Peimenine unleashes therapeutic promise in urothelial bladder cancer: inhibition of proliferation, induction of cell death and modulation of key pathways.

Peimenine (PEI) is a steroid alkaloid substance isolated from Fritillaria thunbergii bulbs. It has various pharmacological activities, such as relief from coughs and asthma, expectorant properties, antibacterial effects, sedative qualities, and anti-inflammatory properties. Notably, PEI can effectively inhibit the proliferation and tumor formation of liver cancer and osteosarcoma cells by inducing autophagic cell death. However, the precise effect and mechanisms of PEI on urothelial bladder cancer (UBC) cells remain uncertain. Thus, this study aims to investigate the impact of PEI on UBC cells both in vivo and in vitro. The IC50 values of BIU-87 and EJ-1 cells after 48 h were 710.3 and 651.1 µg/mL, respectively. Additionally, PEI blocked the cell cycle in BIU-87 and EJ-1 cells during the G1 phase. Furthermore, it hindered the migration of BIU-87 and EJ-1 cells substantially. PEI significantly inhibited the tumor development of EJ-1 cells within the xenograft tumor model in vivo. Mechanically, PEI augmented the protein and mRNA expression of BIM, BAK1, and Cytochrome C (CYCS) in UBC cells. Taken together, PEI suppressed the proliferation of UBC cells both in vitro and in vivo by inducing cell death and cell cycle arrest, suggesting that PEI could be applied in the treatment of UBC.

Involvement of circRNA Regulators MBNL1 and QKI in the Progression of Esophageal Squamous Cell Carcinoma.

OBJECTIVES: To investigate the role of circRNA regulators MBNL1 and QKI in the progression of esophageal squamous cell carcinoma. BACKGROUND: MBNL1 and QKI are pivotal regulators of pre-mRNA alternative splicing, crucial for controlling circRNA production - an emerging biomarker and functional regulator of tumor progression. Despite their recognized roles, their involvement in ESCC progression remains unexplored. METHODS: The expression levels of MBNL1 and QKI were examined in 28 tissue pairs from ESCC and adjacent normal tissues using data from the GEO database. Additionally, a total of 151 ESCC tissue samples, from stage T1 to T4, consisting of 13, 43, 87, and 8 cases per stage, respectively, were utilized for immunohistochemical (IHC) analysis. RNA sequencing was utilized to examine the expression profiles of circRNAs, lncRNAs, and mRNAs across 3 normal tissues, 3 ESCC tissues, and 3 pairs of KYSE150 cells in both wildtype (WT) and those with MBNL1 or QKI knockouts. Transwell, colony formation, and subcutaneous tumorigenesis assays assessed the impact of MBNL1 or QKI knockout on ESCC cell migration, invasion, and proliferation. RESULTS: ESCC onset significantly altered MBNL1 and QKI expression levels, influencing diverse RNA species. Elevated MBNL1 or QKI expression correlated with patient age or tumor invasion depth, respectively. MBNL1 or QKI knockout markedly enhanced cancer cell migration, invasion, proliferation, and tumor growth. Moreover, the absence of either MBNL1 or QKI modulated the expression profiles of multiple circRNAs, causing extensive downstream alterations in the expression of numerous lncRNAs and mRNAs. While the functions of circRNA and lncRNA among the top 20 differentially expressed genes remain unclear, mRNAs like SLCO4C1, TMPRSS15, and MAGEB2 have reported associations with tumor progression. CONCLUSIONS: This study underscores the tumor-suppressive roles of MBNL1 and QKI in ESCC, proposing them as potential biomarkers and therapeutic targets for ESCC diagnosis and treatment.

Limited resection is comparable to lobectomy for tumor size ≤ 2 cm pulmonary invasive mucinous adenocarcinoma.

