Transfer learning-based PET/CT three-dimensional convolutional neural network fusion of image and clinical information for prediction of EGFR mutation in lung adenocarcinoma.

BACKGROUND: To introduce a three-dimensional convolutional neural network (3D CNN) leveraging transfer learning for fusing PET/CT images and clinical data to predict EGFR mutation status in lung adenocarcinoma (LADC). METHODS: Retrospective data from 516 LADC patients, encompassing preoperative PET/CT images, clinical information, and EGFR mutation status, were divided into training (n = 404) and test sets (n = 112). Several deep learning models were developed utilizing transfer learning, involving CT-only and PET-only models. A dual-stream model fusing PET and CT and a three-stream transfer learning model (TS_TL) integrating clinical data were also developed. Image preprocessing includes semi-automatic segmentation, resampling, and image cropping. Considering the impact of class imbalance, the performance of the model was evaluated using ROC curves and AUC values. RESULTS: TS_TL model demonstrated promising performance in predicting the EGFR mutation status, with an AUC of 0.883 (95%CI = 0.849-0.917) in the training set and 0.730 (95%CI = 0.629-0.830) in the independent test set. Particularly in advanced LADC, the model achieved an AUC of 0.871 (95%CI = 0.823-0.919) in the training set and 0.760 (95%CI = 0.638-0.881) in the test set. The model identified distinct activation areas in solid or subsolid lesions associated with wild and mutant types. Additionally, the patterns captured by the model were significantly altered by effective tyrosine kinase inhibitors treatment, leading to notable changes in predicted mutation probabilities. CONCLUSION: PET/CT deep learning model can act as a tool for predicting EGFR mutation in LADC. Additionally, it offers clinicians insights for treatment decisions through evaluations both before and after treatment.

Automatic Urinary Stone Detection System for Abdominal Non-Enhanced CT Images Reduces the Burden on Radiologists.

To develop a fully automatic urinary stone detection system (kidney, ureter, and bladder) and to test it in a real clinical environment. The local institutional review board approved this retrospective single-center study that used non-enhanced abdominopelvic CT scans from patients admitted urology (uPatients) and emergency (ePatients). The uPatients were randomly divided into training and validation sets in a ratio of 3:1. We designed a cascade urinary stone map location-feature pyramid networks (USm-FPNs) and innovatively proposed a ureter distance heatmap method to estimate the ureter position on non-enhanced CT to further reduce the false positives. The performances of the system were compared using the free-response receiver operating characteristic curve and the precision-recall curve. This study included 811 uPatients and 356 ePatients. At stone level, the cascade detector USm-FPNs has the mean of false positives per scan (mFP) 1.88 with the sensitivity 0.977 in validation set, and mFP was further reduced to 1.18 with the sensitivity 0.977 after combining the ureter distance heatmap. At patient level, the sensitivity and precision were as high as 0.995 and 0.990 in validation set, respectively. In a real clinical set of ePatients (27.5% of patients contain stones), the mFP was 1.31 with as high as sensitivity 0.977, and the diagnostic time reduced by > 20% with the system help. A fully automatic detection system for entire urinary stones on non-enhanced CT scans was proposed and reduces obviously the burden on junior radiologists without compromising sensitivity in real emergency data.

Magnetically driven capsules with multimodal response and multifunctionality for biomedical applications.

Untethered capsules hold clinical potential for the diagnosis and treatment of gastrointestinal diseases. Although considerable progress has been achieved recently in this field, the constraints imposed by the narrow spatial structure of the capsule and complex gastrointestinal tract environment cause many open-ended problems, such as poor active motion and limited medical functions. In this work, we describe the development of small-scale magnetically driven capsules with a distinct magnetic soft valve made of dual-layer ferromagnetic soft composite films. A core technological advancement achieved is the flexible opening and closing of the magnetic soft valve by using the competitive interactions between magnetic gradient force and magnetic torque, laying the foundation for the functional integration of both drug release and sampling. Meanwhile, we propose a magnetic actuation strategy based on multi-frequency response control and demonstrate that it can achieve effective decoupled regulation of the capsule's global motion and local responses. Finally, through a comprehensive approach encompassing ideal models, animal ex vivo models, and in vivo assessment, we demonstrate the versatility of the developed magnetic capsules and their multiple potential applications in the biomedical field, such as targeted drug delivery and sampling, selective dual-drug release, and light/thermal-assisted therapy.

