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Potential role of Lycium barbarum polysaccharides in glaucoma management:evidence from preclinical in vivo studies

Neural Regeneration Research 2023年第12期18卷 2623-2632页

作者： Yamunadevi Lakshmanan Francisca Siu Yin Wong Kwok-Fai So henry Ho-Lung chan Centre for Eye and Vision Research(CEVR) 17W Hong Kong Science ParkHong Kong Special Administrative RegionChina Guangdong-Hongkong-Macao(GHM)Institute of CNS Regeneration Jinan UniversityGuangzhouGuangdong ProvinceChina Department of Ophthalmology LKS Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina Laboratory of Experimental Optometry(Neuroscience) School of OptometryThe Hong Kong Polytechnic UniversityHong Kong Special Administrative RegionChina Research Centre for SHARP Vision(RCSV) The Hong Kong Polytechnic UniversityHong Kong Special Administrative RegionChina University Research Facilities in Behavioral and Systems Neuroscience(UBSN) The Hong Kong Polytechnic UniversityHong Kong Special Administrative RegionChina

In recent years,the pharmacological benefits of herbal extracts have been revisited for their potential neuroprotective effects in *** polysaccharides extracted from the fruits of Lycium barbarum L.,or Lycium barbarum polysaccharides,exert their anti-aging effect through reducing oxidative stress,modulating the immune response,enhancing neuronal responses,and promoting *** therapeutic efficacy of Lycium barbarum polysaccharides in preserving retinal ganglion cells and their functions was demonstrated in a range of experimental models of optic *** include the acute and chronic ocular hypertension models,the partial optic nerve transection model,and the ischemic-reperfusion injuries *** on these findings,Lycium barbarum polysaccharides appear to be a good candidate to be developed as a neuroprotective agent for treating multifactorial *** review aims to present a comprehensive review on the latest preclinical evidence on the pre-and post-treatment benefits of Lycium barbarum polysaccharides in retinal ganglion cell *** possible mechanisms of Lycium barbarum polysaccharides mediating retinal ganglion cell neuroprotection will also be ***,the potential research gaps in the effective translation of Lycium barbarum polysaccharides treatment into clinical glaucoma management will be discussed.

关键词： animal model complementary and alternative medicine glaucoma retinal ganglion cell Lycium barbarum polysaccharide neuroprotection neuro-rescue ocular hypertension post-treatment pre-treatment

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AutoPhaseNN:unsupervised physics-aware deep learning of 3D nanoscale Bragg coherent diffraction imaging

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npj Computational Materials 2022年第1期8卷 1146-1153页

作者： Yudong Yao henry chan Subramanian Sankaranarayanan Prasanna Balaprakash Ross J.Harder Mathew J.Cherukara Advanced Photon Source Argonne National LaboratoryLemontIL60439USA Center for Nanoscale Materials Argonne National LaboratoryLemontIL60439USA Mathematics and Computer Science Argonne National LaboratoryLemontIL60439USA

The problem of phase retrieval underlies various imaging methods from astronomy to nanoscale *** phase retrieval methods are iterative and are therefore computationally *** learning(DL)models have been developed to either provide learned priors or completely replace phase ***,such models require vast amounts of labeled data,which can only be obtained through simulation or performing computationally prohibitive phase retrieval on experimental *** 3D X-ray Bragg coherent diffraction imaging(BCDI)as a representative technique,we demonstrate AutoPhaseNN,a DL-based approach which learns to solve the phase problem without labeled *** incorporating the imaging physics into the DL model during training,AutoPhaseNN learns to invert 3D BCDI data in a single shot without ever being shown real space *** trained,AutoPhaseNN can be effectively used in the 3D BCDI data inversion about 100×faster than iterative phase retrieval methods while providing comparable image quality.

