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Protein-nucleic acid hybrid nanostructures for molecular diagnostic applications

Nano Research 2024年第10期17卷 9003-9014页

作者： Noah R.Sundah Yuxuan Seah Auginia Natalia Xiaoyan Chen Panida Cen Yu Liu Huilin Shao Institute for Health Innovation and Technology National University of SingaporeSingapore 117599Singapore Department of Biomedical Engineering College of Design and EngineeringNational University of SingaporeSingapore 117583Singapore Integrative Sciences and Engineering Programme NUS Graduate SchoolNational University of SingaporeSingapore 119077Singapore Institute of Molecular and Cell Biology Agency for ScienceTechnology and ResearchSingapore 138673Singapore Department of Surgery Yong Loo Lin School of MedicineNational University of SingaporeSingapore 117597Singapore

Molecular diagnostic technologies empower new clinical opportunities in precision ***,existing approaches face limitations with respect to performance,operation and *** molecules including proteins and nucleic acids are being increasingly adopted as tools in the development of new molecular diagnostic *** particular,leveraging their complementary properties—the functional diversity of proteins and the precision programmability of nucleic acids—a wide range of protein–nucleic acid hybrid nanostructures have been *** hybrid structures take diverse forms,ranging from one-dimensional to three-dimensional hybrids,as static assemblies to dynamic machines,and possess myriad functions to recognize target biomarkers,encode vast information and execute catalytic *** by recent advances in this area of molecular nanotechnology,we review the state-of-art design and application of various types of protein–nucleic acid hybrid nanostructures for molecular diagnostics,and present an outlook on the challenges and opportunities for emerging pre-clinical and clinical applications,highlighting the promise for earlier detection,more refined diagnosis and highly tailored treatment decision that ultimately lead to improved patient outcomes.

关键词： molecular nanotechnology DNA-protein hybrid molecular diagnostics precision medicine

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Evaluating Student Academic Motivations in One-year CubeSat Project using 3x 2 Achievement Goal Framework

Evaluating Student Academic Motivations in One-year CubeSat ...

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2019 IEEE International Conference on Engineering, Technology and Education, TALE 2019

作者： Luo, Sha Gan, Joo Seng Loh, Ai Po Ee, Eugene Wei Hao Soh, Eng Keng National University of Singapore Department of Electrical and Computer Engineerng Singapore Singapore National University of Singapore Innovation Design Programme Singapore Singapore

ISBN: (纸本)9781728126654

In 2012, National University of Singapore (NUS) started to develop Cubesats as an educational platform to teach and motivate engineering students from multidisciplinary backgrounds to apply their engineering knowledge and skills in real-life contexts. In this CubeSat project, students have the opportunity to work on an actual nanosatellite, which would be launched into space, as their Final Year Projects (FYPs) or one-year master projects with academic credits. In this paper, we investigated students' motivation to work on this project by measuring their achievement goals using a 3x2 achievement goal motivation questionnaire by Elliot, Murayama and Pekrun (2011). Nineteen engineering students were enrolled in our one-year CubeSat project and they were surveyed at the beginning, the middle and at the end of their projects. Students' overall motivation was found to be high but during the middle phase of the project, there was a dip in motivation. Overall, task-approach goal score was increased but their self-avoidance goal score increased faster than their self-approach goal score. There were also variations of students' other-approach and other-avoidance goal scores during the project process. These findings were discussed in relation to the instructional approach in CubeSat and the implications for enhancing students' real-life learning experiences. © 2019 IEEE.

关键词： Students

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Detection of Freezing of Gait using Convolutional Neural Networks and Data from Lower Limb Motion Sensors

TechRxiv

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TechRxiv 2021年

作者： Shi, Bohan Tay, Arthur Au, W.L. Tan, Dawn M.L. Chia, Nicole S.Y. Yen, Shih-Cheng The Department of Electrical and Computer Engineering National University of Singapore Singapore Activate Interactive Pte. Ltd Singapore The Department of Neurology National Neuroscience Institute Singapore The Department of Physiotherapy Singapore General Hospital Singapore The Innovation and Design Programme Faculty of Engineering National University of Singapore Singapore

