A High Order Bound Preserving Finite Difference Linear Scheme for Incompressible Flows

We propose a high order finite difference linear scheme combined with a high order bound preserving maximum-principle-preserving (MPP) flux limiter to solve the incompressible flow system. For such problem with highly oscillatory structure but not strong shocks, our approach seems to be less dissipative and much less costly than a WENO type scheme, and has high resolution due to a Hermite reconstruction. Spurious numerical oscillations can be controlled by the weak MPP flux limiter. Numerical tests are performed for the Vlasov-Poisson system, the 2D guiding-center model and the incompressible Euler system. The comparison between the linear and WENO type schemes, with and without the MPP flux limiter, will demonstrate the good performance of our proposed approach.     

A Priori Subcell Limiting Approach for the FR/CPR Method on Unstructured Meshes

A priori subcell limiting approach is developed for high-order flux reconstruction/correction procedure via reconstruction (FR/CPR) methods on two-dimensional unstructured quadrilateral meshes. Firstly, a modified indicator based on modal energy coefficients is proposed to detect troubled cells, where discontinuities exist. Then, troubled cells are decomposed into nonuniform subcells and each subcell has one solution point. A second-order finite difference shock-capturing scheme based on nonuniform nonlinear weighted (NNW) interpolation is constructed to perform the calculation on troubled cells while smooth cells are calculated by the CPR method. Numerical investigations show that the proposed subcell limiting strategy on unstructured quadrilateral meshes is robust in shock-capturing.     

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.     

肿瘤性复杂性胸壁缺损的修复策略及对肿瘤治疗的积极影响

复杂性胸壁缺损的修复一直是一项极具挑战性的工作。肿瘤性复杂性胸壁缺损的修复决策及其执行困难是限制胸壁肿瘤治疗方法选择及影响预后的重要因素之一。皮瓣解剖学研究的深入、胸壁支持结构重建技术的进步、显微外科技术的发展、麻醉护理的发展、对综合治疗的重视和治疗手段的进步等,使传统认为不可切除的胸壁肿瘤得以彻底地切除和安全有效地修复,从而使与缺损修复相关的肿瘤切除及辅助治疗的禁忌证缩减到最小程度,有效地提高了胸壁肿瘤患者的生存质量,并很大程度上延长了生存率。作者以湖南省肿瘤医院整形外科15年565例胸壁肿瘤切除后修复重建的临床资料为依据,充实了胸壁肿瘤切除及修复的策略:(1)可靠的胸壁骨性支架重建;(2)有效的软组织修复;(3)麻醉及护理与手术团队的合作;(4)系统有序的综合治疗。并进一步明确了复杂胸壁肿瘤切除及重建的细节理念,包括胸部肿瘤治疗中加强多学科合作的密切性和科学性,整形外科医生参与肿瘤治疗整体规划的主动性和时机前移等。     

Deep learning with biopsy whole slide images for pretreatment prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer：A multicenter study

IntroductionPredicting pathological complete response (pCR) for patients receiving neoadjuvant chemotherapy (NAC) is crucial in establishing individualized treatment. Whole-slide images (WSIs) of tumor tissues reflect the histopathologic information of the tumor, which is important for therapeutic response effectiveness. In this study, we aimed to investigate whether predictive information for pCR could be detected from WSIs.Materials and methodsWe retrospectively collected data from four cohorts of 874 patients diagnosed with biopsy-proven breast cancer. A deep learning pathological model (DLPM) was constructed to predict pCR using biopsy WSIs in the primary cohort, and it was then validated in three external cohorts. The DLPM could generate a deep learning pathological score (DLPs) for each patient; stromal tumor-infiltrating lymphocytes (TILs) were selected for comparison with DLPs.ResultsThe WSI feature-based DLPM showed good predictive performance with the highest area under the curve (AUC) of 0.72 among the cohorts. Alternatively, the combination of the DLPM and clinical characteristics offered a better prediction performance (AUC >0.70) in all cohorts. We also evaluated the performance of DLPM in three different breast subtypes with the best prediction for the triple-negative breast cancer (TNBC) subtype (AUC: 0.73). Moreover, DLPM combined with clinical characteristics and stromal TILs achieved the highest AUC in the primary cohort (AUC: 0.82) and validation cohort 1 (AUC: 0.80).ConclusionOur study suggested that WSIs integrated with deep learning could potentially predict pCR to NAC in breast cancer. The predictive performance will be improved by combining clinical characteristics. DLPs from DLPM can provide more information compared to stromal TILs for pCR prediction.     

足趾移植长手指全形再造术的临床应用

目的探讨足趾移植长手指全形再造手术的临床疗效。方法自2015年6月至2019年6月,对16例因外伤致手指缺损患者采用足趾移植长手指全形再造术,术后评估供区及受区的感觉功能、运动功能及外观形态,分析指甲畸形及增生性瘢痕的发生情况,并记录术后发生感染、血肿、皮片坏死及供区愈合不良等情况;通过调查问卷的方式分析患者的满意度。结果所有患者术后获随访1~12个月,其中2例受区发生感染,1例受区皮片边缘发生坏死,经换药后予以缓解;其余患者的供、受区均未出现长时间的痛疼感觉,受区感觉功能恢复达87.50%,受区运动功能恢复均较满意,手指外形基本满意。供区感觉受影响者2例,运动功能受限者1例,外形一般者2例。所有患者无指甲畸形及增生性瘢痕发生;满意者1例,基本满意者14例,不满意者1例。结论采用足趾移植长手指全形再造手术,基本可以满足患者及医师对于缺损手指进行完美修复的目标。