A novel framework for high resolution air quality index prediction with interpretable artificial intelligence and uncertainties estimation.

Accurate air quality index (AQI) prediction is essential in environmental monitoring and management. Given that previous studies neglect the importance of uncertainty estimation and the necessity of constraining the output during prediction, we proposed a new hybrid model, namely TMSSICX, to forecast the AQI of multiple cities. Firstly, time-varying filtered based empirical mode decomposition (TVFEMD) was adopted to decompose the AQI sequence into multiple internal mode functions (IMF) components. Secondly, multi-scale fuzzy entropy (MFE) was applied to evaluate the complexity of each IMF component and clustered them into high and low-frequency portions. In addition, the high-frequency portion was secondarily decomposed by successive variational mode decomposition (SVMD) to reduce volatility. Then, six air pollutant concentrations, namely CO, SO2, PM2.5, PM10, O3, and NO2, were used as inputs. The secondary decomposition and preliminary portion were employed as the outputs for the bidirectional long short-term memory network optimized by the snake optimization algorithm (SOABiLSTM) and improved Catboost (ICatboost), respectively. Furthermore, extreme gradient boosting (XGBoost) was applied to ensemble each predicted sub-model to acquire the consequence. Ultimately, we introduced adaptive kernel density estimation (AKDE) for interval estimation. The empirical outcome indicated the TMSSICX model achieved the best performance among the other 23 models across all datasets. Moreover, implementing the XGBoost to ensemble each predicted sub-model led to an 8.73%, 8.94%, and 0.19% reduction in RMSE, compared to SVM. Additionally, by utilizing SHapley Additive exPlanations (SHAP) to assess the impact of the six pollutant concentrations on AQI, the results reveal that PM2.5 and PM10 had the most notable positive effects on the long-term trend of AQI. We hope this model can provide guidance for air quality management.

Microglia sense and suppress epileptic neuronal hyperexcitability.

Microglia are the resident immune cells of the central nervous system, undertaking surveillance role and reacting to brain homeostasis and neurological diseases. Recent studies indicate that microglia modulate epilepsy-induced neuronal activities, however, the mechanisms underlying microglia-neuron communication in epilepsy are still unclear. Here we report that epileptic neuronal hyperexcitability activates microglia and drives microglial ATP/ADP hydrolyzing ectoenzyme CD39 (encoded by Entpd1) expression via recruiting the cAMP responsive element binding protein (CREB)-regulated transcription coactivator-1 (CRTC1) from cytoplasm to the nucleus and binding to CREB. Activated microglia in turn suppress epileptic neuronal hyperexcitability in a CD39 dependent manner. Disrupting microglial CREB/CRTC1 signaling, however, decreases CD39 expression and diminishes the inhibitory effect of microglia on epileptic neuronal hyperexcitability. Overall, our findings reveal CD39-dependent control of epileptic neuronal hyperexcitability by microglia is through an excitation-transcription coupling mechanism.

Prostate cancer-associated SPOP mutations lead to genomic instability through disruption of the SPOP-HIPK2 axis.

Speckle-type Poz protein (SPOP), an E3 ubiquitin ligase adaptor, is the most frequently mutated gene in prostate cancer. The SPOP-mutated subtype of prostate cancer shows high genomic instability, but the underlying mechanisms causing this phenotype are still largely unknown. Here, we report that upon DNA damage, SPOP is phosphorylated at Ser119 by the ATM serine/threonine kinase, which potentiates the binding of SPOP to homeodomain-interacting protein kinase 2 (HIPK2), resulting in a nondegradative ubiquitination of HIPK2. This modification subsequently increases the phosphorylation activity of HIPK2 toward HP1γ, and then promotes the dissociation of HP1γ from trimethylated (Lys9) histone H3 (H3K9me3) to initiate DNA damage repair. Moreover, the effect of SPOP on the HIPK2-HP1γ axis is abrogated by prostate cancer-associated SPOP mutations. Our findings provide new insights into the molecular mechanism of SPOP mutations-driven genomic instability in prostate cancer.

Associations between dietary fiber intake and mortality from all causes, cardiovascular disease and cancer: a prospective study.

