Collaborative Human-Computer Vision Operative Video Analysis Algorithm for Analyzing Surgical Fluency and Surgical Interruptions in Endonasal Endoscopic Pituitary Surgery: Cohort Study.

BACKGROUND: The endonasal endoscopic approach (EEA) is effective for pituitary adenoma resection. However, manual review of operative videos is time-consuming. The application of a computer vision (CV) algorithm could potentially reduce the time required for operative video review and facilitate the training of surgeons to overcome the learning curve of EEA. OBJECTIVE: This study aimed to evaluate the performance of a CV-based video analysis system, based on OpenCV algorithm, to detect surgical interruptions and analyze surgical fluency in EEA. The accuracy of the CV-based video analysis was investigated, and the time required for operative video review using CV-based analysis was compared to that of manual review. METHODS: The dominant color of each frame in the EEA video was determined using OpenCV. We developed an algorithm to identify events of surgical interruption if the alterations in the dominant color pixels reached certain thresholds. The thresholds were determined by training the current algorithm using EEA videos. The accuracy of the CV analysis was determined by manual review, and the time spent was reported. RESULTS: A total of 46 EEA operative videos were analyzed, with 93.6%, 95.1%, and 93.3% accuracies in the training, test 1, and test 2 data sets, respectively. Compared with manual review, CV-based analysis reduced the time required for operative video review by 86% (manual review: 166.8 and CV analysis: 22.6 minutes; P<.001). The application of a human-computer collaborative strategy increased the overall accuracy to 98.5%, with a 74% reduction in the review time (manual review: 166.8 and human-CV collaboration: 43.4 minutes; P<.001). Analysis of the different surgical phases showed that the sellar phase had the lowest frequency (nasal phase: 14.9, sphenoidal phase: 15.9, and sellar phase: 4.9 interruptions/10 minutes; P<.001) and duration (nasal phase: 67.4, sphenoidal phase: 77.9, and sellar phase: 31.1 seconds/10 minutes; P<.001) of surgical interruptions. A comparison of the early and late EEA videos showed that increased surgical experience was associated with a decreased number (early: 4.9 and late: 2.9 interruptions/10 minutes; P=.03) and duration (early: 41.1 and late: 19.8 seconds/10 minutes; P=.02) of surgical interruptions during the sellar phase. CONCLUSIONS: CV-based analysis had a 93% to 98% accuracy in detecting the number, frequency, and duration of surgical interruptions occurring during EEA. Moreover, CV-based analysis reduced the time required to analyze the surgical fluency in EEA videos compared to manual review. The application of CV can facilitate the training of surgeons to overcome the learning curve of endoscopic skull base surgery. TRIAL REGISTRATION: ClinicalTrials.gov NCT06156020; https://clinicaltrials.gov/study/NCT06156020.

Protective effects of paeonol against cognitive impairment in lung diseases.

Pulmonary inflammation may lead to neuroinflammation resulting in neurological dysfunction, and it is associated with a variety of acute and chronic lung diseases. Paeonol is a herbal phenolic compound with anti-inflammatory and anti-oxidative properties. The aim of this study is to understand the beneficial effects of paeonol on cognitive impairment, pulmonary inflammation and its underlying mechanisms. Pulmonary inflammation-associated cognitive deficit was observed in TNFα-stimulated mice, and paeonol mitigated the cognitive impairment by reducing the expressions of interleukin (IL)-1ß, IL-6, and NOD-like receptor family pyrin domain-containing 3 (NLRP3) in hippocampus. Moreover, elevated plasma miR-34c-5p in lung-inflamed mice was also reduced by paeonol. Pulmonary inflammation induced by intratracheal instillation of TNFα in mice resulted in immune cells infiltration in bronchoalveolar lavage fluid, pulmonary edema, and acute fibrosis, and these inflammatory responses were alleviated by paeonol orally. In MH-S alveolar macrophages, tumor necrosis factor (TNF) α- and phorbol myristate acetate (PMA)-induced inflammasome activation was ameliorated by paeonol. In addition, the expressions of antioxidants were elevated by paeonol, and reactive oxygen species production was reduced. In this study, paeonol demonstrates protective effects against cognitive deficits and pulmonary inflammation by exerting anti-inflammatory and anti-oxidative properties, suggesting a powerful benefit as a potential therapeutic agent.

