Objective To describe the significance of the pretreatment inflammatory indicators in predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC) after undergoing radical radiotherapy. Methods The data of 246 ESCC patients who underwent radical radiotherapy were retrospectively collected. Receiver operating characteristic (ROC) curves were drawn to determine the optimal cutoff values for platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII). The Kaplan-Meier method was used for survival analysis. We conducted univariate and multivariate analyses by using the Cox proportional risk regression model. Software R (version 4.2.0) was used to create the nomogram of prognostic factors. Results The results of the ROC curve analysis showed that the optimal cutoff values of PLR, NLR, and SII were 146.06, 2.67, and 493.97, respectively. The overall response rates were 77.6% and 64.5% in the low and high NLR groups, respectively (P<0.05). The results of the Kaplan-Meier survival analysis revealed that the prognosis of patients in the low PLR, NLR, and SII group was better than that of patients in the high PLR, NLR, and SII group (all P<0.05). The results of the multivariate Cox regression analysis showed that gender, treatment modalities, T stage, and NLR were independent factors affecting the overall survival (OS). In addition, T stage and NLR were independent factors affecting the progression-free survival (PFS) (all P<0.05). The nomogram models of OS and PFS prediction were established based on multivariate analysis. The C-index values were 0.703 and 0.668. The calibration curves showed excellent consistency between the predicted and observed OS and PFS. Conclusion The pretreatment values of PLR, NLR, and SII are correlated with the prognosis of patients with ESCC who underwent radical radiotherapy. Moreover, NLR is an independent factor affecting the OS and PFS of ESCC patients. The NLR-based nomogram model has a good predictive ability.

This article combined the pathogenic characteristics of "latent wind" with the theory of collateral diseases to clarify the pathological features of tumor blood vessels， including their active proliferation， high permeabi-lity， and promotion of metastasis. The theory framework of "latent wind in collaterals" as the tumor mechanism was proposed， which suggests that at the site of tumor lesions， the collaterals inherit the nature of latent wind to grow excessively， adopt an open and discharge nature to leak essence， and tumor toxins， characterized by their rapid movement and frequent changes， spread and metastasize， driving the progression of malignant tumors. Focusing on the fundamental pathogenesis of "latent wind in collaterals"， specific clinical treatment principles and methods centered on treating wind are proposed， including regulating qi and dispelling wind， clearing heat and extinguishing wind， unblocking collaterals and expelling wind， and reinforcing healthy qi to calm wind， so as to provide references for enhancing the precision of traditional Chinese medicine in treating malignant tumors.

Myocardial fibrosis （MF）， characterized by decreased cardiac function and myocardial compliance， is a pathological process and a progression factor in various cardiovascular diseases. The nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 （NLRP3） inflammasome is closely related to the development of MF. Recent studies have shown that traditional Chinese medicine （TCM） can regulate the NLRP3 inflammasome to alleviate MF. Based on this， this article systematically summarizes the research progress on the mechanisms by which TCM regulates the NLRP3 inflammasome to improve MF. It is found that active ingredients of TCM， such as alkaloids （lycorine，vincristine，bufalin）， saponins （astragaloside Ⅳ， diosgenin，ginsenoside Rg3）， terpenoids （celastrol，oridonin）， and phenols （polydatin，curcumin，phloridzin） as well as TCM formulas （Zhachong shisanwei pills，Zhilong huoxue tongyu capsules， Luqi formula） can inhibit the activation of the NLRP3 inflammasome， thereby suppressing the release of inflammatory factors such as interleukin-1β and IL-18， reducing inflammatory damage to myocardial tissue， alleviating excessive deposition of the extracellular matrix， and thus exerting the effect of improving MF.

