Showing papers by "Sun Yat-sen University published in 2021"
Daniel J. Klionsky1, Amal Kamal Abdel-Aziz2, Sara Abdelfatah3, Mahmoud Abdellatif4 +2980 more•Institutions (777)
TL;DR: In this article, the authors present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes.
Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.
1,129 citations
TL;DR: This paper presents a comprehensive review of recent progress in deep learning methods for point clouds, covering three major tasks, including 3D shape classification, 3D object detection and tracking, and 3D point cloud segmentation.
Abstract: Point cloud learning has lately attracted increasing attention due to its wide applications in many areas, such as computer vision, autonomous driving, and robotics As a dominating technique in AI, deep learning has been successfully used to solve various 2D vision problems However, deep learning on point clouds is still in its infancy due to the unique challenges faced by the processing of point clouds with deep neural networks Recently, deep learning on point clouds has become even thriving, with numerous methods being proposed to address different problems in this area To stimulate future research, this paper presents a comprehensive review of recent progress in deep learning methods for point clouds It covers three major tasks, including 3D shape classification, 3D object detection and tracking, and 3D point cloud segmentation It also presents comparative results on several publicly available datasets, together with insightful observations and inspiring future research directions
1,021 citations
Erola Pairo-Castineira1, Erola Pairo-Castineira2, Sara Clohisey2, Lucija Klaric1 +1446 more•Institutions (27)
TL;DR: The GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2244 critically ill Covid-19 patients from 208 UK intensive care units is reported, finding evidence in support of a causal link from low expression of IFNAR2, and high expression of TYK2, to life-threatening disease.
Abstract: Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10−8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10−8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 × 10−12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10−8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte–macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice. A genome-wide association study of critically ill patients with COVID-19 identifies genetic signals that relate to important host antiviral defence mechanisms and mediators of inflammatory organ damage that may be targeted by repurposing drug treatments.
941 citations
TL;DR: Wang et al. as mentioned in this paper developed a deep learning-based CT diagnosis system to identify patients with COVID-19, which achieved an AUC of 0.99, recall (sensitivity) of 0.,93, and precision of 0,96.
Abstract: A novel coronavirus (COVID-19) has emerged recently as an acute respiratory syndrome. The outbreak was originally reported in Wuhan, China, but has subsequently been spread world-widely. As the COVID-19 continues to spread rapidly across the world, computed tomography (CT) has become essentially important for fast diagnoses. Thus, it is urgent to develop an accurate computer-aided method to assist clinicians to identify COVID-19-infected patients by CT images. We collected chest CT scans of 88 patients diagnosed with the COVID-19 from hospitals of two provinces in China, 101 patients infected with bacteria pneumonia, and 86 healthy persons for comparison and modeling. A deep learning-based CT diagnosis system was developed to identify patients with COVID-19. The experimental results showed that our model can accurately identify the COVID-19 patients from the healthy with an AUC of 0.99, recall (sensitivity) of 0.93, and precision of 0.96. When integrating three types of CT images, our model achieved a recall of 0.93 with precision of 0.86 for discriminating COVID-19 patients from others. Moreover, our model could extract main lesion features, especially the ground-glass opacity (GGO) that is visually helpful for assisted diagnoses by doctors. An online server is available for online diagnoses with CT images by http://biomed.nscc-gz.cn/model.php.
477 citations
National Institute for Health Research1, University of London2, University of Auckland3, Anglia Ruskin University4, University of Cambridge5, Sun Yat-sen University6, Queen's University Belfast7, The Fred Hollows Foundation8, Mbarara University of Science and Technology9, Ministry of Health and Family Welfare10, University of Geneva11, St Thomas' Hospital12, Leeds Teaching Hospitals NHS Trust13, Southwest University of Visual Arts14, Orbis International15, International Agency for the Prevention of Blindness16, University of Cape Town17, University Hospitals Birmingham NHS Foundation Trust18, University of Michigan19, Emory University20, Johns Hopkins University21, Massachusetts Eye and Ear Infirmary22, University of São Paulo23, University of Nairobi24, Seva Foundation25, Tilganga Institute of Ophthalmology26, Heidelberg University27, University of New South Wales28, The George Institute for Global Health29, L V Prasad Eye Institute30, College of Health Sciences, Bahrain31, Muhimbili University of Health and Allied Sciences32, International Institute of Minnesota33, University of the West Indies34, University of Melbourne35, Kenya Medical Training College36, Federal University of São Paulo37, Capital Medical University38, Singapore National Eye Center39, National University of Singapore40, Pan American Health Organization41, Brien Holden Vision Institute42, University of Calabar43
TL;DR: In this paper, the authors defined eye health as maximised vision, ocular health, and functional ability, thereby contributing to overall health and wellbeing, social inclusion, and quality of life.
435 citations
TL;DR: Recent progress made in the development of PSs for overcoming nonnegligible challenges remain for its further clinical use, including finite tumor suppression, poor tumor targeting, and limited therapeutic depth are summarized.