LPS priming-induced immune tolerance mitigates LPS-stimulated microglial activation and social avoidance behaviors in mice.

In this study, we investigated the regulatory mechanisms underlying the effects of LPS tolerance on the inflammatory homeostasis of immune cells. LPS priming-induced immune tolerance downregulated cyclooxygenase-2, and lowered the production of prostaglandin-E2 in microglial cells. In addition, LPS tolerance downregulated the expression of suppressor of cytokine signaling 3, and inducible nitric oxide synthase/nitric oxide; suppressed the LPS-mediated induction of tumor necrosis factor-α, interleukin (IL)-6, and IL-1; and reduced reactive oxygen species production in microglial cells. LPS stimulation increased the levels of the adaptive response-related proteins heme oxygenase-1 and superoxide dismutase 2, and the levels of heme oxygenase-1 (HO-1) enhanced after LPS priming. Systemic administration of low-dose LPS (0.5 mg/kg) to mice for 4 consecutive days attenuated high-dose LPS (5 mg/kg)-induced inflammatory response, microglial activation, and proinflammatory cytokine expression. Moreover, repeated exposure to low-dose LPS suppressed the recruitment of peripheral monocytes or macrophages to brain regions and downregulated the expression of proinflammatory cytokines. Notably, LPS-induced social avoidance behaviors in mice were mitigated by immune tolerance. In conclusion, immune tolerance may reduce proinflammatory cytokine expression and reactive oxygen species production. Our findings provide insights into the effects of endotoxin tolerance on innate immune cells and social behaviors.

Inhibition of tumor migration and invasion by fenofibrate via suppressing epithelial-mesenchymal transition in breast cancers.

The recurrence and metastasis in breast cancer within 3 years after the chemotherapies or surgery leads to poor prognosis with approximately 1-year overall survival. Large-scale scanning research studies have shown that taking lipid-lowering drugs may assist to reduce the risk of death from many cancers, since cholesterol in lipid rafts are essential for maintain integral membrane structure and functional signaling regulation. In this study, we examined five lipid-lowering drugs: swertiamarin, gemfibrozil, clofibrate, bezafibrate, and fenofibrate in triple-negative breast cancer, which is the most migration-prone subtype. Using human and murine triple-negative breast cancer cell lines (Hs 578 t and 4 T1), we found that fenofibrate displays the highest potential in inhibiting the colony formation, wound healing, and transwell migration. We further discovered that fenofibrate reduces the activity of pro-metastatic enzymes, matrix metalloproteinases (MMP)-9 and MMP-2. In addition, epithelial markers including E-cadherin and Zonula occludens-1 are increased, whereas mesenchymal markers including Snail, Twist and α-smooth muscle actin are attenuated. Furthermore, we found that fenofibrate downregulates ubiquitin-dependent GDF-15 degradation, which leads to enhanced GDF-15 expression that inhibits cell migration. Besides, nuclear translocation of FOXO1 is also upregulated by fenofibrate, which may responsible for GDF-15 expression. In summary, fenofibrate with anti-cancer ability hinders TNBC from migration and invasion, and may be beneficial to repurposing use of fenofibrate.

Preclinical trial of targeting the Hic-5-mediated pathway to prevent the progression of hepatocellular carcinoma.

The poor prognosis of hepatocellular carcinoma (HCC) was ascribed to metastasis. Targeted therapy aiming at the molecules along the metastatic pathway is a promising therapeutic strategy. Among them, hydrogen peroxide inducible clone-5 (Hic-5) is highlighted. Hic-5, discovered as a reactive oxygen species (ROS)-inducible gene, was identified to be an adaptor protein in focal adhesion and a critical signaling mediator upregulated in various cancers including HCC. Moreover, Hic-5 may regulate epithelial-mesenchymal transition (EMT) transcription factor Snail and its downstream mesenchymal genes including fibronectin and matrix metalloproteinase-9 required for migration and invasion of HCC. However, the comprehensive Hic-5-mediated pathway was not established and whether Hic-5 can be a target for preventing HCC progression has not been validated in vivo. Using whole-transcriptome mRNA sequencing, we found reactive oxygen species modulator (ROMO) and ZNF395 were upregulated by Hic-5 in a patient-derived HCC cell line, HCC372. Whereas ROMO was involved in Hic-5-mediated ROS signaling, ZNF395 locates downstream of Snail for mesenchymal genes expression required for cell migration. Also, ZNF395 but not ROMO was upregulated by Hic-5 for migration in another patient-derived HCC cell line, HCC374. Further, by in vivo knock down of Hic-5 using the Stable Nucleic Acids Lipid nanoparticles (SNALP)-carried Hic-5 siRNA, progression of HCC372 and HCC374 in SCID mice was prevented, coupled with the decrease of the downstream mesenchymal genes. Our study provides the preclinical evidence that targeting Hic-5 is potentially able to prevent the progression of HCCs with Hic-5 overexpression.

