HDAC6 inhibition releases HR23B to activate proteasomes, expand the tumor immunopeptidome and amplify T-cell antimyeloma activity.

Proteasomes degrade intracellular proteins to generate antigenic peptides that are recognized by the adaptive immune system and promote anticancer immunity. However, tumors subvert the antigen presentation machinery to escape immunosurveillance. We hypothesized that proteasome activation could concomitantly increase antigen abundance and diversity in multiple myeloma (MM) cells. High-throughput screens revealed that histone deacetylase 6 (HDAC6) inhibitors activated proteasomes to unmask neoantigens and amplify the tumor-specific antigenic landscape. Treatment of patient CD138+ cells with HDAC6 inhibitors significantly promoted the anti-myeloma activity of autologous CD8+ T-cells. Pharmacologic blockade and genetic ablation of the HDAC6 ubiquitin-binding domain released HR23B, which shuttles ubiquitinylated cargo to proteasomes, while silencing HDAC6 or HR23B in MM cells abolished the effect of HDAC6 inhibitors on proteasomes, antigen presentation and T-cell cytotoxicity. Taken together, our results demonstrate the paradigm-shifting translational impact of proteasome activators to expand the myeloma immunopeptidome and have revealed novel, actionable antigenic targets for T-cell-directed immunotherapy.

Effect of menopausal hormonal therapy on cardiovascular risks in Korean postmenopausal women: A nationwide cohort study.

OBJECTIVE: To evaluate the association between menopausal hormonal therapy (MHT) and the risk of cardiovascular disease (CVD), according to various regimens, dosages, routes of administration and starting ages of MHT. DESIGN: A population-based cohort study using the Korean National Health Insurance Services database. SETTING: Nationwide health insurance database. POPULATION: Women who reported entering menopause at an age of ≥40 years with no history of CVD in the national health examination. METHODS: The study population comprised 1 120 705 subjects enrolled between 2002 and 2019, categorised according to MHT status (MHT group, n = 319 007; non-MHT group, n = 801 698). MAIN OUTCOME MEASURES: Incidence of CVD (a composite of myocardial infarction and stroke). RESULTS: The incidence of CVD was 59 266 (7.4%) in the non-MHT group and 17 674 (5.5%) in the MHT group. After adjusting for confounding factors, an increased risk of CVD was observed with the administration of tibolone (hazard ratio, HR 1.143, 95% CI 1.117-1.170), oral estrogen (HR 1.246, 95% CI 1.198-1.295) or transdermal estrogen (HR 1.289, 95% CI 1.066-1.558), compared with the non-MHT group; the risk was based on an increased risk of stroke. The risk trends were consistent regardless of the age of starting MHT or the physicians' specialty. Among tibolone users, a longer period from entering menopause to taking tibolone and the use of any dosage (1.25 or 2.5 mg) were linked with a higher risk of CVD, compared with non-MHT users. CONCLUSIONS: This nationwide cohort study demonstrated an increased risk of CVD, driven mainly by an increased risk of stroke, among tibolone and oral or transdermal estrogen users, compared with that of non-MHT users.

Optimal antithrombotic strategy in patients with atrial fibrillation beyond 1 year after drug-eluting stent implantation: Design and rationale of the randomized ADAPT AF-DES trial.

BACKGROUND: Both anticoagulation and antiplatelet therapies are recommended after percutaneous coronary intervention (PCI) in patients with atrial fibrillation (AF). Although contemporary guidelines recommend discontinuation of antiplatelet therapy 1 year after drug-eluting stent (DES) implantation due to excessive bleeding risk, supporting randomized trials are still lacking. METHODS: The ADAPT AF-DES trial is a multicenter, prospective, open-label, randomized, non-inferiority trial, enrolling 960 patients with AF with a CHA2DS2-VASc score > 1, who underwent PCI with DES implantation at least 12 months before enrollment. Eligible patients are randomly assigned to receive either non-vitamin K antagonist oral anticoagulant (NOAC) monotherapy or NOAC plus clopidogrel combination therapy. The primary outcome is net adverse clinical event (NACE) at 1 year after randomization, defined as a composite of all-cause death, myocardial infarction, stent thrombosis, stroke, systemic embolism, and major or clinically relevant non-major bleeding, as defined by the International Society on Thrombosis and Hemostasis criteria. We hypothesize that NOAC monotherapy would be non-inferior to NOAC plus clopidogrel combination therapy for NACE in patients with AF beyond 12 months after DES implantation. CONCLUSIONS: The ADAPT AF-DES trial will evaluate the efficacy and safety of NOAC monotherapy versus NOAC plus clopidogrel combination therapy in patients with AF beyond 12 months after PCI with DES implantation. The ADAPT AF-DES trial will provide robust evidence for an optimal antithrombotic strategy in patients with AF after DES implantation. CLINICAL TRIAL REGISTRATION: https://www. CLINICALTRIALS: gov. Unique identifier: NCT04250116.