Abstract: Photodynamic therapy (PDT), a therapeutic mode involving light triggering, has been recognized as an attractive oncotherapy treatment. However, nonnegligible challenges remain for its further clinical use, including finite tumor suppression, poor tumor targeting, and limited therapeutic depth. The photosensitizer (PS), being the most important element of PDT, plays a decisive role in PDT treatment. This review summarizes recent progress made in the development of PSs for overcoming the above challenges. This progress has included PSs developed to display enhanced tolerance of the tumor microenvironment, improved tumor-specific selectivity, and feasibility of use in deep tissue. Based on their molecular photophysical properties and design directions, the PSs are classified by parent structures, which are discussed in detail from the molecular design to application. Finally, a brief summary of current strategies for designing PSs and future perspectives are also presented. We expect the information provided in this review to spur the further design of PSs and the clinical development of PDT-mediated cancer treatments.
385 citations
Peking University1, Second Military Medical University2, Chinese Academy of Sciences3, Capital Medical University4, University of Science and Technology of China5, Southern University of Science and Technology6, Harbin Institute of Technology7, Sun Yat-sen University8, Peking Union Medical College9, Third Military Medical University10, Guangzhou Medical University11, Beijing Normal University12, Shantou University13, Wuhan University14, Huazhong University of Science and Technology15, Shanghai Jiao Tong University16, Chinese PLA General Hospital17, Fudan University18, Guangzhou Institutes of Biomedicine and Health19
TL;DR: In this article, the authors applied single-cell RNA sequencing to 284 samples from 196 COVID-19 patients and controls and created a comprehensive immune landscape with 1.46 million cells.
385 citations
TL;DR: A pan-cancer analysis of single myeloid cells from 210 patients across 15 human cancer types identified distinct features of TIMs across cancer types and suggested future avenues for rational, targeted immunotherapies.
374 citations
TL;DR: Wang et al. as discussed by the authors explored what trigger the public's pandemic "travel fear" and how people impose self-protection, coping and resilience related to travel and found that travel fear can evoke different coping strategies, which increases people's psychological resilience and adoption of cautious travel behaviors.
372 citations
TL;DR: A convolutional autoencoder deep learning framework to support unsupervised image features learning for lung nodule through unlabeled data, which only needs a small amount of labeled data for efficient feature learning.
Abstract: At present, computed tomography (CT) is widely used to assist disease diagnosis. Especially, computer aided diagnosis (CAD) based on artificial intelligence (AI) recently exhibits its importance in intelligent healthcare. However, it is a great challenge to establish an adequate labeled dataset for CT analysis assistance, due to the privacy and security issues. Therefore, this paper proposes a convolutional autoencoder deep learning framework to support unsupervised image features learning for lung nodule through unlabeled data, which only needs a small amount of labeled data for efficient feature learning. Through comprehensive experiments, it shows that the proposed scheme is superior to other approaches, which effectively solves the intrinsic labor-intensive problem during artificial image labeling. Moreover, it verifies that the proposed convolutional autoencoder approach can be extended for similarity measurement of lung nodules images. Especially, the features extracted through unsupervised learning are also applicable in other related scenarios.
345 citations
TL;DR: Aghanim et al. as mentioned in this paper used the same data set to derive a 95% upper bound of 0.020 using the principal component analysis (PCA) model and uniform priors on the PCA mode amplitudes.
Abstract: Author(s): Aghanim, N; Akrami, Y; Ashdown, M; Aumont, J; Baccigalupi, C; Ballardini, M; Banday, AJ; Barreiro, RB; Bartolo, N; Basak, S; Battye, R; Benabed, K; Bernard, JP; Bersanelli, M; Bielewicz, P; Bock, JJ; Bond, JR; Borrill, J; Bouchet, FR; Boulanger, F; Bucher, M; Burigana, C; Butler, RC; Calabrese, E; Cardoso, JF; Carron, J; Challinor, A; Chiang, HC; Chluba, J; Colombo, LPL; Combet, C; Contreras, D; Crill, BP; Cuttaia, F; De Bernardis, P; De Zotti, G; Delabrouille, J; Delouis, JM; DI Valentino, E; DIego, JM; Dore, O; Douspis, M; Ducout, A; Dupac, X; Dusini, S; Efstathiou, G; Elsner, F; Enslin, TA; Eriksen, HK; Fantaye, Y; Farhang, M; Fergusson, J; Fernandez-Cobos, R; Finelli, F; Forastieri, F; Frailis, M; Fraisse, AA; Franceschi, E; Frolov, A; Galeotta, S; Galli, S; Ganga, K; Genova-Santos, RT; Gerbino, M; Ghosh, T; Gonzalez-Nuevo, J; Gorski, KM; Gratton, S; Gruppuso, A; Gudmundsson, JE; Hamann, J; Handley, W; Hansen, FK; Herranz, D; Hildebrandt, SR; Hivon, E; Huang, Z; Jaffe, AH; Jones, WC; Karakci, A; Keihanen, E; Keskitalo, R; Kiiveri, K; Kim, J; Kisner, TS | Abstract: In the original version, the bounds given in Eqs. (87a) and (87b) on the contribution to the early-time optical depth, (15,30), contained a numerical error in deriving the 95th percentile from the Monte Carlo samples. The corrected 95% upper bounds are: τ(15,30) l 0:018 (lowE, flat τ(15, 30), FlexKnot), (1) τ(15, 30) l 0:023 (lowE, flat knot, FlexKnot): (2) These bounds are a factor of 3 larger than the originally reported results. Consequently, the new bounds do not significantly improve upon previous results from Planck data presented in Millea a Bouchet (2018) as was stated, but are instead comparable. Equations (1) and (2) give results that are now similar to those of Heinrich a Hu (2021), who used the same Planck 2018 data to derive a 95% upper bound of 0.020 using the principal component analysis (PCA) model and uniform priors on the PCA mode amplitudes.