OBJECTIVE: Several studies suggest that dietary fiber intake may reduce mortality risk, but this might depend on the fiber types and the evidence regarding the role of soluble fiber or insoluble fiber on death risk remain limited and inconsistent. Therefore, this study aimed to comprehensively evaluate multiple types of dietary fiber intake on mortality from all causes, cardiovascular disease and cancer in the large-scale Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) Screening Trial. METHODS: A multivariate Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: This study finally included 86,642 participants with 17,536 all-cause deaths, 4842 cardiovascular deaths and 5760 cancer deaths identified after a total of 1,444,068 follow-up years. After adjusting for potential confounders, dietary total fiber intake was statistically significantly inversely associated with all-cause death (Q5 vs Q1: HR 0.71, 95% CI 0.66-0.75; P for trend < 0.001), cardiovascular death (Q5 vs Q1: HR 0.73, 95% CI 0.65-0.83; P for trend < 0.001) and cancer mortality (Q5 vs Q1: HR 0.77, 95% CI 0.69-0.86; P for trend < 0.001). Similar results were observed for both insoluble and soluble fiber intake. Restricted cubic spline model analysis suggested that there was a nonlinear association of dietary fiber intake with mortality risk (all P for nonlinearity < 0.05). CONCLUSIONS: In this large nationally representative sample of US adult population, intakes of total fiber, soluble fiber, and insoluble fiber were associated with lower risks of all-cause, cardiovascular and cancer mortality.

MicroRNA-125a-5p Contributes to Hepatic Stellate Cell Activation through Targeting FIH1.

BACKGROUND/AIMS: Emerging evidence shows that microRNAs (miRNAs) play a crucial role in the regulation of activation, proliferation and apoptosis of hepatic stellate cells (HSCs). Previous studies have indicated that miR-125a-5p is correlated with hepatitis B virus replication and disease progression. However, little is known about the biological role and underlying mechanism of miR-125a-5p in liver fibrosis. METHODS: We analyzed the level of miR-125a-5p in carbon tetrachloride-induced liver fibrosis and activated HSCs. We analyzed the effects of miR-125a-5p down-regulation on HSC activation and proliferation. We also analyzed the binding of miR-125a-5p to the 3'-untranslated region of factor inhibiting hypoxia-inducible factor 1 (FIH1) mRNA. RESULTS: Up-regulation of miR-125a-5p was observed in the liver tissues of fibrotic mice and activated HSCs. Down-regulation of miR-125a-5p prevented the activation and proliferation of HSCs. FIH1, a negative modulator of hypoxia inducible factor 1, was confirmed to be a target of miR-125a-5p using the luciferase reporter assay. Further studies demonstrated that miR-125a-5p prompted the activation and proliferation of HSCs, at least in part, by down-regulating FIH1. CONCLUSION: Our findings shed new light on miRNAs as a promising therapeutic target in liver fibrosis.

Epilepsy and demyelination: Towards a bidirectional relationship.

Demyelination stands out as a prominent feature in individuals with specific types of epilepsy. Concurrently, individuals with demyelinating diseases, such as multiple sclerosis (MS) are at a greater risk of developing epilepsy compared to non-MS individuals. These bidirectional connections raise the question of whether both pathological conditions share common pathogenic mechanisms. This review focuses on the reciprocal relationship between epilepsy and demyelination diseases. We commence with an overview of the neurological basis of epilepsy and demyelination diseases, followed by an exploration of how our comprehension of these two disorders has evolved in tandem. Additionally, we discuss the potential pathogenic mechanisms contributing to the interactive relationship between these two diseases. A more nuanced understanding of the interplay between epilepsy and demyelination diseases has the potential to unveiling the molecular intricacies of their pathological relationships, paving the way for innovative directions in future clinical management and treatment strategies for these diseases.

CenterNet++ for Object Detection.

There are two mainstream approaches for object detection: top-down and bottom-up. The state-of-the-art approaches are mainly top-down methods. In this paper, we demonstrate that bottom-up approaches show competitive performance compared with top-down approaches and have higher recall rates. Our approach, named CenterNet, detects each object as a triplet of keypoints (top-left and bottom-right corners and the center keypoint). We first group the corners according to some designed cues and confirm the object locations based on the center keypoints. The corner keypoints allow the approach to detect objects of various scales and shapes and the center keypoint reduces the confusion introduced by a large number of false-positive proposals. Our approach is an anchor-free detector because it does not need to define explicit anchor boxes. We adapt our approach to backbones with different structures, including 'hourglass'-like networks and 'pyramid'-like networks, which detect objects in single-resolution and multi-resolution feature maps, respectively. On the MS-COCO dataset, CenterNet with Res2Net-101 and Swin-Transformer achieve average precisions (APs) of 53.7% and 57.1%, respectively, outperforming all existing bottom-up detectors and achieving state-of-the-art performance. We also design a real-time CenterNet model, which achieves a good trade-off between accuracy and speed, with an AP of 43.6% at 30.5 frames per second (FPS).