Piezo1 facilitates optimal T cell activation during tumor challenge.

Functional effector T cells in the tumor microenvironment (TME) are critical for successful anti-tumor responses. T cell anti-tumor function is dependent on their ability to differentiate from a naïve state, infiltrate into the tumor site, and exert cytotoxic functions. The factors dictating whether a particular T cell can successfully undergo these processes during tumor challenge are not yet completely understood. Piezo1 is a mechanosensitive cation channel with high expression on both CD4+ and CD8+ T cells. Previous studies have demonstrated that Piezo1 optimizes T cell activation and restrains the CD4+ regulatory T cell (Treg) pool in vitro and under inflammatory conditions in vivo. However, little is known about the role Piezo1 plays on CD4+ and CD8+ T cells in cancer. We hypothesized that disruption of Piezo1 on T cells impairs anti-tumor immunity in vivo by hindering inflammatory T cell responses. We challenged mice with T cell Piezo1 deletion (P1KO) with tumor models dependent on T cells for immune rejection. P1KO mice had the more aggressive tumors, higher tumor growth rates and were unresponsive to immune-mediated therapeutic interventions. We observed a decreased CD4:CD8 ratio in both the secondary lymphoid organs and TME of P1KO mice that correlated inversely with tumor size. Poor CD4+ helper T cell responses underpinned the immunodeficient phenotype of P1KO mice. Wild type CD8+ T cells are sub-optimally activated in vivo with P1KO CD4+ T cells, taking on a CD25loPD-1hi phenotype. Together, our results suggest that Piezo1 optimizes T cell activation in the context of a tumor response.

Association Between Body Mass Index and Clinical Outcomes According to Diabetes in Patients Who Underwent Percutaneous Coronary Intervention.

BACKGROUND AND OBJECTIVES: We evaluated the effect of diabetes on the relationship between body mass index (BMI) and clinical outcomes in patients following percutaneous coronary intervention (PCI) with drug-eluting stent implantation. METHODS: A total of 6,688 patients who underwent PCI were selected from five different registries led by Korean Multicenter Angioplasty Team. They were categorized according to their BMI into the following groups: underweight (<18.5 kg/m²), normal weight (18.5-24.9 kg/m²), overweight to obese (≥25.0 kg/m²). Major adverse cardiac and cerebrovascular events (MACCE), defined as a composite of death, nonfatal myocardial infarction, stroke, and target-vessel revascularization, were compared according to the BMI categories (underweight, normal and overweight to obese group) and diabetic status. All subjects completed 1-year follow-up. RESULTS: Among the 6,688 patients, 2,561 (38%) had diabetes. The underweight group compared to normal weight group had higher 1-year MACCE rate in both non-diabetic (adjusted hazard ratio [HR], 2.24; 95% confidence interval [CI], 1.04-4.84; p=0.039) and diabetic patients (adjusted HR, 2.86; 95% CI, 1.61-5.07; p<0.001). The overweight to obese group had a lower MACCE rate than the normal weight group in diabetic patients (adjusted HR, 0.67 [0.49-0.93]) but not in non-diabetic patients (adjusted HR, 1.06 [0.77-1.46]), with a significant interaction (p-interaction=0.025). CONCLUSIONS: Between the underweight and normal weight groups, the association between the BMI and clinical outcomes was consistent regardless of the presence of diabetes. However, better outcomes in overweight to obese over normal weight were observed only in diabetic patients. These results suggest that the association between BMI and clinical outcomes may differ according to the diabetic status.