The trillions of commensal microorganisms living in the gut lumen profoundly influence the physiology and pathophysiology of the liver through a unique gut-liver axis. Disruptions in the gut microbial communities, arising from environmental and genetic factors, can lead to altered microbial metabolism, impaired intestinal barrier and translocation of microbial components to the liver. These alterations collaboratively contribute to the pathogenesis of liver disease, and their continuous impact throughout the disease course plays a critical role in hepatocarcinogenesis. Persistent inflammatory responses, metabolic rearrangements and suppressed immunosurveillance induced by microbial products underlie the pro-carcinogenic mechanisms of gut microbiota. Meanwhile, intrahepatic microbiota derived from the gut also emerges as a novel player in the development and progression of liver cancer. In this review, we first discuss the causes of gut dysbiosis in liver disease, and then specify the pivotal role of gut microbiota in the malignant progression from chronic liver diseases to hepatobiliary cancers. We also delve into the cellular and molecular interactions between microbes and liver cancer microenvironment, aiming to decipher the underlying mechanism for the malignant transition processes. At last, we summarize the current progress in the clinical implications of gut microbiota for liver cancer, shedding light on microbiota-based strategies for liver cancer prevention, diagnosis and therapy.

The trillions of commensal microorganisms living in the gut lumen profoundly influence the physiology and pathophysiology of the liver through a unique gut-liver axis. Disruptions in the gut microbial communities, arising from environmental and genetic factors, can lead to altered microbial metabolism, impaired intestinal barrier and translocation of microbial components to the liver. These alterations collaboratively contribute to the pathogenesis of liver disease, and their continuous impact throughout the disease course plays a critical role in hepatocarcinogenesis. Persistent inflammatory responses, metabolic rearrangements and suppressed immunosurveillance induced by microbial products underlie the pro-carcinogenic mechanisms of gut microbiota. Meanwhile, intrahepatic microbiota derived from the gut also emerges as a novel player in the development and progression of liver cancer. In this review, we first discuss the causes of gut dysbiosis in liver disease, and then specify the pivotal role of gut microbiota in the malignant progression from chronic liver diseases to hepatobiliary cancers. We also delve into the cellular and molecular interactions between microbes and liver cancer microenvironment, aiming to decipher the underlying mechanism for the malignant transition processes. At last, we summarize the current progress in the clinical implications of gut microbiota for liver cancer, shedding light on microbiota-based strategies for liver cancer prevention, diagnosis and therapy.

The trillions of commensal microorganisms living in the gut lumen profoundly influence the physiology and pathophysiology of the liver through a unique gut-liver axis. Disruptions in the gut microbial communities, arising from environmental and genetic factors, can lead to altered microbial metabolism, impaired intestinal barrier and translocation of microbial components to the liver. These alterations collaboratively contribute to the pathogenesis of liver disease, and their continuous impact throughout the disease course plays a critical role in hepatocarcinogenesis. Persistent inflammatory responses, metabolic rearrangements and suppressed immunosurveillance induced by microbial products underlie the pro-carcinogenic mechanisms of gut microbiota. Meanwhile, intrahepatic microbiota derived from the gut also emerges as a novel player in the development and progression of liver cancer. In this review, we first discuss the causes of gut dysbiosis in liver disease, and then specify the pivotal role of gut microbiota in the malignant progression from chronic liver diseases to hepatobiliary cancers. We also delve into the cellular and molecular interactions between microbes and liver cancer microenvironment, aiming to decipher the underlying mechanism for the malignant transition processes. At last, we summarize the current progress in the clinical implications of gut microbiota for liver cancer, shedding light on microbiota-based strategies for liver cancer prevention, diagnosis and therapy.

Recent studies have indicated that the expression of ubiquitin-specific protease 51 (USP51), a novel deubiquitinating enzyme (DUB) that mediates protein degradation as part of the ubiquitin‒proteasome system (UPS), is associated with tumor progression and therapeutic resistance in multiple malignancies. However, the underlying mechanisms and signaling networks involved in USP51-mediated regulation of malignant phenotypes remain largely unknown. The present study provides evidence of USP51's functions as the prominent DUB in chemoresistant triple-negative breast cancer (TNBC) cells. At the molecular level, ectopic expression of USP51 stabilized the 78 kDa Glucose-Regulated Protein (GRP78) protein through deubiquitination, thereby increasing its expression and localization on the cell surface. Furthermore, the upregulation of cell surface GRP78 increased the activity of ATP binding cassette subfamily B member 1 (ABCB1), the main efflux pump of doxorubicin (DOX), ultimately decreasing its accumulation in TNBC cells and promoting the development of drug resistance both in vitro and in vivo. Clinically, we found significant correlations among USP51, GRP78, and ABCB1 expression in TNBC patients with chemoresistance. Elevated USP51, GRP78, and ABCB1 levels were also strongly associated with a poor patient prognosis. Importantly, we revealed an alternative intervention for specific pharmacological targeting of USP51 for TNBC cell chemosensitization. In conclusion, these findings collectively indicate that the USP51/GRP78/ABCB1 network is a key contributor to the malignant progression and chemotherapeutic resistance of TNBC cells, underscoring the pivotal role of USP51 as a novel therapeutic target for cancer management.