关键词： coherent iterative replace

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CEGANN: Crystal Edge Graph Attention Neural Network for multiscale classification of materials environment

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npj Computational Materials 2023年第1期9卷 2106-2117页

作者： Suvo Banik Debdas Dhabal henry chan Sukriti Manna Mathew Cherukara Valeria Molinero Subramanian K.R.S.Sankaranarayanan Center for Nanoscale Materials Argonne National LaboratoryLemontIL 60439USA Department of Mechanical and Industrial Engineering University of IllinoisChicagoIL 60607USA Department of Chemistry The University of UtahSalt Lake CityUT 84112USA Advanced Photon Source Argonne National LaboratoryLemontIL 60439USA

We introduce Crystal Edge Graph Attention Neural Network (CEGANN) workflow that uses graph attention-based architecture tolearn unique feature representations and perform classification of materials across multiple scales (from atomic to mesoscale) anddiverse classes ranging from metals, oxides, non-metals to hierarchical materials such as zeolites and semi-ordered *** can classify based on a global, structure-level representation such as space group and dimensionality (e.g., bulk, 2D,clusters, etc.). Using representative materials such as polycrystals and zeolites, we demonstrate its transferability in performing localatom-level classification tasks, such as grain boundary identification and other heterointerfaces. CEGANN classifies in (thermal)noisy dynamical environments as demonstrated for representative zeolite nucleation and growth from an amorphous ***, we use CEGANN to classify multicomponent systems with thermal noise and compositional diversity. Overall, our approachis material agnostic and allows for multiscale feature classification ranging from atomic-scale crystals to heterointerfaces tomicroscale grain boundaries.

关键词： Crystal classify zeolite

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A Continuous Action Space Tree search for INverse desiGn (CASTING) framework for materials discovery

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npj Computational Materials 2023年第1期9卷 500-515页

作者： Suvo Banik Troy Loefller Sukriti Manna henry chan Srilok Srinivasan Pierre Darancet Alexander Hexemer Subramanian K.R.S.Sankaranarayanan Center for Nanoscale Materials Argonne National LaboratoryLemontIL 60439USA Department of Mechanical and Industrial Engineering University of IllinoisChicagoIL 60607USA Advanced Light Source(ALS)Division Lawrence Berkeley National LaboratoryBerkeleyCA 94720USA

Material properties share an intrinsic relationship with their structural attributes,making inverse design approaches crucial for discovering new materials with desired *** Learning(RL)approaches are emerging as powerful inverse design tools,often functioning in discrete action *** constrains their application in materials design problems,which involve continuous search ***,we introduce an RL-based framework CASTING(Continuous Action Space Tree Search for inverse design),that employs a decision tree-based Monte Carlo Tree Search(MCTS)algorithm with continuous space adaptation through modified policies and *** representative examples like Silver(Ag)for metals,Carbon(C)for covalent systems,and multicomponent systems such as graphane,boron nitride,and complex correlated oxides,we showcase its accuracy,convergence speed,and scalability in materials discovery and ***,with the inverse design of super-hard Carbon phases,we demonstrate CASTING’s utility in discovering metastable phases tailored to user-defined target properties and preferences.

关键词： Action framework Tree

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Comprehensive evaluation of microRNA as a biomarker for the diagnosis of hepatocellular carcinoma

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World Journal of Gastroenterology 2022年第29期28卷 3917-3933页

作者： Juliane Malik Martin Klammer Vinzent Rolny henry Lik-Yuen chan Teerha Piratvisuth Tawesak Tanwandee Satawat Thongsawat Wattana Sukeepaisarnjaroen Juan Ignacio Esteban Marta Bes Bruno Kohler Magdalena Swiatek-de Lange Diagnostics GmbH Penzberg 82377Germany Faculty of Medicine The Chinese University of Hong KongHong Kong 999077China NKC Institute of Gastroenterology and Hepatology Songklanagarind HospitalHat Yai 90112Thailand Division of Gastroenterology Faculty of MedicineSiriraj HospitalMahidol UniversityBangkok 10700Thailand Department of Internal Medicine Maharaj Nakorn Chiang Mai HospitalChiang Mai UniversityChiang Mai 50200Thailand Faculty of Medicine Srinagarind HospitalKhon Kaen UniversityKhon Kaen 40000Thailand Liver Unit Vall d’Hebron University HospitalBarcelona 08035Spain Transfusion Safety Laboratory Banc de Sang i TeixitsBarcelona 08005Spain Department of Medical Oncology National Center for Tumor DiseasesUniversity Hospital HeidelbergHeidelberg 69120Germany Liver Cancer Center Heidelberg University Hospital HeidelbergHeidelberg 69120Germany