Explainable AI for Medical Image Analysis in Medical Cyber-Physical Systems: Enhancing Transparency and Trustworthiness of IoMT.

Medical image analysis plays a crucial role in healthcare systems of Internet of Medical Things (IoMT), aiding in the diagnosis, treatment planning, and monitoring of various diseases. With the increasing adoption of artificial intelligence (AI) techniques in medical image analysis, there is a growing need for transparency and trustworthiness in decision-making. This study explores the application of explainable AI (XAI) in the context of medical image analysis within medical cyber-physical systems (MCPS) to enhance transparency and trustworthiness. To this end, this study proposes an explainable framework that integrates machine learning and knowledge reasoning. The explainability of the model is realized when the framework evolution target feature results and reasoning results are the same and are relatively reliable. However, using these technologies also presents new challenges, including the need to ensure the security and privacy of patient data from IoMT. Therefore, attack detection is an essential aspect of MCPS security. For the MCPS model with only sensor attacks, the necessary and sufficient conditions for detecting attacks are given based on the definition of sparse observability. The corresponding attack detector and state estimator are designed by assuming that some IoMT sensors are under protection. It is expounded that the IoMT sensors under protection play an important role in improving the efficiency of attack detection and state estimation. The experimental results show that the XAI in the context of medical image analysis within MCPS improves the accuracy of lesion classification, effectively removes low-quality medical images, and realizes the explainability of recognition results. This helps doctors understand the logic of the system's decision-making and can choose whether to trust the results based on the explanation given by the framework.

Effect of moderate-intensity statin with ezetimibe combination vs. high-intensity statin therapy according to sex in patients with atherosclerosis.

We aimed to evaluate sex differences in the effects of moderate-intensity statin with ezetimibe combination therapy (rosuvastatin 10 mg plus ezetimibe) versus high-intensity statin (rosuvastatin 20 mg) monotherapy in patients with atherosclerotic cardiovascular disease (ASCVD). This was a sex-specific subgroup analysis of the RACING trial that evaluated the interaction between sex and treatment strategies for the primary outcome (composite of cardiovascular death, major cardiovascular events, or nonfatal stroke at 3 years). Of 3780 patients in the RACING trial, 954 (25.2%) were women. Regardless of sex, the effect of moderate-intensity statin with ezetimibe combination therapy on primary outcome compared with high-intensity statin monotherapy was similar (hazard ratio [HR] 0.98 [0.63-1.52] in women; HR 0.90 [0.71-1.14] in men). The rate of discontinuation or dose reduction of study drugs due to intolerance was lower in the ezetimibe combination group than in the high-intensity statin monotherapy group in both women (4.5% vs. 8.6%, P = 0.014) and men (4.8% vs. 8.0%, P < 0.001). LDL cholesterol levels of < 70 mg/dL at 1, 2, and 3 years were more frequently achieved in the ezetimibe combination group than in the high-intensity statin monotherapy group (all P < 0.001) in both sexes. There were no significant interactions between sex and treatment groups regarding the primary outcome, discontinuation, or dose reduction of study drugs, or the proportion of achievement of LDL cholesterol levels < 70 mg/dL. The effect of ezetimibe combination therapy for the 3-year composite outcomes was not different in both men and women. The benefits of ezetimibe combination therapy on LDL cholesterol lowering and drug tolerance were similarly observed regardless of sex.Trial registration: https://clinicaltrials.gov ; Unique identifier: NCT03044665.

Proposal of a Token-Based Node Selection Mechanism for Node Distribution of Mobility IoT Blockchain Nodes.

Various elements, such as evolutions in IoT services resulting from sensoring by vehicle parts and advances in small communication technology devices, have significantly impacted the mass spread of mobility services that are provided to users in need of limited resources. In particular, business models are progressing away from one-off costs towards longer-term costs, as represented by shared services utilizing kick-boards or bicycles and subscription services for vehicle software. Advances in shared mobility services, as described, are calling for solutions that can enhance the reliability of data aggregated by users leveraging mobility services in the next-generation mobility areas. However, the mining process to renew status ensures continued network communication, and block creation demands high performance in the public block chain. Therefore, easing the mining process for state updates in public blockchains is a way to alleviate the high-performance process requirements of public blockchains. The proposed mechanism assigns token-based block creation authority instead of the mining method, which provides block creation authority to nodes that provide many resources. Blocks are created only by a group of participants with tokens, and after creation, tokens are updated and delivered to new nodes to form a new token group. Additionally, tokens are updated in each block after their initial creation, making it difficult to disguise the tokens and preventing resource-centered centralization.