Currently,electroencephalogram(EEG),functional near-infrared spectroscopy(fNIRS),and functional magnetic resonance imaging have been widely studied and applied to neuropsychiatric disorders.In recent years,the devices which can realize the simultaneous acquisition of EEG and fNIRS has been developed and gradually applied in the studies on neuropsychiatric disorders.The review provides an introduction of the techniques of synchronized detection and data analysis for EEG-fNIRS,summarizes the analysis methods and new findings of the recent studies of stroke,epilepsy,and other neuropsychiatric disorders using EEG-fNIRS,and also discusses the future research directions.

Purpose To explore the application value of combining 18F-FDG PET images with interpretable deep learning radiomics(IDLR)models in the differential diagnosis of primary Parkinson's disease(IPD)and atypical Parkinson's syndrome.Materials and Methods This cross-sectional study was conducted using the Parkinson's Disease PET Imaging Benchmark Database from Huashan Hospital,Fudan University from March 2015 to February 2023.A total of 330 Parkinson's disease patients underwent 18F-FDG PET imaging,both 18F-FDG PET imaging and clinical scale information were collected for all subjects.The study included two cohorts,a training group(n=270)and a testing group(n=60),with a total of 211 cases in the IPD group,59 cases in the progressive supranuclear palsy(PSP)group,and a group of 60 patients with multiple system atrophy(MSA).The clinical information between different groups were compared.An IDLR model was developed to extract feature indicators.Under the supervision of radiomics features,IDLR features were selected from the features collected by neural network extractors,and a binary support vector machine model was constructed for the selected features in images of in testing group.The constructed IDLR model,traditional radiomics model and standard uptake ratio model were separately used to calculate the performance metrics and area under curve values of deep learning models for pairwise classification between IPD/PSP/MSA groups.The study conducted independent classification and testing in two cohorts using 100 10-fold cross-validation tests.Brain-related regions of interest were displayed through feature mapping,using gradient weighted class activation maps to highlight and visualize the most relevant information in the brain.The output heatmaps of different disease groups were examined and compared with clinical diagnostic locations.Results The IDLR model showed promising results for differentiating between Parkinson's syndrome patients.It achieved the best classification performance and had the highest area under the curve values compared to other comparative models such as the standard uptake ratio model(Z=1.22-3.23,all P<0.05),and radiomics model(Z=1.31-2.96,all P<0.05).The area under the curve values for the IDLR model in differentiating MSA and IPD were 0.935 7,for MSA and PSP were 0.975 4,for IPD and PSP were 0.982 5 in the test set.The IDLR model also showed consistency between its filtered feature maps and the visualization of gradient-weighted class activation mapping slice thermal maps in the radiomics regions of interest.Conclusion The IDLR model has the potential for differential diagnosis between IPD and atypical Parkinson's syndrome in 18F-FDG PET images.

In recent years, advancements in microfabrication technology and tissue engineering have propelled the development of a novel platform known as organoid-on-a-chip for drug screening and disease modeling. This platform integrates organoids and organ-on-a-chip technologies, emerging as a promising approach for in vitro modeling of human organs. Organ-on-a-chip leverages microfluidic device to simulate the physiological environment of specific organs, offering a more dynamic and flexible setting that can mimic a more comprehensive human biological context. However, the lack of functional vasculature has remained a major challenge in this technology. Vascularization is crucial for the long-term cultivation and in vitro modeling of organoids, which is of great significance in drug development and personalized medical approaches. The authors reviewed the research progress in the construction of vascularized organoid-on-a-chip including the methods for constructing in vitro vascularized models, vascularization of organoids, etc, which may serve as a reference for the construction of fully functional vascularized organoid-on-a-chip.