MYL9 expressed in cancer-associated fibroblasts regulate the immune microenvironment of colorectal cancer and promotes tumor progression in an autocrine manner.

BACKGROUND: The tumor microenvironment (TME) is an important factor that regulates the progression of colorectal cancer (CRC). Cancer-associated fibroblasts (CAFs) are the main mesenchymal cells in the TME and play a vital role in tumor progression; however, the specific underlying mechanisms require further study. METHODS: Multiple single-cell and transcriptome data were analyzed and validated. Primary CAFs isolation, CCK8 assay, co-culture assay, western blotting, multiple immunofluorescence, qRT-PCR, ELISA, immunoprecipitation, ChIP, double luciferase, and animal experiments were used to explore the potential mechanism of MYL9 regulation in CRC. RESULTS: Our findings revealed that MYL9 was predominantly localized and expressed in CAFs rather than in CRC cells, and bioinformatics analysis revealed that high MYL9 expression was strongly associated with poor overall and disease-free survival in various tumors. In addition, high MYL9 expression is closely associated with M2 macrophage infiltration, which can lead to an immunosuppressive microenvironment in CRC, making it insensitive to immunotherapy. Mechanically, MYL9 can regulate the secretion of CAFs on CCL2 and TGF-ß1, thus affecting the immune microenvironment and progression of CRC. In addition, MYL9 bounded with IQGAP1 to regulate CCL2 and TGF-ß1 secretion through the ERK 1/2 pathway, and CCL2 and TGF-ß1 synergistically promoted CRC cells progression through the PI3K-AKT pathway. Furthermore, MYL9 promotes epithelial-mesenchymal transition (EMT) in CRC. During the upstream regulation of MYL9 in CAFs, we found that the EMT transcription factor ZEB1 could bind to the MYL9 promoter in CAFs, enhancing the activity and function of MYL9. Therefore, MYL9 is predominantly expressed in CAFs and can indirectly influence tumor biology and EMT by affecting CAFs protein expression in CRC. CONCLUSIONS: MYL9 regulates the secretion of cytokines and chemokines in CAFs, which can affect the immune microenvironment of CRC and promote CRC progression. The relationship between MYL9 expression and CRC clinical staging and immunotherapy is closer in CAFs than in tumor cells; therefore, studies using CAFs as a model deserve more attention when exploring tumor molecular targets in clinical research.

Changes in Bacteroides and the microbiota in patients with obstructed colorectal cancer: retrospective cohort study.

BACKGROUND: The relationship between intestinal obstruction due to colorectal cancer (CRC) and the gut microbiota remains largely unknown. The aim of this study was to investigate the potential association between alterations in gut microbiota and CRC in the presence of intestinal obstruction. METHODS: Patients with CRC with or without obstruction were recruited and compared using 1:1 propensity score matching (PSM). Total DNA from tumours and adjacent normal tissues of 84 patients and 36 frozen tumour tissues was extracted and amplified. 16S RNA sequencing was used to uncover differences in microbiota composition between the two groups. RESULTS: A total of 313 patients with CRC were recruited. Survival analysis demonstrated that patients in the obstruction group had shorter overall survival time and disease-free survival (DFS) time than those in the non-obstruction group. Microbial richness and diversity in tumour tissues of patients with obstruction were significantly higher than those of patients with no obstruction. The alpha diversity indices and beta diversity exhibited were different between the two groups (P < 0.05). At the phylum and genus levels, Bacteroidetes were significantly enriched in the tumour tissues of patients with obstruction. Alpha diversity in tumour tissues was closely related to specific microbiota. These findings were replicated in the 16S rRNA analyses from frozen samples. There were more Bacteroidetes in CRC patients with obstruction. CONCLUSIONS: Patients with obstructed CRC have worse prognosis and have differences in their microbiota. Higher levels of Bacteroides were observed in patients with obstructed CRC.

Modified Naples prognostic score for evaluating the prognosis of patients with obstructive colorectal cancer.