A comparison of 18 F-FDG PET-based radiomics and deep learning in predicting regional lymph node metastasis in patients with resectable lung adenocarcinoma: a cross-scanner and temporal validation study.

OBJECTIVE: The performance of 18 F-FDG PET-based radiomics and deep learning in detecting pathological regional nodal metastasis (pN+) in resectable lung adenocarcinoma varies, and their use across different generations of PET machines has not been thoroughly investigated. We compared handcrafted radiomics and deep learning using different PET scanners to predict pN+ in resectable lung adenocarcinoma. METHODS: We retrospectively analyzed pretreatment 18 F-FDG PET from 148 lung adenocarcinoma patients who underwent curative surgery. Patients were separated into analog (n = 131) and digital (n = 17) PET cohorts. Handcrafted radiomics and a ResNet-50 deep-learning model of the primary tumor were used to predict pN+ status. Models were trained in the analog PET cohort, and the digital PET cohort was used for cross-scanner validation. RESULTS: In the analog PET cohort, entropy, a handcrafted radiomics, independently predicted pN+. However, the areas under the receiver-operating-characteristic curves (AUCs) and accuracy for entropy were only 0.676 and 62.6%, respectively. The ResNet-50 model demonstrated a better AUC and accuracy of 0.929 and 94.7%, respectively. In the digital PET validation cohort, the ResNet-50 model also demonstrated better AUC (0.871 versus 0.697) and accuracy (88.2% versus 64.7%) than entropy. The ResNet-50 model achieved comparable specificity to visual interpretation but with superior sensitivity (83.3% versus 66.7%) in the digital PET cohort. CONCLUSION: Applying deep learning across different generations of PET scanners may be feasible and better predict pN+ than handcrafted radiomics. Deep learning may complement visual interpretation and facilitate tailored therapeutic strategies for resectable lung adenocarcinoma.

Reducing abnormal expenses in national health insurance based on a control chart and decision tree-driven define, measure, analyze, improve and control process.

This study examined the cost of medical insurance for "sepsis" treatment in Taiwan. We applied statistical tests, cost control charts, and C5.0 decision trees using the define, measure, analyze, improve and control (DMAIC) process to mine data on Diagnosis-Related Groups (DRGs) and clinics that reported expense anomalies and disposal costs. Analyzing 353 valid samples (application fees) from four DRGs, 70 clinics, and 15 input variables, abnormalities in application fees for adults (age ≧18 years old) with comorbidities or complications was significant (95% confidence interval) in one DRG and nine clinics. Four input variables (ward charge, treatment fee, laboratory fee, and pharmaceutical service charge) had a significant impact. Improvements or controls should be prioritized for three clinics (Nos. 49, 44, and 14) and two input variables (treatment and laboratory fees). This model can be replicated to ascertain excess medical expenditures and improve the efficiency of medical resource use.

Genomic and Glycolytic Entropy Are Reliable Radiogenomic Heterogeneity Biomarkers for Non-Small Cell Lung Cancer.

Radiogenomic heterogeneity features in 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) have become popular in non-small cell lung cancer (NSCLC) research. However, the reliabilities of genomic heterogeneity features and of PET-based glycolytic features in different image matrix sizes have yet to be thoroughly tested. We conducted a prospective study with 46 NSCLC patients to assess the intra-class correlation coefficient (ICC) of different genomic heterogeneity features. We also tested the ICC of PET-based heterogeneity features from different image matrix sizes. The association of radiogenomic features with clinical data was also examined. The entropy-based genomic heterogeneity feature (ICC = 0.736) is more reliable than the median-based feature (ICC = -0.416). The PET-based glycolytic entropy was insensitive to image matrix size change (ICC = 0.958) and remained reliable in tumors with a metabolic volume of <10 mL (ICC = 0.894). The glycolytic entropy is also significantly associated with advanced cancer stages (p = 0.011). We conclude that the entropy-based radiogenomic features are reliable and may serve as ideal biomarkers for research and further clinical use for NSCLC.