Parkinson’s disease (PD) is a chronic, non-reversible neurodegenerative disorder, and freezing of gait (FOG) is one of the most disabling symptoms in PD as it is often the leading cause of falls and injuries that drastically reduces patients’ quality of life. In order to monitor continuously and objectively PD patients who suffer from FOG and enable the possibility of on-demand cueing assistance, a sensor-based FOG detection solution can help clinicians manage the disease and help patients overcome freezing episodes. Many recent studies have leveraged deep learning models to detect FOG using signals extracted from inertial measurement unit (IMU) devices. Usually, the latent features and patterns of FOG are discovered from either the time or frequency domain. In this study, we investigated the use of the time-frequency domain by applying the Continuous Wavelet Transform to signals from IMUs placed on the lower limbs of 63 PD patients who suffered from FOG. We built convolutional neural networks to detect the FOG occurrences, and employed the Bayesian Optimisation approach to obtain the hyper-parameters. The results showed that the proposed subject-independent model was able to achieve a geometric mean of 90.7% and a F1 score of 91.5%. © 2021-08-26, CC BY.

关键词： Wearable sensors

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Transverse Pelvic/Saddle Rotation Characterizing Push-Off Initiation During Saddle-Seat-Type Body-Weight-Supported Treadmill Walking

Transverse Pelvic/Saddle Rotation Characterizing Push-Off In...

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IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Ryohei Terada Hiroaki Hirai Kosei Sasaki Hirokazu Kuga Keisuke Furukawa Kazuhiro Matsui Atsushi Nishikawa Hermano Igo Krebs Department of Mechanical Science and Bioengineering Graduate School of Engineering Science Osaka University Toyonaka Japan Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge USA Department of Neurology University of Maryland School of Medicine Baltimore USA Department of Physical Medicine and Rehabilitation Fujita Health University Nagoya Japan Department of System Design Engineering Keio University Tokyo Japan The Wolfson School of Engineering Loughborough University Loughborough UK Programme Bioengineering Applied Science and Intelligent Systems University Campus Bio-Medico of Rome Rome Italy Healthcare Engineering Innovation Center (HEIC) Khalifa University of Science and Technology Abu Dhabi UAE Department of Mechanical Science and Bioengineering Osaka University Toyonaka Japan

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Background and Aim: A push-off event is a significant gait phase that contributes to initiating the swing leg and propelling the body forward. This study aims to explore a method for estimating push-off initiation, focusing on pelvic and saddle-seat motion peculiar to saddle-seat-type body-weight-supported (BWS) treadmill walking. Methods: The pelvic/saddle-seat rotation and ground reaction force during saddle-seat-type BWS treadmill walking were measured using an IMU sensor and a force plate in the treadmill, respectively. The hypothesis posits that the transverse rotational displacement of the pelvis and saddle seat aids in estimating push-off initiation. Results: The analysis results show that (1) the timing estimated from transverse pelvic rotation moderately agreed with push-off initiation timing (Spearman's rank correlation coefficient $\rho=0.59, \mathrm{p} < 0.01)$ , and (2) the timing estimated from transverse saddle rotation strongly agreed with push-off initiation timing $(\rho=0.67,\mathrm{p} < 0.01)$ . Conclusions: The utilization of a single IMU sensor requires a minimal setup for identifying push-off initiation, which contributes to reducing time, effort, and costs in clinical settings. This preliminary study using intact subjects should be a meaningful first step in the research for gait rehabilitation with saddle-seat-type BWS.

关键词： Legged locomotion Training Force measurement Force Focusing Propulsion Robot sensing systems Timing Pelvis Rotation measurement

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Assessing Elevated Blood Glucose Levels Through Blood Glucose Evaluation and Monitoring Using Machine Learning and Wearable Photoplethysmography Sensors: Algorithm Development and Validation

TechRxiv

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TechRxiv 2022年

作者： Shi, Bohan Dhaliwal, Satvinder Singh Soo, Marcus Chan, Cheri Wong, Jocelin Lam, Natalie W.C. Zhou, Entong Paitimusa, Vivien Loke, Kum Yin Chin, Joel Chua, Mei Tuan Liaw, Kathy Chiew Suan Lim, Amos W.H. Insyirah, Fadil Fatin Yen, Shih-Cheng Tay, Arthur Ang, Seng Bin Actxa Pte Ltd Singapore Singapore Activate Interactive Pte Ltd Singapore Singapore Curtin Health Innovation Research Institute Curtin University Perth Australia Faculty of Health Sciences Curtin University Perth Australia Duke NUS Graduate Medical School National University of Singapore Singapore KK Women’s and Children’s Hospital Singapore Innovation and Design Programme Faculty of Engineering National University of Singapore Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore Family Medicine Academic Clinical Program Duke-NUS Medical School Singapore Menopause Unit KK Women’s and Children’s Hospital Singapore

