Development and validation of a nomogram for predicting specific mortality risk: A study of competing risk model based on real endometrial cancer patients

OBJECTIVE

This study aimed to construct a competing risk prediction model for predicting specific mortality risks in endometrial cancer patients from the SEER database based on their demographic characteristics and tumor information.

METHODS

We collected relevant clinical data on patients with histologically confirmed endometrial cancer in the SEER database between 2010 and 2015. Univariate and multivariate competing risk models were used to analyze the risk factors for endometrial cancer-specific death, and a predictive nomogram was constructed. C-index and receiver operating characteristic curve (ROC) at different time points were used to verify the accuracy of the constructed nomogram.

RESULTS

There were 26 109 eligible endometrial cancer patients in the training cohort and 11 189 in the validation cohort. Univariate and multivariate analyses revealed that Age, Marriage, Grade, Behav, FIGO, Size, Surgery, SurgOth, Radiation, ParaAortic_Nodes, Peritonea, N positive, DX_liver, and DX_lung were independent prognostic factors for specific mortality in endometrial cancer patients. Based on these factors, a nomogram was constructed. Internal validation showed that the nomogram had a good discriminative ability (C-index = 0.883 [95% confidence interval [CI]: 0.881-0.884]), and the 1-, 3-, and 5-year AUC values were 0.901, 0.886 and 0.874, respectively. External validation indicated similar results (C-index = 0.883 [95%CI: 0.882-0.883]), and the 1-, 3-, and 5- AUC values were 0.908, 0.885 and 0.870, respectively.

CONCLUSION

We constructed a competing risk model to predict the specific mortality risk among endometrial cancer patients. This model has favorable accuracy and reliability and can provide a reference for the development and update of endometrial cancer prognostic risk assessment tools.

Slimmable transformer with hybrid axial-attention for medical image segmentation

The transformer architecture has achieved remarkable success in medical image analysis owing to its powerful capability for capturing long-range dependencies. However, due to the lack of intrinsic inductive bias in modeling visual structural information, the transformer generally requires a large-scale pre-training schedule, limiting the clinical applications over expensive small-scale medical data. To this end, we propose a slimmable transformer to explore intrinsic inductive bias via position information for medical image segmentation. Specifically, we empirically investigate how different position encoding strategies affect the prediction quality of the region of interest (ROI) and observe that ROIs are sensitive to different position encoding strategies. Motivated by this, we present a novel Hybrid Axial-Attention (HAA) that can be equipped with pixel-level spatial structure and relative position information as inductive bias. Moreover, we introduce a gating mechanism to achieve efficient feature selection and further improve the representation quality over small-scale datasets. Experiments on LGG and COVID-19 datasets prove the superiority of our method over the baseline and previous works. Internal workflow visualization with interpretability is conducted to validate our success better; the proposed slimmable transformer has the potential to be further developed into a visual software tool for improving computer-aided lesion diagnosis and treatment planning.

The temporal transition zone: A gradual approach to a subjective set-point within the three-second time window

Even though in physics "time" is considered to be continuous, how the brain and mind deal with time might be different. It has been proposed that in cognition, time windows provide logistic platforms for information processing, such as the low-frequency 3-s time window. The following series of behavioral experiments may shed light on the dynamics within such a time window. Using a duration reproduction paradigm, we first replicated a pattern of reproduced duration observed in a previous single-case study. Specifically, the reproduction increases as the pause between standard duration and reproduction increases, but only within the time window of some 3 s; when the pause goes beyond 4 s, the reproduction reaches a plateau of a subjective set-point. This increasing phase is named the "temporal transition zone." Three more experiments were performed to test the features of the transition zone as a low-frequency time window. It is also observed with different standard durations (2, 3, 4.5 s, in Experiment 2), and even when the frequency of the auditory stimuli was different in standard and reproduction (300 Hz in standard duration and 400 Hz in reproduction, in Experiment 4). The transition zone was observed only with pause durations of 2 to 3 s; when the shortest pause duration was 5 s, the transition zone was no longer observed, and the reproduction was stable at the subjective set-point (in Experiment 3). Taken together, we suggest that the temporal transition zone indicates a pre-semantic logistic platform to organize and process the information flow; in such a time window of some 3 seconds, the identity of an ongoing event is substantiated, building the "subjective present."

Electrochemical nitrogen reduction reaction on anchored SnS2 nanosheets with TM2 dimers

The design of efficient, high-stability nitrogen fixation catalysts remains a great challenge to achieve electrochemical nitrogen reduction reaction (NRR) under ambient conditions. Herein, the high-throughput first-principles calculations are performed to obtain potential electrochemical NRR catalysts from transition metal (TM) dimers anchored on SnS2 nanosheets. The selected W2/SnS2 behaves as a promising NRR candidate possessing -0.27 V limiting potential and 0.81 eV maximum kinetic potential, and it exhibits the adsorption advantages of *N2 over other small molecules (*H2O, *O, *OH, *H). More importantly, the moderate d orbital valence electron number and electronegativity of TM atom could obtain better NRR activity, and a new descriptor φ considering the effects of coordination environments and adsorbates is proposed to achieve the fast pre-screening among various candidates. This work presents practical insights into the fast screening of TM2/SnS2 candidates for efficient nitrogen fixation and further streamlining the design of electrochemical NRR catalysts.

Pharmacokinetics, Pharmacodynamics, and Safety of Single Dose HSK7653 Tablets in Chinese Subjects with Normal or Impaired Renal Function

OBJECTIVE

HSK7653 is a novel, ultralong-acting dipeptidyl peptidase-4 (DPP-4) inhibitor, promising for type 2 diabetes mellitus with a dosing regimen of once every 2 weeks. This trial investigates the pharmacokinetics (PKs), pharmacodynamics (PDs),and safety of HSK7653 in outpatients with normal or impaired renal function.

METHODS

This is a multicenter, open-label, nonrandomized, parallel-controlled phase I clinical study that investigates the pharmacokinetic profiles of HSK7653 after a single oral administration in 42 subjects with mild (n = 8), moderate (n = 10), severe renal impairment (n = 10), and end-stage renal disease (without dialysis, n = 5) compared with matched control subjects with normal renal function (n = 9). Safety was evaluated throughout the study, and the pharmacodynamic effects were assessed on the basis of a DPP-4 inhibition rate.

RESULTS

HSK7653 exposure levels including the maximum plasma concentration (Cmax), area under the plasma concentration-time curve from zero to last time of quantifiable concentration (AUC0-t), and area under the plasma concentration-time curve from zero to infinity (AUC0-inf) showed no significant differences related to the severity of renal impairment. Renal clearance (CLR) showed a certain downtrend along with the severity of renal impairment. The CLR of the group with severe renal impairment and the group with end-stage renal disease were basically similar. The DPP-4 inhibition rate-time curve graph was similar among the renal function groups. All groups had favorable safety, and no serious adverse events occurred.

CONCLUSIONS

HSK7653 is a potent oral DPP-4 inhibitor with a long plasma half-life, supporting a dosing regimen of once every 2 weeks. Impaired renal function does not appear to impact the pharmacokinetic and pharmacodynamic properties of HSK7653 after a single administration in Chinese subjects. HSK7653 is also well tolerated without an increase in adverse events with increasing renal impairment. These results indicate that dose adjustment of HSK7653 may not be required in patients with renal impairment.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT05497297.