Dietary glycemic index, glycemic load, and renal cancer risk: findings from prostate, lung, colorectal, and ovarian cancer trial.

Background: Dietary glycemic index (GI) or glycemic load (GL) has been associated with the development of many cancers, but the evidence for renal cancer is still limited. The aim of the present study was to investigate the association between GI or GL and renal cancer risk in the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) Screening Trial. Methods: The cohort for our analysis consisted of 101,190 participants. GI and GL were calculated from the FFQ data using previously published reference values. Multivariate-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox regression model after adjusting for most known renal cancer risk factors. Results: During a median of 12.2 years of follow-up, 443 incident renal cancer cases occurred. Higher dietary GI was significantly associated with a higher risk of renal cancer (HRQ3vsQ1: 1.38; 95% CI: 1.09-1.74; p for trend = 0.008). There was no significant association between dietary GL and renal cancer risk (HRQ3vsQ1 = 1.12, 95% CI = 0.79-1.59, p for trend = 0.591). Spline regression plot revealed a higher risk of renal cancer with a higher GI but not GL. There was no statistical evidence for nonlinearity (p for nonlinearity >0.05). Conclusion: In summary, findings of this large-scale prospective cohort study suggested that dietary GI may be associated with the risk of renal cancer. If confirmed in other populations and settings, dietary GI could be considered as a modifiable risk factor for renal cancer prevention.

Curcumin alleviated oxidation stress injury by mediating osteopontin in nephrolithiasis rats.

PURPOSE: To explore the role and mechanism of curcumin (Cur) in reducing oxidative stress damage in rats with nephrolithiasis induced by ethylene glycol (EG). METHODS: Thirty male rats were divided into normal control, model, positive (10% potassium citrate), Cur-10 (10 mg/kg curcumin) and Cur-20 (20 mg/kg curcumin) groups. RESULTS: The results of kidney tissue section stained by hematoxylin-eosin and von Kossa showed that curcumin treatment can inhibit the formation of kidney stones. The biochemical test results showed that the urea (Ur), creatinine (Cr), uric acid (UA), inorganic phosphorus and Ca2+ concentrations in urine decreased after being treated with curcumin. There were significant differences between different doses of curcumin (P < 0.05). Compared with the Cur-10 group, Cur-20 had a more significant inhibitory effect on malondialdehyde (MDA) (P < 0.05). In addition, reverse transcription polymerase chain reaction (PCR) detection and immunohistochemical results indicated that the osteopontin (OPN) in the kidney was significantly reduced after curcumin treatment. CONCLUSIONS: Curcumin could reduce the oxidative stress damage caused by EG-induced kidney stones.

Preliminary Experience of Partial Nephrectomy Through a New Single-Port Surgical Robot System.

Purpose: To explore the preliminary safety and efficacy of the Shurui single-port (SP) surgical robot in partial nephrectomy (PN). Methods: This study prospectively enrolled patients with T1a renal tumors who met the inclusion criteria from February to July 2022 in The First Affiliated Hospital School of Medicine Zhejiang University. The operative outcomes and perioperative data, including clinical and histological data, were prospectively collected and analyzed. Results: A total of 13 patients were included in this study, including 7 males and 6 females. The median age was 53 (33-74) years, and the average body mass index was 24.9 ± 4.2 kg/m2. There were 6 cases of left kidney tumors and 7 cases of right kidney tumors in the 13 patients. The average tumor diameter was 1.9 ± 0.9 cm. In all operations, the diseased tissue was removed according to the established surgical plan. The average warm ischemia time was 26.2 ± 9.7 minutes; the average device docking time was 3.6 ± 1.8 minutes; and the average robotic arm operation time was 124.7 ± 40.4 minutes. All operations were successfully completed; there was no conversion to open surgery during the operation; and no operation holes were added. The National Aeronautics and Space Administration Task Load Index (NASA-TLX) score was 26.3 ± 2.6 points, and no device-related adverse events occurred during the operation. The median time to discharge was 6 days (range, 4-11 days). Postoperative pathological examination showed that all tumor margins were negative. There were no Clavien grade ≥3 surgical complications in any of the patients during the perioperative period or at the 1-month postoperative follow-up. Conclusion: The new SP surgical robot system is safe, effective, flexible, and stable for application in PN.