Peptidylarginine deiminase 2 plays a key role in osteogenesis by enhancing RUNX2 stability through citrullination.

Peptidylarginine deiminase (PADI) 2 catalyzes the post-translational conversion of peptidyl-arginine to peptidyl-citrulline in a process called citrullination. However, the precise functions of PADI2 in bone formation and homeostasis remain unknown. In this study, our objective was to elucidate the function and regulatory mechanisms of PADI2 in bone formation employing global and osteoblast-specific Padi2 knockout mice. Our findings demonstrate that Padi2 deficiency leads to the loss of bone mass and results in a cleidocranial dysplasia (CCD) phenotype with delayed calvarial ossification and clavicular hypoplasia, due to impaired osteoblast differentiation. Mechanistically, Padi2 depletion significantly reduces RUNX2 levels, as PADI2-dependent stabilization of RUNX2 protected it from ubiquitin-proteasomal degradation. Furthermore, we discovered that PADI2 binds to RUNX2 and citrullinates it, and identified ten PADI2-induced citrullination sites on RUNX2 through high-resolution LC-MS/MS analysis. Among these ten citrullination sites, the R381 mutation in mouse RUNX2 isoform 1 considerably reduces RUNX2 levels, underscoring the critical role of citrullination at this residue in maintaining RUNX2 protein stability. In conclusion, these results indicate that PADI2 plays a distinct role in bone formation and osteoblast differentiation by safeguarding RUNX2 against proteasomal degradation. In addition, we demonstrate that the loss-of-function of PADI2 is associated with CCD, thereby providing a new target for the treatment of bone diseases.

Association of Early Hysterectomy With Risk of Cardiovascular Disease in Korean Women.

Importance: Women who undergo surgical hysterectomy before natural menopause may have an earlier increase in hematocrit and storage iron levels than those who continue menstruation, thereby increasing the risk of cardiovascular disease (CVD) at ages younger than usually seen. Examining this issue may provide important implications for women's cardiovascular health to both physicians and patients. Objective: To evaluate the association of hysterectomy with the risk of incident CVD among women before age 50 years. Design, Setting, and Participants: In this Korean population-based cohort study, 135 575 women aged 40 to 49 years were evaluated from January 1, 2011, to December 31, 2014. After propensity score matching in covariates including age, socioeconomic status, region, Charlson Comorbidity Index, hypertension, diabetes, dyslipidemia, menopause, menopausal hormone therapy, and adnexal surgery before inclusion, 55 539 pairs were included in the hysterectomy and nonhysterectomy groups. Participants were followed up until December 31, 2020. Data analysis was conducted from December 20, 2021, to February 17, 2022. Main Outcomes and Measures: The primary outcome was an incidental CVD, a composite of myocardial infarction, coronary artery revascularization, and stroke. The individual components of the primary outcome were also evaluated. Results: A total of 55 539 pairs were included; median age in the combined groups was 45 (IQR, 42-47) years. During median follow-up periods in the hysterectomy group of 7.9 (IQR, 6.8-8.9) years and nonhysterectomy group of 7.9 (IQR, 6.8-8.8) years, the incidence of CVD was 115 per 100 000 person-years for the hysterectomy group and 96 per 100 000 person-years for the nonhysterectomy group. After adjusting for confounding factors, the hysterectomy group had an increased risk of CVD compared with the nonhysterectomy group (hazard ratio [HR], 1.25; 95% CI, 1.09-1.44). The incidences of myocardial infarction and coronary artery revascularization were comparable between the groups, whereas the risk of stroke was significantly higher in the hysterectomy group (HR, 1.31; 95% CI, 1.12-1.53). Even after excluding women who underwent oophorectomy, the hysterectomy group had higher risks of CVD (HR, 1.24; 95% CI, 1.06-1.44). Conclusions and Relevance: The findings of this cohort study suggest early menopause owing to hysterectomy was associated with increased risks for a composite of CVD, particularly stroke.