Exploring a frequency-domain attention-guided cascade U-Net: Towards spatially tunable segmentation of vasculature

Developing fully automatic and highly accurate medical image segmentation methods is critically important for vascular disease diagnosis and treatment planning. Although advances in convolutional neural networks (CNNs) have spawned an array of automatic segmentation models converging to saturated high performance, none have explored whether CNNs can achieve (spatially) tunable segmentation. As a result, we propose multiple attention modules from a frequency-domain perspective to construct a unified CNN architecture for segmenting vasculature with desired (spatial) scales. The proposed CNN architecture is named frequency-domain attention-guided cascaded U-Net (FACU-Net). Specifically, FACU-Net contains two innovative components: (1) a frequency-domain-based channel attention module that adaptively tunes channel-wise feature responses and (2) a frequency-domain-based spatial attention module that enables the deep network to concentrate on foreground regions of interest (ROIs) effectively. Furthermore, we devised a novel frequency-domain-based content attention module to enhance or weaken the high (spatial) frequency information, allowing us to strengthen or eliminate vessels of interest. Extensive experiments using clinical data from patients with intracranial aneurysms (IA) and abdominal aortic aneurysms (AAA) demonstrated that the proposed FACU-Net met its design goal. In addition, we further investigated the association between varying (spatial) frequency components and the desirable vessel size/scale attributes. In summary, our preliminary findings are encouraging, and further developments may lead to deployable image segmentation models that are spatially tunable for clinical applications.

Automated polyp segmentation based on a multi-distance feature dissimilarity-guided fully convolutional network

Colorectal malignancies often arise from adenomatous polyps, which typically begin as solitary, asymptomatic growths before progressing to malignancy. Colonoscopy is widely recognized as a highly efficacious clinical polyp detection method, offering valuable visual data that facilitates precise identification and subsequent removal of these tumors. Nevertheless, accurately segmenting individual polyps poses a considerable difficulty because polyps exhibit intricate and changeable characteristics, including shape, size, color, quantity and growth context during different stages. The presence of similar contextual structures around polyps significantly hampers the performance of commonly used convolutional neural network (CNN)-based automatic detection models to accurately capture valid polyp features, and these large receptive field CNN models often overlook the details of small polyps, which leads to the occurrence of false detections and missed detections. To tackle these challenges, we introduce a novel approach for automatic polyp segmentation, known as the multi-distance feature dissimilarity-guided fully convolutional network. This approach comprises three essential components, i.e., an encoder-decoder, a multi-distance difference (MDD) module and a hybrid loss (HL) module. Specifically, the MDD module primarily employs a multi-layer feature subtraction (MLFS) strategy to propagate features from the encoder to the decoder, which focuses on extracting information differences between neighboring layers' features at short distances, and both short and long-distance feature differences across layers. Drawing inspiration from pyramids, the MDD module effectively acquires discriminative features from neighboring layers or across layers in a continuous manner, which helps to strengthen feature complementary across different layers. The HL module is responsible for supervising the feature maps extracted at each layer of the network to improve prediction accuracy. Our experimental results on four challenge datasets demonstrate that the proposed approach exhibits superior automatic polyp performance in terms of the six evaluation criteria compared to five current state-of-the-art approaches.

S-Net: a multiple cross aggregation convolutional architecture for automatic segmentation of small/thin structures for cardiovascular applications

With the success of U-Net or its variants in automatic medical image segmentation, building a fully convolutional network (FCN) based on an encoder-decoder structure has become an effective end-to-end learning approach. However, the intrinsic property of FCNs is that as the encoder deepens, higher-level features are learned, and the receptive field size of the network increases, which results in unsatisfactory performance for detecting low-level small/thin structures such as atrial walls and small arteries. To address this issue, we propose to keep the different encoding layer features at their original sizes to constrain the receptive field from increasing as the network goes deeper. Accordingly, we develop a novel S-shaped multiple cross-aggregation segmentation architecture named S-Net, which has two branches in the encoding stage, i.e., a resampling branch to capture low-level fine-grained details and thin/small structures and a downsampling branch to learn high-level discriminative knowledge. In particular, these two branches learn complementary features by residual cross-aggregation; the fusion of the complementary features from different decoding layers can be effectively accomplished through lateral connections. Meanwhile, we perform supervised prediction at all decoding layers to incorporate coarse-level features with high semantic meaning and fine-level features with high localization capability to detect multi-scale structures, especially for small/thin volumes fully. To validate the effectiveness of our S-Net, we conducted extensive experiments on the segmentation of cardiac wall and intracranial aneurysm (IA) vasculature, and quantitative and qualitative evaluations demonstrated the superior performance of our method for predicting small/thin structures in medical images.

Augmenting Prediction of Intracranial Aneurysms' Risk Status Using Velocity-Informatics: Initial Experience

Our primary goal here is to demonstrate that innovative analytics of aneurismal velocities, named velocity-informatics, enhances intracranial aneurysm (IA) rupture status prediction. 3D computer models were generated using imaging data from 112 subjects harboring anterior IAs (4-25 mm; 44 ruptured and 68 unruptured). Computational fluid dynamics simulations and geometrical analyses were performed. Then, computed 3D velocity vector fields within the IA dome were processed for velocity-informatics. Four machine learning methods (support vector machine, random forest, generalized linear model, and GLM with Lasso or elastic net regularization) were employed to assess the merits of the proposed velocity-informatics. All 4 ML methods consistently showed that, with velocity-informatics metrics, the area under the curve and prediction accuracy both improved by approximately 0.03. Overall, with velocity-informatics, the support vector machine's prediction was most promising: an AUC of 0.86 and total accuracy of 77%, with 60% and 88% of ruptured and unruptured IAs being correctly identified, respectively.

Immune Cell Infiltration and Clinical Significance of Angiogenesis-related Genes in Lung Adenocarcinoma

BACKGROUND/AIM

Angiogenesis is one of the hallmarks of cancer. However, the role of molecular subtypes of angiogenesis-associated genes (AAGs) in the tumor immune microenvironment (TIME) of lung adenocarcinoma (LUAD) remains unclear.

MATERIALS AND METHODS

The expression of AAGs in patients with LUAD were studied. Consensus clustering was performed to identify new AAG-associated molecular subgroups. The TIME and immune status of the subgroups were analyzed. Functional enrichment analysis was performed on the differentially expression genes among the clustered subgroups to analyze their relationship with AAGs. Furthermore, a prognostic risk model and clinical nomogram associated with survival time were constructed. Risk scores of drug sensitivity, immune checkpoint molecules, tumor mutational burden, and tumor cell stemness were analyzed. Finally, a series of in vitro experiments were performed to investigate the role of dickkopf WNT signaling pathway inhibitor 1 (DKK1) in LUAD.

RESULTS

Two molecular subgroups with significantly different survival rates and TIME were identified. Immune checkpoint scores were higher in the subgroup with a worse prognosis. Moreover, differentially expressed genes were enriched in cell-cycle regulation, protein metabolism, and the immune microenvironment. The risk model and clinical nomogram constructed based on AAGs accurately predicted the prognosis of patients with LUAD. Patients with high-risk scores were less sensitive to chemotherapy but more sensitive to immunotherapy. DKK1 was highly expressed in basal cells and luminal cells. In addition, the knockdown of DKK1 reduced LUAD cell proliferation, invasion, and migration.

CONCLUSION

Models based on AAGs can play an important role in predicting LUAD prognosis and immunotherapy effects. We further characterized the angiogenesis of TIME and studied the AAG DKK1. Our findings provide a theoretical basis for antitumor strategies targeting angiogenesis.

Radiomic-based Textural Analysis of Intraluminal Thrombus in Aortic Abdominal Aneurysms: A Demonstration of Automated Workflow

Our main objective is to investigate how the structural information of intraluminal thrombus (ILT) can be used to predict abdominal aortic aneurysms (AAA) growth status through an automated workflow. Fifty-four human subjects with ILT in their AAAs were identified from our database; those AAAs were categorized as slowly- (< 5 mm/year) or fast-growing (≥ 5 mm/year) AAAs. In-house deep-learning image segmentation models were used to generate 3D geometrical AAA models, followed by automated analysis. All features were fed into a support vector machine classifier to predict AAA's growth status.The most accurate prediction model was achieved through four geometrical parameters measuring the extent of ILT, two parameters quantifying the constitution of ILT, antihypertensive medication, and the presence of co-existing coronary artery disease. The predictive model achieved an AUROC of 0.89 and a total accuracy of 83%. When ILT was not considered, our prediction's AUROC decreased to 0.75 (P-value < 0.001).

