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Microfluidic bubble-generator enables digital light processing 3D printing of porous structures

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Aggregate 2024年第1期5卷 280-291页

作者： Philipp Weber Ling Cai Francisco Javier Aguilar Rojas Carlos Ezio Garciamendez-Mijares Maria Celeste Tirelli Francesco Nalin Jakub Jaroszewicz Wojciech Swi eszkowski Marco Costantini Yu Shrike Zhang Division of Engineering in Medicine Department of MedicineBrigham and Women’s HospitalHarvard Medical SchoolCambridgeMassachusettsUSA Institute of Physical Chemistry—Polish Academy of Sciences KasprzakaPoland Biomaterials Group Materials Design DivisionFaculty of Materials Science and EngineeringWarsaw University of TechnologyWoloskaPoland

Three-dimensional(3D)printing is an emerging technique that has shown promising success in engineering human tissues in recent years.Further development of vatphotopolymerization printing modalities has significantly enhanced the complexity level for 3D printing of various functional structures and components.Similarly,the development of microfluidic chip systems is an emerging research sector with promising medical applications.This work demonstrates the coupling of a digital light processing(DLP)printing procedure with a microfluidic chip system to produce size-tunable,3D-printable porosities with narrow pore size distributions within a gelatin methacryloyl(GelMA)hydrogel matrix.It is found that the generation of size-tunable gas bubbles trapped within an aqueous GelMA hydrogel-precursor can be controlled with high precision.Furthermore,the porosities are printed in two-dimensional(2D)as well as in 3D using the DLP printer.In addition,the cytocompatibility of the printed porous scaffolds is investigated using fibroblasts,where high cell viabilities as well as cell proliferation,spreading,and migration are confirmed.It is anticipated that the strategy is widely applicable in a range of application areas such as tissue engineering and regenerative medicine,among others.

关键词： 3D printing biofabrication bubble digital light processing microfluidics porous

CoolVox:Advanced 3D convolutional neural network models for predicting solar radiation on building facades

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Building Simulation 2022年第5期15卷 755-768页

作者： Jung Min Han Eun Seuk Choi Ali Malkawi harvard university graduate school of design CambridgeUSA harvard Center for Green Buildings and Cities CambridgeUSA harvard John A.Paulson school of Engineering and Applied Sciences CambridgeUSA

Data-driven models have become increasingly prominent in the building,architecture,and construction industries.One area ideally suited to exploit this powerful new technology is building performance simulation.Physics-based models have traditionally been used to estimate the energy flow,air movement,and heat balance of buildings.However,physics-based models require many assumptions,significant computational power,and a considerable amount of time to output predictions.Artificial neural networks(ANNs)with prefabricated or simulated data are likely to be a more feasible option for environmental analysis conducted by designers during the early design phase.Because ANNs require fewer inputs and shorter computation times and offer superior performance and potential for data augmentation,they have received increased attention for predicting the surface solar radiation on buildings.Furthermore,ANNs can provide innovative and quick design solutions,enabling designers to receive instantaneous feedback on the effects of a proposed change to a building's design.This research introduces deep learning methods as a means of simulating the annual radiation intensities and exposure level of buildings without the need for physics-based engines.We propose the CoolVox model to demonstrate the feasibility of using 3D convolutional neural networks to predict the surface radiation on building facades.The CoolVox model accurately predicted the radiation intensities of building facades under different boundary conditions and performed better than ARINet(with average mean square errors of 0.01 and 0.036,respectively)in predicting the radiation intensity both with(validation error=0.0165)and without(validation error=0.0066)the presence of boundary buildings.

关键词： artificial neural networks 3D convolutional neural networks solar radiation simulation building performance simulation

Deep dive into anionic metal-organic frameworks based quasi-solid-state electrolytes

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Journal of Energy Chemistry 2023年第6期81卷 313-320,I0008页

作者： Tingzheng Hou Wentao Xu Institute of Materials Research Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055GuangdongChina John A.Paulson school of Engineering and Applied Sciences Harvard UniversityCambridgeMA 02138USA

The development and application of high-capacity energy storage has been crucial to the global transition from fossil fuels to green energy.In this context,metal-organic frameworks(MOFs),with their unique 3D porous structure and tunable chemical functionality,have shown enormous potential as energy storage materials for accommodating or transporting electrochemically active ions.In this perspective,we specifically focus on the current status and prospects of anionic MOF-based quasi-solid-state-electrolytes(anionic MOF-QSSEs)for lithium metal batteries(LMBs).An overview of the definition,design,and properties of anionic MOF-QSSEs is provided,including recent advances in the understanding of their ion transport mechanism.To illustrate the advantages of using anionic MOF-QSSEs as electrolytes for LMBs,a thorough comparison between anionic MOF-QSSEs and other well-studied electrolyte systems is made.With these in-depth understandings,viable techniques for tuning the chemical and topological properties of anionic MOF-QSSEs to increase Li+conductivity are discussed.Beyond modulation of the MOFs matrix,we envisage that solvent and solid-electrolyte interphase design as well as emerging fabrication techniques will aid in the design and practical application of anionic MOF-QSSEs.