Single-Port Robot-Assisted Radical Prostatectomy with the Novel Shurui Single-Port Robotic Surgical System.

Purpose: The aim of this study was to explore the safety and efficacy of radical prostatectomy with a novel Shurui single-port (SR-SP) robotic surgical system. Methods: A total of 11 patients with prostate cancer were enrolled in this study. Extraperitoneal radical prostatectomy was performed using the SR-SP robotic surgical system for all patients. Clinicopathologic data, perioperative data, and short-term surgical outcomes were prospectively collected and analyzed. Results: Of the 11 patients, the median age was 65 years (range 52-73), and the median body mass index was 22.6 kg/m2 (range 20.2-26.7). The median operative time was 229 minutes (range 194-317), and the median console time was 167 minutes (range 141-265). The median blood loss was 40 mL (range 10-120), and none of the patients required intraoperative transfusion. There was no conversion to open surgery during the operation, and no assistant ports were added. The surgeons reported a good task load rating with a National Aeronautics and Space Administration Task Load Index (NASA-TLX) score of 25.1 ± 3.3 points. The median postoperative hospital stay time was 7 days (range 4-15). There were no severe intraoperative or postoperative complications (Clavien grade ≥3). Postoperative positive surgical margin occurred in 4 (36.4%) patients. No biochemical recurrence occurred within 1 month of surgery. The continence rate was 72.7% (8/11) 1 month after surgery. Conclusions: The new SR-SP robotic surgical system is safe, effective, flexible, and stable for application in radical prostatectomy.

Circulating succinate-modifying metabolites accurately classify and reflect the status of fumarate hydratase-deficient renal cell carcinoma.

Germline or somatic loss-of-function mutations of fumarate hydratase (FH) predispose patients to an aggressive form of renal cell carcinoma (RCC). Since other than tumor resection there is no effective therapy for metastatic FH-deficient RCC, an accurate method for early diagnosis is needed. Although MRI or CT scans are offered, they cannot differentiate FH-deficient tumors from other RCCs. Therefore, finding noninvasive plasma biomarkers suitable for rapid diagnosis, screening, and surveillance would improve clinical outcomes. Taking advantage of the robust metabolic rewiring that occurs in FH-deficient cells, we performed plasma metabolomics analysis and identified 2 tumor-derived metabolites, succinyl-adenosine and succinic-cysteine, as excellent plasma biomarkers for early diagnosis. These 2 molecules reliably reflected the FH mutation status and tumor mass. We further identified the enzymatic cooperativity by which these biomarkers are produced within the tumor microenvironment. Longitudinal monitoring of patients demonstrated that these circulating biomarkers can be used for reporting on treatment efficacy and identifying recurrent or metastatic tumors.

Genomic Profiling and Response to Immune Checkpoint Inhibition plus Tyrosine Kinase Inhibition in FH-Deficient Renal Cell Carcinoma.