Deep-learning-based image segmentation for image-based computational hemodynamic analysis of abdominal aortic aneurysms: a comparison study

Computational hemodynamics is increasingly being used to quantify hemodynamic characteristics in and around abdominal aortic aneurysms (AAA) in a patient-specific fashion. However, the time-consuming manual annotation hinders the clinical translation of computational hemodynamic analysis. Thus, we investigate the feasibility of using deep-learning-based image segmentation methods to reduce the time required for manual segmentation. Two of the latest deep-learning-based image segmentation methods, ARU-Net and CACU-Net, were used to test the feasibility of automated computer model creation for computational hemodynamic analysis. Morphological features and hemodynamic metrics of 30 computed tomography angiography (CTA) scans were compared between pre-dictions and manual models. The DICE score for both networks was 0.916, and the correlation value was above 0.95, indicating their ability to generate models comparable to human segmentation. The Bland-Altman analysis shows a good agreement between deep learning and manual segmentation results. Compared with manual (computational hemodynamics) model recreation, the time for automated computer model generation was significantly reduced (from ∼2 h to ∼10 min). Automated image segmentation can significantly reduce time expenses on the recreation of patient-specific AAA models. Moreover, our study showed that both CACU-Net and ARU-Net could accomplish AAA segmentation, and CACU-Net outperformed ARU-Net in terms of accuracy and time-saving.

Intercellular mitochondrial component transfer triggers ischemic cardiac fibrosis

Myocardial fibrosis is the villain of sudden cardiac death. Myocardial ischemia/reperfusion (MI/R) injury induces cardiomyocyte damage or even death, which in turn stimulates fibroblast activation and fibrosis, but the intercellular communication mechanism remains unknown. Recent studies have shown that small extracellular vesicles (sEVs) significantly contribute to intercellular communication. Whether and how sEV might mediate post-MI/R cardiomyocyte/fibroblasts communication remain unknown. Here, in vivo and in vitro MI/R models were established. We demonstrate that sEVs derived from cardiomyocyte (Myo-sEVs) carry mitochondrial components, which enter fibroblasts to initiate myocardial fibrosis. Based on bioinformatics screening and experimental verification, the activating molecule in Beclin1-regulated autophagy protein 1 (autophagy/beclin-1 regulator 1, Ambra1) was found to be a critical component of these sEV and might be a new marker for Myo-sEVs. Interestingly, release of Ambra1+-Myo-sEVs was caused by secretory rather than canonical autophagy after MI/R injury and thereby escaped degradation. In ischemic and peripheral areas, Ambra1+-Myo-sEVs were internalized by fibroblasts, and the delivered mtDNA components to activate the fibroblast cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway to promote fibroblast activation and proliferation. In addition, our data show that Ambra1 is expressed on the EV surface and cardiac-specific Ambra1 down regulation inhibits the Ambra1+-Myo-sEVs release and fibroblast uptake, effectively inhibiting ischemic myocardial fibrosis. This finding newly provides the evidence that myocardial secretory autophagy plays a role in intercellular communication during cardiac fibrosis. Ambra1 is a newly characterized molecule with bioactivity and might be a marker for Myo-sEVs, providing new therapeutic targets for cardiac remodeling.

Application of case-based learning in psychology teaching: a meta-analysis

BACKGROUND

Case-based learning (CBL) has been found to be effective for many subjects, but there is currently a lack of evidence regarding its utility in psychology education. The present study investigated whether CBL pedagogy can improve students' academic performance in psychology courses compared to the traditional teaching methods.

METHODS

A systematic review and meta-analysis were conducted to investigate the effectiveness of CBL in psychology teaching. Databases including PubMed, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), the VIP database, and Wanfang data were searched to find eligible randomized controlled trials. Pooled effect estimates were calculated using Hedges' g under the random effects model, and a subgroup analysis was carried to investigate the heterogeneity among studies.

RESULTS

Fifteen studies with 2172 participants, 1086 in the CBL group and 1086 in the traditional lecture-based teaching group, were included in the meta-analysis. Students in the CBL group scored significantly higher on exams than those in the lecture-based group [Hedges' g = 0.68, 95%CI (0.49, 0.88), p < 0.00]. Relatively high heterogeneity was noted among the included studies. Publication bias was examined by the funnel plot and Egger's test, but did not significantly influence the stability of the results. A subsequent evaluation using the trim-and-fill method confirmed that no single study was skewing the overall results. A qualitative review of the included studies suggested that most students in the CBL group were satisfied with the CBL teaching mode.

CONCLUSIONS

This meta-analysis indicated that the CBL pedagogy could be effective in psychology education, and might help increase students' academic scores, while encouraging a more engaging and cooperative learning environment. At present, the application of CBL in psychology education is in its initial stage. Problems related to the curriculum itself, research methodology, and challenges faced by both teachers and learners have confined its practice. Fully tapping into the strengths of CBL in psychology teaching will require additional work and advancing research.

Characterization of small abdominal aortic aneurysms' growth status using spatial pattern analysis of aneurismal hemodynamics

Aneurysm hemodynamics is known for its crucial role in the natural history of abdominal aortic aneurysms (AAA). However, there is a lack of well-developed quantitative assessments for disturbed aneurysmal flow. Therefore, we aimed to develop innovative metrics for quantifying disturbed aneurysm hemodynamics and evaluate their effectiveness in predicting the growth status of AAAs, specifically distinguishing between fast-growing and slowly-growing aneurysms. The growth status of aneurysms was classified as fast (≥ 5 mm/year) or slow (< 5 mm/year) based on serial imaging over time. We conducted computational fluid dynamics (CFD) simulations on 70 patients with computed tomography (CT) angiography findings. By converting hemodynamics data (wall shear stress and velocity) located on unstructured meshes into image-like data, we enabled spatial pattern analysis using Radiomics methods, referred to as "Hemodynamics-informatics" (i.e., using informatics techniques to analyze hemodynamic data). Our best model achieved an AUROC of 0.93 and an accuracy of 87.83%, correctly identifying 82.00% of fast-growing and 90.75% of slowly-growing AAAs. Compared with six classification methods, the models incorporating hemodynamics-informatics exhibited an average improvement of 8.40% in AUROC and 7.95% in total accuracy. These preliminary results indicate that hemodynamics-informatics correlates with AAAs' growth status and aids in assessing their progression.

Frataxin inhibits the sensitivity of the myocardium to ferroptosis by regulating iron homeostasis

RATIONALE

Myocardial ischemia/reperfusion (I/R) injury is characterized by cell death via various cellular mechanisms upon reperfusion. As a new type of cell death, ferroptosis provides new opportunities to reduce myocardial cell death. Ferroptosis is known to be more active during reperfusion than ischemia. However, the mechanisms regulating ferroptosis during ischemia and reperfusion remain largely unknown.

METHODS

The contribution of ferroptosis in ischemic and reperfused myocardium were detected by administered of Fer-1, a ferroptosis inhibitor to C57BL/6 mice, followed by left anterior descending (LAD) ligation surgery. Ferroptosis was evaluated by measurement of cell viability, ptgs2 mRNA level, iron production, malondialdehyde (MDA) and 4-hydroxynonenal (4-HNE) levels. H9C2 cells were exposed to hypoxia/reoxygenation to mimic in vivo I/R. We used LC-MS/MS to identify potential E3 ligases that interacted with frataxin in heart tissue. Cardiac-specific overexpression of frataxin in whole heart was achieved by intracardiac injection of frataxin, carried by adeno-associated virus serotype 9 (AAV9) containing cardiac troponin T (cTnT) promoter.

RESULTS

We showed that regulators of iron metabolism, especially iron regulatory protein activity, were increased in the ischemic myocardium or hypoxia cardiomyocytes. In addition, we found that frataxin, which is involved in iron metabolism, is differentially expressed in the ischemic and reperfused myocardium and involved in the regulation of cardiomyocytes ferroptosis. Furthermore, we identified an E3 ligase, NHL repeat-containing 1 (NHLRC1), that mediates frataxin ubiquitination degradation. Cardiac-specific overexpression of frataxin ameliorated myocardial I/R injury through ferroptosis inhibition.