Fudan University1, Harbin Medical University2, Chongqing Medical University3, Sichuan University4, Sun Yat-sen University5, Anhui Medical University6, Nanjing University7, Zhejiang University8, Jining Medical University9, Huazhong University of Science and Technology10, First Affiliated Hospital of Wenzhou Medical University11, Nanchang University12, Xi'an Jiaotong University13, Bengbu Medical College14, Jilin University15, Peking Union Medical College Hospital16, Southeast University17, Zhengzhou University18, Southwest General Health Center19
TL;DR: The phase 2-3 ORIENT-32 study as discussed by the authors compared sintilimab (a PD-1 inhibitor) plus IBI305, a bevacizumab biosimilar, versus sorafenib as a first-line treatment for unresectable HBV-associated hepatocellular carcinoma.
Abstract: Summary Background China has a high burden of hepatocellular carcinoma, and hepatitis B virus (HBV) infection is the main causative factor. Patients with hepatocellular carcinoma have a poor prognosis and a substantial unmet clinical need. The phase 2–3 ORIENT-32 study aimed to assess sintilimab (a PD-1 inhibitor) plus IBI305, a bevacizumab biosimilar, versus sorafenib as a first-line treatment for unresectable HBV-associated hepatocellular carcinoma. Methods This randomised, open-label, phase 2–3 study was done at 50 clinical sites in China. Patients aged 18 years or older with histologically or cytologically diagnosed or clinically confirmed unresectable or metastatic hepatocellular carcinoma, no previous systemic treatment, and a baseline Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1 were eligible for inclusion. In the phase 2 part of the study, patients received intravenous sintilimab (200 mg every 3 weeks) plus intravenous IBI305 (15 mg/kg every 3 weeks). In the phase 3 part, patients were randomly assigned (2:1) to receive either sintilimab plus IBI305 (sintilimab–bevacizumab biosimilar group) or sorafenib (400 mg orally twice daily; sorafenib group), until disease progression or unacceptable toxicity. Randomisation was done using permuted block randomisation, with a block size of six, via an interactive web response system, and stratified by macrovascular invasion or extrahepatic metastasis, baseline α-fetoprotein, and ECOG performance status. The primary endpoint of the phase 2 part of the study was safety, assessed in all patients who received at least one dose of study drug. The co-primary endpoints of the phase 3 part of the study were overall survival and independent radiological review committee (IRRC)-assessed progression-free survival according to Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 in the intention-to-treat population. The study is registered with ClinicalTrials.gov , NCT03794440 . The study is closed to new participants and follow-up is ongoing for long-term outcomes. Findings Between Feb 11, 2019 and Jan 15, 2020, we enrolled 595 patients: 24 were enrolled directly into the phase 2 safety run-in and 571 were randomly assigned to sintilimab–bevacizumab biosimilar (n=380) or sorafenib (n=191). In the phase 2 part of the trial, 24 patients received at least one dose of the study drug, with an objective response rate of 25·0% (95% CI 9·8–46·7). Based on the preliminary safety and activity data of the phase 2 part, in which grade 3 or worse treatment-related adverse events occurred in seven (29%) of 24 patients, the randomised phase 3 part was started. At data cutoff (Aug 15, 2020), the median follow-up was 10·0 months (IQR 8·5–11·7) in the sintilimab–bevacizumab biosimilar group and 10·0 months (8·4–11·7) in the sorafenib group. Patients in the sintilimab–bevacizumab biosimilar group had a significantly longer IRRC-assessed median progression-free survival (4·6 months [95% CI 4·1–5·7]) than did patients in the sorafenib group (2·8 months [2·7–3·2]; stratified hazard ratio [HR] 0·56, 95% CI 0·46–0·70; p Interpretation Sintilimab plus IBI305 showed a significant overall survival and progression-free survival benefit versus sorafenib in the first-line setting for Chinese patients with unresectable, HBV-associated hepatocellular carcinoma, with an acceptable safety profile. This combination regimen could provide a novel treatment option for such patients. Funding Innovent Biologics. Translation For the Chinese translation of the abstract see Supplementary Materials section.
TL;DR: In this article, a low-cost additive, glucose, was used to modulate the typical ZnSO4 electrolyte system for improving reversible plating/stripping on Zn anode for high-performance Zn ion batteries.