BACKGROUND: Inflammatory, immune, and nutritional status are key factors in obstructive colorectal cancer (OCRC). This study aims to investigate the value of modified Naples prognostic score (M-NPS) in evaluating OCRC prognosis. METHODS: A total of 196 OCRC patients were retrospectively analyzed to construct M-NPS based on serum albumin (ALB), total cholesterol (CHOL), neutrophil:lymphocyte ratio (NLR), and lymphocyte:monocyte ratio (LMR), and then they were divided into three groups. The Kaplan-Meier (KM) method and Cox proportional hazard regression analysis were performed for overall survival (OS) and disease-free survival (DFS) of OCRC patients. RESULTS: Patients with high M-NPS had worse OS and DFS (P = 0.0001, P = 0.0011). Multivariate COX analysis showed that M-NPS was an independent prognostic factor for OCRC patients. Patients in the M-NPS 2 group had significantly worse OS (hazard ratio [HR] = 4.930 (95% confidence interval [95% CI], 2.217-10.964), P < 0.001) and DFS (HR = 3.508 (95% CI, 1.691-7.277), P < 0.001) than those in the 0 group. CONCLUSION: M-NPS was an independent prognostic factor for OCRC patients; it might provide a potential reference for immunonutritional intervention in patients with obstruction.

Using Ultrahigh b -Value Diffusion-Weighted Imaging to Noninvasively Assess Renal Fibrosis in a Rabbit Model of Renal Artery Stenosis.

OBJECTIVE: This study aimed to investigate the feasibility of diffusion-weighted imaging with ultrahigh b values ( ub DWI) for the evaluation of renal fibrosis (RF) induced by renal artery stenosis (RAS) in a rabbit model. METHODS: Thirty-two rabbits underwent left RAS operation, whereas 8 rabbits received sham surgery. All rabbits underwent ub DWI ( b = 0-4500 s/mm 2 ). The standard apparent diffusion coefficient (ADC st ), molecular diffusion coefficient ( D ), perfusion fraction ( f ), perfusion-related diffusion coefficient ( D *) and ultrahigh apparent diffusion coefficient (ADC uh ) were longitudinally assessed before operation and at weeks 2, 4, and 6 after operation. The degree of interstitial fibrosis and the expression of aquaporin (AQP) 1 and AQP2 were determined through pathological examination. RESULTS: In the stenotic kidney, the ADC st , D , f , and ADC uh values of the renal parenchyma significantly decreased compared with those at baseline (all P < 0.05), whereas the D * values significantly increased after RAS induction ( P < 0.05). The ADC st , D , D *, and f were weakly to moderately correlated with interstitial fibrosis as well as with the expression of AQP1 and AQP2. Furthermore, the ADC uh negatively correlated with interstitial fibrosis ( ρ = -0.782, P < 0.001) and positively correlated with AQP1 and AQP2 expression ( ρ = 0.794, P < 0.001, and ρ = 0.789, P < 0.001, respectively). CONCLUSIONS: Diffusion-weighted imaging with ultrahigh b values shows the potential for noninvasive assessment of the progression of RF in rabbits with unilateral RAS. The ADC uh derived from ub DWI could reflect the expression of AQPs in RF.

What Imaging Modality Is More Effective in Predicting Early Recurrence of Hepatocellular Carcinoma after Hepatectomy Using Radiomics Analysis: CT or MRI or Both?

BACKGROUND: It is of great importance to predict the early recurrence (ER) of hepatocellular carcinoma (HCC) after hepatectomy using preoperative imaging modalities. Nevertheless, no comparative studies have been conducted to determine which modality, CT or MRI with radiomics analysis, is more effective. METHODS: We retrospectively enrolled 119 HCC patients who underwent preoperative CT and MRI. A total of 3776 CT features and 4720 MRI features were extracted from the whole tumor. The minimum redundancy and maximum relevance algorithm (MRMR) and least absolute shrinkage and selection operator (LASSO) regression were applied for feature selection, then support vector machines (SVMs) were applied for model construction. Multivariable logistic regression analysis was employed to construct combined models that integrate clinical-radiological-pathological (CRP) traits and radscore. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used to compare the efficacy of CT, MRI, and CT and MRI models in the test cohort. RESULTS: The CT model and MRI model showed no significant difference in the prediction of ER in HCC patients (p = 0.911). RadiomicsCT&MRI demonstrated a superior predictive performance than either RadiomicsCT or RadiomicsMRI alone (p = 0.032, 0.039). The combined CT and MRI model can significantly stratify patients at high risk of ER (area under the curve (AUC) of 0.951 in the training set and 0.955 in the test set) than the CT model (AUC of 0.894 and 0.784) and the MRI model (AUC of 0.856 and 0.787). DCA demonstrated that the CT and MRI model provided a greater net benefit than the models without radiomics analysis. CONCLUSIONS: No significant difference was found in predicting the ER of HCC between CT models and MRI models. However, the multimodal radiomics model derived from CT and MRI can significantly improve the prediction of ER in HCC patients after resection.