OBJECTIVES: Invasive mucinous adenocarcinoma (IMA) has a rare incidence with better prognosis than nonmucinous adenocarcinoma. We aimed to investigate the prognosis between limited resection and lobectomy for patients with clinical stage IA IMA ≤ 2 cm. METHODS: Data were taken from two cohorts: In Shanghai Pulmonary Hospital (SPH) corhort, we identified 403 patients with clinical stage IA IMA who underwent surgery. In the SEER corhort, 480 patients with stage T1 IMA who after surgery were included. Recurrence-free survival (RFS) for SPH corhort, lung cancer-specific survival (LCSS) for the SEER corhort and overall survival (OS) for both corhort were compared between patients undergoing lobectomy and limited resection by Log-rank and Cox proportional hazard regression model. RESULTS: In SPH corhort, patients who underwent limited resection had equivalent prognosis than those underwent lobectomy (5-year RFS: 79.3% versus. 82.6%, p = 0.116; 5-year OS: 86.2% versus. 88.3%, p = 0.235). However, patients with IMA > 2 to 3 cm had worse prognosis than those with IMA ≤ 2 cm (5-year RFS: 73.7% versus. 86.1%, p = 0.007). In the analysis of IMA > 2 to 3 cm subgroup, multivariate analysis showed that limited resection was an independent risk factor of RFS (hazard ratio, 2.417; 95% confidence interval, 1.157-5.049; p = 0.019), while OS (p = 0.122) was not significantly different between two groups. For IMA ≤ 2 cm, limited resection was not a risk factor of RFS (p = 0. 953) and OS (p = 0.552). In the SEER corhort, IMA ≤ 2 cm subgroup, limited resection was equivalent prognosis in LCSS (p = 0.703) and OS (p = 0.830). CONCLUSIONS: Limited resection could be a potential surgical option which comparable to lobectomy in patients with clinical stage IA IMA ≤ 2 cm.

Medicarpin suppresses lung cancer cell growth in vitro and in vivo by inducing cell apoptosis.

Lung cancer (LC) is the leading cause of cancer deaths worldwide. Surgery, chemoradiotherapy, targeted therapy, and immunotherapy are considered dominant treatment strategies for LC in the clinic. However, drug resistance and meta-stasis are two major challenges in cancer therapies. Medicarpin (MED) is an isoflavone compound isolated from alfalfa, which is usually used in traditional medicine. This study was de sig ned to evaluate the anti-LC effect and reveal the underlying mechanisms of MED in vivo and in vitro. We found that MED could significantly inhibit proliferation, induce apoptosis, and cell cycle arrest of A549 and H157 cell lines. Basically, MED induced cell apoptosis of LC cells by upregu lating the expression of pro-apoptotic proteins BAX and Bak1, leading to the cleavage of caspase-3 (Casp3). Moreover, MED inhibited the proliferation of LC cells via downregulating the expression of proliferative protein Bid. Overall, MED inhibited LC cell growth in vitro and in vivo via suppressing cell proliferation and inducing cell apoptosis, suggesting the therapeutic potential of MED in treating LC.

A Two-Stage Generative Model with CycleGAN and Joint Diffusion for MRI-based Brain Tumor Detection.

Accuratedetection and segmentation of brain tumors is critical for medical diagnosis. However, current supervised learning methods require extensively annotated images and the state-of-the-art generative models used in unsupervised methods often have limitations in covering the whole data distribution. In this paper, we propose a novel framework Two-Stage Generative Model (TSGM) that combines Cycle Generative Adversarial Network (CycleGAN) and Variance Exploding stochastic differential equation using joint probability (VE-JP) to improve brain tumor detection and segmentation. The CycleGAN is trained on unpaired data to generate abnormal images from healthy images as data prior. Then VE-JP is implemented to reconstruct healthy images using synthetic paired abnormal images as a guide, which alters only pathological regions but not regions of healthy. Notably, our method directly learned the joint probability distribution for conditional generation. The residual between input and reconstructed images suggests the abnormalities and a thresholding method is subsequently applied to obtain segmentation results. Furthermore, the multimodal results are weighted with different weights to improve the segmentation accuracy further. We validated our method on three datasets, and compared with other unsupervised methods for anomaly detection and segmentation. The DSC score of 0.8590 in BraTs2020 dataset, 0.6226 in ITCS dataset and 0.7403 in In-house dataset show that our method achieves better segmentation performance and has better generalization.

Multi-omics landscape analysis reveals the pan-cancer association of arginine biosynthesis genes with tumor immune evasion and therapy resistance.