BACKGROUND Hepatocellular carcinoma(HCC) is the most common type of primary liver cancer. Current guidelines for HCC management recommend surveillance of high-risk patients every 6 mo using ultrasonography. Serum biomarkers, like alpha-fetoprotein(AFP), protein induced by vitamin K absence/antagonist-Ⅱ(PIVKA-Ⅱ) and lectin-reactive AFP, show suboptimal performance for detection of HCC, which is crucial for successful resection or treatment. Thus, there is a significant need for new biomarkers to aid early diagnosis of HCC. Studies have shown that the expression level of human microRNAs(miRNAs), a small, non-coding RNA species released into the blood, can serve as an early marker for various diseases, including *** To evaluate the diagnostic role of miRNAs in HCC as single markers, signatures or in combination with known protein *** Our prospective, multicenter, case-control study recruited 660 participants(354 controls with chronic liver disease and 306 participants with HCC) and employed a strategy of initial screening by two independent methods, real-time quantitative PCR(n = 60) and next-generation sequencing(n = 100), to assess a large number of miRNAs. The results from the next-generation sequencing and real-time quantitative PCR screening approaches were then combined to select 26 miRNAs(including two putative novel miRNAs). Those miRNAs were analyzed for their diagnostic potential as single markers or in combination with other miRNAs or established protein biomarkers AFP and PIVKA-Ⅱ via real-time quantitative PCR in training(n = 200) and validation cohorts(n = 300).RESULTS We identified 26 miRNAs that differentiated chronic liver disease controls from(early) HCC via two independent discovery approaches. Three miRNAs, miR-21-5p(miR-21), miR-320a and miR-186-5p, were selected by both methods. In the training cohort, only miR-21, miR-320d and miR-423could significantly distinguish(Q < 0.05) between the HCC and chronic liver disease control grou

关键词： Carcinoma Hepatocellular MicroRNAs Biomarkers Alpha-fetoprotein Protein induced by vitamin K absence-Ⅱ Diagnosis

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Inferior vena cava reconstruction in extended right hepatectomy

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Hepatobiliary & Pancreatic Diseases International 2024年第5期23卷 533-534页

作者： Karin KY Ho Sui Ling Sin Kin Pan Au henry HY Lee Daniel TL chan Albert chan Department of Surgery The University of Hong Kong102 Pok Fu Lam RoadHong KongChina Department of Surgery Yan Chai Hospital7 Yan Chai StreetHong KongChina State Key Laboratory of Liver Research(Li Ka Shing Faculty of Medicine The University of Hong Kong)102 Pok Fu Lam RoadHong KongChina

To the Editor : Barcelona Clinic Liver Cancer(BCLC) Stage C hepatocellular carcinoma(HCC) with vascular invasion has been considered unresectable. However, the curative rate from systemic treatment is rather dismal. Even with the use of immunotherapy, complete remission is less than 10% [ 1 ]. On the contrary, recent advances in transplant oncology, especially in the application of liver transplant-related surgical techniques in complex liver resections, make the operation possible for patients with locally advanced HCC who were previously considered to be unresectable [ 2 ]. We hereby present the surgical management of a patient with giant HCC in right liver lobe with inferior vena cava(IVC) invasion.

关键词： invasion vena Liver

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A step forward in breeding for ratooning ability in rice

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Molecular Plant 2024年第3期17卷 368-369页

作者： Amelia henry Rice Breeding Innovations Department International Rice Research InstituteLos BanosLagunaPhilippines

Rice ratoon cropping,or the cultivation of tillers that have regrown from existing stem nodes of a harvested crop,is currently a hot topic in agriculture,and record-high ratoon crop yields have been achieved in China(Xu et al.,2021).Although rice ratoon cropping is most appropriate for certain agro-ecosystems with a suitable climate and cropping schedule,it is a promising strategy to simultaneously increase productivity while reducing inputs and *** ratoon cropping may thereby contribute to global food security and agro-ecosystem sustainability.