The synthetic oleanane triterpenoid CDDO-2P-Im binds GRP78/BiP to induce unfolded protein response-mediated apoptosis in myeloma.

Synthetic oleanane triterpenoids (SOTs) are small molecules with broad anticancer properties. A recently developed SOT, 1-[2-cyano-3,12-dioxooleana-1,9(11)-dien-28-oyl]-4(-pyridin-2-yl)-1H-imidazole (CDDO-2P-Im or '2P-Im'), exhibits enhanced activity and improved pharmacokinetics over CDDO-Im, a previous generation SOT. However, the mechanisms leading to these properties are not defined. Here, we show the synergy of 2P-Im and the proteasome inhibitor ixazomib in human multiple myeloma (MM) cells and 2P-Im activity in a murine model of plasmacytoma. RNA sequencing and quantitative reverse transcription PCR revealed the upregulation of the unfolded protein response (UPR) in MM cells upon 2P-lm treatment, implicating the activation of the UPR as a key step in 2P-Im-induced apoptosis. Supporting this hypothesis, the deletion of genes encoding either protein kinase R-like endoplasmic reticulum kinase (PERK) or DNA damage-inducible transcript 3 protein (DDIT3; also known as CHOP) impaired the MM response to 2P-Im, as did treatment with ISRIB, integrated stress response inhibitor, which inhibits UPR signaling downstream of PERK. Finally, both drug affinity responsive target stability and thermal shift assays demonstrated direct binding of 2P-Im to endoplasmic reticulum chaperone BiP (GRP78/BiP), a stress-inducible key signaling molecule of the UPR. These data reveal GRP78/BiP as a novel target of SOTs, and specifically of 2P-Im, and suggest the potential broader utility of this class of small molecules as modulators of the UPR.

ssFPN: Scale Sequence (S2) Feature-Based Feature Pyramid Network for Object Detection.

Object detection is a fundamental task in computer vision. Over the past several years, convolutional neural network (CNN)-based object detection models have significantly improved detection accuracyin terms of average precision (AP). Furthermore, feature pyramid networks (FPNs) are essential modules for object detection models to consider various object scales. However, the AP for small objects is lower than the AP for medium and large objects. It is difficult to recognize small objects because they do not have sufficient information, and information is lost in deeper CNN layers. This paper proposes a new FPN model named ssFPN (scale sequence (S2) feature-based feature pyramid network) to detect multi-scale objects, especially small objects. We propose a new scale sequence (S2) feature that is extracted by 3D convolution on the level of the FPN. It is defined and extracted from the FPN to strengthen the information on small objects based on scale-space theory. Motivated by this theory, the FPN is regarded as a scale space and extracts a scale sequence (S2) feature by three-dimensional convolution on the level axis of the FPN. The defined feature is basically scale-invariant and is built on a high-resolution pyramid feature map for small objects. Additionally, the deigned S2 feature can be extended to most object detection models based on FPNs. We also designed a feature-level super-resolution approach to show the efficiency of the scale sequence (S2) feature. We verified that the scale sequence (S2) feature could improve the classification accuracy for low-resolution images by training a feature-level super-resolution model. To demonstrate the effect of the scale sequence (S2) feature, experiments on the scale sequence (S2) feature built-in object detection approach including both one-stage and two-stage models were conducted on the MS COCO dataset. For the two-stage object detection models Faster R-CNN and Mask R-CNN with the S2 feature, AP improvements of up to 1.6% and 1.4%, respectively, were achieved. Additionally, the APS of each model was improved by 1.2% and 1.1%, respectively. Furthermore, the one-stage object detection models in the YOLO series were improved. For YOLOv4-P5, YOLOv4-P6, YOLOR-P6, YOLOR-W6, and YOLOR-D6 with the S2 feature, 0.9%, 0.5%, 0.5%, 0.1%, and 0.1% AP improvements were observed. For small object detection, the APS increased by 1.1%, 1.1%, 0.9%, 0.4%, and 0.1%, respectively. Experiments using the feature-level super-resolution approach with the proposed scale sequence (S2) feature were conducted on the CIFAR-100 dataset. By training the feature-level super-resolution model, we verified that ResNet-101 with the S2 feature trained on LR images achieved a 55.2% classification accuracy, which was 1.6% higher than for ResNet-101 trained on HR images.