CONCLUSIONS

Through a multi-level study from molecule to animal model, these findings uncover the key role of frataxin in inhibiting cardiomyocyte ferroptosis and provide new strategies and perspectives for the treatment of myocardial I/R injury.

Temporal reproduction: A paradigm indicating a 3-s time window

The experimental paradigm of temporal reproduction has provided unique insights into the temporal machinery of cognitive processes. Both behavioral observations and electrophysiological methods with this paradigm indicate a time window of some 3 s.

Mitochondrial transplantation as a novel therapeutic strategy for cardiovascular diseases

Cardiovascular disease (CVD) is the leading cause of noncommunicable disease-related death worldwide, and effective therapeutic strategies against CVD are urgently needed. Mitochondria dysfunction involves in the onset and development of CVD. Nowadays, mitochondrial transplantation, an alternative treatment aimed at increasing mitochondrial number and improving mitochondrial function, has been emerged with great therapeutic potential. Substantial evidence indicates that mitochondrial transplantation improves cardiac function and outcomes in patients with CVD. Therefore, mitochondrial transplantation has profound implications in the prevention and treatment of CVD. Here, we review the mitochondrial abnormalities that occur in CVD and summarize the therapeutic strategies of mitochondrial transplantation for CVD.

Automatic segmentation of abdominal aortic aneurysms from CT angiography using a context-aware cascaded U-Net

We delineate abdominal aortic aneurysms, including lumen and intraluminal thrombosis (ILT), from contrast-enhanced computed tomography angiography (CTA) data in 70 patients with complete automation. A novel context-aware cascaded U-Net configuration enables automated image segmentation. Notably, auto-context structure, in conjunction with dilated convolutions, anisotropic context module, hierarchical supervision, and a multi-class loss function, are proposed to improve the delineation of ILT in an unbalanced, low-contrast multi-class labeling problem. A quantitative analysis shows that the automated image segmentation produces comparable results with trained human users (e.g., DICE scores of 0.945 and 0.804 for lumen and ILT, respectively). Resultant morphological metrics (e.g., volume, surface area, etc.) are highly correlated to those parameters generated by trained human users. In conclusion, the proposed automated multi-class image segmentation tool has the potential to be further developed as a translational software tool that can be used to improve the clinical management of AAAs.

USING CONVOLUTIONAL NEURAL NETWORK-BASED SEGMENTATION FOR IMAGE-BASED COMPUTATIONAL FLUID DYNAMICS SIMULATIONS OF BRAIN ANEURYSMS: INITIAL EXPERIENCE IN AUTOMATED MODEL CREATION

"Image-based" computational fluid dynamics (CFD) simulations provide insights into each patient's hemodynamic environment. However, current standard procedures for creating CFD models start with manual segmentation and are time-consuming, hindering the clinical translation of image-based CFD simulations. This feasibility study adopts deep-learning-based image segmentation (hereafter referred to as Artificial Intelligence (AI) segmentation) to replace manual segmentation to accelerate CFD model creation. Two published convolutional neural network-based AI methods (MIScnn and DeepMedic) were selected to perform CFD model extraction from three-dimensional (3D) rotational angiography data containing intracranial aneurysms. In this study, aneurysm morphological and hemodynamic results using models generated by AI segmentation methods were compared with those obtained by two human users for the same data. Interclass coefficients (ICC), Bland-Altman plots, and Pearson's correlation coefficients (PCC) were combined to assess how well AI-generated CFD models were performed. We found that almost perfect agreement was obtained between the human and AI results for all eleven morphological and five out of eight hemodynamic parameters, while a moderate agreement was obtained from the remaining three hemodynamic parameters. Given this level of agreement, using AI segmentation to create CFD models is feasible, given more developments.

Immunotherapy: A promising novel endometriosis therapy

Endometriosis is a common disease of the female reproductive system and has malignant features. Although endometriosis by itself is a benign disease, its erosive growth characteristics lead to severe pelvic pain and female infertility. Unfortunately, several aspects of the pathogenesis of endometriosis are still unclear. Furthermore, the clinical therapeutic methods are unsatisfactory. The recurrence rate of endometriosis is high. Accumulating evidence suggests that the onset and development of endometriosis are closely related to the abnormal function of the female autoimmune system, especially the function of some immune cells such as the aggregation of neutrophils, abnormal differentiation of macrophages, decreased cytotoxicity of NK cells, and abnormal function of T- and B-cell lines. Therefore, immunotherapy is probably a novel therapeutic strategy for endometriosis besides surgery and hormone therapy. However, information regarding the clinical application of immunotherapy in the treatment of endometriosis is very limited. This article aimed to review the effects of existing immunomodulators on the development of endometriosis, including immune cell regulators and immune factor regulators. These immunomodulators clinically or experimentally inhibit the pathogenesis and development of endometriosis lesions by acting on the immune cells, immune factors, or immune-related signaling pathways. Thus, immunotherapy is probably a novel and effective clinical treatment choice for endometriosis. Experimental studies of the detailed mechanism of immunotherapy and large-scale clinical studies about the effectiveness and safety of this promising therapeutic method are required in the future.

Can we explain machine learning-based prediction for rupture status assessments of intracranial aneurysms?

Although applying machine learning (ML) algorithms to rupture status assessment of intracranial aneurysms (IA) has yielded promising results, the opaqueness of some ML methods has limited their clinical translation. We presented the first explainability comparison of six commonly used ML algorithms: multivariate logistic regression (LR), support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), multi-layer perceptron neural network (MLPNN), and Bayesian additive regression trees (BART). A total of 112 IAs with known rupture status were selected for this study. The ML-based classification used two anatomical features, nine hemodynamic parameters, and thirteen morphologic variables. We utilized permutation feature importance, local interpretable model-agnostic explanations (LIME), and SHapley Additive exPlanations (SHAP) algorithms to explain and analyze 6 Ml algorithms. All models performed comparably: LR area under the curve (AUC) was 0.71; SVM AUC was 0.76; RF AUC was 0.73; XGBoost AUC was 0.78; MLPNN AUC was 0.73; BART AUC was 0.73. Our interpretability analysis demonstrated consistent results across all the methods; i.e., the utility of the top 12 features was broadly consistent. Furthermore, contributions of 9 important features (aneurysm area, aneurysm location, aneurysm type, wall shear stress maximum during systole, ostium area, the size ratio between aneurysm width, (parent) vessel diameter, one standard deviation among time-averaged low shear area, and one standard deviation of temporally averaged low shear area less than 0.4 Pa) were nearly the same. This research suggested that ML classifiers can provide explainable predictions consistent with general domain knowledge concerning IA rupture. With the improved understanding of ML algorithms, clinicians' trust in ML algorithms will be enhanced, accelerating their clinical translation.

An attention residual u-net with differential preprocessing and geometric postprocessing: Learning how to segment vasculature including intracranial aneurysms

OBJECTIVE

Intracranial aneurysms (IA) are lethal, with high morbidity and mortality rates. Reliable, rapid, and accurate segmentation of IAs and their adjacent vasculature from medical imaging data is important to improve the clinical management of patients with IAs. However, due to the blurred boundaries and complex structure of IAs and overlapping with brain tissue or other cerebral arteries, image segmentation of IAs remains challenging. This study aimed to develop an attention residual U-Net (ARU-Net) architecture with differential preprocessing and geometric postprocessing for automatic segmentation of IAs and their adjacent arteries in conjunction with 3D rotational angiography (3DRA) images.

METHODS

The proposed ARU-Net followed the classic U-Net framework with the following key enhancements. First, we preprocessed the 3DRA images based on boundary enhancement to capture more contour information and enhance the presence of small vessels. Second, we introduced the long skip connections of the attention gate at each layer of the fully convolutional decoder-encoder structure to emphasize the field of view (FOV) for IAs. Third, residual-based short skip connections were also embedded in each layer to implement in-depth supervision to help the network converge. Fourth, we devised a multiscale supervision strategy for independent prediction at different levels of the decoding path, integrating multiscale semantic information to facilitate the segmentation of small vessels. Fifth, the 3D conditional random field (3DCRF) and 3D connected component optimization (3DCCO) were exploited as postprocessing to optimize the segmentation results.

