo grade, HR 2.3 (95% CI 1.21–4.31) for tumor grades 2 or 3, and HR 1.002 (95% CI 1.001–1.004) for surgical margins.ConclusionsOur study found overall acceptable morbidity and mortality, and identified prognostic markers for overall survival. Recurrent tumors were not associated with worse survival. Multifocality is associated with a worse overall survival. The prognostic factors identified were; tumor grade, multifocality, intralesional margins and postoperative complications.     

Health-related quality of life after isolated limb perfusion compared to extended resection,or amputation for locally advanced extremity sarcoma: Is a limb salvage strategy worth the effort?

IntroductionThe aim of this study was to compare long-term patient reported outcomes (PROs) in patients with locally advanced extremity soft tissue sarcoma (eSTS) after isolated limb perfusion followed by resection (IR), compared to extended resection (ER), primary amputation (A) or secondary amputation after IR (IR-A).MethodsPatients were selected from the respondents of a multi-institutional cross-sectional cohort survivorship study (SURVSARC) conducted among sarcoma survivors registered in the Netherlands Cancer Registry (NCR), 2–10 years after diagnosis. Used PROs were the EORTC QLQ-C30, the Cancer worry scale (CWS), the Hospital Anxiety and Depression Scale (HADS), and the Toronto Extremity Salvage Score (TESS).ResultsWe identified 97 eSTS survivors: IR = 20, ER = 49, A = 20, IR-A = 8. While there were no differences in PROs between IR and ER, results showed better functioning and functionality in both groups versus the amputation groups. The amputation groups scored significantly lower on physical functioning (A = 62.7, IR-A = 65.7 versus IR = 78.0, ER = 82.7, p = 0.001) and role functioning (A = 67.5, IR-A = 52.8 versus IR = 79.2, ER = 80.6, p = 0.039), both EORTC QLQ-C30 scales. Also for the TESS, the scores were significantly lower for the amputation groups compared to the limb sparing groups (upper extremity p = 0.007 with A = 68.9, IR-A = 71.6 versus IR = 93.3, ER = 91.1; lower extremity p < 0.001 with A = 72.2, IR-A50.9 versus IR = 84.5 and ER = 85.5). There were no significant differences between the groups on cancer worry, anxiety and depression.ConclusionHRQoL in eSTS survivors treated with IR or ER is equal; for maintenance of physical functioning and functionality IR and ER outperform an amputation.     

Assessment of a novel deep learning-based marker-less motion capture system for gait study

BackgroundMarker-less systems based on digital video cameras and deep learning for gait analysis could have a deep impact in clinical routine. A recently developed system has shown promising results in terms of joint center position but has not been yet evaluated in terms of gait outcomes.Research questionHow does this novel marker-less system compare to a marker-based reference system in terms of clinically relevant gait parameters?MethodsThe deep learning method behind the developed marker-less system was trained on a dedicated dataset consisting of forty-one asymptomatic and pathological subjects each performing ten walking trials. The system could estimate the three-dimensional position of seventeen joint centers or keypoints (e.g., neck, shoulders, hip, knee, and ankles). We evaluated the marker-less system against a marker-based system in terms of differences in joint position (Euclidean distance), detection of gait events (e.g., heel strike and toe-off), spatiotemporal parameters (e.g., step length, time), kinematic parameters (e.g., hip and knee extension-flexion), and inter-trial reliability for kinematic parameters.ResultsThe marker-less system was able to estimate the three-dimensional position of joint centers with a mean difference of 13.1 mm (SD = 10.2 mm). 99% of the estimated gait events were estimated within 10 ms of the corresponding reference values. Estimated spatiotemporal parameters showed zero bias. The mean and standard deviation of the differences of the estimated kinematic parameters varied by parameter (for example, the mean and standard deviation for knee extension flexion angle were −3.0° and 2.7°). Inter-trial reliability of the measured parameters was similar to that of the marker-based references.SignificanceThe developed marker-less system can measure the spatiotemporal parameters within the range of the minimum detectable changes obtained using the marker-based reference system. Moreover, except for hip extension flexion, the system showed promising results in terms of several kinematic parameters.     

Automatic segmentation of thoracic CT images using three deep learning models

PurposeDeep learning (DL) techniques are widely used in medical imaging and in particular for segmentation. Indeed, manual segmentation of organs at risk (OARs) is time-consuming and suffers from inter- and intra-observer segmentation variability. Image segmentation using DL has given very promising results. In this work, we present and compare the results of segmentation of OARs and a clinical target volume (CTV) in thoracic CT images using three DL models.Materials and methodsWe used CT images of 52 patients with breast cancer from a public dataset. Automatic segmentation of the lungs, the heart and a CTV was performed using three models based on the U-Net architecture. Three metrics were used to quantify and compare the segmentation results obtained with these models: the Dice similarity coefficient (DSC), the Jaccard coefficient (J) and the Hausdorff distance (HD).ResultsThe obtained values of DSC, J and HD were presented for each segmented organ and for the three models. Examples of automatic segmentation were presented and compared to the corresponding ground truth delineations. Our values were also compared to recent results obtained by other authors.ConclusionThe performance of three DL models was evaluated for the delineation of the lungs, the heart and a CTV. This study showed clearly that these 2D models based on the U-Net architecture can be used to delineate organs in CT images with a good performance compared to other models. Generally, the three models present similar performances. Using a dataset with more CT images, the three models should give better results.