Background: Diabetes mellitus is the most challenging and fastest-growing global public health concern. Approximately 10.5% of the global adult population is affected by diabetes, and almost half of them are undiagnosed. The growing at-risk population exacerbates the shortage of health resources, with an estimated 10.6% and 6.2% of adults worldwide having impaired glucose tolerance and impaired fasting glycemia, respectively. All current diabetes screening methods are invasive and opportunistic and must be conducted in a hospital or laboratory by trained professionals. At-risk participants might remain undetected for years and miss the precious time window for early intervention to prevent or delay the onset of diabetes and its complications. Objective: We aimed to develop an artificial intelligence solution to recognize elevated blood glucose levels (≥7.8 mmol/L) noninvasively and evaluate diabetic risk based on repeated measurements. Methods: This study was conducted at KK Women’s and Children’s Hospital in Singapore, and 500 participants were recruited (mean age 38.73, SD 10.61 years;mean BMI 24.4, SD 5.1 kg/m2). The blood glucose levels for most participants were measured before and after consuming 75 g of sugary drinks using both a conventional glucometer (Accu-Chek Performa) and a wrist-worn wearable. The results obtained from the glucometer were used as ground-truth measurements. We performed extensive feature engineering on photoplethysmography (PPG) sensor data and identified features that were sensitive to glucose changes. These selected features were further analyzed using an explainable artificial intelligence approach to understand their contribution to our predictions. Results: Multiple machine learning models were trained and assessed with 10-fold cross-validation, using participant demographic data and critical features extracted from PPG measurements as predictors. A support vector machine with a radial basis function kernel had the best detection p

关键词： Wearable sensors

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A nonlinear hidden layer enables actor-critic agents to learn multiple paired association navigation

arXiv

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arXiv 2021年

作者： Kumar, M. Ganesh Tan, Cheston Libedinsky, Camilo Yen, Shih-Cheng Tan, Andrew Y.Y. Integrative Sciences and Engineering Programme NUS Graduate School National University of Singapore Singapore N.1 Institute for Health National University of Singapore Singapore Innovation and Design Programme Faculty of Engineering National University of Singapore Singapore Institute for Infocomm Research Agency for Science Technology and Research Singapore Department of Psychology National University of Singapore Singapore Institute of Molecular and Cell Biology A*STAR Singapore Department of Physiology Yong Loo Lin School of Medicine National University of Singapore Singapore Healthy Longevity Translational Research Programme Yong Loo Lin School of Medicine National University of Singapore Singapore Cardiovascular Disease Translational Research Programme Yong Loo Lin School of Medicine National University of Singapore Singapore Neurobiology Programme Life Sciences Institute National University of Singapore Singapore

Navigation to multiple cued reward locations has been increasingly used to study rodent learning. Though deep reinforcement learning agents have been shown to be able to learn the task, they are not biologically plausible. Biologically plausible classic actor-critic agents have been shown to learn to navigate to single reward locations, but which biologically plausible agents are able to learn multiple cue-reward location tasks has remained unclear. In this computational study, we show versions of classic agents that learn to navigate to a single reward location, and adapt to reward location displacement, but are not able to learn multiple paired association navigation. The limitation is overcome by an agent in which place cell and cue information are first processed by a feedforward nonlinear hidden layer with synapses to the actor and critic subject to temporal difference error-modulated plasticity. Faster learning is obtained when the feedforward layer is replaced by a recurrent reservoir network. Copyright © 2021, The Authors. All rights reserved.

关键词： Navigation

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One-shot learning of paired association navigation with biologically plausible schemas

arXiv

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arXiv 2021年

作者： Kumar, M. Ganesh Tan, Cheston Libedinsky, Camilo Yen, Shih-Cheng Tan, Andrew Y.Y. Integrative Sciences and Engineering Programme NUS Graduate School National University of Singapore Singapore The N.1 Institute for Health National University of Singapore Singapore Engineering Design and Innovation Centre College of Design and Engineering National University of Singapore Singapore School of Engineering and Applied Sciences Harvard University United States Institute for Infocomm Research Agency for Science Technology and Research Singapore Department of Psychology National University of Singapore Singapore Institute of Molecular and Cell Biology Agency for Science Technology and Research Singapore Department of Physiology Yong Loo Lin School of Medicine National University of Singapore Singapore Healthy Longevity Translational Research Programme Yong Loo Lin School of Medicine National University of Singapore Singapore Cardiovascular Disease Translational Research Programme Yong Loo Lin School of Medicine National University of Singapore Singapore Neurobiology Programme Life Sciences Institute National University of Singapore Singapore