Abstract: Dendrite growth and by-products in Zn metal aqueous batteries have impeded their development as promising energy storage devices We utilize a low-cost additive, glucose, to modulate the typical ZnSO4 electrolyte system for improving reversible plating/stripping on Zn anode for high-performance Zn ion batteries (ZIBs) Combing experimental characterizations and theoretical calculations, we show that the glucose in ZnSO4 aqueous environment can simultaneously modulate solvation structure of Zn2+ and Zn anode-electrolyte interface The electrolyte engineering can alternate one H2 O molecule from the primary Zn2+ -6H2 O solvation shell and restraining side reactions due to the decomposition of active water Concomitantly, glucose molecules are inclined to absorb on the surface of Zn anode, suppressing the random growth of Zn dendrite As a proof of concept, a symmetric cell and Zn-MnO2 full cell with glucose electrolyte achieve boosted stability than that with pure ZnSO4 electrolyte
University of California, San Diego1, Northwestern University2, University of Zurich3, University of Amsterdam4, Washington University in St. Louis5, Claude Bernard University Lyon 16, University of Colorado Denver7, United States Department of Veterans Affairs8, Katholieke Universiteit Leuven9, University of Padua10, Queen Mary University of London11, Vanderbilt University12, University of Bordeaux13, Ege University14, University of Michigan15, Universidad del Desarrollo16, Flinders University17, University of Pisa18, University of Chile19, Case Western Reserve University20, Sanjay Gandhi Post Graduate Institute of Medical Sciences21, Chulalongkorn University22, University of Melbourne23, University of Ulsan24, Cornell University25, Mayo Clinic26, New York University27, Monash University28, University of Alberta29, University of Bern30, Kosin University31, University of Milan32, University of South Florida33, Autonomous University of Barcelona34, University College Hospital35, University of Washington36, National University of Singapore37, The Chinese University of Hong Kong38, Sun Yat-sen University39
TL;DR: The Chicago Classification v4.4.0 as discussed by the authors is the most recent version of the Chicago Classification, which uses high-resolution manometry (HRM) for motility disorders.
Abstract: Chicago Classification v4.0 (CCv4.0) is the updated classification scheme for esophageal motility disorders using metrics from high-resolution manometry (HRM). Fifty-two diverse international experts separated into seven working subgroups utilized formal validated methodologies over two-years to develop CCv4.0. Key updates in CCv.4.0 consist of a more rigorous and expansive HRM protocol that incorporates supine and upright test positions as well as provocative testing, a refined definition of esophagogastric junction (EGJ) outflow obstruction (EGJOO), more stringent diagnostic criteria for ineffective esophageal motility and description of baseline EGJ metrics. Further, the CCv4.0 sought to define motility disorder diagnoses as conclusive and inconclusive based on associated symptoms, and findings on provocative testing as well as supportive testing with barium esophagram with tablet and/or functional lumen imaging probe. These changes attempt to minimize ambiguity in prior iterations of Chicago Classification and provide more standardized and rigorous criteria for patterns of disorders of peristalsis and obstruction at the EGJ.
University of Utah1, University of Colorado Denver2, Oregon Health & Science University3, Harvard University4, University of California, San Diego5, University of Texas Health Science Center at Houston6, Medical College of Wisconsin7, Medical University of South Carolina8, Northwestern University9, Emory University10, University of Pennsylvania11, University of São Paulo12, Ghent University13, Sun Yat-sen University14, Karolinska Institutet15, University of Chicago16, Rush University Medical Center17, University of Barcelona18, University of California, Los Angeles19, Vanderbilt University20, University of Arizona21, University of Kansas22, Université de Montréal23, University of Auckland24, Rutgers University25, University of Amsterdam26, Columbia University27, Eastern Virginia Medical School28, University of New South Wales29, Katholieke Universiteit Leuven30, Guy's Hospital31, Stanford University32, University of British Columbia33, Mayo Clinic34, Johns Hopkins University35, Korea University36, Uniformed Services University of the Health Sciences37, Jikei University School of Medicine38, University of Washington39, University of Siena40, University of East Anglia41, University of Adelaide42, Pusan National University43, University of Calgary44, University of Cincinnati45, University of North Carolina at Chapel Hill46, Cleveland Clinic47, University of Winnipeg48, Chulalongkorn University49, Cornell University50, National University of Singapore51, University of Alabama at Birmingham52, University of Alberta53, Capital Medical University54
TL;DR: The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR‐RS) has witnessed foundational progress in the understanding and treatment of rhinologic disease.
Abstract: I. Executive summary BACKGROUND: The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR-RS) has witnessed foundational progress in our understanding and treatment of rhinologic disease. These advances are reflected within the more than 40 new topics covered within the ICAR-RS-2021 as well as updates to the original 140 topics. This executive summary consolidates the evidence-based findings of the document. Methods ICAR-RS presents over 180 topics in the forms of evidence-based reviews with recommendations (EBRRs), evidence-based reviews, and literature reviews. The highest grade structured recommendations of the EBRR sections are summarized in this executive summary. Results ICAR-RS-2021 covers 22 topics regarding the medical management of RS, which are grade A/B and are presented in the executive summary. Additionally, 4 topics regarding the surgical management of RS are grade A/B and are presented in the executive summary. Finally, a comprehensive evidence-based management algorithm is provided. Conclusion This ICAR-RS-2021 executive summary provides a compilation of the evidence-based recommendations for medical and surgical treatment of the most common forms of RS.
