Enhancer of zeste homolog 2 (EZH2) is the catalytic subunit of polycomb repressive complex 2 (PRC2). Dysregulation of EZH2 causes alteration of gene expression and functions, thereby promoting cancer ...development. The regulatory function of EZH2 varies across different tumor types. The canonical role of EZH2 is gene silencing through catalyzing the trimethylation of lysine 27 of histone H3 (H3K27me3) in a PRC2‐dependent manner. Accumulating evidence indicates that EZH2 has an H3K27me3‐independent function as a transcriptional coactivator and plays a critical role in cancer initiation, development, and progression. In this review, we summarize the regulation and function of EZH2 and focus on the current understanding of the noncanonical role of EZH2 in cancer.
In this review, we summarize the regulation and function of EZH2 and focus on the current understanding of the noncanonical role of EZH2 in cancer.
Background
We attempted to train and validate a model of deep learning for the preoperative prediction of the response of patients with intermediate-stage hepatocellular carcinoma (HCC) undergoing ...transarterial chemoembolization (TACE).
Method
All computed tomography (CT) images were acquired for 562 patients from the Nan Fang Hospital (NFH), 89 patients from Zhu Hai Hospital Affiliated with Jinan University (ZHHAJU), and 138 patients from the Sun Yat-sen University Cancer Center (SYUCC). We built a predictive model from the outputs using the transfer learning techniques of a residual convolutional neural network (ResNet50). The prediction accuracy for each patch was revaluated in two independent validation cohorts.
Results
In the training set (NFH), the deep learning model had an accuracy of 84.3% and areas under curves (AUCs) of 0.97, 0.96, 0.95, and 0.96 for complete response (CR), partial response (PR), stable disease (SD), and progressive disease (PD), respectively. In the other two validation sets (ZHHAJU and SYUCC), the deep learning model had accuracies of 85.1% and 82.8% for CR, PR, SD, and PD. The ResNet50 model also had high AUCs for predicting the objective response of TACE therapy in patches and patients of three cohorts. Decision curve analysis (DCA) showed that the ResNet50 model had a high net benefit in the two validation cohorts.
Conclusion
The deep learning model presented a good performance for predicting the response of TACE therapy and could help clinicians in better screening patients with HCC who can benefit from the interventional treatment.
Key Points
• Therapy response of TACE can be predicted by a deep learning model based on CT images.
• The probability value from a trained or validation deep learning model showed significant correlation with different therapy responses.
• Further improvement is necessary before clinical utilization.
We aimed to develop radiology-based models for the preoperative prediction of the initial treatment response to transarterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC) ...since the integration of radiomics and deep learning (DL) has not been reported for TACE.
Three hundred and ten intermediate-stage HCC patients who underwent TACE were recruited from three independent medical centers. Based on computed tomography (CT) images, recursive feature elimination (RFE) was used to select the most useful radiomics features. Five radiomics conventional machine learning (cML) models and a DL model were used for training and validation. Mutual correlations between each model were analyzed. The accuracies of integrating clinical variables, cML, and DL models were then evaluated.
Good predictive accuracies were showed across the two cohorts in the five cML models, especially the random forest algorithm (AUC = 0.967 and 0.964, respectively). DL showed high accuracies in the training and validation cohorts (AUC = 0.981 and 0.972, respectively). Significant mutual correlations were revealed between tumor size and the five cML models and DL model (each
< 0.001). The highest accuracies were achieved by integrating DL and the random forest algorithm in the training and validation cohorts (AUC = 0.995 and 0.994, respectively).
The radiomics cML models and DL model showed notable accuracy for predicting the initial response to TACE treatment. Moreover, the integrated model could serve as a novel and accurate method for prediction in intermediate-stage HCC.
