Objective To explore the impact of number of positive regional lymph nodes (nPRLN) in N1 stage on the prognosis of non-small cell lung cancer (NSCLC) patients. Methods Patients with TxN1M0 stage NSCLC who underwent lobectomy and mediastinal lymph node dissection from 2010 to 2015 were screened from SEER database (17 Regs, 2022nov sub). The optimal cutoff value of nPRLN was determined using X-tile software, and patients were divided into 2 groups according to the cutoff value: a nPRLN≤optimal cutoff group and a nPRLN>optimal cutoff group. The influence of confounding factors was minimized by propensity score matching (PSM) at a ratio of 1 : 1. Kaplan-Meier curves and Cox proportional hazards models were used to evaluate overall survival (OS) and lung cancer-specific survival (LCSS) of patients. Results A total of 1316 patients with TxN1M0 stage NSCLC were included, including 662 males and 654 females, with a median age of 67 (60, 73) years. The optimal cutoff value of nPRLN was 3, with 1165 patients in the nPRLN≤3 group and 151 patients in the nPRLN>3 group. After PSM, there were 138 patients in each group. Regardless of before or after PSM, OS and LCSS of patients in the nPRLN≤3 group were superior to those in the nPRLN>3 group (P<0.001). N1 stage nPRLN>3 was an independent prognostic risk factor for OS [HR=1.52, 95%CI (1.22, 1.89), P<0.001] and LCSS [HR=1.72, 95%CI (1.36, 2.18), P<0.001]. Conclusion N1 stage nPRLN>3 is an independent prognostic risk factor for NSCLC patients in TxN1M0 stage, which may provide new evidence for future revision of TNM staging N1 stage subclassification.

Objective To explore the application value of dual-phase dual-energy CT (DECT) perfusion imaging in preoperative lung function assessment of lung cancer patients. Methods Data were collected from patients with stageⅠA non-small cell lung cancer who underwent surgical treatment in the Department of Thoracic Surgery, the First Affiliated Hospital of Nanjing Medical University, from November 2022 to June 2024. All patients underwent DECT perfusion imaging and pulmonary function testing (PFT) before surgery. PFT observation indicators included ventilation function indicators such as forced expiratory volume in one second (FEV1), forced vital capacity (FVC), 1-second rate (FEV1/FVC), maximal voluntary ventilation (MVV), and diffusion function indicators such as diffusing capacity for carbon monoxide (DLCO) and DLCO per liter of alveolar volume (DLCO/VA). The software eXamine was used to obtain quantitative parameters of DECT perfusion imaging, including volume parameters and perfusion parameters of both lungs and each lung lobe. The correlation between the volume parameters and perfusion parameters of both lungs and the ventilation and diffusion function indicators of the patients, as well as the differences in quantitative parameters of each lung lobe, was analyzed. Results The end-inspiration lung volume and biphasic volume difference were strongly positively correlated with FEV1 and FVC (r=0.636, r=0.682, r=0.614, r=0.624, P<0.001) and moderately positively correlated with MVV and DLCO (r=0.499, r=0.514, r=0.549, r=0.447, P<0.001); the end-expiration lung volume was weakly negatively correlated with DLCO/VA (r=−0.295, P=0.026); the volume ratio was positively correlated with FEV1, FVC, MVV, and MVV% (r=0.424, r=0.399, r=0.415, r=0.310, P<0.05); the end-inspiration iodine content was weakly positively correlated with DLCO/VA% (rs=0.292, P=0.030); the end-expiration iodine content was weakly positively correlated with FEV1, FVC, MVV, DLCO%, and DLCO/VA (r=0.307, r=0.299, r=0.295, r=0.366, r=0.320, P<0.05) and moderately positively correlated with DLCO (r=0.439, P<0.001); the end-inspiration iodine concentration was negatively correlated with FEV1, FVC, MVV, and MVV% (rs=−0.407, rs=−0.426, rs=−0.352, rs=−0.277, P＜0.05); the end-expiratory phase iodine concentration was moderately positively correlated with DLCO/VA (r=0.403, P=0.002); both the iodine concentration difference and the iodine concentration ratio were moderately positively correlated with FEV1, FEV1%, FVC, MVV, MVV% (P<0.05). The lung volume and iodine concentration ratio values were both highest in the left upper lung lobe and lowest in the right middle lung lobe; the differences in lung volume, lung volume ratio, intrapulmonary iodine content, and intrapulmonary iodine concentration were all highest in the lower lobes of both lungs and lowest in the middle lobe of the right lung. Conclusion Dual-phase DECT perfusion imaging can accurately assess overall lung function and quantify regional lung function.

