Background: Tumor-infiltrating lymphocytes (TILs) are clinically significant in triple-negative breast cancer (TNBC). Although a standardized methodology for visual TILs assessment (VTA) exists, it has several inherent limitations. We established a deep learning-based computational TIL assessment (CTA) method broadly following VTA guideline and compared it with VTA for TNBC to determine the prognostic value of the CTA and a reasonable CTA workflow for clinical practice. Methods: We trained three deep neural networks for nuclei segmentation, nuclei classification and necrosis classification to establish a CTA workflow. The automatic TIL (aTIL) score generated was compared with manual TIL (mTIL) scores provided by three pathologists in an Asian (n = 184) and a Caucasian (n = 117) TNBC cohort to evaluate scoring concordance and prognostic value. Findings: The intraclass correlations (ICCs) between aTILs and mTILs varied from 0.40 to 0.70 in two cohorts. Multivariate Cox proportional hazards analysis revealed that the aTIL score was associated with disease free survival (DFS) in both cohorts, as either a continuous [hazard ratio (HR)=0.96, 95% CI 0.94À0.99] or dichotomous variable (HR=0.29, 95% CI 0.12À0.72). A higher C-index was observed in a composite mTIL/aTIL threetier stratification model than in the dichotomous model, using either mTILs or aTILs alone. Interpretation: The current study provides a useful tool for stromal TIL assessment and prognosis evaluation for patients with TNBC. A workflow integrating both VTA and CTA may aid pathologists in performing risk management and decision-making tasks.
The temperature dependence of the magnetic susceptibility, the magnetization at 4.2 K in fields up to 35 T, and the specific heat between 1.3 and 40 K in fields up to 5 T of the ternary Ce intermetallic compounds CeCuX (X = Si, Ge, Sn) have been studied. All three compounds form in ordered ternary structures related to the hexagonal AlB, type. Ferromagnetic order is found below 14.9 K for CeCuSi and below 10.2 K for CeCuGe. The magnetic order of CeCuSn below 8.6 K is of antiferromagnetic type but probably complex. as indicated by a double peak in the specific heat and the occurrence of a very low zero-field moment.
An assessment has been made of the suitability of magnesia, calcia, alumina, and yttria for manufacturing melting crucibles and investment casting moulds for c-TiAl alloys. Small refractory crucibles have been prepared by pressing or plasma spraying techniques and used to melt a small quantity of a Ti ± 48Al ± 2Nb ± 2Mn (at.-%) alloy in a carbon resistance furnace. The effects of the refractory type and melting time on the oxygen content, penetration, and microstructure have been established. The depth of penetration versus the holding time at 1550³C can be expressed by a power law. Based on these small-scale tests, it can be concluded that magnesia and silica containing alumina are unsuitable, whereas both pure calcia, yttria, and yttria-coated magnesia show promise for melting and casting c-TiAl alloys.MST/4439
The effect of bottom and top ®lling running systems on the properties of four investment cast alloys susceptible to contamination by oxide ®lms during ®lling was studied. The alloys were air cast 2L99 Al ± Si ± Mg alloy and 254-SMO super duplex stainless steel and vacuum cast IN939 and IN738LC nickel based superalloys. The Weibull moduli for the tensile strength of investment cast bars produced using top and bottom ®lling were compared as indicators of casting reliability and of oxide damage produced by the running systems. A Weibull modulus of 18 was obtained for top ®lled 2L99 castings; this was increased to 34 when a correctly designed bottom ®lling system with a ®lter was used, thus re¯ecting the decreased scatter in properties. However, a similar effect was not found for the stainless steel. The use of improved running system designs led to minor increases in the Weibull modulus of the IN738LC and IN939 Ni alloys.MST/4609
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.