Summary
Introduction
Diabetic nephropathy (DN) is a common complication in diabetics. Recent evidence suggests that neutrophil–lymphocyte ratio (NLR) affects the development and acceleration of some ...diabetic complications. Scholars have rarely investigated the relationship between DN and NLR. This study aims to evaluate the relationship between DN and NLR and estimate whether or not NLR is a reliable marker for early‐stage DN.
Patients and methods
The study included 253 patients with type 2 diabetes mellitus, 115 of whom have early‐stage DN. The control group was composed of 210 healthy age‐ and sex‐matched subjects.
Results
The NLR values of the patients with diabetes were significantly higher than those of the healthy controls (P < 0·001), and the NLR values of the patients with early‐stage DN were higher than those of the patients without DN (P < 0·001). Logistic regression analysis showed that the risk predictors of DN include NLR, creatinine, total cholesterol, systolic blood pressure, HbA1c and insulin resistance. NLR (P = 0·004, EXP(B) = 2·088, 95% CI = 1·271–3·429) levels positively correlated with DN. The DN odds ratio increased by a factor of 2·088 (95% CI, 1·271–3·429) for every one unit increase in NLR.
Conclusions
Increased NLR was significantly associated with DN, and high NLR values may be a reliable predictive marker of early‐stage DN.
Lithium metal is considered a promising anode material for lithium secondary batteries by virtue of its ultra-high theoretical specific capacity, low redox potential, and low density, while the ...application of lithium is still challenging due to its high activity. Lithium metal easily reacts with the electrolyte during the cycling process, resulting in the continuous rupture and reconstruction of the formed SEI layer, which reduces the cycling reversibility. On the other hand, repeated lithium plating/stripping processes can lead to uncontrolled growth of lithium dendrites and a series of safety issues caused by short-circuiting of the battery. Currently, modification of the battery separator layer is a good strategy to inhibit lithium dendrite growth, which can improve the Coulombic efficiency in the cycle. This paper reviews the preparation, behavior, and mechanism of the modified coatings using metals, metal oxides, nitrides, and other materials on the separator to inhibit the formation of lithium dendrites and achieve better stable electrochemical cycles. Finally, further strategies to inhibit lithium dendrite growth are proposed.
Current study aims to determine the prognostic value of Multiparameter MRI after combined Lenvatinib and TACE therapy in patients with advanced unresectable hepatocellular carcinoma (HCC).
A total of ...61 HCC patients with pre-treatment Multiparameter MRI in Sun Yat-sen University Cancer Center from January 2019 to March 2021 were recruited in the current study. All patients received combined Lenvatinib and TACE treatment. Potential clinical and imaging risk factors for disease progression were analyzed using Cox regression model. Each patient extracts signs from the following 7 sequences: T1WI, T1WI arterial phase, T1WI portal phase, T1WI delay phase, T2WI, DWI (b = 800), ADC.1782 quantitative 3D radiomic features were extracted for each sequence, A random forest algorithm is used to select the first 20 features by feature importance. 7 logit regression-based prediction model was built for seven sequences based on the selected features and fivefold cross validation was used to evaluate the performance of each model.
CR, PR, SD were reported in 14 (23.0%), 35 (57.4%) and 7 (11.5%) patients, respectively. In multivariate analysis, tumor number (hazard ratio, HR = 4.64, 95% CI 1.03-20.88), and arterial phase intensity enhancement (HR = 0.24, 95% CI 0.09-0.64; P = 0.004) emerged as independent risk factors for disease progression. In addition to clinical factors, the radiomics signature enhanced the accuracy of the clinical model in predicting disease progression, with an AUC of 0.71, a sensitivity of 0.99%, and a specificity of 0.95.