Association between renal surface nodularity and increased adverse vascular event risk in patients with arterial hypertension.

OBJECTIVE: To explore the association of renal surface nodularity (RSN) with the increased adverse vascular event (AVE) risk in patients with arterial hypertension. METHODS: This cross-sectional study included patients with arterial hypertension aged 18-60 years who underwent contrasted computed tomography (CT) of kidney from January 2012 to December 2020. The subjects were classified into AVE or not (non-AVE) matched with age (≤5 years) and sex. Their CT images were analyzed using both qualitative (semiRSN) and quantitative RSN (qRSN) methods, respectively. Their clinical characteristics included age, sex, systolic blood pressure (SBP), diastolic blood pressure, hypertension course, diabetes history, hyperlipidemia, and estimated glomerular filtration rate (eGFR). RESULTS: Compared with non-AVE group (n = 91), AVE (n = 91) was at lower age, higher SBP, and fewer rate of diabetes and hyperlipidemia history (all P < .01). Rate of positive semiRSN was higher in AVE than non-AVE (49.45% vs 14.29%, P < .001). qRSN was larger in AVE than non-AVE [1.03 (0.85, 1.33) vs 0.86 (0.75,1.03), P < .001]. The increased AVE was associated with semiRSN (odds ratio = 7.04, P < .001) and qRSN (odds ratio = 5.09, P = .003), respectively. For distinguishing AVE from non-AVE, the area under receiver operating characteristic was bigger in the models combining the clinical characteristics with either semiRSN or qRSN than that of semiRSN or qRSN alone (P ≤.01). CONCLUSION: Among the patients with arterial hypertension aged 18-60 years, CT imaging-based RSN was associated with increased AVE risk.

Perineural invasion affects prognosis of patients undergoing colorectal cancer surgery: a propensity score matching analysis.

BACKGROUND: Tumour perineural invasion (PNI) is a predictor of poor prognosis, but its effect on the prognosis of patients with colorectal cancer (CRC) has not yet been elucidated. METHODS: This retrospective study used propensity score matching (PSM). The clinical case data of 1470 patients with surgically treated stage I-IV CRC at Wuhan Union Hospital were collected. PSM was used to analyse and compare the clinicopathological characteristics, perioperative outcomes, and long-term prognostic outcomes of the PNI(+) and PNI(-) groups. The factors influencing prognosis were screened using Cox univariate and multivariate analyses. RESULTS: After PSM, 548 patients were included in the study (n = 274 in each group). Multifactorial analysis showed that neurological invasion was an independent prognostic factor affecting patients' OS and DFS (hazard ratio [HR], 1.881; 95% confidence interval [CI], 1.35-2.62; P = 0.0001; HR, 1.809; 95% CI, 1.353-2.419; P < 0.001). Compared to PNI(+) patients without chemotherapy, those who received chemotherapy had a significant improvement in OS (P < 0.01). The AUROC curve of OS in the PNI(+) subgroup (0.802) was higher than that after PSM (0.743), while that of DFS in the PNI(+) subgroup (0.746) was higher than that after PSM (0.706). The independent predictors of PNI(+) could better predict the prognosis and survival of patients with PNI(+). CONCLUSIONS: PNI significantly affects the long-term survival and prognosis of patients with CRC undergoing surgery and is an independent risk factor for OS and DFS in patients with CRC undergoing surgery. Postoperative chemotherapy significantly improved the OS of PNI(+) patients.

The predictive value of [18F]FDG PET/CT radiomics combined with clinical features for EGFR mutation status in different clinical staging of lung adenocarcinoma.

