PET/CT-based deep learning grading signature to optimize surgical decisions for clinical stage I invasive lung adenocarcinoma and biologic basis under its prediction: a multicenter study.

PURPOSE: No consensus on a grading system for invasive lung adenocarcinoma had been built over a long period of time. Until October 2020, a novel grading system was proposed to quantify the whole landscape of histologic subtypes and proportions of pulmonary adenocarcinomas. This study aims to develop a deep learning grading signature (DLGS) based on positron emission tomography/computed tomography (PET/CT) to personalize surgical treatments for clinical stage I invasive lung adenocarcinoma and explore the biologic basis under its prediction. METHODS: A total of 2638 patients with clinical stage I invasive lung adenocarcinoma from 4 medical centers were retrospectively included to construct and validate the DLGS. The predictive performance of the DLGS was evaluated by the area under the receiver operating characteristic curve (AUC), its potential to optimize surgical treatments was investigated via survival analyses in risk groups defined by the DLGS, and its biological basis was explored by comparing histologic patterns, genotypic alternations, genetic pathways, and infiltration of immune cells in microenvironments between risk groups. RESULTS: The DLGS to predict grade 3 achieved AUCs of 0.862, 0.844, and 0.851 in the validation set (n = 497), external cohort (n = 382), and prospective cohort (n = 600), respectively, which were significantly better than 0.814, 0.810, and 0.806 of the PET model, 0.813, 0.795, and 0.824 of the CT model, and 0.762, 0.734, and 0.751 of the clinical model. Additionally, for DLGS-defined high-risk population, lobectomy yielded an improved prognosis compared to sublobectomy p = 0.085 for overall survival [OS] and p = 0.038 for recurrence-free survival [RFS]) and systematic nodal dissection conferred a superior prognosis to limited nodal dissection (p = 0.001 for OS and p = 0.041 for RFS). CONCLUSION: The DLGS harbors the potential to predict the histologic grade and personalize the surgical treatments for clinical stage I invasive lung adenocarcinoma. Its applicability to other territories should be further validated by a larger international study.

Clinical utility of [18F]FDG PET/CT in the assessment of mediastinal lymph node disease after neoadjuvant chemoimmunotherapy for non-small cell lung cancer.

OBJECTIVES: The performance of positron emission tomography/computed tomography (PET/CT) for the prediction of ypN2 disease in non-small cell lung cancer (NSCLC) after neoadjuvant chemoimmunotherapy has not been reported. This multicenter study investigated the utility of PET/CT to assess ypN2 disease in these patients. METHODS: A total of 181 consecutive patients (chemoimmunotherapy = 86, chemotherapy = 95) at four institutions were enrolled in this study. Every patient received a PET/CT scan prior to surgery and complete resection with systematic nodal dissection. The diagnostic performance was evaluated through area under the curve (AUC). Kaplan-Meier method and Cox analysis were performed to identify the risk factors affecting recurrences. RESULTS: The sensitivity, specificity, and accuracy of PET/CT for ypN2 diseases were 0.667, 0.835, and 0.779, respectively. Therefore, the AUC was 0.751. Compared with the false positive cases, the mean value of max standardized uptake value (SUVmax) (6.024 vs. 2.672, p < 0.001) of N2 nodes was significantly higher in true positive patients. Moreover, the SUVmax of true positive (7.671 vs. 5.976, p = 0.365) and false (2.433 vs. 2.339, p = 0.990) positive cases were similar between chemoimmunotherapy and chemotherapy, respectively. Survival analysis proved that pathologic N (ypN) 2 patients could be stratified by PET/CT-N2(+ vs. -) for both chemoimmunotherapy (p = 0.023) and chemotherapy (p = 0.010). CONCLUSIONS: PET/CT is an accurate and non-invasive test for mediastinal restaging of NSCLC patients who receive neoadjuvant chemoimmunotherapy. The ypN2 patients with PET/CT-N2( +) are identified as an independent prognostic factor compared with PET/CT-N2(-). CLINICAL RELEVANCE STATEMENT: Imaging with 18F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) plays an integral role during disease diagnosis, staging, and therapeutic response assessments in patients with NSCLC. PET/CT could be an effective non-invasive tool for predicting ypN2 diseases after neoadjuvant chemoimmunotherapy. KEY POINTS: • PET/CT could serve as an effective non-invasive tool for predicting ypN2 diseases. • The ypN2 patients with PET/CT-N2( +) were a strong and independent prognostic factor. • The application of PET/CT for restaging should be encouraged in clinical practice.

