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Abstract Background: Neoadjuvant chemoradiotherapy combined with immunotherapy (NICRT) is a new neoadjuvant treatment approach that has raised concerns regarding potential challenges in surgery and postoperative complications. This study aimed to compare the efficacy and safety of neoadjuvant chemoradiotherapy (NCRT) and NICRT for the treatment of resectable locally advanced esophageal squamous cell carcinoma (ESCC). Methods: We retrospectively analyzed 291 patients with locally advanced ESCC who underwent neoadjuvant therapy and esophagectomy at three centers between January 2019 and September 2023 and added the data from PALACE-1 for the analysis, Among these patients, 248 and 61 patients received NCRT and NICRT, respectively. Propensity score matching (PSM) was used to balance the potential bias. Results: After the PSM,the rate of a pathological complete response (pCR) in the NCRT group was not significantly different from that in the NICRT group (46.90% vs 36.36%, P = 0.180). There were no significant differences in the tumor regression grade (TRG) and positive lymph node pCR rates between the two groups (P = 0.233 and P = 0.354, respectively). Treatment-related toxicities and postoperative complications were not significantly different between the NCRT group and the NICRT group (P = 0.199, P = 0.284). Conclusion: Compared with NCRT, NICRT did not lead to the better treatment efficacy. There were no significant differences was observed in the incidence of treatment-related toxicities and postoperative complications.

Abstract Surface defect detection is an essential task for ensuring the quality of products. Many excellent object detectors have been employed to detect surface defects in resent years, which has achieved outstanding success. To further improve the detection performance, a defect detector based on state‐of‐the‐art YOLOv8, named improved YOLOv8 by neck, head and data (NHD‐YOLO), is proposed. Specifically, YOLOv8 from three crucial aspects including neck, head and data is improved. First, a shortcut feature pyramid network is designed to effectively fuse features from backbone by improving the information transmission. Then, an adaptive decoupled head is proposed to alleviate the feature spatial misalignment between the classification and regression tasks. Finally, to enhance the training on small objects, a data augmentation method named selective small object copy and paste is proposed. Extensive experiments are conducted on three real‐world datasets: detection dataset from Northeastern University (NEU‐DET), printed circuit boards from Peking University (PKU‐Market‐PCB) and common objects in context (COCO). According to the results, NHD‐YOLO achieves the highest detection accuracy and exhibits outstanding inference speed and generalisation performance.

Abstract Objectives The purpose of this study was to investigate the prognostic significance of radiomics in conjunction with hematological parameters in relation to the overall survival (OS) of individuals diagnosed with esophageal squamous cell carcinoma (ESCC) following definitive chemoradiotherapy (dCRT). Methods In this retrospective analysis, a total of 122 patients with locally advanced ESCC were included. These patients were randomly assigned to either the training cohort (n = 85) or the validation cohort (n = 37). In the training group, the least absolute shrinkage and selection operator (LASSO) regression was utilized to choose the best radiomic features for calculating the Rad-score. To develop a nomogram model, both univariate and multivariate analyses were conducted to identify the clinical factors and hematologic parameters that could predict the OS. The performance of the predictive model was evaluated using the C-index, while the accuracy was assessed through the calibration curve. Results The Rad-score was calculated by selecting 10 radiomic features through LASSO regression. OS was predicted independently by neutrophil-to-monocyte ratio (NMR) and Rad-score according to the results of multivariate analysis. Patients who had a Rad-score > 0.47 and an NMR > 9.76 were at a significant risk of mortality. A nomogram was constructed using the findings from the multivariate analysis. In the training cohort, the nomogram had a C-index of 0.619, while in the validation cohort, it was 0.573. The model’s accuracy was demonstrated by the calibration curve, which was excellent. Conclusion A prognostic model utilizing radiomics and hematologic parameters was developed, enabling the prediction of OS in patients with ESCC following dCRT. Critical relevance statement Patients with esophageal cancer who underwent definitive chemoradiotherapy may benefit from including CT radiomics in the nomogram model. Key points • Predicting the prognosis of ESCC patients before treatment is particularly important. • Patients with a Rad-score > 0.47 and neutrophil-to-monocyte ratio > 9.76 had a high risk of mortality. • CT-based radiomics nomogram model could be used to predict the survival of patients. Graphical Abstract