Glucose metabolic heterogeneity correlates with pathological features and improves survival stratification of resectable lung adenocarcinoma.

OBJECTIVE: We investigated whether glycolytic heterogeneity correlated with histopathology, and further stratified the survival outcomes pertaining to resectable lung adenocarcinoma. METHODS: We retrospectively analyzed the 18F-fluorodeoxyglucose positron emission tomography-derived entropy and histopathology from 128 patients who had undergone curative surgery for lung adenocarcinoma. Disease-free survival (DFS) and overall survival (OS) were analyzed using univariate and multivariate Cox regression models. Independent predictors were used to construct survival prediction models. RESULTS: Entropy significantly correlated with histopathology, including tumor grades, lympho-vascular invasion, and visceral pleural invasion. Furthermore, entropy was an independent predictor of unfavorable DFS (p = 0.031) and OS (p = 0.004), while pathological nodal metastasis independently predicted DFS (p = 0.009). Our entropy-based models outperformed the traditional staging system (c-index = 0.694 versus 0.636, p = 0.010 for DFS; c-index = 0.704 versus 0.630, p = 0.233 for OS). The models provided further survival stratification in subgroups comprising different tumor grades (DFS: HR = 2.065, 1.315, and 1.408 for grade 1-3, p = 0.004, 0.001, and 0.039, respectively; OS: HR = 25.557, 6.484, and 2.570, for grade 1-3, p = 0.006, < 0.001, and = 0.224, respectively). CONCLUSION: The glycolytic heterogeneity portrayed by entropy is associated with aggressive histopathological characteristics. The proposed entropy-based models may provide more sophisticated survival stratification in addition to histopathology and may enable personalized treatment strategies for resectable lung cancer.

Suppressing of Src-Hic-5-JNK-AKT Signaling Reduced GAPDH Expression for Preventing the Progression of HuCCT1 Cholangiocarcinoma.

Cholangiocarcinoma (CCA) is a malignant neoplasm of the bile ducts, being the second most common type of cancer in the liver, and most patients are diagnosed at a late stage with poor prognosis. Targeted therapy aiming at receptors tyrosine kinases (RTKs) such as c-Met or EGFR have been developed but with unsatisfactory outcomes. In our recent report, we found several oncogenic molecules downstream of RTKs, including hydrogen peroxide clone-5 (Hic-5), Src, AKT and JNK, were elevated in tissues of a significant portion of metastatic CCAs. By inhibitor studies and a knockdown approach, these molecules were found to be within the same signal cascade responsible for the migration of HuCCT1 cells, a conventionally used CCA cell line. Herein, we also found Src inhibitor dasatinib and Hic-5 siRNA corporately suppressed HuCCT1 cell invasion. Moreover, dasatinib inhibited the progression of the HuCCT1 tumor on SCID mice skin coupled with decreasing the expression of Hic-5 and EGFR and the activities of Src, AKT and JNK. In addition, we found a glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and several cytoskeletal molecules such as tubulin and cofilin were dramatically decreased after a long-term treatment of the HuCCT1 tumor with a high dose of dasatinib. Specifically, GAPDH was shown to be a downstream effector of the Hic-5/Src/AKT cascade involved in HuCCT1 cell migration. On the other hand, TFK1, another CCA cell line without Hic-5 expression, exhibited very low motility, whereas an ectopic Hic-5 expression enhanced the activation of Src and AKT and marginally increased TFK1 migration. In the future, it is tempting to investigate whether cotargeting Src, Hic-5 and/or GAPDH is efficient for preventing CCA progression in future clinical trials.

Diltiazem inhibits breast cancer metastasis via mediating growth differentiation factor 15 and epithelial-mesenchymal transition.