Radiomics for Survival Risk Stratification of Clinical and Pathologic Stage IA Pure-Solid Non-Small Cell Lung Cancer.

Background Radiomics-based biomarkers enable the prognostication of resected non-small cell lung cancer (NSCLC), but their effectiveness in clinical stage and pathologic stage IA pure-solid tumors requires further determination. Purpose To construct an efficient radiomics signature for survival risk stratification personalized for patients with clinical stage and pathologic stage IA pure-solid NSCLC. Materials and Methods In this retrospective study, six radiomics signatures were constructed for patients with stage IA pure-solid NSCLC who underwent resection between January 2011 and December 2013 at authors' institution and were tested in the radiogenomics data set. The radiomics features were extracted from the intratumoral two-dimensional region, three-dimensional volume, and peritumoral area using PyRadiomics. The discriminative abilities of the signatures were quantified using the area under the time-dependent receiver operating characteristic curve (AUC), and the optimal signature was selected for patient stratification. Results The study included 592 patients with stage IA pure-solid NSCLC (median age, 61 years; interquartile range, 55-66 years; 269 women) for radiomics analysis: 381 patients for training, 163 for internal validation, and 48 for external validation. The radiomics signature combining three-region features yielded the highest 3- and 5-year AUCs of 0.77 and 0.78, respectively, in the internal validation set and 0.76 and 0.75, respectively, in the external validation set. Multivariable analysis suggested that the radiomics signature remained an independent prognostic factor (hazard ratio, 6.2; 95% CI: 3.5, 11.0; P < .001) and improved the discriminative ability and clinical usefulness of conventional clinical predictors. Conclusion The radiomics signature with multiregional features helped stratify the survival risk of patients with clinical stage and pathologic stage IA pure-solid non-small cell lung cancer. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Hsu and Sohn in this issue.

Deep Learning for Prediction of N2 Metastasis and Survival for Clinical Stage I Non-Small Cell Lung Cancer.

Background Preoperative mediastinal staging is crucial for the optimal management of clinical stage I non-small cell lung cancer (NSCLC). Purpose To develop a deep learning signature for N2 metastasis prediction and prognosis stratification in clinical stage I NSCLC. Materials and Methods In this retrospective study conducted from May 2020 to October 2020 in a population with clinical stage I NSCLC, an internal cohort was adopted to establish a deep learning signature. Subsequently, the predictive efficacy and biologic basis of the proposed signature were investigated in an external cohort. A multicenter diagnostic trial (registration number: ChiCTR2000041310) was also performed to evaluate its clinical utility. Finally, on the basis of the N2 risk scores, the instructive significance of the signature in prognostic stratification was explored. The diagnostic efficiency was quantified with the area under the receiver operating characteristic curve (AUC), and the survival outcomes were assessed using the Cox proportional hazards model. Results A total of 3096 patients (mean age ± standard deviation, 60 years ± 9; 1703 men) were included in the study. The proposed signature achieved AUCs of 0.82, 0.81, and 0.81 in an internal test set (n = 266), external test cohort (n = 133), and prospective test cohort (n = 300), respectively. In addition, higher deep learning scores were associated with a lower frequency of EGFR mutation (P = .04), higher rate of ALK fusion (P = .02), and more activation of pathways of tumor proliferation (P < .001). Furthermore, in the internal test set and external cohort, higher deep learning scores were predictive of poorer overall survival (adjusted hazard ratio, 2.9; 95% CI: 1.2, 6.9; P = .02) and recurrence-free survival (adjusted hazard ratio, 3.2; 95% CI: 1.4, 7.4; P = .007). Conclusion The deep learning signature could accurately predict N2 disease and stratify prognosis in clinical stage I non-small cell lung cancer. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Park and Lee in this issue.