BACKGROUND: This study aims to construct radiomics models based on [18F]FDG PET/CT using multiple machine learning methods to predict the EGFR mutation status of lung adenocarcinoma and evaluate whether incorporating clinical parameters can improve the performance of radiomics models. METHODS: A total of 515 patients were retrospectively collected and divided into a training set (n = 404) and an independent testing set (n = 111) according to their examination time. After semi-automatic segmentation of PET/CT images, the radiomics features were extracted, and the best feature sets of CT, PET, and PET/CT modalities were screened out. Nine radiomics models were constructed using logistic regression (LR), random forest (RF), and support vector machine (SVM) methods. According to the performance in the testing set, the best model of the three modalities was kept, and its radiomics score (Rad-score) was calculated. Furthermore, combined with the valuable clinical parameters (gender, smoking history, nodule type, CEA, SCC-Ag), a joint radiomics model was built. RESULTS: Compared with LR and SVM, the RF Rad-score showed the best performance among the three radiomics models of CT, PET, and PET/CT (training and testing sets AUC: 0.688, 0.666, and 0.698 vs. 0.726, 0.678, and 0.704). Among the three joint models, the PET/CT joint model performed the best (training and testing sets AUC: 0.760 vs. 0.730). The further stratified analysis found that CT_RF had the best prediction effect for stage I-II lesions (training set and testing set AUC: 0.791 vs. 0.797), while PET/CT joint model had the best prediction effect for stage III-IV lesions (training and testing sets AUC: 0.722 vs. 0.723). CONCLUSIONS: Combining with clinical parameters can improve the predictive performance of PET/CT radiomics model, especially for patients with advanced lung adenocarcinoma.

Development and Interpretation of a Clinicopathological-Based Model for the Identification of Microsatellite Instability in Colorectal Cancer.

Chemotherapy is not recommended for patients with deficient mismatch repair (dMMR) in colorectal cancer (CRC); therefore, assessing the status of MMR is crucial for the selection of subsequent treatment. This study is aimed at building predictive models to accurately and rapidly identify dMMR. A retrospective analysis was performed at Wuhan Union Hospital between May 2017 and December 2019 based on the clinicopathological data of patients with CRC. The variables were subjected to collinearity, least absolute shrinkage and selection operator (LASSO) regression, and random forest (RF) feature screening analyses. Four sets of machine learning models (extreme gradient boosting (XGBoost), support vector machine (SVM), naive Bayes (NB), and RF) and a conventional logistic regression (LR) model were built for model training and testing. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive performance of the developed models. In total, 2279 patients were included in the study and were randomly divided into either the training or test group. Twelve clinicopathological features were incorporated into the development of the predictive models. The area under curve (AUC) values of the five predictive models were 0.8055 for XGBoost, 0.8174 for SVM, 0.7424 for NB, 8584 for RF, and 0.7835 for LR (Delong test, P value < 0.05). The results showed that the RF model exhibited the best recognition ability and outperformed the conventional LR method in identifying dMMR and proficient MMR (pMMR). Our predictive models based on routine clinicopathological data can significantly improve the diagnostic performance of dMMR and pMMR. The four machine learning models outperformed the conventional LR model.

Endoscopic fully covered self-expandable metal stent and vacuum-assisted drainage to treat postoperative colorectal cancer anastomotic stenosis with fistula.

BACKGROUND: Digestive tract reconstruction is required after the surgical resection of a colorectal malignant tumor. Some patients may have concomitant anastomotic complications, such as anastomotic stenosis with fistula (ASF), postoperatively. Therefore, we evaluated the efficacy and safety of endoscopic fully covered self-expandable metal stent and homemade vacuum sponge-assisted drainage (FSEM-HVSD) for the treatment of ASF following the radical resection of colorectal cancer. METHODS: Patients treated with FESM-HVSD were prospectively analyzed and followed up for ASF following colorectal cancer treatment in our medical center from 2017 to 2021 for the observation and evaluation of its safety and efficacy. RESULTS: Fifteen patients with a mean age of 55.80 ± 11.08 years were included. Nine patients (60%) underwent protective ileostomy. All 15 patients were treated with endoscopic FSEM-HVSD. The median time from the index operation to the initiation of FSEM-HVSD was 80 ± 20.34 days in patients who underwent protective ileostomy versus 11.4 ± 4.4 days in those who did not. The average number of endoscopic treatments per patient was 5.70 ± 1.25 times. The mean length of hospital stay was 27.60 ± 4.43 days. FSEM-HVSD treatment was successful in 13 patients, and no patients had any complications. The follow-up time was 1 year. Twelve of 15 (80%) patients achieved prolonged clinical success after FSEM-HVSD treatment, 1 experienced anastomotic tumor recurrence and underwent surgery again, and 1 patient required balloon dilation for anastomotic stenosis recurrence. CONCLUSIONS: FSEM-HVSD is an effective, safe, and minimally invasive treatment for ASF following colorectal cancer treatment. This technique could be the preferred treatment strategy for patients with ASF.

Association of renal surface nodularity with arterial hypertension compared to normotensive patients.