Radiomic signatures derived from pretreatment MRIs could predict response to combined Lenvatinib and TACE therapy. Furthermore, it can increase the accuracy of a combined model for predicting disease progression. In order to improve clinical outcomes, clinicians may use this to select an optimal treatment strategy and develop a personalized monitoring protocol.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Emotions have specific effects on behavior. At present, studies are increasingly interested in how emotions affect driving behavior. We designed the experiment by combing driving tasks and eye ...tracking. DSM-V assessment scale was applied to evaluate the depression and manic for participants. In order to explore the dual impacts of emotional issues and cognitive load on attention mechanism, we defined the safety-related region as the area of interest (AOI) and quantified the concentration of eye tracking data. Participants with depression issues had lower AOI sample percentage and shorter AOI fixation duration under no external cognitive load. During our experiment, the depression group had the lowest accuracy in arithmetic quiz. Additionally, we used full connected network to detect the depression group from the control group, reached 83.33%. Our experiment supported that depression have negative influences on driving behavior. Participants with depression issues reduced attention to the safety-related region under no external cognitive load, they were more prone to have difficulties in multitasking when faced with high cognitive load. Besides, participants tended to reallocate more attention resources to the central area under high cognitive load, a phenomenon we called "visual centralization" in driving behavior.
Nonaqueous redox flow batteries are promising in pursuit of high energy density storage systems owing to the broad voltage windows (>2 V) but currently are facing key challenges such as limited ...cyclability and rate performance. To address these technical hurdles, here we report the nonaqueous organic flow battery chemistry based on N-methylphthalimide anolyte and 2,5-di-tert-butyl-1-methoxy-4-2′-methoxyethoxybenzene catholyte, which harvests a theoretical cell voltage of 2.30 V. The redox flow chemistry exhibits excellent cycling stability under both cyclic voltammetry and flow cell tests upon repeated cycling. A series of Daramic and Celgard porous separators are evaluated in this organic flow battery, which enable the cells to be operated at greatly improved current densities as high as 50 mA cm–2 compared to those of other nonaqueous flow systems. The stable cyclability and high-current operations of the organic flow battery system represent significant progress in the development of promising nonaqueous flow batteries.
Objectives
We aimed to compare the therapeutic outcomes of radiofrequency ablation (RFA) and microwave ablation (MWA) as first-line therapies in patients with small single perivascular hepatocellular ...carcinoma (HCC).
Methods
A total of 144 eligible patients with small (≤ 3 cm) single perivascular (proximity to hepatic and portal veins) HCC who underwent RFA (
N
= 70) or MWA (
N
= 74) as first-line treatment were included. The overall survival (OS), disease-free survival (DFS), and local tumor progression (LTP) rates between the two ablation modalities were compared. The inverse probability of treatment weighting (IPTW) method was used to reduce selection bias. Subgroup analysis was performed according to the type of hepatic vessels.
Results
After a median follow-up time of 38.2 months, there were no significant differences in OS (5-year OS: RFA 77.7% vs. MWA 74.6%;
p
= 0.600) and DFS (5-year DFS: RFA 24.7% vs. MWA 40.4%;
p
= 0.570). However, a significantly higher LTP rate was observed in the RFA group than the MWA group (5-year LTP: RFA 24.3% vs. MWA 8.4%;
p
= 0.030). IPTW-adjusted analyses revealed similar results. The treatment modality (RFA vs. MWA: HR 7.861, 95% CI 1.642–37.635,
p
= 0.010) was an independent prognostic factor for LTP. We observed a significant interaction effect of ablation modality and type of peritumoral vessel on LTP (
p
= 0.034). For patients with periportal HCC, the LTP rate was significantly higher in the RFA group than in the MWA group (
p
= 0.045). However, this difference was not observed in patients with perivenous HCC (
p
= 0.116).
Conclusions
In patients with a small single periportal HCC, MWA exhibited better tumor control than RFA.
Key Points
• Microwave ablation exhibited better local tumor control than radiofrequency ablation for small single periportal hepatocellular carcinoma.
• There was a significant interaction between the treatment effect of ablation modality and type of peritumoral vessel on local tumor progression.
• The type of peritumoral vessel is vital in choosing ablation modalities for hepatocellular carcinoma.
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