关键词： Anionic metal–organic frameworks Quasi-solid-state electrolytes Ionic conduction Lithium metal batteries Lithium-ion batteries

Agent-based models reveal limits of mark-release-recapture estimates for the rare butterfly, Bhutanitis thaidina (Lepidoptera: Papilionidae)

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Insect Science 2022年第2期29卷 550-566页

作者： Zhengyang Wang Yuanheng Li Anuj Jain Naomi E.Pierce Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology Harvard UniversityCambridgeMA 02138 USA

Insect diversity and abundance are in drastic decline worldwide,but quantifying insect populations to better conserve them is a difficult task.Mark-release-recapture(MRR)is widely used as an ecological indicator for insect populations,but the accuracy of MRR estimates can vary with factors such as spatial scale,sampling effort and models of inference.We conducted a 3-year MRR study of B.thaidina in Yanzigou valley,Mt.Gongga but failed to obtain sufficient data for a robust population estimate.This prompted us to integrate B.thaidina life history information to parameterize agent-based models and evaluate the conditions under which successful MRR studies could be conducted.We evaluated:(1)the performance of MRR models under different landscape types,and(2)the influence of experimental design on the accuracy and variance of MRR-based estimates.Our simulations revealed systematic underestimates of true population parameters by MRR models when sampling effort was insufficient.In a total of 2772 simulations,subjective decisions in sampling protocol(e.g.,frequency,number of sampling locations,use of spatially explicit models,type of estimands)accounted for nearly half of the variation in estimates.We conclude that MRR-based estimates could be improved with the addition of more field-specific parameters.

关键词： agent-based simulation Aristolochia moupinensis habitat hostplant landscape Mt.Gongga program MARK spatially explicit capture-recapture(SECR)

A Comparative Study of Methods for Delineating Sphere of Urban Influence: A Case Study on Central China

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Chinese Geographical Science 2014年第6期24卷 751-762页

作者： WANG Hao DENG Yu TIAN Enze WANG Kaiyong Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences university of Chinese Academy of Sciences harvard university graduate school of design cambridge 02138 USA

A number of urban and regional plans have been developed with the advancement of urbanization and regional integration, among which the delineation of sphere of urban influence and improvement of integration between the city and its hinterland have become vital important for guiding practices. In terms of delineating sphere of urban influence, existing studies have been focused on static study by using single year data or single method, resulting in a lack of time-series longitudinal analysis or comprehensive analysis based on multiple methods. This study emphasizes on comparing two methods from both the theoretical and empirical perspective. Both gravity model and improved field model are applied to the selected study area for measurements and comparison, to explore their strengths and weaknesses. A research framework for comprehensive analysis on delineating sphere of urban influence is proposed. In the end, the differences of delineating methods are illustrated and the feasibility of comprehensive analysis is discussed. Recommendations are provided for selecting appropriate methods for delineating sphere of urban influence or developing regional hierarchy system plans and urban spatial structure schemes.

关键词：城市化中国案例区域规划势力范围区域一体化时间序列研究区域

From Bench to the Clinic: The Path to Translation of Nanotechnology-Enabled mRNA SARS-CoV-2 Vaccines

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Nano-Micro Letters 2022年第3期14卷 1-31页

作者： Diana O.Lopez‑Cantu Xichi Wang Hector Carrasco‑Magallanes Samson Afewerki Xingcai Zhang Joseph V.Bonventre Guillermo U.Ruiz‑Esparza Division of Engineering in Medicine Department of MedicineBrigham and Women’s HospitalHarvard Medical SchoolBostonMA 02115USA Division of Health Sciences and Technology Harvard University-Massachusetts Institute of TechnologyBostonMA 02115USA Division of Renal Medicine Department of MedicineBrigham and Women’s HospitalHarvard Medical SchoolBostonMA 02115USA Tecnologico de Monterrey School of Engineering and Sciences64849 MonterreyNLMexico Department of Cardiovascular Surgery Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022People’s Republic of China harvard T.H.Chan school of Public Health BostonMA 02115USA Tecnologico de Monterrey School of Medicine and Health Sciences64849 MonterreyNLMexico John A.Paulson school of Engineering and Applied Sciences Harvard UniversityCambridgeMA 02138USA school of Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA

During the last decades,the use of nanotechnology in med icine has effectively been translated to the design of drug delivery systems,nanostructured tissues,diagnostic platforms,and novel nanomaterials against several human diseases and infectious pathogens.Nanotechnology-enabled vaccines have been positioned as solutions to mitigate the pandemic outbreak caused by the novel pathogen severe acute respiratory syndrome coronavirus 2.To fast-track the development of vaccines,unprecedented industrial and academic collaborations emerged around the world,resulting in the clinical translation of effective vaccines in less than one year.In this article,we provide an overview of the path to translation from the bench to the clinic of nanotechnology-enabled messenger ribonucleic acid vaccines and examine in detail the types of delivery systems used,their mechanisms of action,obtained results during each phase of their clinical development and their regulatory approval process.We also analyze how nanotechnology is impacting global health and economy during the COVID-19 pandemic and beyond.

关键词： Nanovaccines mRNA Coronavirus SARS-CoV-2 COVID-19

Liquid-metal micro-networks with strain-induced conductivity for soft electronics and robotic skin

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npj Flexible Electronics 2022年第1期6卷 799-808页

作者： Yeongmin Park Jaewoong Jung Younghoon Lee Dongwoo Lee Joost J.Vlassak Yong-Lae Park Department of Mechanical Engineering Institute of Advanced Machines and DesignInstitute of Engineering ResearchSeoul National UniversitySeoul 08826Korea Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology(MIT)CambridgeMA 02139USA school of Mechanical Engineering Sungkyunkwan UniversitySuwon 16419Korea John A.Paulson school of Engineering and Applied Sciences Harvard UniversityCambridgeMA 02138USA

Thin-film devices made of room-temperature liquid metals(LMs)have contributed to the development of electronic skin for human-robot/machine interfaces but still have limitations,including degradations of performance and robustness under repeated deformations.In this paper,we describe an interesting phenomenon of the formation of LM microscale networks(LMMNs)and propose to use the LMMNs for fabricating thin-film conductors.A simple layer-by-layer(LBL)deposition process enables the growth of a hierarchical structure of LM microdroplets that forms a conductive network(i.e.,LMMN)when stretched.The strain-history behavior of LMMNs allows conductivity enhancement up to 2.37×10^(6) S m^(-1) in response to increased tensile strains.By adjusting the number of LM layers in LBL deposition,the gauge factor(0.2≤GF≤1),the linearity,and the sheet resistance of LMMN films can be easily controlled,providing high potentials in various applications,including skin-mountable circuits,energy harvesters,and soft artificial skin.

关键词： strain networks conductivity

Machine Learning Modeling of Protein-intrinsic Features Predicts Tractability of Targeted Protein Degradation

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Genomics, Proteomics & Bioinformatics 2022年第5期20卷 882-898页

作者： Wubing Zhang Shourya S.Roy Burman Jiaye Chen Katherine A.Donovan Yang Cao Chelsea Shu Boning Zhang Zexian Zeng Shengqing Gu Yi Zhang Dian Li Eric S.Fischer Collin Tokheim X.Shirley Liu Department of Data Science Dana-Farber Cancer InstituteBostonMA 02215USA Department of Biostatistics Harvard T.H.Chan School of Public HealthBostonMA 02115USA Department of Cancer Biology Dana-Farber Cancer InstituteBostonMA 02215USA Department of Biological Chemistry and Molecular Pharmacology Harvard Medical SchoolBostonMA 02115USA Department of Biomedical Informatics Harvard Medical SchoolBostonMA 02115USA Center of Growth Metabolismand AgingKey Laboratory of Bio-resource and Eco-environmentMinistry of EducationCollege of Life SciencesSichuan UniversityChengdu 610064China Research Scholar Initiative Graduate School of Arts and SciencesHarvard UniversityCambridgeMA 02138USA

Targeted protein degradation(TPD)has rapidly emerged as a therapeutic modality to eliminate previously undruggable proteins by repurposing the cell’s endogenous protein degradation machinery.However,the susceptibility of proteins for targeting by TPD approaches,termed“degradability”,is largely unknown.Here,we developed a machine learning model,model-free analysis of protein degradability(MAPD),to predict degradability from features intrinsic to protein targets.MAPD shows accurate performance in predicting kinases that are degradable by TPD compounds[with an area under the precision–recall curve(AUPRC)of 0.759 and an area under the receiver operating characteristic curve(AUROC)of 0.775]and is likely generalizable to independent non-kinase proteins.We found five features with statistical significance to achieve optimal prediction,with ubiquitination potential being the most predictive.By structural modeling,we found that E2-accessible ubiquitination sites,but not lysine residues in general,are particularly associated with kinase degradability.Finally,we extended MAPD predictions to the entire proteome to find964 disease-causing proteins(including proteins encoded by 278 cancer genes)that may be tractable to TPD drug development.