Oral TGF-ßR1 inhibitor Vactosertib promotes osteosarcoma regression by targeting tumor proliferation and enhancing anti-tumor immunity.

Osteosarcoma (OS) is an aggressive malignant bone cancer, with refractory and metastatic disease remaining a significant challenge. Transforming growth factor-ß1 (TGF-ß) is a potent immune suppressive cytokine in OS and the TGF-ß is increased in the sera of OS patients and this increase is associated with high-grade OS and lung metastases. Therefore, blocking TGF-ß1 signaling may be a novel therapy for OS treatment. Here we show that blocking TGF-ß1 signaling using TGF-ßR1 inhibitor, Vactosertib, significantly inhibited OS proliferation in vitro and in vivo. Notably, Vactosertib inhibits c-Myc expression in the OS cells. Vactosertib increased immune effectors (IFNγ+CD8+ cells and NK cells) and inhibited immune suppressors (M2-like TAM, MDSC) in the OS tumor microenvironment. Our results suggest that inhibition of TGF-ß1 signaling is an effective therapeutic strategy against OS through a multi-pronged approach that targets tumor intrinsic and extrinsic factors to achieve optimal immune-effector functions and maximal clinical response.

Body mass index affecting ticagrelor monotherapy vs. ticagrelor with aspirin in patients with acute coronary syndrome: A pre-specified sub-analysis of the TICO randomized trial.

Background: Although ticagrelor monotherapy after 3-month dual antiplatelet therapy (DAPT) results in a significantly greater net clinical benefit over that with ticagrelor-based 12-month DAPT in patients with acute coronary syndrome (ACS), it remains uncertain whether this effect is dependent on body mass index (BMI). We aimed to evaluate the BMI-dependent effect of these treatment strategies on clinical outcomes. Methods: This was a pre-specified subgroup analysis from the TICO trial (Ticagrelor Monotherapy After 3 Months in Patients Treated With New Generation Sirolimus-eluting Stent for Acute Coronary Syndrome), evaluating the interaction between BMI and treatment strategies for the primary outcome [composite of major bleeding and adverse cardiac and cerebrovascular events (MACCE): death, myocardial infarction, stent thrombosis, stroke, or target-vessel revascularization]. The secondary outcomes were major bleeding and MACCE. Results: Based on a pre-specified BMI threshold of 25 kg/m2, 3,056 patients were stratified. Patients with BMI <25 kg/m2 had a higher risk of primary and secondary outcomes than those with BMI ≥25 kg/m2. Regardless of the BMI subgroup, the effects of ticagrelor monotherapy after 3-month DAPT on the primary outcome (p int = 0.61), major bleeding (p int = 0.76), and MACCE (p int = 0.80) were consistent without significant interaction compared with ticagrelor-based 12-month DAPT. The treatment effects according to the BMI quartiles and age, sex, and diabetic status were also consistent without significant interaction. Conclusion: The BMI-dependent impact of ticagrelor monotherapy after 3-month DAPT compared with 12-month DAPT on clinical outcomes was not heterogeneous in patients with ACS. Clinical Trial Registration: [www.ClinicalTrials.gov], identifier [NCT02494895].

Isolation and identification of extracellular matrix proteins from oil-based CASPERized mouse brains for matrisomal analysis.

The extracellular matrix (ECM) components present within all tissues and organs help to maintain the cytoskeletal architecture and tissue morphology. Although the ECM plays a role in cellular events and signaling pathways, it has not been well studied due its insolubility and complexity. Brain tissue has a higher cell density and weaker mechanical strength than other tissues in the body. When removing cells using a general decellularization method to produce scaffolds and obtain ECM proteins, various problems must be considered because tissues are easily damaged. To retain the brain shape and ECM components, we performed decellularization in combination with polymerization. We immersed mouse brains in oil for polymerization and decellularization via O-CASPER (Oil-based Clinically and Experimentally Applicable Acellular Tissue Scaffold Production for Tissue Engineering and Regenerative Medicine) and then isolated ECM components using sequential matrisome preparation reagents (SMPRs), namely, RIPA, PNGase F, and concanavalin A. Adult mouse brains were preserved with our decellularization method. Western blot and LC-MS/MS analyses revealed that ECM components, including collagen and laminin, were isolated efficiently from decellularized mouse brains using SMPRs. Our method will be useful to obtain matrisomal data and perform functional studies using adult mouse brains and other tissues.