Objective To establish an individualized nomogram model and evaluate its efficacy to provide a possible evaluation basis for the prognosis of lower third and abdominal part of oesophageal adenocarcinoma (EAC). Methods Lower third and abdominal part of EAC patients from 2010 to 2015 were chosen from the SEER Research Plus Database (17 Regs, 2022nov sub). The patients were randomly allocated to the training cohort and the internal validation cohort with a ratio of 7∶3 using bootstrap resampling. The Cox proportional hazards regression analysis was used to determine significant contributors to overall survival (OS) in EAC patients, which would be elected to construct the nomogram prediction model. C-index, calibration curve and receiver operating characteristic (ROC) curve were performed to evaluate its efficacy. Finally, the efficacy to evaluate the OS of EAC patients was compared between the nomogram prediction model and TNM staging system. Results In total, 3945 patients with lower third and abdominal part of EAC were enrolled, including 3475 males and 470 females with a median age of 65 (57-72) years. The 2761 patients were allocated to the training cohort and the remaining 1184 patients to the internal validation cohort. In the training and the internal validation cohorts, the C-index of the nomogram model was 0.705 and 0.713, respectively. Meanwhile, the calibration curve also suggested that the nomogram model had a strong capability of predicting 1-, 3-, and 5-year OS rates of EAC patients. The nomogram also had a higher efficacy than the TNM staging system in predicting 1-, 3-, and 5-year OS rates of EAC patients. Conclusion This nomogram prediction model has a high efficiency for predicting OS in the patients with lower third and abdominal part of EAC, which is higher than that of the current TNM staging system.

Disorders of consciousness (DOC) are pathological conditions characterized by severely suppressed brain function and the persistent interruption or loss of consciousness. Accurate diagnosis and evaluation of DOC are prerequisites for precise treatment. Traditional assessment methods are primarily based on behavioral scales, which are inherently subjective and rely on observable behaviors. Moreover, traditional methods have a high misdiagnosis rate, particularly in distinguishing minimally conscious state (MCS) from vegetative state/unresponsive wakefulness syndrome (VS/UWS). This diagnostic uncertainty has driven the exploration of objective, reliable, and efficient assessment tools. Among these tools, electroencephalography (EEG) has garnered significant attention for its non-invasive nature, portability, and ability to capture real-time neurodynamics. This paper systematically reviews the application of EEG biomarkers in DOC assessment. These biomarkers are categorized into 3 main types: resting-state EEG features, task-related EEG features, and features derived from transcranial magnetic stimulation-EEG (TMS-EEG). Resting-state EEG biomarkers include features based on spectrum, microstates, nonlinear dynamics, and brain network metrics. These biomarkers provide baseline representations of brain activity in DOC patients. Studies have shown their ability to distinguish different levels of consciousness and predict clinical outcomes. However, because they are not task-specific, they are challenging to directly associate with specific brain functions or cognitive processes. Strengthening the correlation between resting-state EEG features and consciousness-related networks could offer more direct evidence for the pathophysiological mechanisms of DOC. Task-related EEG features include event-related potentials, event-related spectral modulations, and phase-related features. These features reveal the brain’s responses to external stimuli and provide dynamic information about residual cognitive functions, reflecting neurophysiological changes associated with specific cognitive, sensory, or behavioral tasks. Although these biomarkers demonstrate substantial value, their effectiveness rely on patient cooperation and task design. Developing experimental paradigms that are more effective at eliciting specific EEG features or creating composite paradigms capable of simultaneously inducing multiple features may more effectively capture the brain activity characteristics of DOC patients, thereby supporting clinical applications. TMS-EEG is a technique for