Observation of tW production in the single-lepton channel in pp collisions at root s=13 TeV

A measurement of the cross section of the associated production of a single top quark and a W boson in final states with a muon or electron and jets in proton-proton collisions at root s = 13 TeV is presented. The data correspond to an integrated luminosity of 36 fb(-1) collected with the CMS detector at the CERN LHC in 2016. A boosted decision tree is used to separate the tW signal from the dominant t (t) over bar background, whilst the subleading W+jets and multijet backgrounds are constrained using data-based estimates. This result is the first observation of the tW process in final states containing a muon or electron and jets, with a significance exceeding 5 standard deviations. The cross section is determined to be 89 +/- 4 (stat) +/- 12 (syst) pb, consistent with the standard model.Peer reviewe

X-ray Diffraction, Micro-Raman and X-ray Photoemission Spectroscopic Investigations for Hydrothermally Obtained Hybrid Compounds of Delafossite CuGaO2 and Wurtzite ZnO

P-type delafossite CuGaO2 is a wide-bandgap semiconductor for optoelectronic applications, and its lattice parameters are very similar to those of n-type semiconductor wurtzite ZnO. Accordingly, the investigation of crystalline heterostructures of CuGaO2 and ZnO has attracted significant attention. In this study, interfacial CuGaO2/ZnO hetero-compounds were examined through X-ray diffraction (XRD) analysis, confocal micro-Raman spectroscopy, and X-ray photo-electron spectroscopy (XPS). XRD and Raman analysis revealed that the hydrothermal deposition of ZnO on hexagonal platelet CuGaO2 base crystals was successful, and the subsequent reduction process could induce a unique, unprecedented reaction between CuGaO2 and ZnO, depending on the deposition parameters. XPS allowed the comparison of the binding energies (peak position and width) of the core level electrons of the constituents (Cu, Ga, Zn, and O) of the pristine CuGaO2 single crystallites and interfacial CuGaO2/ZnO hybrids. The presences of Cu2+ ions and strained GaO6 octahedra were the main characteristics of the CuGaO2/ZnO hybrid interface. The XPS and modified Auger parameter analysis gave an insight into a specific polarization of the interface, promising for further development of CuGaO2/ZnO hybrids

X-ray Diffraction, Micro-Raman and X-ray Photoemission Spectroscopic Investigations for Hydrothermally Obtained Hybrid Compounds of Delafossite CuGaO₂ and Wurtzite ZnO

P-type delafossite CuGaO2 is a wide-bandgap semiconductor for optoelectronic applications, and its lattice parameters are very similar to those of n-type semiconductor wurtzite ZnO. Accordingly, the investigation of crystalline heterostructures of CuGaO2 and ZnO has attracted significant attention. In this study, interfacial CuGaO2/ZnO hetero-compounds were examined through X-ray diffraction (XRD) analysis, confocal micro-Raman spectroscopy, and X-ray photo-electron spectroscopy (XPS). XRD and Raman analysis revealed that the hydrothermal deposition of ZnO on hexagonal platelet CuGaO2 base crystals was successful, and the subsequent reduction process could induce a unique, unprecedented reaction between CuGaO2 and ZnO, depending on the deposition parameters. XPS allowed the comparison of the binding energies (peak position and width) of the core level electrons of the constituents (Cu, Ga, Zn, and O) of the pristine CuGaO2 single crystallites and interfacial CuGaO2/ZnO hybrids. The presences of Cu2+ ions and strained GaO6 octahedra were the main characteristics of the CuGaO2/ZnO hybrid interface. The XPS and modified Auger parameter analysis gave an insight into a specific polarization of the interface, promising for further development of CuGaO2/ZnO hybrids

Deep learning model improves tumor-infiltrating lymphocyte evaluation and therapeutic response prediction in breast cancer