Stent expansion evaluated by optical coherence tomography and subsequent outcomes.

Regarding stent expansion indices, previous optical coherence tomography (OCT) studies have shown minimal stent area (MSA) to be most predictive of adverse events. We sought to evaluate the impact of various stent expansion and apposition indices by post-stent OCT on clinical outcomes and find OCT-defined optimal stent implantation criteria. A total of 1071 patients with 1123 native coronary artery lesions treated with new-generation drug-eluting stents with OCT guidance and final post-stent OCT analysis were included. Several stent expansion indices (MSA, MSA/average reference lumen area, MSA/distal reference lumen area, mean stent expansion, and stent expansion by linear model [stent volume/adaptive reference lumen volume]) were evaluated for their association with device-oriented clinical endpoints (DoCE) including cardiac death, target vessel-related myocardial infarction (MI) or stent thrombosis, and target lesion revascularization. MSA was negatively correlated with the risk of DoCE (hazard ratio [HR] 0.80 [0.68‒0.94]). However, stent expansion by linear model representing the overall volumetric stent expansion was associated with greater risk of DoCE (HR 1.02 [1.00‒1.04]). As categorical criteria, MSA < 5.0 mm2 (HR 3.90 [1.99‒7.65]), MSA/distal reference lumen area < 90% (HR 2.16 [1.12‒4.19]), and stent expansion by linear model ≥ 65.0% (HR 1.95 [1.03‒3.89]) were independently associated with DoCE. This OCT study highlights the importance of sufficient stent expansion to achieve adequate, absolute, and relative MSA criteria for improving clinical outcome. It also emphasises that overall volumetric excessive stent expansion may have detrimental effects.

Enhanced Ca2+-channeling complex formation at the ER-mitochondria interface underlies the pathogenesis of alcohol-associated liver disease.

Ca2+ overload-induced mitochondrial dysfunction is considered as a major contributing factor in the pathogenesis of alcohol-associated liver disease (ALD). However, the initiating factors that drive mitochondrial Ca2+ accumulation in ALD remain elusive. Here, we demonstrate that an aberrant increase in hepatic GRP75-mediated mitochondria-associated ER membrane (MAM) Ca2+-channeling (MCC) complex formation promotes mitochondrial dysfunction in vitro and in male mouse model of ALD. Unbiased transcriptomic analysis reveals PDK4 as a prominently inducible MAM kinase in ALD. Analysis of human ALD cohorts further corroborate these findings. Additional mass spectrometry analysis unveils GRP75 as a downstream phosphorylation target of PDK4. Conversely, non-phosphorylatable GRP75 mutation or genetic ablation of PDK4 prevents alcohol-induced MCC complex formation and subsequent mitochondrial Ca2+ accumulation and dysfunction. Finally, ectopic induction of MAM formation reverses the protective effect of PDK4 deficiency in alcohol-induced liver injury. Together, our study defines a mediatory role of PDK4 in promoting mitochondrial dysfunction in ALD.

Attention-Based Bi-Prediction Network for Versatile Video Coding (VVC) over 5G Network.

As the demands of various network-dependent services such as Internet of things (IoT) applications, autonomous driving, and augmented and virtual reality (AR/VR) increase, the fifthgeneration (5G) network is expected to become a key communication technology. The latest video coding standard, versatile video coding (VVC), can contribute to providing high-quality services by achieving superior compression performance. In video coding, inter bi-prediction serves to improve the coding efficiency significantly by producing a precise fused prediction block. Although block-wise methods, such as bi-prediction with CU-level weight (BCW), are applied in VVC, it is still difficult for the linear fusion-based strategy to represent diverse pixel variations inside a block. In addition, a pixel-wise method called bi-directional optical flow (BDOF) has been proposed to refine bi-prediction block. However, the non-linear optical flow equation in BDOF mode is applied under assumptions, so this method is still unable to accurately compensate various kinds of bi-prediction blocks. In this paper, we propose an attention-based bi-prediction network (ABPN) to substitute for the whole existing bi-prediction methods. The proposed ABPN is designed to learn efficient representations of the fused features by utilizing an attention mechanism. Furthermore, the knowledge distillation (KD)- based approach is employed to compress the size of the proposed network while keeping comparable output as the large model. The proposed ABPN is integrated into the VTM-11.0 NNVC-1.0 standard reference software. When compared with VTM anchor, it is verified that the BD-rate reduction of the lightweighted ABPN can be up to 5.89% and 4.91% on Y component under random access (RA) and low delay B (LDB), respectively.