RESULTS

Comprehensive experimental assessments validated the effectiveness of our ARU-Net. The proposed ARU-Net model achieved comparable or superior performance to the state-of-the-art methods through quantitative and qualitative evaluations. Notably, we found that ARU-Net improved the identification of arteries connecting to an IA, including small arteries that were hard to recognize by other methods. Consequently, IA geometries segmented by the proposed ARU-Net model yielded superior performance during subsequent computational hemodynamic studies (also known as "patient-specific" computational fluid dynamics [CFD] simulations). Furthermore, in an ablation study, the five key enhancements mentioned above were confirmed.

CONCLUSIONS

The proposed ARU-Net model can automatically segment the IAs in 3DRA images with relatively high accuracy and potentially has significant value for clinical computational hemodynamic analysis.

How We Understand Others: A Theory of How Social Perspective Taking Unfolds

Social perspective taking—the process through which perceivers discern the thoughts, feelings, and motivations of a target—is foundational for navigating social interactions, building relationships, maintaining mental health, promoting well-being, and a wide array of other desired outcomes. Despite its importance, little is known about how discrete social perspective taking attempts unfold. We propose a theory that the social perspective taking process consists of up to four distinguishable phases: perception of the target, motivation to engage in social perspective taking, strategy selection, and evaluation of the attempt. Scholars have emphasized two proximal outcomes of this process—social perspective taking effort and accuracy. We review the literature in support of these phases, noting the relative maturity of each area of research. In doing so, we hope this theory provides a framework for contextualizing how existing studies relate to one another across different subfields of psychology, facilitates testable predictions, prioritizes future investigations, and guides applied research designed to improve real-world social perspective taking.

The Function of FoxK Transcription Factors in Diseases

Forkhead box (FOX) transcription factors play a crucial role in the regulation of many diseases, being an evolutionarily conserved superfamily of transcription factors. In recent years, FoxK1/2, members of its family, has been the subject of research. Even though FoxK1 and FoxK2 have some functional overlap, increasing evidence indicates that the regulatory functions of FoxK1 and FoxK2 are not the same in various physiological and disease states. It is important to understand the biological function and mechanism of FoxK1/2 for better understanding pathogenesis of diseases, predicting prognosis, and finding new therapeutic targets. There is, however, a lack of comprehensive and systematic analysis of the similarities and differences of FoxK1/2 roles in disease, prompting us to perform a literature review.

SIRT6 Protects Against Myocardial Ischemia-Reperfusion Injury by Attenuating Aging-Related CHMP2B Accumulation

Impaired autophagic flux induces aging-related ischemia vulnerability, which is the hallmark pathology in cardiac aging. Our previous work has confirmed that the accumulation of charged multivesicular body protein 2B (CHMP2B), a subunit of the ESCRT-III complex, in the heart can impair autophagy flux. However, whether CHMP2B accumulation contributes to aging-related intolerance to ischemia/reperfusion (I/R) injury and the regulatory mechanism for CHMP2B in aged heart remain elusive. The cardiac CHMP2B level was significantly higher in aged human myocardium than that in young myocardium. Increased CHMP2B were shown to inhibit autophagic flux leading to the deterioration of MI/R injury in aged mice hearts. Interestingly, a negative correlation was observed between SIRT6 and CHMP2B expression in human heart samples. Specific activation of SIRT6 suppressed CHMP2B accumulation and ameliorated autophagy flux in aged hearts. Using myocardial-specific SIRT6 heterozygous knockout mice and recovery experiments confirmed that SIRT6 regulated myocardial CHMP2B levels. Finally, activation of SIRT6 decreased acetylation of FoxO1 to promote its transcriptional function on Atrogin-1, a muscle-specific ubiquitin ligase, which subsequently enhanced the degradation of CHMP2B by Atrogin-1. This is a novel mechanism for SIRT6 against aging-related myocardial ischemia vulnerability, particularly by preventing excessive accumulation of autophagy key factors.

Targeting radiation-tolerant persister cells as a strategy for inhibiting radioresistance and recurrence in glioblastoma

BACKGROUND

Compelling evidence suggests that glioblastoma (GBM) recurrence results from the expansion of a subset of tumor cells with robust intrinsic or therapy-induced radioresistance. However, the mechanisms underlying GBM radioresistance and recurrence remain elusive. To overcome obstacles in radioresistance research, we present a novel preclinical model ideally suited for radiobiological studies.

METHODS

With this model, we performed a screen and identified a radiation-tolerant persister (RTP) subpopulation. RNA sequencing was performed on RTP and parental cells to obtain mRNA and miRNA expression profiles. The regulatory mechanisms among NF-κB, YY1, miR-103a, XRCC3, and FGF2 were investigated by transcription factor activation profiling array analysis, chromatin immunoprecipitation, western blot analysis, luciferase reporter assays, and the MirTrap system. Transferrin-functionalized nanoparticles (Tf-NPs) were employed to improve blood-brain barrier permeability and RTP targeting.

RESULTS

RTP cells drive radioresistance by preferentially activating DNA damage repair and promoting stemness. Mechanistic investigations showed that continual radiation activates the NF-κB signaling cascade and promotes nuclear translocation of p65, leading to enhanced expression of YY1, the transcription factor that directly suppresses miR-103a transcription. Restoring miR-103a expression under these conditions suppressed the FGF2-XRCC3 axis and decreased the radioresistance capability. Moreover, Tf-NPs improved radiosensitivity and provided a significant survival benefit.

CONCLUSIONS

We suggest that the NF-κB-YY1-miR-103a regulatory axis is indispensable for the function of RTP cells in driving radioresistance and recurrence. Thus, our results identified a novel strategy for improving survival in patients with recurrent/refractory GBM.

Progressive global perception and local polishing network for lung infection segmentation of COVID-19 CT images

In this paper, a progressive global perception and local polishing (PCPLP) network is proposed to automatically segment the COVID-19-caused pneumonia infections in computed tomography (CT) images. The proposed PCPLP follows an encoder-decoder architecture. Particularly, the encoder is implemented as a computationally efficient fully convolutional network (FCN). In this study, a multi-scale multi-level feature recursive aggregation (mmFRA) network is used to integrate multi-scale features (viz. global guidance features and local refinement features) with multi-level features (viz. high-level semantic features, middle-level comprehensive features, and low-level detailed features). Because of this innovative aggregation of features, an edge-preserving segmentation map can be produced in a boundary-aware multiple supervision (BMS) way. Furthermore, both global perception and local perception are devised. On the one hand, a global perception module (GPM) providing a holistic estimation of potential lung infection regions is employed to capture more complementary coarse-structure information from different pyramid levels by enlarging the receptive fields without substantially increasing the computational burden. On the other hand, a local polishing module (LPM), which provides a fine prediction of the segmentation regions, is applied to explicitly heighten the fine-detail information and reduce the dilution effect of boundary knowledge. Comprehensive experimental evaluations demonstrate the effectiveness of the proposed PCPLP in boosting the learning ability to identify the lung infected regions with clear contours accurately. Our model is superior remarkably to the state-of-the-art segmentation models both quantitatively and qualitatively on a real CT dataset of COVID-19.

Particulate matter 2.5 triggers airway inflammation and bronchial hyperresponsiveness in mice by activating the SIRT2-p65 pathway

Exposure to particulate matter 2.5 (PM2.5) potentially triggers airway inflammation by activating nuclear factor-κB (NF-κB). Sirtuin 2 (SIRT2) is a key modulator in inflammation. However, the function and specific mechanisms of SIRT2 in PM2.5-induced airway inflammation are largely understudied. Therefore, this work investigated the mechanisms of SIRT2 in regulating the phosphorylation and acetylation of p65 influenced by PM2.5-induced airway inflammation and bronchial hyperresponsiveness. Results revealed that PM2.5 exposure lowered the expression and activity of SIRT2 in bronchial tissues. Subsequently, SIRT2 impairment promoted the phosphorylation and acetylation of p65 and activated the NF-κB signaling pathway. The activation of p65 triggered airway inflammation, increment of mucus secretion by goblet cells, and acceleration of tracheal stenosis. Meanwhile, p65 phosphorylation and acetylation, airway inflammation, and bronchial hyperresponsiveness were deteriorated in SIRT2 knockout mice exposed to PM2.5. Triptolide (a specific p65 inhibitor) reversed p65 activation and ameliorated PM2.5-induced airway inflammation and bronchial hyperresponsiveness. Our findings provide novel insights into the molecular mechanisms underlying the toxicity of PM2.5 exposure. Triptolide inhibition of p65 phosphorylation and acetylation could be an effective therapeutic approach in averting PM2.5-induced airway inflammation and bronchial hyperresponsiveness.