Abstract Tumor-infiltrating lymphocytes (TILs) have been recognized as key players in the tumor microenvironment of breast cancer, but substantial interobserver variability among pathologists has impeded its utility as a biomarker. We developed a deep learning (DL)-based TIL analyzer to evaluate stromal TILs (sTILs) in breast cancer. Three pathologists evaluated 402 whole slide images of breast cancer and interpreted the sTIL scores. A standalone performance of the DL model was evaluated in the 210 cases (52.2%) exhibiting sTIL score differences of less than 10 percentage points, yielding a concordance correlation coefficient of 0.755 (95% confidence interval [CI], 0.693–0.805) in comparison to the pathologists’ scores. For the 226 slides (56.2%) showing a 10 percentage points or greater variance between pathologists and the DL model, revisions were made. The number of discordant cases was reduced to 116 (28.9%) with the DL assistance (p < 0.001). The DL assistance also increased the concordance correlation coefficient of the sTIL score among every two pathologists. In triple-negative and human epidermal growth factor receptor 2 (HER2)-positive breast cancer patients who underwent the neoadjuvant chemotherapy, the DL-assisted revision notably accentuated higher sTIL scores in responders (26.8 ± 19.6 vs. 19.0 ± 16.4, p = 0.003). Furthermore, the DL-assistant revision disclosed the correlation of sTIL-high tumors (sTIL ≥ 50) with the chemotherapeutic response (odd ratio 1.28 [95% confidence interval, 1.01–1.63], p = 0.039). Through enhancing inter-pathologist concordance in sTIL interpretation and predicting neoadjuvant chemotherapy response, here we report the utility of the DL-based tool as a reference for sTIL scoring in breast cancer assessment

Artificial Intelligence-Powered Analyzer Reduces Inter-observer Variation in PD-L1 Tumor Proportion Score of Non-Small Cell Lung Cancer

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ANO1-downregulation induced by schisandrathera D: a novel therapeutic target for the treatment of prostate and oral cancers

Anoctamin 1 (ANO1), a drug target for various cancers, including prostate and oral cancers, is an intracellular calcium-activated chloride ion channel that plays various physiopathological roles, especially in the induction of cancer growth and metastasis. In this study, we tested a novel compound isolated from Schisandra sphenanthera, known as schisandrathera D, for its inhibitory effect on ANO1. Schisandrathera D dose-dependently suppressed the ANO1 activation-mediated decrease in fluorescence of yellow fluorescent protein; however, it did not affect the adenosine triphosphate-induced increase in the intracellular calcium concentration or forskolin-induced cystic fibrosis transmembrane conductance regulator activity. Specifically, schisandrathera D gradually decreased the levels of ANO1 protein and significantly reduced the cell viability in ANO1-expressing cells when compared to those in ANO1-knockout cells. These effects could be attributed to the fact that schisandrathera D displayed better binding capacity to ANO1 protein than the previously known ANO1 inhibitor, Ani9. Finally, schisandrathera D increased the levels of caspase-3 and cleaved poly (ADP-ribose) polymerase 1, thereby indicating that its anticancer effect is mediated through apoptosis. Thus, this study highlights that schisandrathera D, which reduces ANO1 protein levels, has apoptosis-mediated anticancer effects in prostate and oral cancers, and thus, can be further developed into an anticancer agent

Artificial Intelligence-Powered Spatial Analysis of Tumor-Infiltrating Lymphocytes as Complementary Biomarker for Immune Checkpoint Inhibition in Non-Small-Cell Lung Cancer

PURPOSE Biomarkers on the basis of tumor-infiltrating lymphocytes (TIL) are potentially valuable in predicting the effectiveness of immune checkpoint inhibitors (ICI). However, clinical application remains challenging because of methodologic limitations and laborious process involved in spatial analysis of TIL distribution in whole-slide images (WSI). METHODS We have developed an artificial intelligence (AI)-powered WSI analyzer of TIL in the tumor microenvironment that can define three immune phenotypes (IPs): inflamed, immune-excluded, and immune-desert. These IPs were correlated with tumor response to ICI and survival in two independent cohorts of patients with advanced non-small-cell lung cancer (NSCLC). RESULTS Inflamed IP correlated with enrichment in local immune cytolytic activity, higher response rate, and prolonged progression-free survival compared with patients with immune-excluded or immune-desert phenotypes. At the WSI level, there was significant positive correlation between tumor proportion score (TPS) as determined by the AI model and control TPS analyzed by pathologists (P &lt; .001). Overall, 44.0% of tumors were inflamed, 37.1% were immune-excluded, and 18.9% were immune-desert. Incidence of inflamed IP in patients with programmed death ligand-1 TPS at &lt; 1%, 1%-49%, and &gt;= 50% was 31.7%, 42.5%, and 56.8%, respectively. Median progression-free survival and overall survival were, respectively, 4.1 months and 24.8 months with inflamed IP, 2.2 months and 14.0 months with immune-excluded IP, and 2.4 months and 10.6 months with immune-desert IP. CONCLUSION The AI-powered spatial analysis of TIL correlated with tumor response and progression-free survival of ICI in advanced NSCLC. This is potentially a supplementary biomarker to TPS as determined by a pathologist.Y