TL;DR: Acarbazole isomer, typically present as an impurity in commercially produced carbazole batches, is shown to be responsible for the ultralong phosphorescence observed in these compounds and their derivatives.
Abstract: Commercial carbazole has been widely used to synthesize organic functional materials that have led to recent breakthroughs in ultralong organic phosphorescence1, thermally activated delayed fluorescence2,3, organic luminescent radicals4 and organic semiconductor lasers5. However, the impact of low-concentration isomeric impurities present within commercial batches on the properties of the synthesized molecules requires further analysis. Here, we have synthesized highly pure carbazole and observed that its fluorescence is blueshifted by 54 nm with respect to commercial samples and its room-temperature ultralong phosphorescence almost disappears6. We discover that such differences are due to the presence of a carbazole isomeric impurity in commercial carbazole sources, with concentrations <0.5 mol%. Ten representative carbazole derivatives synthesized from the highly pure carbazole failed to show the ultralong phosphorescence reported in the literature1,7–15. However, the phosphorescence was recovered by adding 0.1 mol% isomers, which act as charge traps. Investigating the role of the isomers may therefore provide alternative insights into the mechanisms behind ultralong organic phosphorescence1,6–18. A carbazole isomer, typically present as an impurity in commercially produced carbazole batches, is shown to be responsible for the ultralong phosphorescence observed in these compounds and their derivatives.
TL;DR: In this paper, the authors analyzed a coronavirus disease 2019 (COVID-19) outbreak involving three families in a restaurant in Guangzhou, China, assessed the possibility of airborne transmission, and characterized the associated environmental conditions.
TL;DR: It is indicated that typical imaging characteristics and their changes can play crucial roles in the detection and management of COVID-19 and AI or other quantitative image analysis methods are urgently needed to maximize the value of imaging in the management of the disease.
Abstract: Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading rapidly around the world, resulting in a massive death toll. Lung infection or pneumonia is the common complication of COVID-19, and imaging techniques, especially computed tomography (CT), have played an important role in diagnosis and treatment assessment of the disease. Herein, we review the imaging characteristics and computing models that have been applied for the management of COVID-19. CT, positron emission tomography - CT (PET/CT), lung ultrasound, and magnetic resonance imaging (MRI) have been used for detection, treatment, and follow-up. The quantitative analysis of imaging data using artificial intelligence (AI) is also explored. Our findings indicate that typical imaging characteristics and their changes can play crucial roles in the detection and management of COVID-19. In addition, AI or other quantitative image analysis methods are urgently needed to maximize the value of imaging in the management of COVID-19.
TL;DR: In this paper, the authors investigate how external stimuli such as Limited Quantity Scarcity (LQS) and Limited Time Scarcity(LTS) affect the emotional arousal among people, which in turn influences consumers' impulsive and obsessive buying behaviors.
TL;DR: In this article, a single-atom strategy was used to construct excellent metal-organic frameworks (MOFs) hydrogen evolution reaction electrocatalyst (NiRu0.13-BDC) by introducing atomically dispersed Ru.
Abstract: Developing high-performance electrocatalysts toward hydrogen evolution reaction is important for clean and sustainable hydrogen energy, yet still challenging. Herein, we report a single-atom strategy to construct excellent metal-organic frameworks (MOFs) hydrogen evolution reaction electrocatalyst (NiRu0.13-BDC) by introducing atomically dispersed Ru. Significantly, the obtained NiRu0.13-BDC exhibits outstanding hydrogen evolution activity in all pH, especially with a low overpotential of 36 mV at a current density of 10 mA cm−2 in 1 M phosphate buffered saline solution, which is comparable to commercial Pt/C. X-ray absorption fine structures and the density functional theory calculations reveal that introducing Ru single-atom can modulate electronic structure of metal center in the MOF, leading to the optimization of binding strength for H2O and H*, and the enhancement of HER performance. This work establishes single-atom strategy as an efficient approach to modulate electronic structure of MOFs for catalyst design. Developing high-performance, neutral-media H2-evolution electrocatalysts is important for clean and sustainable hydrogen energy, yet rare, expensive elements are most active. Here, authors show that metal-organic frameworks modified with single ruthenium atoms as high-performances catalysts.
Chinese PLA General Hospital1, Nanjing University2, Zhejiang University3, Harbin Medical University4, Sun Yat-sen University5, Huazhong University of Science and Technology6, Fujian Medical University7, Fudan University8, Nanchang University9, Sichuan University10, Guangxi Medical University11, Central South University12, Anhui Medical University13, Tianjin Medical University Cancer Institute and Hospital14, Fourth Military Medical University15, Zhengzhou University16, Xi'an Jiaotong University17
TL;DR: Camrelizumab combined with apatinib showed promising efficacy and manageable safety in patients with advanced HCC in both the first-line and second-line setting, and might represent a novel treatment option for these patients.
