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Using 448.1 × 106 ψ(3686) decays collected with the BESIII detector at the BEPCII e+e− storage rings, the branching fractions and angular distributions of the decays χcJ → Ξ−Ξ¯¯¯¯+ and Ξ0Ξ¯¯¯¯0 (J = 0, 1, 2) are measured based on a partial-reconstruction technique. The decays χc1 → Ξ0Ξ¯¯¯¯0 and χc2 → Ξ0Ξ¯¯¯¯0 are observed for the first time with statistical significances of 7σ and 15σ, respectively. The results of this analysis are in good agreement with previous measurements and have significantly improved precision.
In Ref. [1] the BESIII collaboration published a cross section measurement of the process e+e− → π+π− in the energy range between 600 and 900 MeV. In this corrigendum, we report a corrected evaluation of the statistical errors in terms of a fully propagated covariance matrix. The correction also yields a reduced statistical uncertainty for the hadronic vacuum polarization contribution to the anomalous magnetic moment of the muon, which now reads as aππ,LO μ (600 − 900 MeV) = (368.2 ± 1.5stat ± 3.3syst) × 10−10. The central values of the cross section measurement and of aππ,LO μ , as well as the systematic uncertainties remain unchanged.
Purpose: Preoperative (neoadjuvant) chemoradiotherapy (CRT) and total mesorectal excision is the standard treatment for rectal cancer patients (UICC stage II/III). Up to one-third of patients treated with CRT achieve a pathological complete response (pCR). These patients could be spared from surgery and its associated morbidity and mortality, and assigned to a “watch and wait” strategy. However, reliably identifying pCR based on clinical or imaging parameters remains challenging.
Experimental design: We generated gene-expression profiles of 175 patients with locally advanced rectal cancer enrolled in the CAO/ARO/AIO-94 and -04 trials. One hundred and sixty-one samples were used for building, training and validating a predictor of pCR using a machine learning algorithm. The performance of the classifier was validated in three independent cohorts, comprising 76 patients from (i) the CAO/ARO/AIO-94 and -04 trials (n = 14), (ii) a publicly available dataset (n = 38) and (iii) in 24 prospectively collected samples from the TransValid A trial.
Results: A 21-transcript signature yielded the best classification of pCR in 161 patients (Sensitivity: 0.31; AUC: 0.81), when not allowing misclassification of non-complete-responders (False-positive rate = 0). The classifier remained robust when applied to three independent datasets (n = 76).
Conclusion: The classifier can identify >1/3 of rectal cancer patients with a pCR while never classifying patients with an incomplete response as having pCR. Importantly, we could validate this finding in three independent datasets, including a prospectively collected cohort. Therefore, this classifier could help select rectal cancer patients for a “watch and wait” strategy.
Translational relevance: Forgoing surgery with its associated side effects could be an option for rectal cancer patients if the prediction of a pathological complete response (pCR) after preoperative chemoradiotherapy would be possible. Based on gene-expression profiles of 161 patients a classifier was developed and validated in three independent datasets (n = 76), identifying over 1/3 of patients with pCR, while never misclassifying a non-complete-responder. Therefore, the classifier can identify patients suited for “watch and wait”.