Background: The metabolism of arginine, a conditionally essential amino acid, plays a crucial role in cancer progression and prognosis. However, a more detailed understanding of the influence of arginine biosynthesis genes in cancer is currently unavailable. Methods: We performed an integrative multi-omics analysis using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to determine the characteristics of these genes across multiple cancer types. To measure the overall activity of arginine biosynthesis genes in cancer, we calculated arginine biosynthesis scores based on gene expression. Results: Our results indicated that the arginine biosynthesis score was negatively correlated with immune-related pathways, immune infiltration, immune checkpoint expression, and patient prognosis, and single-cell data further clarified that patients with high arginine biosynthesis scores showed a reduced proportion of T and B cells in an immune desert tumor microenvironment and were insensitive to immunotherapy. We also identified several potential drugs through the Cancer Therapeutic Response Portal (CTRP) and Genomics of Drug Sensitivity in Cancer (GDSC) databases that could target arginine biosynthesis genes and potentially improve the response rate to immunotherapy in patients with a high arginine biosynthesis fraction. Conclusion: Overall, our analyses emphasize that arginine biosynthesis genes are associated with immune evasion in several cancers. Targeting these genes may facilitate more effective immunotherapy.

Malignant melanoma located in the ureter and gallbladder: A case report and literature review.

RATIONALE: Melanoma is one of a common cutaneous malignancy. Currently, metastatic malignant melanoma is difficult to be diagnosed through imaging examinations. Furthermore, the incidence of metastatic melanoma affecting the gallbladder and ureter is exceptionally rare. PATIENT CONCERNS: A 54-year-old female was admitted to the hospital with a half-month history of left lower back pain. Correlative examination revealed an occupying lesion in the mid-left ureter and the neck of the gallbladder. DIAGNOSES: The patient was initially diagnosed with gallbladder cancer and left ureteral carcinoma based on imaging. Following 2 operations, immunohistochemical staining confirmed the presence of metastatic melanoma involving both the gallbladder and ureter. INTERVENTION: After multidisciplinary consultation and obtaining consent from the patient and her family, the patient underwent left radical nephroureterectomy, radical cholecystectomy, laparoscopic partial hepatectomy (Hep IV, Hep V), and lymph node dissection of hepatoduodenal ligament. OUTCOMES: One month after treatment, the patient imaging showed no disease progression, and at 6 months of follow-up, the patient was still alive. LESSONS: It is difficult to distinguish metastatic melanoma from carcinoma in situ by imaging. In addition, metastatic malignant melanoma lacks specific clinical manifestations and is prone to misdiagnosis, which emphasizes the highly aggressive nature of malignant melanoma.

HES4 is a potential biomarker for bladder cancer: a Mendelian randomization study.

Background: Patients with bladder cancer (BLCA) have a poor prognosis and little progress has been made in treatment. Therefore, the purpose of this work was to employ Mendelian randomization (MR) and transcriptome analysis to identify a novel biomarker that could be used to reliably diagnose BLCA. Methods: TCGA-BLCA and GSE121711 datasets were obtained from public databases. Genome-wide association study (GWAS) data of BLCA outcome (373,295 samples containing 9,904,926 single nucleotide polymorphisms) were obtained through the IEU OpenGWAS database. Differentially expressed genes were applied as exposure factors, and MR analysis was performed to identify genes that had a causal relationship with BLCA. Then, the patients were divided into high and low expression groups according to the expression levels of candidate genes, and genes with survival differences were identified. Univariate and multivariate Cox regression were used to investigate the prognostic value of the expression of these genes. A nomogram was constructed based on independent prognostic factors, and we analyzed the functions and pathways associated with the identified genes as well as their relationship with the immune microenvironment. Results: HES4 was identified as a biomarker. HES4 status, age, and stage were identified as independent prognostic factors, and an excellent nomogram was established. Bioinformatic analysis suggested that HES4 might be associated with the activation of the immune response, bone development, and cancer pathways. The BLCA samples were divided into high and low HES4 groups. The stromal score and 33 immune cells were remarkably different between the two groups, with HES4 expression being negatively correlated with macrophages and mast cells, and positively correlated with eosinophils and central memory CD4+ T cells. Finally, HES4 was up-regulated in cancer samples in both TCGA-BLCA and GSE121711 datasets. Conclusion: This study identified HES4 as an independent prognostic factor for BLCA outcome based on MR and transcriptome analysis, which provides useful information for future research on and treatment of BLCA.

Copper-Catalyzed Asymmetric Remote C(sp3)-H Alkylation of N-Fluorocarboxamides with Glycine Derivatives and Peptides.