Abstract Background Chemoradiotherapy is a critical treatment for patients with locally advanced and unresectable non-small cell lung cancer (NSCLC), and it is essential to identify high-risk patients as early as possible owing to the high incidence of radiation pneumonitis (RP). Increasing attention is being paid to the effects of endogenous factors for RP. This study aimed to investigate the value of computed tomography (CT)-based radiomics combined with genomics in analyzing the risk of grade ≥ 2 RP in unresectable stage III NSCLC. Methods In this retrospective multi-center observational study, 100 patients with unresectable stage III NSCLC who were treated with chemoradiotherapy were analyzed. Radiomics features of the entire lung were extracted from pre-radiotherapy CT images. The least absolute shrinkage and selection operator algorithm was used for optimal feature selection to calculate the Rad-score for predicting grade ≥ 2 RP. Genomic DNA was extracted from formalin-fixed paraffin-embedded pretreatment biopsy tissues. Univariate and multivariate logistic regression analyses were performed to identify predictors of RP for model development. The area under the receiver operating characteristic curve was used to evaluate the predictive capacity of the model. Statistical comparisons of the area under the curve values between different models were performed using the DeLong test. Calibration and decision curves were used to demonstrate discriminatory and clinical benefit ratios, respectively. Results The Rad-score was constructed from nine radiomic features to predict grade ≥ 2 RP. Multivariate analysis demonstrated that histology, Rad-score, and XRCC1 (rs25487) allele mutation were independent high-risk factors correlated with RP. The area under the curve of the integrated model combining clinical factors, radiomics, and genomics was significantly higher than that of any single model (0.827 versus 0.594, 0.738, or 0.641). Calibration and decision curve analyses confirmed the satisfactory clinical feasibility and utility of the nomogram. Conclusion Histology, Rad-score, and XRCC1 (rs25487) allele mutation could predict grade ≥ 2 RP in patients with locally advanced unresectable NSCLC after chemoradiotherapy, and the integrated model combining clinical factors, radiomics, and genomics demonstrated the best predictive efficacy.

The 2.45–2.20 Ga period during the early Paleoproterozoic era is considered to have witnessed a global “Tectono-Magmatic Lull (TML)” and thus marks a relatively quiescent period. Our study unveils a 2.45–2.20 Ga magmatic suite from the Xiong’ershan area in the southern North China Craton, offering some key constraints on localized active tectonics during the TML. Zircon U-Pb dating shows Paleoproterozoic ages for the meta-basalt (2.31, 2.28 Ga), Na-rich meta-andesite (~2.33 Ga), tonalite-trondhjemite-granodiorite (TTG) gneisses (2.36, 2.30 Ga), K-rich granodiorite (~2.29 Ga), and monzogranite (2.33, 2.27 Ga). The meta-basalts geochemically and petrographically belong to calc-alkaline basalts and show distinctive Nb, Ta, and Ti contents and primitive mantle normalized patterns from different places in the Xiong’ershan area. Combined with their enriched εHf(t) values, the magmas were derived from subduction-related enriched mantle sources within a convergent plate boundary. The meta-andesites display high MgO content (average 4.5 wt%) and Mg# (44–57), strongly fractionated rare-earth pattern, calc-alkaline affinity, and negative Nb, Ta, and Ti anomalies. The TTG gneisses are of high SiO2 type (>62 wt%), high (La/Yb)N (17.5, 39.2), and Sr/Y (50.2, 104.3) and mostly display positive Eu anomalies and high-pressure type. Zircons from these rocks show a relatively narrow range of δ18O isotope values (5.35‰, 6.79‰) with εHf(t) isotope characteristics (−9.3, −3.3), suggesting derivation from partial melting of a thickened mafic lower crust. The youngest K-rich granodiorite and monzogranite show high K2O/Na2O ratios (0.65, 2.45). Variable molar ratio Al2O3/(CaO+Na2O+K2O) (A/CNK) and low zircon εHf(t) values suggest that the K-rich granitoids formed from the partial melting of different levels of crust. The presence of meta-basalt to andesite assemblages and diverse intermediate to felsic magmatic rocks implies magmatic activity within a convergent plate boundary tectonic environment with potential influence from plume-triggered extensional processes, supported by evidence of slab rollback and upwelling of mantle material.