SIRT6 in Senescence and Aging-Related Cardiovascular Diseases

SIRT6 belongs to the nicotinamide adenine dinucleotide (NAD⁺)-dependent deacetylases and has established diverse roles in aging, metabolism and disease. Its function is similar to the Silent Information Regulator 2 (SIR2), which prolongs lifespan and regulates genomic stability, telomere integrity, transcription, and DNA repair. It has been demonstrated that increasing the sirtuin level through genetic manipulation extends the lifespan of yeast, nematodes and flies. Deficiency of SIRT6 induces chronic inflammation, autophagy disorder and telomere instability. Also, these cellular processes can lead to the occurrence and progression of cardiovascular diseases (CVDs), such as atherosclerosis, hypertrophic cardiomyopathy and heart failure. Herein, we discuss the implications of SIRT6 regulates multiple cellular processes in cell senescence and aging-related CVDs, and we summarize clinical application of SIRT6 agonists and possible therapeutic interventions in aging-related CVDs.

Synthesis and characterization of metal-organic framework/biomass-derived CoSe/C@C hierarchical structures with excellent sodium storage performance

Metal selenide has attracted much attention for use in rechargeable batteries due to its excellent conductivity and considerable capacity. However, it is still necessary to achieve a long cycle life and excellent Na+ storage performance to enable its practical application. Volume expansion and poor stability of selenide during operation also hinder its industrial applications. As metal-organic frameworks and aerogels possess porous structures, carbon materials derived from them can effectively reduce the volume expansion of selenide, resulting in improving cycling stability and enhancing Na+ storage. In this work, CoSe/C@C composites with a hierarchical structure were successfully prepared by freeze-drying and in situ selenization as anode materials. The CoSe/C@C composites exhibited superior cycling stability (a capacity of 332.3 mA h g-1) and capacity retention (63.1% compared to the second cycle) at 200 mA g-1, after 500 cycles. CoSe/C@C also exhibited a high rate performance of 403.4 mA h g-1 at 2 A g-1. Moreover, thanks to the high capacitance contribution and some redox reactions during cycling, the CoSe/C@C electrode possesses outstanding rate capability.

Metformin-Enhanced Cardiac AMP-Activated Protein Kinase/Atrogin-1 Pathways Inhibit Charged Multivesicular Body Protein 2B Accumulation in Ischemia-Reperfusion Injury

Background: Cardiac autophagic flux is impaired during myocardial ischemia/reperfusion (MI/R). Impaired autophagic flux may exacerbate MI/R injury. Charged multivesicular body protein 2B (CHMP2B) is a subunit of the endosomal sorting complex required for transport (ESCRT-III) complex that is required for autophagy. However, the reverse role of CHMP2B accumulation in autophagy and MI/R injury has not been established. The objective of this article is to elucidate the roles of AMP-activated protein kinase (AMPK)/atrogin-1 pathways in inhibiting CHMP2B accumulation in ischemia–reperfusion injury.

Methods: Male C57BL/6 mice (3–4 months) and H9c2 cardiomyocytes were used to evaluate MI/R and hypoxia/reoxygenation (H/R) injury in vivo and in vitro, respectively. MI/R was built by a left lateral thoracotomy and occluded the left anterior descending artery. H9c2 cells were firstly treated in 95% N₂ and 5% CO₂ for 15 h and reoxygenation for 1 h. Metformin (100 mg/kg/d) and CHMP2B (Ad-CHMP2B) transfected adenoviruses were administered to the mice. The H9c2 cells were treated with metformin (2.5 mM), MG-132 (10 μM), bafilomycin A1 (10 nM), and compound C (20 μM).

Results: Autophagic flux was found to be inhibited in H/R-treated cardiomyocytes and MI/R mice, with elevated cardiac CHMP2B accumulation. Upregulated CHMP2B levels in the in vivo and in vitro experiments were shown to inhibit autophagic flux leading to the deterioration of H/R-cardiomyocytes and MI/R injury. This finding implies that CHMP2B accumulation increases the risk of myocardial ischemia. Metformin suppressed CHMP2B accumulation and ameliorated H/R-induced autophagic dysfunction by activating AMPK. Activated AMPK upregulated the messenger RNA expression and protein levels of atrogin-1, a muscle-specific ubiquitin ligase, in the myocardium. Atrogin-1 significantly enhanced the interaction between atrogin-1 and CHMP2B, therefore, promoting CHMP2B degradation in the MI/R myocardium. Finally, this study revealed that metformin-inhibited CHMP2B accumulation induced autophagic impairment and ischemic susceptibility in vivo through the AMPK-regulated CHMP2B degradation by atrogin-1.

Conclusion: Impaired CHMP2B clearance in vitro and in vivo inhibits autophagic flux and weakens the myocardial ischemic tolerance. Metformin treatment degrades CHMP2B through the AMPK-atrogin-1-dependent pathway to maintain the homeostasis of autophagic flux. This is a novel mechanism that enriches the understanding of cardioprotection.

Association of metformin monotherapy or combined therapy with cardiovascular risks in patients with type 2 diabetes mellitus

Background

Metformin is a first-line drug in type 2 diabetes mellitus (T2DM) treatment, yet whether metformin may increase all-cause or cardiovascular mortality of T2DM patients remains inconclusive.

Methods

We searched PubMed and Embase for data extracted from inception to July 14, 2020, with a registration in PROSPERO (CRD42020177283). This study included randomized controlled trials (RCT) assessing the cardiovascular effects of metformin for T2DM. This study is followed by PRISMA and Cochrane guideline. Risk ratio (RR) with 95% CI was pooled across trials by a random-effects model. Primary outcomes include all-cause mortality and cardiovascular mortality.

Results

We identified 29 studies that randomly assigned patients with 371 all-cause and 227 cardiovascular death events. Compared with untreated T2DM patients, metformin-treated patients was not associated with lower risk of all-cause mortality (RR: 0.98; 95%CI: 0.69–1.38; P = 0.90), cardiovascular mortality (RR: 1.13; 95% CI: 0.60, 2.15; P = 0.70), macrovascular events (RR: 0.87; 95%CI: 0.70–1.07; P = 0.19), heart failure (RR: 1.02; 95% CI:0.61–1.71; P = 0.95), and microvascular events (RR: 0.78; 95% CI:0.54–1.13; P = 0.19). Combination of metformin with another hypoglycemic drug was associated with higher risk of all-cause mortality (RR: 1.49; 95% CI: 1.02, 2.16) and cardiovascular mortality (RR: 2.21; 95% CI: 1.22, 4.00) compared with hypoglycemic drug regimens with no metformin.

Conclusion

The combination of metformin treatment may impose higher risk in all-cause and cardiovascular mortality. This finding, at least in part, shows no evidence for benefits of metformin in combination in terms of all-cause/cardiovascular mortality and cardiovascular events for T2DM. However, the conclusion shall be explained cautiously considering the limitations from UK Prospective Diabetes Study (UKPDS).