BACKGROUND: Renal surface nodularity (RSN) is a subclinical biomarker of renal injury and may be associated with arterial hypertension. PURPOSE: To explore the association of RSN with arterial hypertension compared to normotensive patients. MATERIAL AND METHODS: A total of 205 inpatients with or without high blood pressure (HBP vs. control group) who underwent abdominal computed tomography (CT) scans were included. Their clinical characteristics included age, sex, HBP course, HBP grade, history of diabetes mellitus (DM), and renal function (estimated glomerular filtration rate [eGFR]). The HBP group included HBP/+DM and HBP/-DM based on the presence or absence of DM. The CT-based RSN grade was scored from 0 to 2 by two radiologists, respectively, where RSN grade 0 indicated smooth renal surface, grade 1 was mild RSN, and grade 2 was marked RSN. RESULTS: The inter-rater agreement on RSN was good (Kappa = 0.76). The age-specific rate of RSN grade 1-2 was bigger in the HBP group than in the control group (42.86% [40%-49.22%] vs. 2.18% [0.00%-22.5%]; P = 0.005). RSN grade was associated with HBP course (P < 0.02). The rates of RSN grade 1-2 and of RSN grade 2 were bigger in the HBP/+DM group than those in the HBP/-DM group (48.84% vs. 37.84%, and 18.61% vs. 1.35%, respectively; all P = 0.001). Neither HBP course nor HBP grade correlated with rate of RSN grade (P > 0.05). The eGFR was similar among the RSN grades in HBP or between the HBP and control groups (P > 0.05). CONCLUSION: RSN was associated with HBP compared to normotensive patients.

Application of nanotechnology in the early diagnosis and comprehensive treatment of gastrointestinal cancer.

Gastrointestinal cancer (GIC) is a common malignant tumour of the digestive system that seriously threatens human health. Due to the unique organ structure of the gastrointestinal tract, endoscopic and MRI diagnoses of GIC in the clinic share the problem of low sensitivity. The ineffectiveness of drugs and high recurrence rates in surgical and drug therapies are the main factors that impact the curative effect in GIC patients. Therefore, there is an urgent need to improve diagnostic accuracies and treatment efficiencies. Nanotechnology is widely used in the diagnosis and treatment of GIC by virtue of its unique size advantages and extensive modifiability. In the diagnosis and treatment of clinical GIC, surface-enhanced Raman scattering (SERS) nanoparticles, electrochemical nanobiosensors and magnetic nanoparticles, intraoperative imaging nanoparticles, drug delivery systems and other multifunctional nanoparticles have successfully improved the diagnosis and treatment of GIC. It is important to further improve the coordinated development of nanotechnology and GIC diagnosis and treatment. Herein, starting from the clinical diagnosis and treatment of GIC, this review summarizes which nanotechnologies have been applied in clinical diagnosis and treatment of GIC in recent years, and which cannot be applied in clinical practice. We also point out which challenges must be overcome by nanotechnology in the development of the clinical diagnosis and treatment of GIC and discuss how to quickly and safely combine the latest nanotechnology developed in the laboratory with clinical applications. Finally, we hope that this review can provide valuable reference information for researchers who are conducting cross-research on GIC and nanotechnology.

Duhuo Jisheng Decoction inhibits the activity of osteoclasts in osteonecrosis of the femoral head via regulation of the RELA/AKT1 axis.

OBJECTIVE: To investigate the effect of Duhuo Jisheng Decotion (DHJSD) on the activity of osteoclasts in osteonecrosis of the femoral head (ONFH) and its underlying mechanism relating to the RELA/AKT1 axis. METHODS: The TCMSP database was used to search for the effective ingredients and the targets of various Chinese medicines in DHJSD. Its targets were intersected with ONFH risk genes in DisGeNET and Malacards databases to obtain the potential target genes. qRT-PCR was used to detect the expression of potential target genes in ONFH tissues, and the ChIP experiment was used to verify the relationship between RELA and AKT1 promoter. An ONFH rat model was established and DHJSD was used for the treatment. The expressions of RELA and AKT1 in rats were intervened, and rats were grouped. qRT-PCR was applied to detect the expression levels of osteoclast markers ACP5, CTSK, and RANK in the tissues to evaluate the regulation of DHJSD on target genes and the mechanism of osteoclast differentiation. RESULTS: A total of 231 effective targets of DHJSD were screened out in the TCMSP database. Intersection with ONFH risk genes yielded a total of 20 candidate genes. Protein-protein interaction analysis showed that AKT1 regulated other genes. KEGG functional enrichment analysis revealed that STAT1, AKT1, PPARG, PPARG, TNF and RELA were enriched in osteoclast differentiation pathway. Compared with normal tissues, the expression of STAT1 was decreased in ONFH tissues, and the expressions of AKT1, PPARG, TNF, and RELA were increased, among which, RELA and AKT1 are the most significantly increased genes (all P<0.05). ChIP experiment found that RELA had a binding relationship with AKT1 promoter. DHJST had the inhibitory effect on the expression of RELA and AKT1 in ONFH tissues, as well as the levels of ACP5, CTSK, and RANK. However, overexpression of RELA or AKT1 attenuated the inhibitory effect of DHJSD on the levels of ACP5, CTSK and RANK. Meanwhile, knocking down RELA partially reversed the effect of AKT1 on the effect of DHJSD. CONCLUSION: DHJSD inhibits the activity of osteoclasts in ONFH by inhibiting the RELA/AKT1 axis. This study further clarifies the potential specific mechanism of DHJSD to improve ONFH.