BACKGROUND: FH-deficient renal cell carcinoma (RCC) is a rare and exceptionally aggressive RCC subtype. There is currently limited understanding of the molecular alterations, pathogenesis, survival outcomes, and systemic therapy efficacy for this cancer. OBJECTIVE: To perform a retrospective multicenter analysis of molecular profiling and clinical outcomes for patients with FH-deficient RCC, with an emphasis on treatment response to first-line immune checkpoint inhibitor plus tyrosine kinase inhibitor (ICI/TKI) versus bevacizumab plus erlotinib (Bev/Erlo) combination therapy in patients with advanced disease. DESIGN, SETTING, AND PARTICIPANTS: The study included 77 cases of FH-deficient RCC from 15 centers across China. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Clinical characteristics, molecular correlates, 18F-fluorodeoxyglucose positron emission tomography/computed tomography imaging, and treatment outcomes were analyzed. RESULTS AND LIMITATIONS: A total of 77 patients were identified, including 70 cases with a germline FH alteration (hereditary leiomyomatosis RCC syndrome [HLRCC]-associated RCC) and seven patients with somatic FH loss. Recurrent pathogenic alterations were found in NF2 (six/57, 11%), CDH1 (six/57, 11%), PIK3CA (six/57, 11%), and TP53 (five/57, 8.8%). Sixty-seven patients were evaluable for response to first-line systemic therapy with Bev/Erlo (n = 12), TKI monotherapy (n = 29), or ICI/TKI (n = 26). ICI/TKI combination therapy was associated with more favorable overall survival on systemic treatment (hazard ratio [HR] 0.19, 95% confidence interval [CI] 0.04-0.90) and progression-free survival on first-line therapy (HR 0.22, 95% CI 0.07-0.71) compared to Bev/Erlo combination therapy. The main limitation is the retrospective study design. CONCLUSIONS: We described the genomic characteristics of FH-deficient RCC in an Asian population and observed a favorable response to ICI/TKI combinational therapy among patients with advanced disease. PATIENT SUMMARY: This real-world study provides evidence supporting the antitumour activity of combining molecular targeted therapy plus immunotherapy for kidney cancer deficient in fumarate hydratase. Further studies are needed to investigate the efficacy of this combination strategy in this rare cancer.

DetPoseNet: Improving Multi-Person Pose Estimation via Coarse-Pose Filtering.

Human detection and pose estimation are essential for understanding human activities in images and videos. Mainstream multi-human pose estimation methods take a top-down approach, where human detection is first performed, then each detected person bounding box is fed into a pose estimation network. This top-down approach suffers from the early commitment of initial detections in crowded scenes and other cases with ambiguities or occlusions, leading to pose estimation failures. We propose the DetPoseNet, an end-to-end multi-human detection and pose estimation framework in a unified three-stage network. Our method consists of a coarse-pose proposal extraction sub-net, a coarse-pose based proposal filtering module, and a multi-scale pose refinement sub-net. The coarse-pose proposal sub-net extracts whole-body bounding boxes and body keypoint proposals in a single shot. The coarse-pose filtering step based on the person and keypoint proposals can effectively rule out unlikely detections, thus improving subsequent processing. The pose refinement sub-net performs cascaded pose estimation on each refined proposal region. Multi-scale supervision and multi-scale regression are used in the pose refinement sub-net to simultaneously strengthen context feature learning. Structure-aware loss and keypoint masking are applied to further improve the pose refinement robustness. Our framework is flexible to accept most existing top-down pose estimators as the role of the pose refinement sub-net in our approach. Experiments on COCO and OCHuman datasets demonstrate the effectiveness of the proposed framework. The proposed method is computationally efficient (5-6x speedup) in estimating multi-person poses with refined bounding boxes in sub-seconds.

Inhibition of neuronal nitric oxide synthase protects against hippocampal neuronal injuries by increasing neuropeptide Y expression in temporal lobe epilepsy mice.

Neuronal nitric oxide synthase (nNOS) plays a pivotal role in the pathological process of neuronal injury in the development of epilepsy. Our previous study has demonstrated that nitric oxide (NO) derived from nNOS in the epileptic brain is neurotoxic due to its reaction with the superoxide radical with the formation of peroxynitrite. Neuropeptide Y (NPY) is widely expressed in the mammalian brain, which has been implicated in energy homeostasis and neuroprotection. Recent studies suggest that nNOS may act as a mediator of NPY signaling. Here in this study, we sought to determine whether NPY expression is regulated by nNOS, and if so, whether the regulation of NPY by nNOS is associated with the neuronal injuries in the hippocampus of epileptic brain. Our results showed that pilocarpine-induced temporal lobe epilepsy (TLE) mice exhibited an increased level of nNOS expression and a decreased level of NPY expression along with hippocampal neuronal injuries and cognition deficit. Genetic deletion of nNOS gene, however, significantly upregulated hippocampal NPY expression and reduced TLE-induced hippocampal neuronal injuries and cognition decline. Knockdown of NPY abolished nNOS depletion-induced neuroprotection and cognitive improvement in the TLE mice, suggesting that inhibition of nNOS protects against hippocampal neuronal injuries by increasing neuropeptide Y expression in TLE mice. Targeting nNOS-NPY signaling pathway in the epileptic brain might provide clinical benefit by attenuating neuronal injuries and preventing cognitive deficits in epilepsy patients.