Lipocalin-2-induced proliferative endoplasmic reticulum stress participates in Kawasaki disease-related pulmonary arterial abnormalities

Clinical cases have reported pulmonary arterial structural and functional abnormalities in patients with Kawasaki disease (KD); however, the underlying mechanisms are unclear. In this study, a KD rat model was established via the intraperitoneal injection of Lactobacillus casei cell wall extract (LCWE). The results showed that pulmonary arterial functional and structural abnormalities were observed in KD rats. Furthermore, proliferative endoplasmic reticulum stress (ER stress) was observed in the pulmonary arteries of KD rats. Notably, the level of lipocalin-2 (Lcn 2), a trigger factor of inflammation, was remarkably elevated in the plasma and lung tissues of KD rats; increased Lcn 2 levels following LCWE stimulation may result from polymorphonuclear neutrophils (PMNs). Correspondingly, in cultured pulmonary artery smooth muscle cells (PASMCs), Lcn 2 markedly augmented the cleavage and nuclear localization of activating transcription factor-6 (ATF6), upregulated the transcription of glucose regulated protein 78 (GRP78) and neurite outgrowth inhibitor (NOGO), and promoted PASMCs proliferation. However, proapoptotic C/EBP homologous protein (CHOP) and caspase 12 levels were not elevated. Treatment with 4-phenyl butyric acid (4-PBA, a specific inhibitor of ER stress) inhibited PASMCs proliferation induced by Lcn 2 and attenuated pulmonary arterial abnormalities and right ventricular hypertrophy and reduced right ventricular systolic pressure in KD rats. In conclusion, Lcn 2 remarkably facilitates proliferative ER stress in PASMCs, which probably accounts for KD-related pulmonary arterial abnormalities.

Therapeutic effect of metformin in the treatment of endometrial cancer

The present review aims at reviewing the role of metformin in the treatment of endometrial cancer (EC). According to the literature, excessive estrogen levels and insulin resistance are established risk factors of EC. As a traditional insulin sensitizer and newly discovered anticancer agent, metformin directly and indirectly inhibits the development of EC. The direct mechanisms of metformin include inhibition of the LKB1-AMP-activated protein kinase-mTOR, PI3K-Akt and insulin-like growth factor 1-related signaling pathways, which reduces the proliferation and promotes the apoptosis of EC cells. In the indirect mechanism, metformin increases the insulin sensitivity of body tissues and decreases circulating insulin levels. Decreased levels of insulin increase the blood levels of sex hormone binding globulin, which leads to reductions in circulating estrogen and androgens. The aforementioned findings suggest that metformin serves an important role in the treatment of EC. Increased understanding of the mechanism of metformin in EC may provide novel insights into the treatment of this malignancy.

Targeting AMP-Activated Protein Kinase in Aging-Related Cardiovascular Diseases

Aging is a pivotal risk factor for developing cardiovascular diseases (CVD) due to the lifelong exposure to various risk factors that may affect the heart and vasculature during aging. AMP-activated protein kinase (AMPK), a serine/threonine protein kinase, is a pivotal endogenous energy regulator that protects against various pathological alterations. In this report, we first introduced the protective mechanisms of AMPK signaling in myocardium, such as oxidative stress, apoptosis, inflammation, autophagy and inflammatory response. Next, we introduced the potential correlation between AMPK and cardiac aging. Then, we highlighted the roles of AMPK signaling in cardiovascular diseases, including myocardial ischemia, cardiomyopathy, and heart failure. Lastly, some potential directions and further perspectives were expanded. The information extends our understanding on the protective roles of AMPK in myocardial aging, which may contribute to the design of drug targets and sheds light on potential treatments of AMPK for aging-related CVD.

Blockade of Discoidin Domain Receptor 2 as a Strategy for Reducing Inflammation and Joint Destruction in Rheumatoid Arthritis Via Altered Interleukin-15 and Dkk-1 Signaling in Fibroblast-Like Synoviocytes

OBJECTIVE

This study was undertaken to uncover the pathophysiologic role of discoidin domain receptor 2 (DDR-2), a putative fibrillar collagen receptor, in inflammation promotion and joint destruction in rheumatoid arthritis (RA).

METHODS

In synovial tissue from patients with RA and from mice with collagen antibody-induced arthritis (CAIA) (using Ddr2^-/- and DBA/1 mice), gene and protein expression levels of DDR-2, interleukin-15 (IL-15), and Dkk-1 were measured by quantitative reverse transcription-polymerase chain reaction, Western blotting, and immunohistochemistry. Gene knockdown of DDR2 in human RA fibroblast-like synoviocytes (FLS) was conducted via small interfering RNA. Interaction between the long noncoding RNA H19 and microRNA 103a (miR-103a) was assessed in RA FLS using RNA pulldown assays. Cellular localization of H19 was examined using fluorescence in situ hybridization assays. Chromatin immunoprecipitation and dual luciferase reporter assays were applied to verify H19 transcriptional and posttranscriptional regulation by miR-103a.

RESULTS

DDR2 messenger RNA (mRNA) expression was significantly associated with the levels of IL-15 and Dkk-1 mRNA in the synovial tissue of RA patients (r² = 0.2022-0.3293, all P < 0.05; n = 33) and with the serum levels of IL-15 and Dkk-1 in mice with CAIA (P < 0.05). In human RA FLS, activated DDR-2 induced the expression of H19 through c-Myc. Moreover, H19 directly interacted with and promoted the degradation of miR-103a.

CONCLUSION

These results indicate a novel role for activated DDR-2 in RA FLS, showing that DDR-2 is responsible for regulating the expression of IL-15 and Dkk-1 in RA FLS and is involved in the promotion of inflammation and joint destruction during pathophysiologic development of RA. Moreover, DDR-2 inhibition, acting through the H19-miR-103a axis, leads to reductions in the inflammatory reaction and severity of joint destruction in mice with CAIA, suggesting that inhibition of DDR-2 may be a potential therapeutic strategy for RA.

Metformin mediates cardioprotection against aging-induced ischemic necroptosis

Necroptosis is crucially involved in severe cardiac pathological conditions. However, whether necroptosis contributes to age‐related intolerance to ischemia/reperfusion (I/R) injury remains elusive. In addition, metformin as a potential anti‐aging related injury drug, how it interacts with myocardial necroptosis is not yet clear. Male C57BL/6 mice at 3–4‐ (young) and 22–24 months of age (aged) and RIPK3‐deficient (Ripk3^−/−) mice were used to investigate aging‐related I/R injury in vivo. Metformin (125 μg/kg, i.p.), necrostatin‐1 (3.5 mg/kg), and adenovirus vector encoding p62‐shRNAs (Ad‐sh‐p62) were used to treat aging mice. I/R‐induced myocardial necroptosis was exaggerated in aged mice, which correlated with autophagy defects characterized by p62 accumulation in aged hearts or aged human myocardium. Functionally, blocking autophagic flux promoted H/R‐evoked cardiomyocyte necroptosis in vitro. We further revealed that p62 forms a complex with RIP1‐RIP3 (necrosome) and promotes the binding of RIP1 and RIP3. In mice, necrostatin‐1 treatment (a RIP1 inhibitor), RIP3 deficiency, and cardiac p62 knockdown in vivo demonstrated that p62‐RIP1‐RIP3‐dependent myocardial necroptosis contributes to aging‐related myocardial vulnerability to I/R injury. Notably, metformin treatment disrupted p62‐RIP1‐RIP3 complexes and effectively repressed I/R‐induced necroptosis in aged hearts, ultimately reducing mortality in this model. These findings highlight previously unknown mechanisms of aging‐related myocardial ischemic vulnerability: p62‐necrosome‐dependent necroptosis. Metformin acts as a cardioprotective agent that inhibits this unfavorable chain mechanism of aging‐related I/R susceptibility.

Metformin promotes autophagy in ischemia/reperfusion myocardium via cytoplasmic AMPKα1 and nuclear AMPKα2 pathways

AIMS

In myocardial ischemia-reperfusion (MI/R) injury, impaired autophagy function worsens cardiomyocyte death. AMP-activated protein kinase (AMPK) is a heterotrimeric protein that plays an important role in cardioprotection and myocardial autophagic function. AMPKα1 and α2 are localized primarily in the cytoplasm and nucleus, respectively, in cardiomyocytes, but the isoform-specific autophagy regulation of AMPK during MI/R remains unclear.