Abstract: Purpose: We assessed the efficacy and safety of camrelizumab [an anti-programmed death (PD-1) mAb] plus apatinib (a VEGFR-2 tyrosine kinase inhibitor) in patients with advanced hepatocellular carcinoma (HCC). Patients and Methods: This nonrandomized, open-label, multicenter, phase II study enrolled patients with advanced HCC who were treatment-naive or refractory/intolerant to first-line targeted therapy. Patients received intravenous camrelizumab 200 mg (for bodyweight ≥50 kg) or 3 mg/kg (for bodyweight Results: Seventy patients in the first-line setting and 120 patients in the second-line setting were enrolled. As of January 10, 2020, the ORR was 34.3% [24/70; 95% confidence interval (CI), 23.3–46.6] in the first-line and 22.5% (27/120; 95% CI, 15.4–31.0) in the second-line cohort per IRC. Median progression-free survival in both cohorts was 5.7 months (95% CI, 5.4–7.4) and 5.5 months (95% CI, 3.7–5.6), respectively. The 12-month survival rate was 74.7% (95% CI, 62.5–83.5) and 68.2% (95% CI, 59.0–75.7), respectively. Grade ≥3 treatment-related adverse events (TRAE) were reported in 147 (77.4%) of 190 patients, with the most common being hypertension (34.2%). Serious TRAEs occurred in 55 (28.9%) patients. Two (1.1%) treatment-related deaths occurred. Conclusions: Camrelizumab combined with apatinib showed promising efficacy and manageable safety in patients with advanced HCC in both the first-line and second-line setting. It might represent a novel treatment option for these patients. See related commentary by Pinato et al., p. 908
TL;DR: The current obstacles and future chances for the development of 2D TMDs electrocatalyststs are proposed to provide insight into and valuable guidelines for fabricating effective HER electrocatalysts.
Abstract: Hydrogen has been deemed as an ideal substitute fuel to fossil energy because of its renewability and the highest energy density among all chemical fuels One of the most economical, ecofriendly, and high-performance ways of hydrogen production is electrochemical water splitting Recently, 2D transition metal dichalcogenides (also known as 2D TMDs) showed their utilization potentiality as cost-effective hydrogen evolution reaction (HER) catalysts in water electrolysis Herein, recent representative research efforts and systematic progress made in 2D TMDs are reviewed, and future opportunities and challenges are discussed Furthermore, general methods of synthesizing 2D TMDs materials are introduced in detail and the advantages and disadvantages for some specific methods are provided This explanation includes several important regulation strategies of creating more active sites, heteroatoms doping, phase engineering, construction of heterostructures, and synergistic modulation which are capable of optimizing the electrical conductivity, exposure to the catalytic active sites, and reaction energy barrier of the electrode material to boost the HER kinetics In the last section, the current obstacles and future chances for the development of 2D TMDs electrocatalysts are proposed to provide insight into and valuable guidelines for fabricating effective HER electrocatalysts
TL;DR: The state-of-the-art development of HT-PEMFC key materials, components and device assembly along with degradation mechanisms, mitigation strategies, and HT- PEMFC based CHP systems is comprehensively reviewed.
Abstract: High temperature proton exchange membrane fuel cells (HT-PEMFCs) are one type of promising energy device with the advantages of fast reaction kinetics (high energy efficiency), high tolerance to fuel/air impurities, simple plate design, and better heat and water management. They have been expected to be the next generation of PEMFCs specifically for application in hydrogen-fueled automobile vehicles and combined heat and power (CHP) systems. However, their high-cost and low durability interposed by the insufficient performance of key materials such as electrocatalysts and membranes at high temperature operation are still the challenges hindering the technology's practical applications. To develop high performance HT-PEMFCs, worldwide researchers have been focusing on exploring new materials and the related technologies by developing novel synthesis methods and innovative assembly techniques, understanding degradation mechanisms, and creating mitigation strategies with special emphasis on catalysts for oxygen reduction reaction, proton exchange membranes and bipolar plates. In this paper, the state-of-the-art development of HT-PEMFC key materials, components and device assembly along with degradation mechanisms, mitigation strategies, and HT-PEMFC based CHP systems is comprehensively reviewed. In order to facilitate further research and development of HT-PEMFCs toward practical applications, the existing challenges are also discussed and several future research directions are proposed in this paper.
TL;DR: Wang et al. as discussed by the authors showed that SARS-CoV-2 infection leads to major histocompability complex class Ι (MHC-Ι) down-regulation both in vitro and in vivo.
Abstract: COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic and has claimed over 2 million lives worldwide. Although the genetic sequences of SARS-CoV and SARS-CoV-2 have high homology, the clinical and pathological characteristics of COVID-19 differ significantly from those of SARS. How and whether SARS-CoV-2 evades (cellular) immune surveillance requires further elucidation. In this study, we show that SARS-CoV-2 infection leads to major histocompability complex class Ι (MHC-Ι) down-regulation both in vitro and in vivo. The viral protein encoded by open reading frame 8 (ORF8) of SARS-CoV-2, which shares the least homology with SARS-CoV among all viral proteins, directly interacts with MHC-Ι molecules and mediates their down-regulation. In ORF8-expressing cells, MHC-Ι molecules are selectively targeted for lysosomal degradation via autophagy. Thus, SARS-CoV-2-infected cells are much less sensitive to lysis by cytotoxic T lymphocytes. Because ORF8 protein impairs the antigen presentation system, inhibition of ORF8 could be a strategy to improve immune surveillance.