probing the neurodynamics within thalamocortical networks without involving sensory, motor, or cognitive functions. Parameters such as the perturbational complexity index (PCI) have been proposed as reliable indicators of consciousness, providing objective quantification of cortical dynamics. However, despite its high sensitivity and objectivity compared to traditional EEG methods, TMS-EEG is constrained by physiological artifacts, operational complexity, and variability in stimulation parameters and targets across individuals. Future research should aim to standardize experimental protocols, optimize stimulation parameters, and develop automated analysis techniques to improve the feasibility of TMS-EEG in clinical applications. Our analysis suggests that no single EEG biomarker currently achieves an ideal balance between accuracy, robustness, and generalizability. Progress is constrained by inconsistencies in analysis methods, parameter settings, and experimental conditions. Additionally, the heterogeneity of DOC etiologies and dynamic changes in brain function add to the complexity of assessment. Future research should focus on the standardization of EEG biomarker research, integrating features from resting-state, task-related, and TMS-EEG paradigms to construct multimodal diagnostic models that enhance evaluation efficiency and accuracy. Multimodal data integration (e.g., combining EEG with functional near-infrared spectroscopy) and advancements in source localization algorithms can further improve the spatial precision of biomarkers. Leveraging machine learning and artificial intelligence technologies to develop intelligent diagnostic tools will accelerate the clinical adoption of EEG biomarkers in DOC diagnosis and prognosis, allowing for more precise evaluations of consciousness states and personalized treatment strategies.

Multiple system atrophy (MSA) is a rare neurodegenerative disease with complex clinical manifestations, presenting substantial challenges in clinical diagnosis and treatment. Its symptoms and the eight extraordinary meridians are potentially correlated; therefore, this article explores the association between MSA symptom clusters and the eight extraordinary meridians based on their circulation and physiological functions, as well as their treatment strategies. The progression from deficiency to damage in the eight extraordinary meridians aligns with the core pathogenesis of MSA, which is characterized by "the continuous accumulation of impacts from the vital qi deficiency leading to eventual damage". Liver and kidney deficiency and the emptiness of the eight extraordinary meridians are required for the onset of MSA; the stagnation of qi deficiency and the gradual damage to the eight extraordinary meridians are the key stages in the prolonged progression of MSA. The disease often begins with the involvement of the yin and yang qiao mai, governor vessel, thoroughfare vessel, and conception vessel before progressing to multiple meridian involvements, ultimately affecting all eight extraordinary meridians simultaneously. The treatment approach emphasizes that "the direct method may be used for joining battle, but indirect method will be needed in order to secure victory" and focuses on "eliminate pathogenic factors and reinforce healthy qi". Distinguishing the extraordinary meridians and focusing on the primary symptoms are pivotal to improving efficacy. Clinical treatment is aimed at the target, and tailored treatment based on careful clinical observation ensures precision in targeting the disease using the eight extraordinary meridians as the framework and core symptoms as the specific focus. Additionally, combining acupuncture, daoyin therapy, and other method may help prolong survival. This article classifies clinical manifestations based on the theory of the eight extraordinary meridians and explores treatment.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

