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"Lei Chen"
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Visual language transformer framework for multimodal dance performance evaluation and progression monitoring
Dance is often perceived as complex due to the need for coordinating multiple body movements and precisely aligning them with musical rhythm and content. Research in automatic dance performance assessment has the potential to enhance individuals’ sensorimotor skills and motion analysis. Recent studies on dance performance assessment primarily focus on evaluating simple dance movements using a single task, typically estimating final performance scores. We propose a novel transformer-based visual-language framework for multi-modal dance performance evaluation and progression monitoring. Our approach addresses two core challenges: the learning of feature representations for complex dance movements synchronized with music across diverse styles, genres, and expertise levels, and capturing the multi-task nature of dance performance evaluation. To achieve this, we integrate contrastive self-supervised learning, spatiotemporal graph convolutional networks (STGCN), long short-term memory networks (LSTM), and transformer-based text prompting. Our model evaluates three key tasks: (i) multilabel dance classification, (ii) dance quality estimation, and (iii) dance-music synchronization, leveraging primitive-based segmentation and multi-modal inputs. During the pre-training phase, we utilize contrastive loss to capture primitive-based features from complex dance motion and music data. For downstream tasks, we propose a transformer-based text prompting approach to conduct multi-task evaluations for the three assessment objectives. Our model outperforms in diverse downstream tasks. For multilabel dance classification, our model achieves a score of 75.20, representing a 10.25% improvement over CotrastiveDance, on the dance quality estimation task, the proposed model achieved a 92.09% lower loss on CotrastiveDance. For dance-music synchronization, our model excels with a score of 2.52, outperforming CotrastiveDance by 48.67%.
Journal Article
Security, privacy, and digital forensics in the Cloud
This title explains both Cloud security and privacy, and digital forensics in a unique, systematical way. It discusses both security and privacy of Cloud and digital forensics in a systematic way.
Book
Structural basis for the binding of DNP and purine nucleotides onto UCP1
Uncoupling protein 1 (UCP1) conducts protons through the inner mitochondrial membrane to uncouple mitochondrial respiration from ATP production, thereby converting the electrochemical gradient of protons into heat
1
,
2
. The activity of UCP1 is activated by endogenous fatty acids and synthetic small molecules, such as 2,4-dinitrophenol (DNP), and is inhibited by purine nucleotides, such as ATP
3
–
5
. However, the mechanism by which UCP1 binds to these ligands remains unknown. Here we present the structures of human UCP1 in the nucleotide-free state, the DNP-bound state and the ATP-bound state. The structures show that the central cavity of UCP1 is open to the cytosolic side. DNP binds inside the cavity, making contact with transmembrane helix 2 (TM2) and TM6. ATP binds in the same cavity and induces conformational changes in TM2, together with the inward bending of TM1, TM4, TM5 and TM6 of UCP1, resulting in a more compact structure of UCP1. The binding site of ATP overlaps with that of DNP, suggesting that ATP competitively blocks the functional engagement of DNP, resulting in the inhibition of the proton-conducting activity of UCP1.
Using cryo-electron microscopy, the structures of human UCP1 in the nucleotide-free state, the DNP activator-bound state, and the inhibitory ATP-bound state are resolved, providing details of how purine nucleotides inhibit UCP1.
Journal Article
Itaconate inhibits TET DNA dioxygenases to dampen inflammatory responses
As one of the most induced genes in activated macrophages,
immune-responsive gene 1
(
IRG1
) encodes a mitochondrial metabolic enzyme catalysing the production of itaconic acid (ITA). Although ITA has an anti-inflammatory property, the underlying mechanisms are not fully understood. Here we show that ITA is a potent inhibitor of the TET-family DNA dioxygenases. ITA binds to the same site on TET2 as the co-substrate α-ketoglutarate, inhibiting TET2 catalytic activity. Lipopolysaccharide treatment, which induces Irg1 expression and ITA accumulation, inhibits Tet activity in macrophages. Transcriptome analysis reveals that TET2 is a major target of ITA in suppressing lipopolysaccharide-induced genes, including those regulated by the NF-κB and STAT signalling pathways. In vivo, ITA decreases the levels of 5-hydroxymethylcytosine, reduces lipopolysaccharide-induced acute pulmonary oedema as well as lung and liver injury, and protects mice against lethal endotoxaemia, depending on the catalytic activity of Tet2. Our study thus identifies ITA as an immune modulatory metabolite that selectively inhibits TET enzymes to dampen the inflammatory responses.