TL;DR: A nanopatterned electron transport layer is introduced that overcomes this trade-off by modifying the spatial distribution of the passivation layer to form nanoscale localized charge transport pathways through an otherwise passivated interface, thereby providing both effective passivation and excellent charge extraction.
Abstract: Polymer passivation layers can improve the open-circuit voltage of perovskite solar cells when inserted at the perovskite-charge transport layer interfaces. Unfortunately, many such layers are poor conductors, leading to a trade-off between passivation quality (voltage) and series resistance (fill factor, FF). Here, we introduce a nanopatterned electron transport layer that overcomes this trade-off by modifying the spatial distribution of the passivation layer to form nanoscale localized charge transport pathways through an otherwise passivated interface, thereby providing both effective passivation and excellent charge extraction. By combining the nanopatterned electron transport layer with a dopant-free hole transport layer, we achieved a certified power conversion efficiency of 21.6% for a 1-square-centimeter cell with FF of 0.839, and demonstrate an encapsulated cell that retains ~91.7% of its initial efficiency after 1000 hours of damp heat exposure.
TL;DR: Wang et al. as discussed by the authors reviewed the rates and trends of cancer incidence and mortality and disability-adjusted life year (DALY) burden in China, and compared them with those in the United States (US) and the United Kingdom (UK).
Abstract: Background Cancer is one of the leading causes of death and a main economic burden in China. Investigating the differences in cancer patterns and control strategies between China and developed countries could provide reference for policy planning and contribute to improving cancer control measures. In this study, we reviewed the rates and trends of cancer incidence and mortality and disability-adjusted life year (DALY) burden in China, and compared them with those in the United States (US) and the United Kingdom (UK). Methods Cancer incidence, mortality, and DALY data for China, US and UK were obtained from the GLOBOCAN 2020 online database, Global Burden of Disease (GBD) 2019 study, and Cancer Incidence in Five Continents plus database (CI5 plus). Trends of cancer incidence and mortality in China, US, and UK were analyzed using Joinpoint regression models to calculate annual percent changes (APCs) and identify the best-fitting joinpoints. Results An estimated 4,568,754 newly diagnosed cancer cases and 3,002,899 cancer deaths occurred in China in 2020. Additionally, cancers resulted in 67,340,309 DALYs in China. Compared to the US and UK, China had lower cancer incidence but higher cancer mortality and DALY rates. Furthermore, the cancer spectrum of China was changing, with a rapid increase incidence and burden of lung, breast, colorectal, and prostate cancer in addition to a high incidence and heavy burden of liver, stomach, esophageal, and cervical cancer. Conclusions The cancer spectrum of China is changing from a developing country to a developed country. Population aging and increase of unhealthy lifestyles would continue to increase the cancer burden of China. Therefore, the Chinese authorities should adjust the national cancer control program with reference to the practices of cancer control which have been well-established in the developed countries, and taking consideration of the diversity of cancer types by of different regions in China at the same time.
TL;DR: A deeply supervised (DS) attention metric-based network (DSAMNet) is proposed in this article to learn change maps by means of deep metric learning, in which convolutional block attention modules (CBAM) are integrated to provide more discriminative features.
Abstract: Change detection (CD) aims to identify surface changes from bitemporal images. In recent years, deep learning (DL)-based methods have made substantial breakthroughs in the field of CD. However, CD results can be easily affected by external factors, including illumination, noise, and scale, which leads to pseudo-changes and noise in the detection map. To deal with these problems and achieve more accurate results, a deeply supervised (DS) attention metric-based network (DSAMNet) is proposed in this article. A metric module is employed in DSAMNet to learn change maps by means of deep metric learning, in which convolutional block attention modules (CBAM) are integrated to provide more discriminative features. As an auxiliary, a DS module is introduced to enhance the feature extractor's learning ability and generate more useful features. Moreover, another challenge encountered by data-driven DL algorithms is posed by the limitations in change detection datasets (CDDs). Therefore, we create a CD dataset, Sun Yat-Sen University (SYSU)-CD, for bitemporal image CD, which contains a total of 20,000 aerial image pairs of size 256 x 256. Experiments are conducted on both the CDD and the SYSU-CD dataset. Compared to other state-of-the-art methods, our network achieves the highest accuracy on both datasets, with an F1 of 93.69% on the CDD dataset and 78.18% on the SYSU-CD dataset.
Peking Union Medical College1, Sun Yat-sen University2, Harbin Medical University3, Shanghai Chest Hospital4, Hebei Medical University5, Zhengzhou University6, Fudan University7, Anhui Medical University8, Henan University of Science and Technology9, Peking University10, Shandong University11, Tianjin Medical University Cancer Institute and Hospital12, Fourth Military Medical University13
TL;DR: The ESCORT-1st trial as discussed by the authors evaluated the efficacy and adverse events of camrelizumab plus chemotherapy vs placebo plus chemotherapy as a first-line treatment in advanced or metastatic esophageal squamous cell carcinoma.