Schemas are knowledge structures that can enable rapid learning. Rodent one-shot learning in a multiple paired association navigation task has been postulated to be schema-dependent. We still only poorly understand how schemas, conceptualized at Marr's computational level, are neurally implemented. Moreover, a biologically plausible computational model of the rodent learning has not been demonstrated. Accordingly, we here compose an agent from schemas with biologically plausible neural implementations. The agent gradually learns a metric representation of its environment using a path integration temporal difference error, allowing it to localize in any environment. Additionally, the agent contains an associative memory that can stably form numerous one-shot associations between sensory cues and goal coordinates, implemented with a feedforward layer or a reservoir of recurrently connected neurons whose plastic output weights are governed by a 4-factor reward-modulated Exploratory Hebbian (EH) rule. A third network performs vector subtraction between the agent’s current and goal location to decide the direction of movement. We further show that schemas supplemented by an actor-critic allows the agent to succeed even if an obstacle prevents direct heading, and that temporal-difference learning of a working memory gating mechanism enables one-shot learning despite distractors. Our agent recapitulates learning behavior observed in experiments and provides testable predictions that can be probed in future experiments. Copyright © 2021, The Authors. All rights reserved.

关键词： Zero-shot learning

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Genomic Epidemiology of SARS-CoV-2 in Pakistan

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Genomics, Proteomics & Bioinformatics 2021年第5期19卷 727-740页

作者： Shuhui Song Cuiping Li Lu Kang Dongmei Tian Nazish Badar Wentai Ma Shilei Zhao Xuan Jiang Chun Wang Yongqiao Sun Wenjie Li Meng Lei Shuangli Li Qiuhui Qi Aamer Ikram Muhammad Salman Massab Umair Huma Shireen Fatima Batool Bing Zhang Hua Chen Yun-Gui Yang Amir Ali Abbasi Mingkun Li Yongbiao Xue Yiming Bao China National Center for Bioinformation Beijing 100101China National Genomics Data Center Beijing Institute of GenomicsChinese Academy of SciencesBeijing 100101China CAS Key Laboratory of Genome Sciences and Information Beijing Institute of GenomicsChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China CAS Key Laboratory of Genomic and Precision Medicine Beijing Institute of GenomicsChinese Academy of SciencesBeijing 100101China Department of Virology and Immunology National Institute of HealthIslamabad 45500Pakistan National Center for Bioinformatics Programme of Comparative and Evolutionary GenomicsFaculty of Biological SciencesQuaid-i-Azam UniversityIslamabad 45320Pakistan Center for Excellence in Animal Evolution and Genetics Chinese Academy of SciencesKunming 650223China State Key Laboratory of Plant Cell and Chromosome Engineering Institute of Genetics and Developmental BiologyThe Innovation Academy of Seed DesignChinese Academy of SciencesBeijing 100101China

COVID-19 has swept globally and Pakistan is no *** investigate the initial introductions and transmissions of the SARS-CoV-2 in Pakistan,we performed the largest genomic epidemiology study of COVID-19 in Pakistan and generated 150 complete SARS-CoV-2 genome sequences from samples collected from March 16 to June 1,*** identified a total of 347 mutated positions,31 of which were over-represented in ***,we found over 1000 intra-host single-nucleotide variants(iSNVs).Several of them occurred concurrently,indicating possible interactions among them or *** of the high-frequency iSNVs in Pakistan were not observed in the global population,suggesting strong purifying *** genomic epidemiology revealed five distinctive spreading *** largest cluster consisted of 74 viruses which were derived from different geographic locations of Pakistan and formed a deep hierarchical structure,indicating an extensive and persistent nation-wide transmission of the virus that was probably attributed to a signature mutation(G8371T in ORF1ab)of this ***,28 putative international introductions were identified,several of which are consistent with the epidemiological *** all,this study has inferred the possible pathways of introductions and transmissions of SARS-CoV-2 in Pakistan,which could aid ongoing and future viral surveillance and COVID-19 control.