Prognostic and predictive value of the newly proposed grading system of invasive pulmonary adenocarcinoma in Chinese patients: a retrospective multicohort study.

Our aim was to validate and analyze the prognostic impact of the novel International Association for the Study of Lung Cancer (IASLC) Pathology Committee grading system for invasive pulmonary adenocarcinomas (IPAs) in Chinese patients and to evaluate its utility in predicting a survival benefit from adjuvant chemotherapy (ACT). In this multicenter, retrospective, cohort study, we included 926 Chinese patients with completely resected stage I IPAs and classified them into three groups (Grade 1, n = 119; Grade 2, n = 431; Grade 3, n = 376) according to the new grading system proposed by the IASLC. Recurrence-free survival (RFS) and overall survival (OS) were estimated by the Kaplan-Meier method, and prognostic factors were assessed using univariable and multivariable Cox proportional hazards models. All included cohorts were well stratified in terms of RFS and OS by the novel grading system. Furthermore, the proposed grading system was found to be independently associated with recurrence and death in the multivariable analysis. Among patients with stage IB IPA (N = 490), the proposed grading system identified patients who could benefit from ACT but who were undergraded by the adenocarcinoma (ADC) classification. The novel grading system not only demonstrated prognostic significance in stage I IPA in a multicenter Chinese cohort but also offered clinical value for directing therapeutic decisions regarding adjuvant chemotherapy.

Lung cancer with PET/CT-defined occult nodal metastasis yields favourable prognosis and benefits from adjuvant therapy: a multicentre study.

PURPOSE: To investigate the surgical prognosis and efficacy of adjuvant therapy in non-small cell lung cancer (NSCLC) with occult lymph node metastasis (ONM) defined by positron emission tomography/computed tomography (PET/CT). METHODS: A total of 3537 NSCLC patients receiving surgical resection were included in this study. The prognosis between patients with ONM and evident nodal metastasis, ONM patients with and without adjuvant therapy was compared, respectively. RESULTS: ONM was associated with significantly better prognosis than evident nodal metastasis whether for patients with N1 (5-year OS: 56.8% versus 52.3%, adjusted p value = 0.267; 5-year RFS: 44.7% versus 33.2%, adjusted p value = 0.031) or N2 metastasis (5-year OS: 42.8% versus 32.3%, adjusted p value = 0.010; 5-year RFS: 31.3% versus 21.6%, adjusted p value = 0.025). In ONM population, patients receiving adjuvant therapy yielded better prognosis comparing to those without adjuvant therapy (5-year OS: 50.1% versus 33.5%, adjusted p value < 0.001; 5-year RFS: 38.4% versus 22.1%, adjusted p value < 0.001). CONCLUSIONS: ONM defined by PET/CT identifies a unique clinical subtype of lung cancer, ONM is a favorable prognostic factor whether for pathological N1 or N2 NSCLC and adjuvant therapy could provide additional survival benefits for ONM patients.

Prognostic evaluation of the proposed residual tumor classification in a Chinese non-small cell lung cancer population.