Development and validation of a prognostic scoring system for patients with colorectal cancer hepato-pulmonary metastasis: a retrospective study.

BACKGROUND: Hepato-pulmonary metastasis of colorectal cancer (CRC) is a rare disease with poor prognosis. This study aims to establish a highly efficient nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with colorectal cancer hepato-pulmonary metastasis (CRCHPM). METHODS: We retrospectively analyzed the data of patients with CRCHPM from SEER database and Wuhan Union Hospital Cancer Center (WUHCC). A total of 1250 CRCHPM patients were randomly assigned to the training, internal validation, and external validation cohorts from 2010 to 2016.Univariate and multivariate cox analysis were performed to identify independent clinicopathological predictors of OS and CSS, and a nomogram was constructed to predict OS and CSS in CRCHPM patients. RESULTS: A nomogram of OS was constructed based on seven independent predictors of age, degree of differentiation, T stage, chemotherapy, number of lsampled lymph nodes, number of positive lymph nodes, and tumor size. Nomogram showed favorable sensitivity in predicting OS at 1, 3 and 5 years, with area under the receiver operating characteristic curve (AUROC) values of 0.802, 0.759 and 0.752 in the training cohort;0.814, 0.769 and 0.716 in the internal validation cohort;0.778, 0.756 and 0.753 in the external validation cohort, respectively. A nomogram of CSS was constructed based on three independent predictors of T stage, chemotherapy, and tumor size. The AUROC values of 1, 3 and 5 years were 0.709,0.588,0.686 in the training cohort; 0.751, 0.648,0.666 in the internal validation cohort;0.781,0.588,0.645 in the external validation cohort, respectively. Calibration curves, Concordance index (C-index), and decision curve analysis (DCA) results revealed that using our model to predict OS and CSS is more efficient than other single clinicopathological characteristics. CONCLUSION: A nomogram of OS and CSS based on clinicopathological characteristics can be conveniently used to predict the prognosis of CRCHPM patients.

miR-100 alleviates the inflammatory damage and apoptosis of H2O2-induced human umbilical vein endothelial cells via inactivation of Notch signaling by targeting MMP9.

OBJECTIVE: Thromboangiitis obliterans is a nonatherosclerotic segmental inflammatory disease, and miR-100 plays an anti-inflammatory role in chronic inflammation. Therefore, we hypothesized that miR-100 might alleviate the inflammatory damage and apoptosis of H2O2-induced ECV304 cells and aimed to investigate the relationship between miR-100 and thromboangiitis obliterans and the related molecular mechanism. METHODS: Cell counting kit-8 was used to detect cell viability, and the expression of inflammatory factors and oxidative stress was measured by ELISA. TUNEL assay was used to detect the apoptosis of human umbilical vein endothelial cells after induction by H2O2. Furthermore, the interaction between miR-100 and matrix metalloproteinase-9 was verified by dual-luciferase assay. Quantitative reverse transcription polymerase chain reaction and western blot were used to detect the expression of the adhesion factors, apoptosis-related proteins and Notch pathway-related protein. RESULTS: The results revealed that miR-100 was decreased in H2O2-induced human umbilical vein endothelial cells. Overexpression of miR-100 attenuated inflammatory response and cell apoptosis in H2O2-induced human umbilical vein endothelial cells. The overexpression of miR-100 inhibited matrix metalloproteinase-9 expression in H2O2-induced human umbilical vein endothelial cells. miR-100 inhibited H2O2-induced human umbilical vein endothelial cell inflammation, oxidative stress, and cell apoptosis via inactivation of Notch signaling by targeting matrix metalloproteinase. CONCLUSIONS: Our study demonstrated that miR-100 reduced the inflammatory damage and apoptosis of H2O2-induced human umbilical vein endothelial cells via inactivation of Notch signaling by targeting matrix metalloproteinase. These findings suggested that miR-100 might be a novel therapeutic target for the prevention of thromboangiitis obliterans.