Migration and metastasis commonly happen to triple-negative breast cancer (TNBC) patients with advanced diseases. In many studies, it has been suggested that epithelial-mesenchymal transition (EMT) is one of the key mechanisms triggering cancer metastasis. Accumulating evidence has proven that calcium channel blockers mediate cell motility. Therefore, we attempt to investigate the effects of diltiazem, which has been selected from several FDA-approved clinical calcium channel blockers, on EMT in TNBC. By using both mouse and human TNBC cell lines, we found that diltiazem decreases colony formation and cell migration in breast cancer cells. The expression of epithelial markers such as E-cadherin and ZO-1 were increased dose-dependently by diltiazem, while mesenchymal markers such as Snail and Twist were decreased. In addition, we found that the expression of growth differentiation factor-15 (GDF-15) was also increased by diltiazem. Administering recombinant GDF-15 also reverses EMT, inhibits colony formation and migration in breast cancer cells. Moreover, treatment with diltiazem in tumor-bearing mice also decreases cancer metastasis and nodule formation, with more GDF-15 expression in diltiazem-treated mice than saline-treated mice, respectively. These findings suggest that diltiazem regulates EMT and cell motility through elevating GDF-15 expression in breast cancers in vitro and in vivo.

Association between Pre-Existing Sleep Disorders and Survival Rates of Patients with Breast Cancer.

PURPOSE: To investigate the effects of pre-existing sleep disorders on the survival outcomes of women receiving standard treatments for breast invasive ductal carcinoma (IDC). METHODS: We recruited patients from the Taiwan Cancer Registry Database who had received surgery for clinical stage I-III breast IDC. The Cox proportional hazards model was used to analyze all-cause mortality. We categorized the patients into those with and without sleep disorders (Groups 1 and 2, respectively) through propensity score matching. RESULTS: In the multivariate Cox regression analysis, the adjusted hazard ratio for all-cause mortality for Group 1 compared with Group 2 was 1.51 (95% confidence interval: 1.19, 1.91; p < 0.001). CONCLUSION: Our study demonstrated that the sleep disorder group had poorer survival rates than the non-sleep disorder group in breast cancer. Therefore, patients should be screened and evaluated for pre-existing sleep disorders prior to breast surgery, with such disorders serving as a predictor of survival in patients with breast cancer. Future studies may investigate the survival benefits of pharmacological and behavioral treatments for sleep problems in patients with breast cancer.

Tumor glycolytic heterogeneity improves detection of regional nodal metastasis in patients with lung adenocarcinoma.

OBJECTIVE: The diagnostic performance of 18F-FDG PET for detecting regional lymph node metastasis in resectable lung cancer is variable, and its sensitivity for adenocarcinoma is even lower. We aimed to evaluate the value of 18F-FDG PET-derived features in predicting pathological lymph node metastasis in patients with lung adenocarcinoma. METHODS: We retrospectively analyzed pretreatment 18F-FDG PET-derived features of 126 lung adenocarcinoma patients who underwent curative surgery. A logistic regression model was used to analyze the association between study variables and pathological regional lymph node status obtained from the curative surgery. Furthermore, Cox regression analysis was used to test the effect of the study variables on survival outcomes, including disease-free survival (DFS) and overall survival (OS). RESULTS: The primary tumor entropy (OR = 1.7, p = 0.014) and visual interpretation of regional nodes via 18F-FDG PET (OR = 2.5, p = 0.026) independently predicted pathological regional lymph node metastasis. The areas under the receiver-operating-characteristic curves were 0.631, 0.671, and 0.711 for visual interpretation, primary tumor entropy, and their combination, respectively. Based on visual interpretation, a primary tumor entropy ≥ 3.0 improved the positive predictive value of positive visual interpretation from 51.2% to 63.0%, whereas an entropy < 3.0 improved the negative predictive value of negative visual interpretation from 75.3% to 82.6%. In cases with positive visual interpretation and low entropy, or negative visual interpretation and high entropy, the nodal metastasis rates were approximately 30%. In the survival analyses, the primary tumor entropy was also independently associated with DFS (HR = 2.7, p = 0.001) and OS (HR = 4.8, p = 0.001). CONCLUSIONS: Our preliminary results show that the primary tumor entropy may improve 18F-FDG PET visual interpretation in predicting pathological nodal metastasis in lung adenocarcinoma, and may also show a survival prognostic value. This versatile biomarker may facilitate tailored therapeutic strategies for patients with resectable lung adenocarcinoma.