Saturated hydrocarbon bonds are ubiquitous in organic molecules; to date, the selective functionalization of C(sp3)-H bonds continues to pose a notorious difficulty, thereby garnering significant attention from the synthetic chemistry community. During the past several decades, a wide array of powerful new methodologies has been developed to enantioselectively modify C(sp3)-H bonds that is successfully applied in asymmetric formation of diverse bonds, including C-C, C-N, and C-O bonds; nevertheless, the asymmetric C(sp3)-H alkylation is elusive and, therefore, far less explored. In this work, we report a direct and robust strategy to construct highly valuable enantioenriched unnatural α-amino acid (α-AA) cognates and peptides by a copper-catalyzed enantioselective remote C(sp3)-H alkylation of N-fluorocarboxamides and readily accessible glycine esters under ambient conditions. The key to success lies in the optically active Cu catalyst generated through the coordination of glycine derivatives to enantiopure bisphosphine/Cu(I) species, which is beneficial to the single electronic reduction of N-fluorocarboxamides and the subsequent stereodetermining alkylation. More importantly, all types (primary, secondary, tertiary, and even α-oxy) of δ-C(sp3)-H bonds could be site- and stereospecifically activated by the kinetically favored 1,5-hydrogen atom transfer (1,5-HAT) step.

Histone deacetylase 6 deficiency protects the liver against ischemia/reperfusion injury by activating PI3K/AKT/mTOR signaling.

Liver transplantation (LT) is the only effective method to treat end-stage liver disease. Hepatic ischemia-reperfusion injury (IRI) continues to limit the prognosis of patients receiving LT. Histone deacetylase 6 (HDAC6) is a unique HDAC member involved in inflammation and apoptosis. However, its role and mechanism in hepatic IRI have not yet been reported. We examined HDAC6 levels in liver tissue from LT patients, mice challenged with liver IRI, and hepatocytes subjected to hypoxia/reoxygenation (H/R). In addition, HDAC6 global-knockout (HDAC6-KO) mice, adeno-associated virus-mediated liver-specific HDAC6 overexpressing (HDAC6-LTG) mice, and their corresponding controls were used to construct hepatic IRI models. Hepatic histology, inflammatory responses, and apoptosis were detected to assess liver injury. The molecular mechanisms of HDAC6 in hepatic IRI were explored in vivo and in vitro. Moreover, the HDAC6-selective inhibitor tubastatin A was used to detect the therapeutic effect of HDAC6 on liver IRI. Together, our results showed that HDAC6 expression was significantly upregulated in liver tissue from LT patients, mice subjected to hepatic I/R surgery, and hepatocytes challenged by hypoxia/reoxygenation (H/R) treatment. Compared with control mice, HDAC6 deficiency mitigated liver IRI by inhibiting inflammatory responses and apoptosis, whereas HDAC6-LTG mice displayed the opposite phenotype. Further molecular experiments show that HDAC6 bound to and deacetylated AKT and HDAC6 deficiency improved liver IRI by activating PI3K/AKT/mTOR signaling. In conclusion, HDAC6 is a key mediator of hepatic IRI that functions to promote inflammation and apoptosis via PI3K/AKT/mTOR signaling. Targeting hepatic HDAC6 inhibition may be a promising approach to attenuate liver IRI.

Robot-assisted radical cystectomy with intracorporeal urinary diversion: an updated systematic review and meta-analysis of its differential effect on effectiveness and safety.