Pulmonary nodules detection assistant platform: An effective computer aided system for early pulmonary nodules detection in physical examination.

BACKGROUND AND OBJECTIVE: Early detection of the pulmonary nodule from physical examination low-dose computer tomography (LDCT) images is an effective measure to reduce the mortality rate of lung cancer. Although there are many computer aided diagnosis (CAD) methods used for detecting pulmonary nodules, there are few CAD systems for small pulmonary nodule detection with a large amount of physical examination LDCT images. METHODS: In this work, we designed a CAD system called Pulmonary Nodules Detection Assistant Platform for early pulmonary nodules detection and classification based on the physical examination LDCT images. Based on the preprocessed physical examination CT images, the three-dimensional (3D) CNN-based model is presented to detect candidate pulmonary nodules and output detection results with quantitative parameters, the 3D ResNet is used to classify the detected nodules into intrapulmonary nodules and pleural nodules to reduce the physician workloads, and the Fully Connected Neural Network (FCNN) is used to classify ground-glass opacity (GGO) nodules and non-GGO nodules to help doctor pay more attention to those suspected early lung cancer nodules. RESULTS: Experiments are performed on our 1000 samples of physical examinations (LNPE1000) with an average diameter of 5.3 mm and LUNA16 dataset with an average diameter of 8.31 mm, which show that the designed CAD system is automatic and efficient for detecting smaller and larger nodules from different datasets, especially for the detection of smaller nodules with diameter between 3 mm and 6 mm in physical examinations. The accuracy of pulmonary nodule detection reaches 0.879 with an average of 1 false positive per CT in LNPE1000 dataset, which is comparable to the experienced physicians. The classification accuracy reaches 0.911 between intrapulmonary and pleural nodules, and 0.950 between GGO and non-GGO nodules, respectively. CONCLUSION: Experimental results show that the proposed pulmonary nodule detection model is robust for different datasets, which can successfully detect smaller and larger nodules in CT images obtained by physical examination. The interactive platform of the designed CAD system has been on trial in a hospital by combining with manual reading, which helps doctors analyze clinical data dynamically and improves the nodule detection efficiency in physical examination applications.

Fast Online Video Pose Estimation by Dynamic Bayesian Modeling of Mode Transitions.

We propose a fast online video pose estimation method to detect and track human upper-body poses based on a conditional dynamic Bayesian modeling of pose modes without referring to future frames. The estimation of human body poses from videos is an important task with many applications. Our method extends fast image-based pose estimation to live video streams by leveraging the temporal correlation of articulated poses between frames. Video pose estimation is inferred over a time window using a conditional dynamic Bayesian network (CDBN), which we term time-windowed CDBN. Specifically, latent pose modes and their transitions are modeled and co-determined from the combination of three modules: 1) inference based on current observations; 2) the modeling of mode-to-mode transitions as a probabilistic prior; and 3) the modeling of state-to-mode transitions using a multimode softmax regression. Given the predicted pose modes, the body poses in terms of arm joint locations can then be determined more accurately and robustly. Our method is suitable to investigate high frame rate (HFR) scenarios, where pose mode transitions can effectively capture action-related temporal information to boost performance. We evaluate our method on a newly collected HFR-Pose dataset and four major video pose datasets (VideoPose2, TUM Kitchen, FLIC, and Penn_Action). Our method achieves improvements in both accuracy and efficiency over existing online video pose estimation methods.

Learning Self-Supervised Space-Time CNN for Fast Video Style Transfer.