Chen et al. report that the immune modulatory metabolite itaconic acid selectively inhibits the activity of TET DNA dioxygenases to repress the inflammatory responses.
Journal Article
Temporal profiles of viral load in posterior oropharyngeal saliva samples and serum antibody responses during infection by SARS-CoV-2: an observational cohort study
Coronavirus disease 2019 (COVID-19) causes severe community and nosocomial outbreaks. Comprehensive data for serial respiratory viral load and serum antibody responses from patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are not yet available. Nasopharyngeal and throat swabs are usually obtained for serial viral load monitoring of respiratory infections but gathering these specimens can cause discomfort for patients and put health-care workers at risk. We aimed to ascertain the serial respiratory viral load of SARS-CoV-2 in posterior oropharyngeal (deep throat) saliva samples from patients with COVID-19, and serum antibody responses.
We did a cohort study at two hospitals in Hong Kong. We included patients with laboratory-confirmed COVID-19. We obtained samples of blood, urine, posterior oropharyngeal saliva, and rectal swabs. Serial viral load was ascertained by reverse transcriptase quantitative PCR (RT-qPCR). Antibody levels against the SARS-CoV-2 internal nucleoprotein (NP) and surface spike protein receptor binding domain (RBD) were measured using EIA. Whole-genome sequencing was done to identify possible mutations arising during infection.
Between Jan 22, 2020, and Feb 12, 2020, 30 patients were screened for inclusion, of whom 23 were included (median age 62 years [range 37–75]). The median viral load in posterior oropharyngeal saliva or other respiratory specimens at presentation was 5·2 log10 copies per mL (IQR 4·1–7·0). Salivary viral load was highest during the first week after symptom onset and subsequently declined with time (slope −0·15, 95% CI −0·19 to −0·11; R2=0·71). In one patient, viral RNA was detected 25 days after symptom onset. Older age was correlated with higher viral load (Spearman's ρ=0·48, 95% CI 0·074–0·75; p=0·020). For 16 patients with serum samples available 14 days or longer after symptom onset, rates of seropositivity were 94% for anti-NP IgG (n=15), 88% for anti-NP IgM (n=14), 100% for anti-RBD IgG (n=16), and 94% for anti-RBD IgM (n=15). Anti-SARS-CoV-2-NP or anti-SARS-CoV-2-RBD IgG levels correlated with virus neutralisation titre (R2>0·9). No genome mutations were detected on serial samples.
Posterior oropharyngeal saliva samples are a non-invasive specimen more acceptable to patients and health-care workers. Unlike severe acute respiratory syndrome, patients with COVID-19 had the highest viral load near presentation, which could account for the fast-spreading nature of this epidemic. This finding emphasises the importance of stringent infection control and early use of potent antiviral agents, alone or in combination, for high-risk individuals. Serological assay can complement RT-qPCR for diagnosis.
Richard and Carol Yu, May Tam Mak Mei Yin, The Shaw Foundation Hong Kong, Michael Tong, Marina Lee, Government Consultancy Service, and Sanming Project of Medicine.
Journal Article
The Life Cycle Transitions of Temperate Phages: Regulating Factors and Potential Ecological Implications
Phages are viruses that infect bacteria. They affect various microbe-mediated processes that drive biogeochemical cycling on a global scale. Their influence depends on whether the infection is lysogenic or lytic. Temperate phages have the potential to execute both infection types and thus frequently switch their infection modes in nature, potentially causing substantial impacts on the host-phage community and relevant biogeochemical cycling. Understanding the regulating factors and outcomes of temperate phage life cycle transition is thus fundamental for evaluating their ecological impacts. This review thus systematically summarizes the effects of various factors affecting temperate phage life cycle decisions in both culturable phage-host systems and natural environments. The review further elucidates the ecological implications of the life cycle transition of temperate phages with an emphasis on phage/host fitness, host-phage dynamics, microbe diversity and evolution, and biogeochemical cycles.