BACKGROUND: Robot-assisted laparoscopic cystectomy with intracorporeal urinary diversion (iRARC) is increasingly being used in recent years. Whether iRARC offers advantages over open radical cystectomy (ORC) remains controversial. This study aimed to compare the difference of perioperative outcomes, oncological outcomes and complications between iRARC and ORC. METHODS: The PubMed, Embase, Cochrane Library, Web of Science and CNKI databases were searched in July 2023 according to the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analyses) statement. Studies were identified to be eligible if they compared perioperative outcomes, oncological outcomes and complications in patients who underwent iRARC with ORC. RESULTS: Twenty-two studies involving 7020 patients were included. Compared to ORC, iRARC was superior for estimated blood loss [estimated blood loss (EBL) weighted mean difference (WMD): -555.52; 95% CI, -681.64 to -429.39; P <0.001], blood transfusion rate [odds ratio (OR): 0.16; 95% CI, 0.09-0.28; P <0.001], length of hospital stay [length of hospital stay (LOS) WMD: -2.05; 95% CI, -2.93 to -1.17; P <0.001], Clavien-Dindo grades ≥III complication rate [30 days: OR: 0.57; 95% CI 0.44-0.75; P <0.001; 90 days: OR: 0.71; 95% CI 0.60-0.84; P <0.001], and positive surgical margin [positive surgical margin (PSM) OR: 0.65; 95% CI 0.49-0.85; P =0.002]. However, iRARC had a longer operative time [operative time (OT) WMD: 68.54; 95% CI 47.41-89.67; P <0.001] and a higher rate of ureteroenteric stricture [ureteroenteric stricture (UES) OR: 1.56; 95% CI 1.16-2.11; P =0.003]. Time to flatus, time to bowel, time to regular diet, readmission rate, Clavien-Dindo grades less than III complication rate for iRARC were similar to that for ORC. Interestingly, the results of subgroup analysis revealed no difference in EBL between iRARC and ORC when the diversion type was neobladder. When the ileal conduit was selected as the diversion type, the LOS was similar in both procedures. CONCLUSION: Robot-assisted laparoscopic cystectomy with intracorporeal urinary diversion appears to be superior to open radical cystectomy in terms of effectiveness and safety. However, attention should be paid to the occurrence of ureteroenteric stricture during follow-up.

Development of a stemness-related prognostic index to provide therapeutic strategies for bladder cancer.

Bladder cancer (BC) is a heterogeneous disease with varying clinical outcomes. Recent evidence suggests that cancer progression involves the acquisition of stem-like signatures, and assessing stemness indices help uncover patterns of intra-tumor molecular heterogeneity. We used the one-class logistic regression algorithm to compute the mRNAsi for each sample in BLCA cohort. We subsequently classified BC patients into two subtypes based on 189 mRNAsi-related genes, using the unsupervised consensus clustering. Then, we identified nine hub genes to construct a stemness-related prognostic index (SRPI) using Cox regression, LASSO regression and Random Forest methods. We further validated SRPI using two independent datasets. Afterwards, we examined the molecular and immune characterized of SRPI. Finally, we conducted multiply drug screening and experimental approaches to identify and confirm the most proper agents for patients with high SRPI. Based on the mRNAsi-related genes, BC patients were classified into two stemness subtypes with distinct prognosis, functional annotations, genomic variations and immune profiles. Using the SRPI, we identified a specific subgroup of BC patients with high SRPI, who had a poor response to immunotherapy, and were less sensitive to commonly used chemotherapeutic agents, FGFR inhibitors, and EGFR inhibitors. We further identified that dasatinib was the most promising therapeutic agent for this subgroup of patients. This study provides further insights into the stemness classification of BC, and demonstrates that SRPI is a promising tool for predicting prognosis and therapeutic opportunities for BC patients.

Functional Food Chemical Ingredient Strategies for Non-alcoholic Fatty Liver Disease (NAFLD) and Hepatic Fibrosis: Chemical Properties, Health Benefits, Action, and Application.

PURPOSE OF REVIEW: The liver is an important digestive gland in the body. Lifestyle and dietary habits are increasingly damaging our liver, leading to various diseases and health problems. Non-alcoholic fatty liver disease (NAFLD) has become one of the most serious liver disease problems in the world. Diet is one of the important factors in maintaining liver health. Functional foods and their components have been identified as novel sources of potential preventive agents in the prevention and treatment of liver disease in daily life. However, the effects of functional components derived from small molecules in food on different types of liver diseases have not been systematically summarized. RECENT FINDINGS: The components and related mechanisms in functional foods play a significant role in the development and progression of NAFLD and liver fibrosis. A variety of structural components are found to treat and prevent NAFLD and liver fibrosis through different mechanisms, including flavonoids, alkaloids, polyphenols, polysaccharides, unsaturated fatty acids, and peptides. On the other hand, the relevant mechanisms include oxidative stress, inflammation, and immune regulation, and a large number of literature studies have confirmed a close relationship between the mechanisms. The purpose of this article is to examine the current literature related to functional foods and functional components used for the treatment and protection against NAFLD and hepatic fibrosis, focusing on chemical properties, health benefits, mechanisms of action, and application in vitro and in vivo. The roles of different components in the biological processes of NAFLD and liver fibrosis were also discussed.