关键词： breeding cropping thereby

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Machine learning enabled autonomous microstructural characterization in 3D samples

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npj Computational Materials 2020年第1期6卷 1654-1662页

作者： henry chan Mathew Cherukara Troy D.Loeffler Badri Narayanan Subramanian K.R.S.Sankaranarayanan Center for Nanoscale Materials Argonne National LaboratoryArgonneILUSA Department of Mechanical Engineering University of LouisvilleLouisvilleKYUSA Department of Mechanical and Industrial Engineering University of Illinois at ChicagoChicagoILUSA

We introduce an unsupervised machine learning(ML)based technique for the identification and characterization of microstructures in three-dimensional(3D)samples obtained from molecular dynamics simulations,particle tracking data,or *** technique combines topology classification,image processing,and clustering algorithms,and can handle a wide range of microstructure types including grains in polycrystalline materials,voids in porous systems,and structures from self/directed assembly in soft-matter complex *** technique does not require a priori microstructure description of the target system and is insensitive to disorder such as extended defects in polycrystals arising from line and plane *** demonstrate quantitively that our technique provides unbiased microstructural information such as precise quantification of grains and their size distributions in 3D polycrystalline samples,characterizes features such as voids and porosity in 3D polymeric samples and micellar size distribution in 3D complex *** demonstrate the efficacy of our ML approach,we benchmark it against a diverse set of synthetic data samples representing nanocrystalline metals,polymers and complex fluids as well as experimentally published characterization *** technique is computationally efficient and provides a way to quickly identify,track,and quantify complex microstructural features that impact the observed material behavior.

关键词： microstructure polycrystalline porosity

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Stopping nucleos(t)ide analog treatment in chronic hepatitis B-Who and when?

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Liver Research 2017年第2期1卷 135-139页

作者： Suzette Grace R.Kho-Herman henry Lik-Yuen chan Institute of Digestive Disease The Chinese University of Hong KongHong KongChina Makati Medical Center MakatiPhilippines

Nucleos(t)ide analogs(NAs)are one of the first-line treatments for chronic hepatitis B(CHB)*** are highly efficient in suppressing viral replication but are associated with a low rate of hepatitis B surface antigen(HBsAg)seroclearance and a high risk of post-treatment virologic *** a result,the optimal timing of NA cessation remains unclear,and long-term treatment is often *** international guidelines suggest that NA can be discontinued in hepatitis B e antigen(HBeAg)-positive patients who achieve HBeAg seroconversion with undetectable hepatitis B virus(HBV)DNA levels,the recommendations for discontinuing NA treatment in HBeAg-negative patients remain ***,there is no consensus regarding in whom and when to restart treatment among patients with hepatitis relapse after stopping NA *** studies suggest that virologic markers such as HBsAg and hepatitis B core-related antigen(HBcrAg)titers may be useful to guide when to stop NAs in CHB,since both markers appear to correlate with intrahepatic covalently closed circular HBV DNA ***,additional studies are required to refine their use.

关键词： Hepatitis B Entecavir Tenofovir Hepatitis B virus deoxyribonucleic acid (HBV DNA) Hepatitis B surface antigen(HBsAg) Hepatitis B core-related antigen(HBcrAg) Hepatitis B e antigen(HBeAg)

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Multi-reward reinforcement learning based development of inter-atomic potential models for silica

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npj Computational Materials 2023年第1期9卷 1059-1071页

作者： Aditya Koneru henry chan Sukriti Manna Troy D.Loeffler Debdas Dhabal Andressa A.Bertolazzo Valeria Molinero Subramanian K.R.S.Sankaranarayanan Department of Mechanical and Industrial Engineering University of IllinoisChicagoIL 60607USA Center for Nanoscale Materials Argonne National LaboratoryLemontIL 60439USA Department of Chemistry The University of UtahSalt Lake CityUT 84112USA

Silica is an abundant and technologically attractive *** to the structural complexities of silica polymorphs coupled with subtle differences in Si–O bonding characteristics,the development of accurate models to predict the structure,energetics and properties of silica polymorphs remain *** models for silica range from computationally efficient Buckingham formalisms(BKS,CHIK,Soules)to reactive(ReaxFF)and more recent machine-learned potentials that are flexible but computationally ***,we introduce an improved formalism and parameterization of BKS model via a multireward reinforcement learning(RL)using an experimental training *** model concurrently captures the structure,energetics,density,equation of state,and elastic constants of quartz(equilibrium)as well as 20 other metastable silica *** also assess its ability in capturing amorphous properties and highlight the limitations of the BKS-type functional forms in simultaneously capturing crystal and amorphous *** demonstrate ways to improve model flexibility and introduce a flexible formalism,machine-learned ML-BKS,that outperforms existing empirical models and is on-par with the recently developed 50 to 100 times more expensive Gaussian approximation potential(GAP)in capturing the experimental structure and properties of silica polymorphs and amorphous silica.

关键词： amorphous potential attractive

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