BACKGROUND: This study aimed to validate the R classification including uncertain resection (R-un) proposed by the International Association for the Study of Lung Cancer (IASLC) in a Chinese non-small cell lung cancer (NSCLC) population. METHODS: The study retrospectively investigated a 2009-2013 single-institutional NSCLC resection cohort in China. After reclassification, recurrence-free survival (RFS) and overall survival (OS) were calculated using survival analyses and compared with those using the 2005 version IASLC R classification. RESULTS: Under the proposed stratification, 3819 (72.1%) individuals were classified as R0, 1371 (25.9%) as R-un, 71 (1.3%) as R1, and 32 (0.6%) as R2. The 5-year OS probabilities for the R0, R-un, and R1/R2 groups were 71%, 46%, and 34%, respectively. The prognostic stratification remained significant in the fully adjusted Cox models (p < 0.001). Compared with the original classification, Harrell's concordance index of reclassification improved significantly, from 0.508 to 0.679 for RFS and from 0.510 to 0.692 for OS (RFS: p = 0.007; OS: p = 0.001). The survival analysis showed that R-un patients with highest mediastinal lymph node station metastasis had significantly worse survival than R0 patients with mediastinal nodal metastasis (RFS: 44 vs. 36 months, hazard ratio [HR]: 1.29, p < 0.001; OS: 59 vs. 50 months, HR: 1.34, p < 0.001). Cox proportional hazards regression analysis showed that highest mediastinal lymph node station metastasis was an independent risk factor for RFS (HR: 1.22) and OS (HR: 1.25). CONCLUSIONS: The proposed R classification showed valid prognostic stratification, including highest mediastinal nodal station metastasis.

Viral long non-coding RNA regulates virus life-cycle and pathogenicity.

Viral infection is still a serious global health problem that kills hundreds of thousands of people annually. Understanding the mechanism by which virus replicates, packages, and infects the host cells can provide new strategies to control viral infection. Long non-coding RNAs (lncRNAs) have been identified as critical regulators involved in viral infection process and antiviral response. A lot of host lncRNAs have been identified and shown to be involved in antiviral immune response during viral infection. However, our knowledge about lncRNAs expressed by viruses is still at its infancy. LncRNAs expressed by viruses are involved in the whole viral life cycle, including promoting genome replication, regulating gene expression, involvement in genome packaging, assembling new viruses and releasing virions to the host cells. Furthermore, they enhance the pathogenicity of viral infections by down-regulating the host cell's antiviral immune response and maintain the viral latency through a refined procedure of genome integration. This review focuses on the regulatory roles of viral lncRNA in the life-cycle and pathogenicity of viruses. It gives an insight into the viral lncRNAs that can be utilized as therapeutic targets against viral diseases, and future researches aimed to identify and explore new viral lncRNAs and the mechanisms of their involvement in viral infection is encouraged.

Non-Dissociative Activation of Chemisorbed Dinitrogen on One or Two Vanadium Atoms Supported by a Mo6 S8 Cluster.

Adsorption of N2 on Mo6 S8 q _Vx clusters (x=0, 1, 2; q=0, ±1) were systematically studied by density functional theory calculations with dispersion corrections. It was found that the N2 can be chemisorbed and undergo non-dissociative activation on single or double metal atoms. The adsorption and activation are influenced by metal types (V or Mo), N2 coordination modes and charge states of the clusters. Particularly, anionic Mo6 S8 - _V2 clusters have remarkable ability to fix and activate N2 . In Mo6 S8 - _V2 , two V atoms prefer to adsorb on two adjacent S-Mo-S hollow sites, leading to the formation of a supported V…V unit. The N2 is bridged side-on coordinated with these two V atoms with high adsorption energy and significant charge transfer. The bond order, bond length and vibration frequency of the adsorbed N2 are close to those of a N-N single bond.

Non-stoichiometric molybdenum sulfide clusters and their reactions with the hydrogen molecule.

Structures of non-stoichiometric MoxSy clusters (x = 2-4; y = 2-10) were studied by density functional calculations with global optimization. Besides 1T phase like structures, a novel regular grid structure in which Mo atoms are well separated by S atoms was found, which might be used as a building-block to construct a new type of two-dimensional molybdenum sulfide monolayer. The hydrogen molecule prefers to be adsorbed onto Mo atoms rather than S atoms, and Mo atoms with less S coordination have a higher ability to adsorb H2. In addition, the reaction pathways for H2 dissociation were studied on two clusters with the highest H2 adsorption energy (Mo2S4 and Mo3S3). The vacant bridge site of Mo-Mo in S-deficient clusters, which corresponds to the sulfur vacancy in the bulk phase MoS2, is favored by H atom adsorption and plays an important role in the H atom transfer on MoxSy clusters. Our results provide a new aspect to understand the reason why S defect in MoS2 and MoS2 with an Mo-edge could enhance the catalytic performance in the hydrogen evolution reaction.