LASS2 enhances chemosensitivity to cisplatin by inhibiting PP2A-mediated ß-catenin dephosphorylation in a subset of stem-like bladder cancer cells.

BACKGROUND: The benefits of first-line, cisplatin-based chemotherapy for muscle-invasive bladder cancer are limited due to intrinsic or acquired resistance to cisplatin. Increasing evidence has revealed the implication of cancer stem cells in the development of chemoresistance. However, the underlying molecular mechanisms remain to be elucidated. This study investigates the role of LASS2, a ceramide synthase, in regulating Wnt/ß-catenin signaling in a subset of stem-like bladder cancer cells and explores strategies to sensitize bladder cancer to cisplatin treatment. METHODS: Data from cohorts of our center and published datasets were used to evaluate the clinical characteristics of LASS2. Flow cytometry was used to sort and analyze bladder cancer stem cells (BCSCs). Tumor sphere formation, soft agar colony formation assay, EdU assay, apoptosis analysis, cell viability, and cisplatin sensitivity assay were used to investigate the functional roles of LASS2. Immunofluorescence, immunoblotting, coimmunoprecipitation, LC-MS, PCR array, luciferase reporter assays, pathway reporter array, chromatin immunoprecipitation, gain-of-function, and loss-of-function approaches were used to investigate the underlying mechanisms. Cell- and patient-derived xenograft models were used to investigate the effect of LASS2 overexpression and a combination of XAV939 on cisplatin sensitization and tumor growth. RESULTS: Patients with low expression of LASS2 have a poorer response to cisplatin-based chemotherapy. Loss of LASS2 confers a stem-like phenotype and contributes to cisplatin resistance. Overexpression of LASS2 results in inhibition of self-renewal ability of BCSCs and increased their sensitivity to cisplatin. Mechanistically, LASS2 inhibits PP2A activity and dissociates PP2A from ß-catenin, preventing the dephosphorylation of ß-catenin and leading to the accumulation of cytosolic phospho-ß-catenin, which decreases the transcription of the downstream genes ABCC2 and CD44 in BCSCs. Overexpression of LASS2 combined with a tankyrase inhibitor (XAV939) synergistically inhibits tumor growth and restores cisplatin sensitivity. CONCLUSIONS: Targeting the LASS2 and ß-catenin pathways may be an effective strategy to overcome cisplatin resistance and inhibit tumor growth in bladder cancer patients.

A computed tomography urography-based machine learning model for predicting preoperative pathological grade of upper urinary tract urothelial carcinoma.

OBJECTIVES: Development and validation of a computed tomography urography (CTU)-based machine learning (ML) model for prediction of preoperative pathology grade of upper urinary tract urothelial carcinoma (UTUC). METHODS: A total of 140 patients with UTUC who underwent CTU examination from January 2017 to August 2023 were retrospectively enrolled. Tumor lesions on the unenhanced, medullary, and excretory periods of CTU were used to extract Features, respectively. Feature selection was screened by the Pearson and Spearman correlation analysis, least absolute shrinkage and selection operator algorithm, random forest (RF), support vector machine (SVM), and eXtreme Gradient Boosting (XGBoost). The logistic regression (LR) was used to screen for independent influencing factors of clinical baseline characteristics. Machine learning models based on different feature datasets were constructed and validated using algorithms such as LR, RF, SVM, and XGBoost. By computing the selected features, a radiomics score was generated, and a diverse feature dataset was constructed. Based on the training set, 16 ML models were created, and their performance was evaluated using the validation set for metrics including sensitivity, specificity, accuracy, area under the receiver operating characteristic curve (AUC), and others. RESULTS: The training set consisted of 98 patients (mean age: 64.5 ± 10.5 years; 30 males), whereas the validation set consisted of 42 patients (mean age: 65.3 ± 9.78 years; 17 males). Hydronephrosis was the best independent influence factor (p < 0.05). The RF model had the best performance in predicting high-grade UTUC, with AUC of 0.914 (95% Confidence Interval [95%CI] 0.852-0.977) and 0.903 (95%CI 0.809-0.997) in the training set and validation set, and accuracy of 0.878 and 0.857, respectively. CONCLUSIONS: An ML model based on the RF algorithm exhibits excellent predictive performance, offering a non-invasive approach for predicting preoperative high-grade UTUC.