ObjectiveThis study aims to investigate the effect of Dictamni Cortex on intestinal barrier damage in rats and its mechanism by untargeted metabolomics and targeted metabolomics for short-chain fatty acids （SCFAs）. MethodsRats were randomly divided into a control group， a high-dose group of Dictamni Cortex （8.1 g·kg^-1）， a medium-dose group （2.7 g·kg^-1）， and a low-dose group （0.9 g·kg^-1）. Except for the control group， the other groups were administered different doses of Dictamni Cortex by gavage for eight consecutive weeks. Hematoxylin-eosin （HE） staining was used to observe the pathological changes in the ileal tissue. Enzyme-linked immunosorbent assay （ELISA） was employed to detect the level of cytokines， including tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， and interleukin-1β （IL-1β）， in the ileal tissue of rats. Quantitative real-time fluorescence polymerase chain reaction （Real-time PCR） technology was used to detect the expression level of tight junction proteins， including zonula occludens-1 （ZO-1）， Occludin， and Claudin-1 mRNAs， in the ileal tissue of rats to preliminarily explore the effects of Dictamni Cortex on intestinal damage. The dose with the most significant toxic phenotype was selected to further reveal the effects of Dictamni Cortex on the metabolic profile of ileal tissue in rats by non-targeted metabolomics combined with targeted metabolomics for SCFAs. ResultsCompared with the control group， all doses of Dictamni Cortex induced varying degrees of pathological damage in the ileum， increased TNF-α （P<0.01）， IL-6 （P<0.01）， and IL-1β （P<0.01） levels in the ileal tissue， and decreased the expression level of ZO-1 （P<0.05， P<0.01）， Occludin （P<0.01）， and Claudin-1 （P<0.05） in the ileal tissue， with the high-dose group showing the most significant toxic phenotypes. The damage mechanisms of the high-dose group of Dictamni Cortex on the ileal tissue were further explored by integrating non-targeted metabolomics and targeted metabolomics for SCFAs. The non-targeted metabolomics results showed that 21 differential metabolites were identified in the control group and the high-dose group. Compared with that in the control group， after Dictamni Cortex intervention， the level of 14 metabolites was significantly increased （P<0.05， P<0.01）， and the level of seven metabolites was significantly decreased （P<0.05， P<0.01） in the ileal contents. These metabolites collectively acted on 10 related metabolic pathways， including glycerophospholipids and primary bile acid biosynthesis. The quantitative data of targeted metabolomics for SCFAs showed that Dictamni Cortex intervention disrupted the level of propionic acid， butyric acid， acetic acid， caproic acid， isobutyric acid， isovaleric acid， valeric acid， and isocaproic acid in the ileal contents of rats. Compared with those in the control group， the level of isobutyric acid， isovaleric acid， and valeric acid were significantly increased， while the level of propionic acid， butyric acid， and acetic acid were significantly decreased in the ileal contents of rats after Dictamni Cortex intervention （P<0.05， P<0.01）. ConclusionDictamni Cortex can induce intestinal damage by regulating glycerophospholipid metabolism， primary bile acid biosynthesis， and metabolic pathways for SCFAs.

Objective To evaluate the value of postoperative radiotherapy (PORT) in patients with stage ⅢA-N2 non-small cell lung cancer who received complete resection and chemotherapy. Methods Patients with stage ⅢA-N2 non-small cell lung cancer who received complete resection and chemotherapy were chosen from the SEER Research Plus Database [17 Registries, November 2012 Submission (2000-2019)]. The patients were divided into a PORT group and a non-PORT group according to whether the PORT was used. To balance baseline characteristics between non-PORT and PORT groups, R software was used to conduct a propensity score matching (PSM) with a ratio of 1 : 1 and a matching tolerance of 0.01. Both the Cox regression analysis and Kaplan-Meier survival analysis were conducted to evaluate the value of PORT in terms of overall survival (OS) and disease-specific survival (DSS). Results In total, 2468 patients with stage ⅢA-N2 non-small cell lung cancer were enrolled, including 1078 males and 1390 females with a median age of 65 (58-71) years. There were 1336 patients in the PORT group, and 1132 patients in the non-PORT group. Cox regression analysis showed that PORT was not significantly associated with OS (multivariate analysis: HR=1.051, 95%CI 0.949-1.164, P=0.338) and DSS (multivariate analysis: HR=1.094, 95%CI 0.976-1.225, P=0.123). No statistical difference was found in the OS or DSS between non-PORT group and PORT group after PSM analysis (P＞0.05). Conclusion PORT does not have a survival benefit for patients with stage ⅢA-N2 non-small cell lung cancer who received complete resection and chemotherapy.