A disease-associated XPA allele interferes with TFIIH binding and primarily affects transcription-coupled nucleotide excision repair.

XPA is a central scaffold protein that coordinates the assembly of repair complexes in the global genome (GG-NER) and transcription-coupled nucleotide excision repair (TC-NER) subpathways. Inactivating mutations in XPA cause xeroderma pigmentosum (XP), which is characterized by extreme UV sensitivity and a highly elevated skin cancer risk. Here, we describe two Dutch siblings in their late forties carrying a homozygous H244R substitution in the C-terminus of XPA. They present with mild cutaneous manifestations of XP without skin cancer but suffer from marked neurological features, including cerebellar ataxia. We show that the mutant XPA protein has a severely weakened interaction with the transcription factor IIH (TFIIH) complex leading to an impaired association of the mutant XPA and the downstream endonuclease ERCC1-XPF with NER complexes. Despite these defects, the patient-derived fibroblasts and reconstituted knockout cells carrying the XPA-H244R substitution show intermediate UV sensitivity and considerable levels of residual GG-NER (~50%), in line with the intrinsic properties and activities of the purified protein. By contrast, XPA-H244R cells are exquisitely sensitive to transcription-blocking DNA damage, show no detectable recovery of transcription after UV irradiation, and display a severe deficiency in TC-NER-associated unscheduled DNA synthesis. Our characterization of a new case of XPA deficiency that interferes with TFIIH binding and primarily affects the transcription-coupled subpathway of nucleotide excision repair, provides an explanation of the dominant neurological features in these patients, and reveals a specific role for the C-terminus of XPA in TC-NER.

Raw Electroencephalogram-Based Cognitive Workload Classification Using Directed and Nondirected Functional Connectivity Analysis and Deep Learning.

With the phenomenal rise in internet-of-things devices, the use of electroencephalogram (EEG) based brain-computer interfaces (BCIs) can empower individuals to control equipment with thoughts. These allow BCI to be used and pave the way for pro-active health management and the development of internet-of-medical-things architecture. However, EEG-based BCIs have low fidelity, high variance, and EEG signals are very noisy. These challenges compel researchers to design algorithms that can process big data in real-time while being robust to temporal variations and other variations in the data. Another issue in designing a passive BCI is the regular change in user's cognitive state (measured through cognitive workload). Though considerable amount of research has been conducted on this front, methods that could withstand high variability in EEG data and still reflect the neuronal dynamics of cognitive state variations are lacking and much needed in literature. In this research, we evaluate the efficacy of a combination of functional connectivity algorithms and state-of-the-art deep learning algorithms for the classification of three different levels of cognitive workload. We acquire 64-channel EEG data from 23 participants executing the n-back task at three different levels; 1-back (low-workload condition), 2-back (medium-workload condition), and 3-back (high-workload condition). We compared two different functional connectivity algorithms, namely phase transfer entropy (PTE) and mutual information (MI). PTE is a directed functional connectivity algorithm, whereas MI is non-directed. Both methods are suitable for extracting functional connectivity matrices in real-time, which could eventually be used for rapid, robust, and efficient classification. For classification, we use the recently proposed BrainNetCNN deep learning model, designed specifically to classify functional connectivity matrices. Results reveal a classification accuracy of 92.81% with MI and BrainNetCNN and a staggering 99.50% with PTE and BrainNetCNN on test data. PTE can yield a higher classification accuracy due to its robustness to linear mixing of the data and its ability to detect functional connectivity across a range of analysis lags.