关键词： Targeted protein degradation Degradability Protein-intrinsic feature Ubiquitination Machine learning

The ALMA-QUARKS Survey.Ⅰ.Survey Description and Data Reduction

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Research in Astronomy and Astrophysics 2024年第2期24卷 104-124页

作者：刘训川 Tie Liu Lei Zhu Guido Garay Hong-Li Liu Paul Goldsmith Neal Evans Kee-Tae Kim Sheng-Yuan Liu Fengwei Xu Xing Lu Anandmayee Tej Xiaofeng Mai Leonardo Bronfman Shanghuo Li Diego Mardones Amelia Stutz Ken'ichi Tatematsu Ke Wang Qizhou Zhang Sheng-Li Qin Jianwen Zhou Qiuyi Luo Siju Zhang Yu Cheng Jinhua He Qilao Gu Ziyang Li Zhenying Zhang Suinan Zhang Anindya Saha Lokesh Dewangan Patricio Sanhueza Zhiqiang Shen Shanghai Astronomical Observatory Chinese Academy of SciencesShanghai 200030China Chinese Academy of Sciences South America Center for Astronomy National Astronomical ObservatoriesChinese Academy of SciencesBeijing 100101China Departamento de Astronomía Universidad de ChileLas Condes7591245 SantiagoChile school of Physics and Astronomy Yunnan UniversityKunming 650091China Jet Propulsion Laboratory California Institute of Technology4800 Oak Grove DrivePasadena CA 91109USA Department of Astronomy The University of Texas at AustinTX 78712-1205USA Korea Astronomy and Space Science Institute 776 Daedeokdae-roYuseong-guDaejeon 34055Republic of Korea Institute of Astronomy and Astrophysics Academia SinicaRoosevelt RoadTaipei 10617China Kavli Institute for Astronomy and Astrophysics Peking UniversityBeijing 100871China Department of Astronomy School of PhysicsPeking UniversityBeijing 100871China Indian Institute of Space Science and Technology Thiruvananthapuram 695547KeralaIndia Max Planck Institute for Astronomy Königstuhl 17D-69117 HeidelbergGermany Departamento de Astronomía Universidad de ConcepciónCasilla 160-CConcepciónChile Nobeyama Radio Observatory National Astronomical Observatory of JapanNational Institutes of Natural Sciences462-2 NobeyamaMinamimakiMinamisakuNagano 384-1305Japan Center for Astrophysics∣harvard&Smithsonian 60 Garden StreetCambridgeMA 02138USA Max-Planck-Institut für Radioastronomie Auf dem Hügel 69D-53125 BonnGermany school of Astronomy and Space Sciences University of Chinese Academy of SciencesBeijing 100049China National Astronomical Observatory of Japan 2-21-1 OsawaMitakaTokyo181-8588Japan Yunnan Observatories Chinese Academy of SciencesKunming 650216China Physical Research Laboratory NavrangpuraAhmedabad-380009India Astronomical Science Program The Graduate University for Advanced StudiesSOKENDAI2-21-1 OsawaMitakaTokyo 181-8588Japan university of Science and Technology Korea(UST)217 Gajeong-roYuseong-guDaejeon 34113Republic o

This paper presents an overview of the QUARKS survey,which stands for Querying Underlying mechanisms of massive star formation with ALMA-Resolved gas Kinematics and Structures."The QUARKS survey is observing139 massive clumps covered by 156 pointings at Atacama Large Millimeter/submillimeter Array(ALMA)Band 6(λ~1.3 mm).In conjunction with data obtained from the ALMA-ATOMS survey at Band 3(λ~3 mm),QUARKS aims to carry out an unbiased statistical investigation of massive star formation process within protoclusters down to a scale of 1000 au.This overview paper describes the observations and data reduction of the QUARKS survey,and gives a first look at an exemplar source,the mini-starburst Sgr B2(M).The wide-b and width(7.5 GHz)and high-angular-resolution(~0."3)observations of the QUARKS survey allow for the resolution of much more compact cores than those could be done by the ATOMS survey,and to detect previously unrevealed fainter filamentary structures.The spectral windows cover transitions of species including CO,SO,N_(2)D^(+),SiO,H_(30)α,H_(2)CO,CH_(3)CN,and many other complex organic molecules,tracing gas components with different temperatures and spatial extents.QUARKS aims to deepen our understanding of several scientific topics of massive star formation,such as the mass transport within protoclusters by(hub-)filamentary structures,the existence of massive starless cores,the physical and chemical properties of dense cores within protoclusters,and the feedback from already formed high-mass young protostars.

关键词： stars formation-stars kinematics and dynamics-ISM clouds-ISM molecules