MATERIALS AND METHODS

An MI/R model was built, and the protein expression of AMPKα1/α2, p-AMPK, mTOR, p-mTOR, TFEB, p-FoxO3a, SKP2, CARM1, TBP, Atg5, LAMP2, LC3B, and p62 during ischemia and reperfusion was determined by western blotting. Recombinant adeno-associated virus (serotype 9) vectors carrying tandem fluorescent-tagged LC3 or mRFP-GFP-LC3/GFP-LC3 were used to evaluate the autophagy status. AMPKα2 knockout mice were used for in vivo studies.

KEY FINDINGS

Both cytoplasmic AMPKα1 and nuclear α2 subunit expression decreased during the reperfusion period, which led to AMPKα1-mTOR-TFEB and AMPKα2-Skp2-CARM1-TFEB signaling inhibition, respectively. The decreased TFEB level during reperfusion suppressed autophagy. Metformin could activate both the AMPKα1- and α2- mediated pathways, thus restoring autophagy flux during reperfusion. Nevertheless, in AMPKα2 knockout mice, nuclear α2-regulated Skp2-CARM1-TFEB signaling was inhibited, while α1-related signaling was comparatively unaffected, which partially impaired metformin-enhanced autophagy.

SIGNIFICANCE

Our study suggests that metformin had the dual effects of promoting both cytoplasmic AMPKα1- and nuclear AMPKα2-related signaling to improve autophagic flux and restore cardiac function during MI/R.

Gene expression changes in cervical squamous cancers following neoadjuvant interventional chemoembolization

BACKGROUND

The efficacy of therapy for cervical cancer is related to the alteration of multiple molecular events and signaling networks during treatment. The aim of this study was to evaluate gene expression alterations in advanced cervical cancers before- and after-trans-uterine arterial chemoembolization- (TUACE).

METHODS

Gene expression patterns in three squamous cell cervical cancers before- and after-TUACE were determined using microarray technique. Changes in AKAP12 and CA9 genes following TUACE were validated by quantitative real-time PCR.

RESULTS

Unsupervised cluster analysis revealed that the after-TUACE samples clustered together, which were separated from the before-TUACE samples. Using a 2-fold threshold, we identified 1131 differentially expressed genes that clearly discriminate after-TUACE tumors from before-TUACE tumors, including 209 up-regulated genes and 922 down-regulated genes. Pathway analysis suggests these genes represent diverse functional categories. Results from real-time PCR confirmed the expression changes detected by microarray.

CONCLUSIONS

Gene expression signature significantly changes during TUACE therapy of cervical cancer. Theses alterations provide useful information for the development of novel treatment strategies for cervical cancers on the molecular level.

MiR-7-5p suppresses stemness and enhances temozolomide sensitivity of drug-resistant glioblastoma cells by targeting Yin Yang 1

Glioblastoma multiforme (GBM) is the most malignant tumor of the central nervous system, and chemoresistance blunts the effect of temozolomide (TMZ) in the treatment of GBM. Clarifying the underlying mechanism of chemoresistance might yield novel strategies to improve the patients' response to chemotherapeutics. Mounting evidence indicates that microRNAs (miRNAs) are involved in chemoresistance and tumorigenesis. At present, miR-7-5p has been recognized as a tumor suppressor involved in multiple cancers. However, the biological effects of miR-7-5p in TMZ resistance have not been illuminated. In this study, we used RNA sequencing and high-throughput screening techniques, which revealed that miR-7-5p is significantly downregulated in TMZ resistant LN229 cells (LN229/TMZ-R) compared to control cells (LN229), and low miR-7-5p expression was correlated with recurrence in GBM patients. Ectopic overexpression of miR-7-5p sensitized LN229/TMZ-R cells to TMZ and suppressed the stemness of glioblastoma stem cells (GSCs). Further experiments demonstrated that miR-7-5p exerts its role by directly targeting the 3'-untranslated region of Yin Yang 1 (YY1). Our findings suggest that combinational use of miR-7-5p and TMZ might be a promising therapeutic strategy to increase the long-term drug response in GBM patients.

Role of JNK signalling pathway and platelet‑lymphocyte aggregates in myocardial ischemia‑reperfusion injury and the cardioprotective effect of ischemic postconditioning in rats

In myocardial ischemia‑reperfusion injury (MIRI), increased activity of the c‑Jun N‑terminal kinase (JNK) pathway and the activation of platelets that leads to the formation of platelet‑leukocyte aggregates (PLAs) have been observed. It was hypothesized that ischemic postconditioning in MIRI exerts cardioprotective effects by altering JNK activity, which in turn leads to reduced PLA levels. A total of 60 rats were randomly divided into 6 groups (n=10 for each group): i) Control; ii) ischemia‑reperfusion injury alone; iii) ischemia‑reperfusion with postconditioning (PostC group), iv) treatment with the JNK inhibitor‑SP600125; v) postC and treatment with anisomycin; and vi) treatment with the JNK activator‑anisomycin. Subsequently, the levels of PLA, infarct size, myocardial injury markers (creatinine kinase‑muscle/brain and troponin I) and were measured. Western blotting was used to determine the protein expression of phosphorylated‑JNK. MIRI led to increased myocardial infarct size that was associated with raised troponin I and creatine kinase‑muscle/brain. At different time points of MIRI, the level of PLA gradually increased. Compared with the injury‑reperfusion group, the level of PLA in the PostC and Inhibitor‑JNK groups was significantly reduced at 60 min and 3 h following reperfusion. MIRI was able to increase the expression of phosphorylated JNK. These effects were significantly reduced by ischemic postC or by treatment with SP600125. By contrast, the addition of anisomycin attenuated these protective effects. JNK is a critical mediator of MIRI. Ischemic postC can reduce the level of PLA during reperfusion by inhibiting the phosphorylation of JNK MAPK, thereby reducing MIRI. Pharmacological inhibition and activation of JNK can improve and reduce cardioprotective effects, respectively. These results explained the mechanism of the cardioprotection of postC and provided novel insight and target for the therapeutic strategy of MIRI.

Patent foramen ovale closure versus medical therapy for stroke prevention: A systematic review and meta-analysis of randomized controlled trials

Background: Previous randomized trials on patent foramen ovale (PFO) closure versus medical therapy for stroke prevention were inconclusive. Recently, two new randomized trials and new findings from an extended follow-up of a previous trial have been published on this topic. We conducted a systematic review and meta-analysis of randomized trials comparing PFO closure with medical therapy for stroke prevention.

Methods: PubMed and Cochrane Library were searched until 16 ^th September 2017.  The following search terms were used for PubMed: "patent foramen ovale" AND (stroke OR embolism) and "randomized" AND "Trial". For Cochrane Library, the following terms were used: "patent foramen ovale" AND "closure" AND (stroke OR embolism).

Results: A total of 91 and 55 entries were retrieved from each database using our search strategy respectively, of which six studies on five trials met the inclusion criteria. This meta-analysis included 1829 patients in the PFO closure arm (mean age: 45.3 years; 54% male) and 1972 patients in the medical therapy arm (mean age: 45.1 years; 51% male). The median follow-up duration was 50 ± 30 months. When compared to medical therapy, PFO closure significantly reduced primary endpoint events with a risk ratio [RR] of 0.60 (95% CI: 0.44-0.83, P < 0.0001; I²: 15%). It also reduced stroke (RR: 0.50, 95% CI: 0.35-0.73, P < 0.0001; I²: 32%) despite increasing the risk of atrial fibrillation/flutter (RR: 1.90, 95% CI: 1.23-2.93, P < 0.01; I²: 43%). However, it did not reduce transient ischemic accident events (0.75; 95% CI: 0.51-1.10, P = 0.14; I²: 0%), all-cause bleeding (RR: 0.89; 95% CI: 0.44-1.78, P = 0.74; I²: 51%) or gastrointestinal complications (RR: 0.92; 95% CI: 0.32-2.70, P = 0.88; I²: 0%).

Conclusions: PFO closure significantly reduces risk of stroke when compared to medical treatment and should therefore be considered for stroke prevention in PFO patients.