Graph-based multi-user scheduling for indoor cooperative visible light transmission.

Recent progress in the indoor visible light communication (VLC) has shown promising signs of alleviating an increasing strain on the radio frequency spectrum and enhancing transmission capacity. Nevertheless, the indoor VLC usually suffers from inter-channel interference (ICI) due to the dense light-emitting diode (LED) deployment. The ICI is considered as a key factor affecting signal to interference and noise ratio (SINR) and spectral efficiency. To address this challenge, an efficient multi-user scheduling framework that employs interference coordination and cooperative transmission is investigated based on the graph theory. To effectively mitigate ICI and maximize benefit of the cooperative transmission, the cell-centric (CC) and user-centric (UC) clustering are introduced for cooperative transmission. For the CC clustering, the multi-user scheduling problem under the proportional fairness criterion is formulated to maximize spectral efficiency while ensuring user fairness. Such a problem is solved by linear programming and greedy algorithms after transforming it into a maximum weighted independent set problem with the aid of a modified interference graph. For the UC clustering, the multi-user scheduling problem under the max-min criterion is formulated and solved by a proposed heuristic approach based on the bipartite graph theory. Numerical results show that the proposed graph-based scheduling is capable of providing up to 7.7 dB gain in SINR over the non-cooperative transmission. The bipartite graph scheduling offers high spectral efficiency and service fairness index. In the worst case with an occlusion probability of 1, a small SINR penalty of up to 1 dB is observed with the greedy algorithm. It is shown that the graph-based scheduling is robust to receiver rotation and occlusion in terms of spectral efficiency, SINR, and user fairness.

Small stoichiometric (MoS2)n clusters with the 1T phase.

Stoichiometric (MoS2)n clusters (n = 1-6) were systematically studied by density functional theory calculations with hybrid B3LYP and pure GGA PW91 functionals. The most stable structures of these clusters were obtained by global optimizations with a genetic algorithm. A triangle of Mo3 capped with a S atom was found to be a favourite building block, which can construct the most stable structures (or at least candidates) for n = 3-6 clusters. These types of structures can be viewed as fragments of MoS2 monolayer with the 1T phase, which is an important phase that has unique reactivity and conductivity properties. Electronic structures were analyzed by means of density of states and frontier molecular orbitals (FMOs), which suggest that both Mo and S contribute to the FMOs below the Fermi energy while Mo atoms contribute more toward the unoccupied FMOs.

The Co-oligomers of Aß42 and Human Islet Amyloid Polypeptide Exacerbate Neurotoxicity and Alzheimer-like Pathology at Cellular Level.

The Aß hypothesis has long been central to Alzheimer's disease (AD) theory, with a recent surge in attention following drug approvals targeting Aß plaque clearance. Aß42 oligomers (AßO) are key neurotoxins. While ß-amyloid (Aß) buildup is a hallmark of AD, postmortem brain analyses have unveiled human islet amyloid polypeptide (hIAPP) deposition in AD patients, suggesting a potential role in Alzheimer's pathology. This study investigates the neurotoxic effects of co-aggregates of Aß42 and hIAPP, specifically focusing on their impact on cell survival, apoptosis, and AD-like pathology. We analyzed and compared the impact of AßO and Aß42-hIAPP on cell survival in SH-SY5Y cells, apoptosis and inducing AD-like pathology in glutamatergic neurons. Aß42-hIAPP co-oligomers exhibited significantly greater toxicity, causing 2.3-3.5 times higher cell death compared to AßO alone. Furthermore, apoptosis rates were significantly exacerbated in glutamatergic neurons when exposed to Aß42-hIAPP co-oligomers. The study also revealed that Aß42-hIAPP co-oligomers induced typical AD-like pathology in glutamatergic neurons, including the presence of Aß deposits (detected by 6E10 and 4G8 immunofluorescence) and alterations in tau protein (changes in total tau HT7, phosphorylated tau AT8, AT180). Notably, Aß42-hIAPP co-oligomers induced a more severe AD pathology compared to AßO alone. These findings provide compelling evidence for the heightened toxicity of Aß42-hIAPP co-oligomers on neurons and their role in exacerbating AD pathology. The study contributes novel insights into the pathogenesis of Alzheimer's disease, highlighting the potential involvement of hIAPP in AD pathology. Together, these findings offer novel insights into AD pathogenesis and routes for constructing animal models.