Soybean Agglutinin Alters the Gut Microbiota and Promotes Inflammation in Lupus-Prone MRL/lpr Mice.

BACKGROUND: Certain foods can trigger flares in patients with systemic lupus erythematosus. Lectins in edible plants have been reported to increase inflammation. OBJECTIVE: This study aimed to determine the effects of 1-time intake of soybean agglutinin (SBA) on the gut microbiota and immune response in lupus-prone MRL/MpJ (MRL)/lpr mice. METHODS: MRL/MpJ-Faslpr/J (MRL/lpr) and MRL mice were randomly assigned into 4 groups (8 mice/group): MRL mice + phosphate-buffered saline (PBS) (CON), MRL mice + SBA (CS), MRL/lpr mice + PBS (LPR), and MRL/lpr + SBA (LS). PBS and SBA were orally administered at 16 wk of age, and all mice were killed 24 h after oral challenge. The disease phenotype, levels of proinflammatory cytokines, and composition of the intestinal microbiota were determined. RESULTS: Interferon-gamma (IFN-γ) in the serum was significantly higher, whereas the level of serum IL-10 was significantly lower in LS mice than in LPR mice [fold change (FC) = 1.31 and FC = 0.36, respectively]. The expression levels of IL-6 and TNF-α in the spleen of LS mice were significantly higher than those in LPR mice (FC = 1.66 and FC = 1.96, respectively). The expression levels of IL-6, TNF-α, and IL-1ß in the kidney were also significantly higher in LS mice than in LPR mice (FC = 2.89, FC = 3.78, and FC = 2.02, respectively). The relative abundances of Erysipelotrichaceae and Turicibacter in LS mice were significantly higher than those in LPR mice (FC = 1.73 and FC = 1.74, respectively). The percentage of Breg cells in the mesenteric lymph nodes was significantly lower in LS mice than in LPR mice (FC = 0.53) (P < 0.05). No change was found between SBA treatment or not in the control (MRL) mice. CONCLUSIONS: One-time intake of SBA can promote the secretion of proinflammatory cytokines, downregulate Breg cells, and alter the intestinal flora in MRL/lpr mice within 24 h of oral challenge, which may contribute to exacerbation of lupus.

A gradient mapping guided explainable deep neural network for extracapsular extension identification in 3D head and neck cancer computed tomography images.

BACKGROUND: Diagnosis and treatment management for head and neck squamous cell carcinoma (HNSCC) is guided by routine diagnostic head and neck computed tomography (CT) scans to identify tumor and lymph node features. The extracapsular extension (ECE) is a strong predictor of patients' survival outcomes with HNSCC. It is essential to detect the occurrence of ECE as it changes staging and treatment planning for patients. Current clinical ECE detection relies on visual identification and pathologic confirmation conducted by clinicians. However, manual annotation of the lymph node region is a required data preprocessing step in most of the current machine learning-based ECE diagnosis studies. PURPOSE: In this paper, we propose a Gradient Mapping Guided Explainable Network (GMGENet) framework to perform ECE identification automatically without requiring annotated lymph node region information. METHODS: The gradient-weighted class activation mapping (Grad-CAM) technique is applied to guide the deep learning algorithm to focus on the regions that are highly related to ECE. The proposed framework includes an extractor and a classifier. In a joint training process, informative volumes of interest (VOIs) are extracted by the extractor without labeled lymph node region information, and the classifier learns the pattern to classify the extracted VOIs into ECE positive and negative. RESULTS: In evaluation, the proposed methods are well-trained and tested using cross-validation. GMGENet achieved test accuracy and area under the curve (AUC) of 92.2% and 89.3%, respectively. GMGENetV2 achieved 90.3% accuracy and 91.7% AUC in the test. The results were compared with different existing models and further confirmed and explained by generating ECE probability heatmaps via a Grad-CAM technique. The presence or absence of ECE has been analyzed and correlated with ground truth histopathological findings. CONCLUSIONS: The proposed deep network can learn meaningful patterns to identify ECE without providing lymph node contours. The introduced ECE heatmaps will contribute to the clinical implementations of the proposed model and reveal unknown features to radiologists. The outcome of this study is expected to promote the implementation of explainable artificial intelligence-assiste ECE detection.