Journal Article
Modern Image-Guided Surgery: A Narrative Review of Medical Image Processing and Visualization
Medical image analysis forms the basis of image-guided surgery (IGS) and many of its fundamental tasks. Driven by the growing number of medical imaging modalities, the research community of medical imaging has developed methods and achieved functionality breakthroughs. However, with the overwhelming pool of information in the literature, it has become increasingly challenging for researchers to extract context-relevant information for specific applications, especially when many widely used methods exist in a variety of versions optimized for their respective application domains. By being further equipped with sophisticated three-dimensional (3D) medical image visualization and digital reality technology, medical experts could enhance their performance capabilities in IGS by multiple folds. The goal of this narrative review is to organize the key components of IGS in the aspects of medical image processing and visualization with a new perspective and insights. The literature search was conducted using mainstream academic search engines with a combination of keywords relevant to the field up until mid-2022. This survey systemically summarizes the basic, mainstream, and state-of-the-art medical image processing methods as well as how visualization technology like augmented/mixed/virtual reality (AR/MR/VR) are enhancing performance in IGS. Further, we hope that this survey will shed some light on the future of IGS in the face of challenges and opportunities for the research directions of medical image processing and visualization.
Journal Article
Uncovering the mechanism of resveratrol in the treatment of diabetic kidney disease based on network pharmacology, molecular docking, and experimental validation
Background
Diabetic kidney disease (DKD) has been the leading cause of chronic kidney disease in developed countries. Evidence of the benefits of resveratrol (RES) for the treatment of DKD is accumulating. However, comprehensive therapeutic targets and underlying mechanisms through which RES exerts its effects against DKD are limited.
Methods
Drug targets of RES were obtained from Drugbank and SwissTargetPrediction Databases. Disease targets of DKD were obtained from DisGeNET, Genecards, and Therapeutic Target Database. Therapeutic targets for RES against DKD were identified by intersecting the drug targets and disease targets. GO functional enrichment analysis, KEGG pathway analysis, and disease association analysis were performed using the DAVID database and visualized by Cytoscape software. Molecular docking validation of the binding capacity between RES and targets was performed by UCSF Chimera software and SwissDock webserver. The high glucose (HG)-induced podocyte injury model, RT-qPCR, and western blot were used to verify the reliability of the effects of RES on target proteins.
Results
After the intersection of the 86 drug targets and 566 disease targets, 25 therapeutic targets for RES against DKD were obtained. And the target proteins were classified into 6 functional categories. A total of 11 cellular components terms and 27 diseases, and the top 20 enriched biological processes, molecular functions, and KEGG pathways potentially involved in the RES action against DKD were recorded. Molecular docking studies showed that RES had a strong binding affinity toward PPARA, ESR1, SLC2A1, SHBG, AR, AKR1B1, PPARG, IGF1R, RELA, PIK3CA, MMP9, AKT1, INSR, MMP2, TTR, and CYP2C9 domains. The HG-induced podocyte injury model was successfully constructed and validated by RT-qPCR and western blot. RES treatment was able to reverse the abnormal gene expression of PPARA, SHBG, AKR1B1, PPARG, IGF1R, MMP9, AKT1, and INSR.
Conclusions
RES may target PPARA, SHBG, AKR1B1, PPARG, IGF1R, MMP9, AKT1, and INSR domains to act as a therapeutic agent for DKD. These findings comprehensively reveal the potential therapeutic targets for RES against DKD and provide theoretical bases for the clinical application of RES in the treatment of DKD.
Journal Article
Selective and stable CO2 electroreduction at high rates via control of local H2O/CO2 ratio
Controlling the concentrations of H
2
O and CO
2
at the reaction interface is crucial for achieving efficient electrochemical CO
2
reduction. However, precise control of these variables during catalysis remains challenging, and the underlying mechanisms are not fully understood. Herein, guided by a multi-physics model, we demonstrate that tuning the local H
2
O/CO
2
concentrations is achievable by thin polymer coatings on the catalyst surface. Beyond the often-explored hydrophobicity, polymer properties of gas permeability and water-uptake ability are even more critical for this purpose. With these insights, we achieve CO
2
reduction on copper with Faradaic efficiency exceeding 87% towards multi-carbon products at a high current density of −2 A cm
−2
. Encouraging cathodic energy efficiency (>50%) is also observed at this high current density due to the substantially reduced cathodic potential. Additionally, we demonstrate stable CO
2
reduction for over 150 h at practically relevant current densities owning to the robust reaction interface. Moreover, this strategy has been extended to membrane electrode assemblies and other catalysts for CO
2
reduction. Our findings underscore the significance of fine-tuning the local H
2
O/CO
2
balance for future CO
2
reduction applications.
While challenging, controlling H
2
O/CO
2
concentrations at the reaction interface is critical for achieving efficient electrochemical CO
2
reduction. This work demonstrates that polymer coatings on the catalyst surface can effectively tune local H
2
O/CO
2
concentrations, leading to selective, energy efficient and robust CO
2
electroreduction.
Journal Article