Prognostic outcomes and recurrence patterns in resected stage I lung adenocarcinoma harbouring atypical epidermal growth factor receptor mutations.

OBJECTIVES: Limited data exist on the characteristics of atypical epidermal growth factor receptor (EGFR) mutations in early-stage lung cancer. Our goal was to elucidate the associations with outcomes and recurrence patterns in resected stage I lung adenocarcinoma harbouring atypical EGFR mutations. METHODS: Eligible patients between 2014 and 2019 were retrospectively identified and grouped into exon20 insertion mutations and major atypical mutations, which included G719X, L861Q and S768I. Disease-free survival (DFS) was evaluated in the entire cohort and stratified by radiologic characteristics. Recurrence patterns were investigated and compared between groups. A competing risk model was used to estimate the cumulative incidence of recurrence. RESULTS: A total of 710 patients were finally included. Among them, 289 (40.7%) patients had exon 20 insertion mutations and 421 (59.3%) patients had major atypical mutations. There was no significant difference regarding DFS (P = 0.142) between groups in the entire cohort. The interaction between mutation subtype and the presence of ground-glass opacities was significant (hazard ratio 2.00, 95% confidence interval 1.59-2.51, P < 0.001), indicating DFS between exon 20 insertion mutations and major atypical mutations may be different among subsolid and solid tumours. Survival analysis consistently revealed no significant difference in subsolid tumours (P = 0.680), but favourable DFS of exon 20 insertion mutations in solid tumours (P = 0.037). Furthermore, patients with exon 20 insertion mutations had a lower risk of developing bone metastases did those with radiologic solid tumours (Gray's test, P = 0.012). CONCLUSIONS: Exon 20 insertion mutations were correlated with favourable DFS and lower incidence of bone metastases in radiologic solid lung adenocarcinomas harbouring atypical EGFR mutations.

Neoadjuvant chemoimmunotherapy confers survival advantage for patients undergoing sleeve lobectomy.

OBJECTIVES: It has been demonstrated that neoadjuvant immune checkpoint inhibitor (ICI) plus chemotherapy was safe and feasible referred to neoadjuvant chemotherapy for patients with non-small cell lung cancer undergoing sleeve lobectomy. Nevertheless, no survival data were reported in the previous researches. Therefore, we conducted this study to compare neoadjuvant ICI plus chemotherapy versus neoadjuvant chemotherapy followed by sleeve lobectomy for long-term survival outcomes. METHODS: Patients who underwent bronchial sleeve lobectomy following neoadjuvant ICI plus chemotherapy or neoadjuvant chemotherapy were retrospectively identified. Treatment response, perioperative outcomes, event-free survival and overall survival were compared between groups in the overall and the inverse probability of treatment weighting-adjusted cohort. RESULTS: A total of 139 patients with 39 lung cancer recurrence and 21 death were included. Among them, 83 (59.7%) and 56 (40.3%) patients received neoadjuvant chemotherapy and neoadjuvant ICI plus chemotherapy, respectively. After inverse probability of treatment weighting, more patients achieved complete pathological response in the neoadjuvant ICI plus chemotherapy group (6.0% vs 26.3%, P < 0.001). There was no significant difference regarding overall postoperative complication (23.8% vs 20.2%, P = 0.624) and specific complications (all P > 0.05). Patients receiving neoadjuvant ICI plus chemotherapy had favourable event-free survival (hazard ratio 0.37, 95% confidence interval 0.16-0.85, P = 0.020) and overall survival (hazard ratio 0.23, 95% confidence interval 0.06-0.80, P = 0.021). Multivariable analysis revealed that neoadjuvant ICI plus chemotherapy was an independent predictor for favourable event-free survival (hazard ratio 0.37, 95% confidence interval 0.15-0.86, P = 0.020, adjusted for clinical TNM stage). CONCLUSIONS: Neoadjuvant ICI plus chemotherapy was correlated with favourable long-term survival in patients with non-small cell lung cancer undergoing sleeve lobectomy.