Abstract: Importance Standard first-line therapy for advanced or metastatic esophageal carcinoma is chemotherapy, but the prognosis remains poor. Camrelizumab (an anti–programmed death receptor 1 [PD-1] antibody) showed antitumor activity in previously treated advanced or metastatic esophageal squamous cell carcinoma. Objective To evaluate the efficacy and adverse events of camrelizumab plus chemotherapy vs placebo plus chemotherapy as a first-line treatment in advanced or metastatic esophageal squamous cell carcinoma. Design, Setting, and Participants This randomized, double-blind, placebo-controlled, multicenter, phase 3 trial (ESCORT-1st study) enrolled patients from 60 hospitals in China between December 3, 2018, and May 12, 2020 (final follow-up, October 30, 2020). A total of 751 patients were screened and 596 eligible patients with untreated advanced or metastatic esophageal squamous cell carcinoma were randomized. Interventions Patients were randomized 1:1 to receive either camrelizumab 200 mg (n = 298) or placebo (n = 298), combined with up to 6 cycles of paclitaxel (175 mg/m2) and cisplatin (75 mg/m2). All treatments were given intravenously every 3 weeks. Main Outcomes and Measures Coprimary end points were overall survival (significance threshold, 1-sidedP Results Of the 596 patients randomized (median age, 62 years [interquartile range, 56-67 years]; 523 men [87.8%]), 1 patient in the placebo-chemotherapy group did not receive planned treatment. A total of 490 patients (82.2%) had discontinued the study treatment. The median follow-up was 10.8 months. The overall survival for the camrelizumab-chemotherapy group was a median of 15.3 months (95% CI, 12.8-17.3; 135 deaths) vs a median of 12.0 months (95% CI, 11.0-13.3; 174 deaths) for the placebo-chemotherapy group (hazard ratio [HR] for death, 0.70 [95% CI, 0.56-0.88]; 1-sidedP = .001). Progression-free survival for camrelizumab plus chemotherapy was a median of 6.9 months (95% CI, 5.8-7.4; 199 progression or deaths) vs 5.6 months (95% CI, 5.5-5.7; 229 progression or deaths) for the placebo-chemotherapy group (HR for progression or death, 0.56 [95% CI, 0.46-0.68]; 1-sidedP Conclusions and Relevance Among patients with advanced or metastatic esophageal squamous cell carcinoma, the addition of camrelizumab to chemotherapy, compared with placebo and chemotherapy, significantly improved overall survival and progression-free survival. Trial Registration ClinicalTrials.gov Identifier:NCT03691090
TL;DR: It is believed that an in‐depth understanding of lncRNA‐mediated cancer metabolic reprogramming can help to identify cellular vulnerabilities that can be exploited for cancer diagnosis and therapy.
Abstract: Altered metabolism is a hallmark of cancer, and the reprogramming of energy metabolism has historically been considered a general phenomenon of tumors. It is well recognized that long noncoding RNAs (lncRNAs) regulate energy metabolism in cancer. However, lncRNA-mediated posttranslational modifications and metabolic reprogramming are unclear at present. In this review, we summarized the current understanding of the interactions between the alterations in cancer-associated energy metabolism and the lncRNA-mediated posttranslational modifications of metabolic enzymes, transcription factors, and other proteins involved in metabolic pathways. In addition, we discuss the mechanisms through which these interactions contribute to tumor initiation and progression, and the key roles and clinical significance of functional lncRNAs. We believe that an in-depth understanding of lncRNA-mediated cancer metabolic reprogramming can help to identify cellular vulnerabilities that can be exploited for cancer diagnosis and therapy.
TL;DR: In this paper, cationic polyelectrolyte brushes grafted from bacterial cellulose (BC) nanofibers are introduced into polydopamine/polyacrylamide hydrogels.
Abstract: Treatment of wounds in special areas is challenging due to inevitable movements and difficult fixation. Common cotton gauze suffers from incomplete joint surface coverage, confinement of joint movement, lack of antibacterial function, and frequent replacements. Hydrogels have been considered as good candidates for wound dressing because of their good flexibility and biocompatibility. Nevertheless, the adhesive, mechanical, and antibacterial properties of conventional hydrogels are not satisfactory. Herein, cationic polyelectrolyte brushes grafted from bacterial cellulose (BC) nanofibers are introduced into polydopamine/polyacrylamide hydrogels. The 1D polymer brushes have rigid BC backbones to enhance mechanical property of hydrogels, realizing high tensile strength (21-51 kPa), large tensile strain (899-1047%), and ideal compressive property. Positively charged quaternary ammonium groups of tethered polymer brushes provide long-lasting antibacterial property to hydrogels and promote crawling and proliferation of negatively charged epidermis cells. Moreover, the hydrogels are rich in catechol groups and capable of adhering to various surfaces, meeting adhesive demand of large movement for special areas. With the above merits, the hydrogels demonstrate less inflammatory response and faster healing speed for in vivo wound healing on rats. Therefore, the multifunctional hydrogels show stable covering, little displacement, long-lasting antibacteria, and fast wound healing, demonstrating promise in wound dressing.