Application of dual-stream 3D convolutional neural network based on 18F-FDG PET/CT in distinguishing benign and invasive adenocarcinoma in ground-glass lung nodules.

PURPOSE: This work aims to train, validate, and test a dual-stream three-dimensional convolutional neural network (3D-CNN) based on fluorine 18 (18F)-fluorodeoxyglucose (FDG) PET/CT to distinguish benign lesions and invasive adenocarcinoma (IAC) in ground-glass nodules (GGNs). METHODS: We retrospectively analyzed patients with suspicious GGNs who underwent 18F-FDG PET/CT in our hospital from November 2011 to November 2020. The patients with benign lesions or IAC were selected for this study. According to the ratio of 7:3, the data were randomly divided into training data and testing data. Partial image feature extraction software was used to segment PET and CT images, and the training data after using the data augmentation were used for the training and validation (fivefold cross-validation) of the three CNNs (PET, CT, and PET/CT networks). RESULTS: A total of 23 benign nodules and 92 IAC nodules from 106 patients were included in this study. In the training set, the performance of PET network (accuracy, sensitivity, and specificity of 0.92 ± 0.02, 0.97 ± 0.03, and 0.76 ± 0.15) was better than the CT network (accuracy, sensitivity, and specificity of 0.84 ± 0.03, 0.90 ± 0.07, and 0.62 ± 0.16) (especially accuracy was significant, P-value was 0.001); in the testing set, the performance of both networks declined. However, the accuracy and sensitivity of PET network were still higher than that of CT network (0.76 vs. 0.67; 0.85 vs. 0.70). For dual-stream PET/CT network, its performance was almost the same as PET network in the training set (P-value was 0.372-1.000), while in the testing set, although its performance decreased, the accuracy and sensitivity (0.85 and 0.96) were still higher than both CT and PET networks. Moreover, the accuracy of PET/CT network was higher than two nuclear medicine physicians [physician 1 (3-year experience): 0.70 and physician 2 (10-year experience): 0.73]. CONCLUSION: The 3D-CNN based on 18F-FDG PET/CT can be used to distinguish benign lesions and IAC in GGNs, and the performance is better when both CT and PET images are used together.

Investigating the association between ground-glass nodules glucose metabolism and the invasive growth pattern of early lung adenocarcinoma.

BACKGROUND: To explore the association between the glucose metabolism level of lung ground-glass nodules (GGNs), as revealed by 18F-flurodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) imaging, and the invasive pathological growth pattern of early lung adenocarcinoma. METHODS: We retrospectively analyzed patients who underwent PET/CT examination and surgical resection due to persistent GGNs, which were confirmed to be early lung adenocarcinoma by postoperative pathology examination. After adjusting for confounding factors and performing stratified analysis, we explored the association between the maximum standard uptake value of PET (SUVmax) and the invasive pathological growth pattern of early stage lung adenocarcinoma. RESULTS: The proportions of invasive adenocarcinoma (INV) in the SUVmax of Tertile 1, Tertile 2, and Tertile 3 were 52.7%, 73.3%, and 87.1%, respectively. After adjusting for potential confounding factors, the risk of INV gradually increased as the GGN SUVmax increased [odds ratio (OR): 1.520, 95% confidence interval (CI): 1.044-2.213, P=0.029]. This trend was statistically significant (OR: 1.678, 95% CI: 1.064-2.647, P=0.026), especially in Tertile 3 vs. Tertile 1 (OR: 4.879, 95% CI: 1.349-17.648, P=0.016). Curve fitting showed that the SUVmax and INV risk were linearly and positively associated. The association was consistent in different subgroups based on GGN number, type, shape, edge, bronchial sign, vacuole sign, pleural depression sign, diameters, and consolidation-to-tumor ratio, suggesting that there was no significant interaction between different grouping parameters and the association (P for interaction range = 0.129-0.909). CONCLUSIONS: In FDG PET, the glucose metabolism level (SUVmax) of lung GGNs is independently associated with INV risk, and this association is linear and positive.