Predicting complication risks after sleeve lobectomy for non-small cell lung cancer.

Background: Sleeve lobectomy is a challenging procedure with a high risk of postoperative complications. To facilitate surgical decision-making and optimize perioperative treatment, we developed risk stratification models to quantify the probability of postoperative complications after sleeve lobectomy. Methods: We retrospectively analyzed the clinical features of 691 non-small cell lung cancer (NSCLC) patients who underwent sleeve lobectomy between July 2016 and December 2019. Logistic regression models were trained and validated in the cohort to predict overall complications, major complications, and specific minor complications. The impact of specific complications in prognostic stratification was explored via the Kaplan-Meier method. Results: Of 691 included patients, 232 (33.5%) developed complications, including 35 (5.1%) and 197 (28.5%) patients with major and minor complications, respectively. The models showed robust discrimination, yielding an area under the receiver operating characteristic (ROC) curve (AUC) of 0.853 [95% confidence interval (CI): 0.705-0.885] for predicting overall postoperative complication risk and 0.751 (95% CI: 0.727-0.762) specifically for major complication risks. Models predicting minor complications also achieved good performance, with AUCs ranging from 0.78 to 0.89. Survival analyses revealed a significant association between postoperative complications and poor prognosis. Conclusions: Risk stratification models could accurately predict the probability and severity of complications in NSCLC patients following sleeve lobectomy, which may inform clinical decision-making for future patients.

Incorporation of the lepidic component as an additional pathological T descriptor for non-small cell lung cancer: Data from 3335 cases of lung adenocarcinoma.

OBJECTIVES: The Lepidic Component (LP) identifies a subgroup with an excellent prognosis for lung adenocarcinoma (LUAD). Our research aimed to propose an improved pathological T (pT) stage for LUAD based on LP. MATERIALS AND METHODS: Totally, 3335 surgical patients with pathological stage I LUAD were incorporated. Factors affecting survival were investigated by analyzing recurrence-free survival (RFS) and overall survival (OS) using the Kaplan-Meier method and Cox regression analyses. Subgroup analysis based on Lepidic Ratio (LR) was further evaluated. The net benefit from the modified pT category (pTm) was assessed using the Area Under the time-dependent Receiver Operating Curve (AUC), Harrell's Concordance Index (C-index), Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI). RESULTS: The presence of LP (LP+) was identified in 1425 (42.7 %) patients, indicating a significantly better RFS (P < 0.001) and OS (P < 0.001) than those without LP, and similar results were reproduced in pT1a-pT2a subcategory (P < 0.050 for all). Multivariable Cox analysis revealed LP+ as an independent prognostic factor for both RFS (HR, 0.622; P < 0.001) and OS (HR, 0.710; P = 0.019). However, lepidic ratio (LR) was not independently associated with both RFS and OS for LP+ patients. The 5-year RFS and OS rates between T1a (LP-) and T1b (LP+), T1b (LP-) and T1c (LP+), and T1b (LP-) and T2a (LP+) were comparable (P > 0.050 for all). After modification, compared with current 8th edition pT stage system (pT8), pTm independently predicted RFS and OS, and AUCs, c-index, NRI, and IDI analysis all demonstrated pTm holds better discrimination performances than pT8 for LUAD prognosis. CONCLUSION: LP can be an additional down-staged T descriptor for pathological stage I LUAD and improve the survival predictive performance of reclassification.

TransVG++: End-to-End Visual Grounding With Language Conditioned Vision Transformer.