Style transfer on images has achieved significant advances in recent years, with the deep convolutional neural network (CNN). Directly applying image style transfer algorithms to each frame of a video independently often leads to flickering and unstable results. In this work, we present a self-supervised space-time convolutional neural network (CNN) based method for online video style transfer, named as VTNet, which is end-to-end trained from nearly unlimited unlabeled video data to produce temporally coherent stylized videos in real-time. Specifically, our VTNet transfer the style of a reference image to the source video frames, which is formed by the temporal prediction branch and the stylizing branch. The temporal prediction branch is used to capture discriminative spatiotemporal features for temporal consistency, pretrained in an adversarial manner from unlabeled video data. The stylizing branch is used to transfer the style image to a video frame with the guidance from the temporal prediction branch to ensure temporal consistency. To guide the training of VTNet, we introduce the style-coherence loss net (SCNet), which assembles the content loss, the style loss, and the new designed coherence loss. These losses are computed based on high-level features extracted from a pretrained VGG-16 network. The content loss is used to preserve high-level abstract contents of the input frames, and the style loss introduces new colors and patterns from the style image. Instead of using optical flow to explicitly redress the stylized video frames, we design the coherence loss to make the stylized video inherit the dynamics and motion patterns from the source video to remove temporal flickering. Extensive subjective and objective evaluations on various styles demonstrate that the proposed method achieves favorable results against the state-of-the-arts with high efficiency.

Mesenchymal Stem Cells Attenuates TGF-ß1-Induced EMT by Increasing HGF Expression in HK-2 Cells.

BACKGROUND: Mesenchymal stem cells (MSCs) have recently shown promise for the treatment of various types of chronic kidney disease models. However, the mechanism of this effect is still not well understood. Our study is aimed to investigate the effect of MSCs on transforming growth factor beta 1 (TGF-ß1)-induced epithelial mesenchymal transition (EMT) in renal tubular epithelial cells (HK-2 cells) and the underlying mechanism related to the reciprocal balance between hepatocyte growth factor (HGF) and TGF-ß1. METHODS: Our study was performed at Ningbo University, Ningbo, Zhejiang, China between Mar 2017 and Jun 2018. HK-2 cells were initially treated with TGF-ß1, then co-cultured with MSCs. The induced EMT was assessed by cellular morphology and the expressions of alpha-smooth muscle actin (α-SMA) and EMT-related proteins. MTS assay and flow cytometry were employed to detect the effect of TGF-ß1 and MSCs on HK-2 cell proliferation and apoptosis. SiRNA against hepatocyte growth factor (siHGF) was transfected to decrease the expression of HGF to identify the role of HGF in MSCs inhibiting HK-2 cells EMT. RESULTS: Overexpressing TGF-ß1 decreased HGF expression, induced EMT, suppressed proliferation and promoted apoptosis in HK-2 cells; but when co-cultured with MSCs all the outcomes were reversed. However, after treated with siHGF, all the benefits taken from MSCs vanished. CONCLUSION: TGF-ß1 was a motivating factor of kidney cell EMT and it suppressed the HGF expression. However, MSCs provided protection against EMT by increasing HGF level and decreasing TGF-ß1 level. Our results also demonstrated HGF is one of the critical factor in MSCs anti- fibrosis.

CRL3-SPOP ubiquitin ligase complex suppresses the growth of diffuse large B-cell lymphoma by negatively regulating the MyD88/NF-κB signaling.

Recurrent oncogenic mutations of MyD88 have been identified in a variety of lymphoid malignancies. Gain-of-function mutations of MyD88 constitutively activate downstream NF-κB signaling pathways, resulting in increased cellular proliferation and survival. However, whether MyD88 activity can be aberrantly regulated in MyD88-wild-type lymphoid malignancies remains poorly understood. SPOP is an adaptor protein of CUL3-based E3 ubiquitin ligase complex and frequently mutated genes in prostate and endometrial cancers. In this study, we reveal that SPOP binds to and induces the nondegradative ubiquitination of MyD88 by recognizing an atypical SPOP-binding motif in MyD88. This modification blocks Myddosome assembly and downstream NF-κB activation. SPOP is mutated in a subset of lymphoid malignancies, including diffuse large B-cell lymphoma (DLBCL). Lymphoid malignancies-associated SPOP mutants exhibited impaired binding to MyD88 and suppression of NF-κB activation. The DLBCL-associated, SPOP-binding defective mutants of MyD88 escaped from SPOP-mediated ubiquitination, and their effect on NF-κB activation is stronger than that of wild-type MyD88. Moreover, SPOP suppresses DLBCL cell growth in vitro and tumor xenograft in vivo by inhibiting the MyD88/NF-κB signaling. Therefore, SPOP acts as a tumor suppressor in DLBCL. Mutations in the SPOP-MyD88 binding interface may disrupt the SPOP-MyD88 regulatory axis and promote aberrant MyD88/NF-κB activation and cell growth in DLCBL.