In this work, we explore neat yet effective Transformer-based frameworks for visual grounding. The previous methods generally address the core problem of visual grounding, i.e., multi-modal fusion and reasoning, with manually-designed mechanisms. Such heuristic designs are not only complicated but also make models easily overfit specific data distributions. To avoid this, we first propose TransVG, which establishes multi-modal correspondences by Transformers and localizes referred regions by directly regressing box coordinates. We empirically show that complicated fusion modules can be replaced by a simple stack of Transformer encoder layers with higher performance. However, the core fusion Transformer in TransVG is stand-alone against uni-modal encoders, and thus should be trained from scratch on limited visual grounding data, which makes it hard to be optimized and leads to sub-optimal performance. To this end, we further introduce TransVG++ to make two-fold improvements. For one thing, we upgrade our framework to a purely Transformer-based one by leveraging Vision Transformer (ViT) for vision feature encoding. For another, we devise Language Conditioned Vision Transformer that removes external fusion modules and reuses the uni-modal ViT for vision-language fusion at the intermediate layers. We conduct extensive experiments on five prevalent datasets, and report a series of state-of-the-art records.

Masked Contrastive Representation Learning for Reinforcement Learning.

In pixel-based reinforcement learning (RL), the states are raw video frames, which are mapped into hidden representation before feeding to a policy network. To improve sample efficiency of state representation learning, recently, the most prominent work is based on contrastive unsupervised representation. Witnessing that consecutive video frames in a game are highly correlated, to further improve data efficiency, we propose a new algorithm, i.e., masked contrastive representation learning for RL (M-CURL), which takes the correlation among consecutive inputs into consideration. In our architecture, besides a CNN encoder for hidden presentation of input state and a policy network for action selection, we introduce an auxiliary Transformer encoder module to leverage the correlations among video frames. During training, we randomly mask the features of several frames, and use the CNN encoder and Transformer to reconstruct them based on context frames. The CNN encoder and Transformer are jointly trained via contrastive learning where the reconstructed features should be similar to the ground-truth ones while dissimilar to others. During policy evaluation, the CNN encoder and the policy network are used to take actions, and the Transformer module is discarded. Our method achieves consistent improvements over CURL on 14 out of 16 environments from DMControl suite and 23 out of 26 environments from Atari 2600 Games. The code is available at https://github.com/teslacool/m-curl.

Meta-analysis of the association between RNF213 polymorphisms and clinical features of moyamoya disease in Asian population.

BACKGROUND: We performed this study to explore the relationship between ring finger protein 213 (RNF213) gene polymorphisms and clinical features in moyamoya disease (MMD). METHODS: Electronic databases (PubMed, Google Scholar, Embase, Scopus, Cochrane Library) were conducted from inception to May 15th, 2022. Odds ratios (ORs) with 95 % confidence intervals (CIs) were generated as effect size for binary variants. Subgroup analyses were performed by the RNF213 polymorphisms. Sensitivity was used to examine the robustness of associations. RESULTS: A total of 16 articles and 3061 MMD patients were included and the association of five RNF213 polymorphisms on 9 clinical features of MMD were identified. Patients under 18 years of age at onset, familial MMD, cerebral ischemic stroke and posterior cerebral artery involvement (PCi) were significantly more common in mutant type compared with wild type of RNF213. Compared with each wild type, subgroup analysis showed that rs11273543 and rs9916351 remarkably increased risk of MMD on early onset, but rs371441113 evidently delayed the onset of MMD. Rs112735431 in mutant type was significantly higher than wild type in patients with PCi. Subgroup analysis in mutant type showed that rs112735431 conspicuously decreased intracerebral/ intraventricular hemorrhage (ICH/IVH) risk and yet rs148731719 obviously increased the risk in ICH/IVH. CONCLUSION: More attention should be paid to patients on whom the ischemic MMD occurs younger than 18 years old. RNF213 polymorphism screening and cerebrovascular imaging examination should be performed to evaluate intracranial vascular involvement, to achieve early detection and early treatment and avoid more serious cerebrovascular events.