关键词： SARS-CoV-2 Virus Molecular evolution Haplotype network Pakistan

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Sensitivity analysis of heating a typical UK dwelling and implications for retrofit design

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Journal of Physics: Conference Series 2021年第1期2042卷

作者： Kate Simpson Peter Childs Jennifer Whyte Data-Centric Engineering Programme Alan Turing Institute London UK Dyson School of Design Engineering Imperial College London UK Centre for Systems Engineering and Innovation Imperial College London UK

The aim of this research is to quantify the impact of heating set point on space heating energy demand for a typical UK dwelling. Retrofit includes fabric energy efficiency improvements. Energy performance certificates (EPCs) inform the householder of typical savings per measure, but this has previously been found to inaccurately estimate space heating energy demand, leading to errors in 'typical savings' presented to householders. The most sensitive inputs have been found to be temperature set point, followed by fabric efficiency. The BREDEM methodology assumes a temperature of 21°C for nine hours a day, rather than ~16°C and ~20°C found in research. The methods used to inform this study are local sensitivity analysis of the domestic energy model, based on a typical dwelling example with calibrated inputs. This is done using an open calibrated Python model, based on BREDEM. The impact of heating patterns on space heating energy demand are modelled pre retrofit; according to differing heating set points, following wall and loft fabric upgrade and full fabric upgrade. The BREDEM heating set point assumptions lead to space heating energy demand predicted ~50-100 kWh/m2/yr higher than real heating set points. Implications for retrofit design and EPCs are discussed.

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He Kāinga Oranga: reflections on 25 years of measuring the improved health, wellbeing and sustainability of healthier housing

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Journal of the Royal Society of New Zealand 2024年第3期54卷 290-315页

作者： Philippa Howden-Chapman Julian Crane Michael Keall Nevil Pierse Michael G. Baker Chris Cunningham Kate Amore Clare Aspinall Julie Bennett Sarah Bierre Mikael Boulic Ralph Chapman Elinor Chisholm Cheryl Davies Geoff Fougere Brodie Fraser Caro Fyfe Libby Grant Arthur Grimes Caroline Halley Amber Logan-Riley Kim Nathan Crystal Olin Jenny Ombler Kimberley O’Sullivan Tiria Pehi Guy Penny Robyn Phipps Manfred Plagman Edward Randal Lynn Riggs Bridget Robson Jacinta Ruru Caroline Shaw Ben Schrader Mary Anne Teariki Lucy Telfar Barnard Ramona Tiatia Bridgette Toy-Cronin Hope Tupara Helen Viggers Teresa Wall Marg Wilkie Alistair Woodward Wei Zhang a He Kāinga Oranga/Housing and Health Research Programme University of Otago Wellington New Zealand b Research Centre for Hauora & Health Massey University Wellington New Zealand c School of the Built Environment Massey University Auckland New Zealand d School of Geography Environment and Earth Sciences Te Herenga Waka Victoria University of Wellington New Zealand e Tu Kotahi Māori Asthma Trust Wainuiomata Lower Hutt New Zealand f Motu Economic and Public Policy Research Wellington New Zealand g EMPlan Services Ltd Wellington New Zealand h Faculty of Architecture and Design Innovation Te Herenga Waka Victoria University of Wellington Wellington New Zealand i Building Research Association of New Zealand Porirua New Zealand j Eru Pomare Māori Health Research Centre University of Otago Wellington New Zealand k Faculty of Law University of Otago Dunedin New Zealand l Department of Public Health University of Otago Wellington New Zealand m Stout Research Centre Te Herenga Waka Victoria University of Wellington Wellington New Zealand n Wall Consultants Wellington New Zealand o School of Population Health University of Auckland Auckland New Zealand

ABSTRACTThis paper reflects on the influences and outcomes of He Kāinga Oranga/Housing and Health Research programme over 25 years, and their impact on housing and health policy in Aotearoa and internationally. Working in partnership particularly with Māori and Pasifika communities, we have conducted randomised control trials which have shown the health and broad co-benefits of retrofitted insulation, heating and remediation of home hazards, which have underpinned government policy in the Warm Up NZ-Heat Smart programme and the Healthy Homes Standards for rental housing. These trials have been included as evidence in the WHO Housing and Health Guidelines and led to our designation as a WHO Collaborating Centre on Housing and Wellbeing. We are increasingly explicitly weaving Māori frameworks, values and processes with traditional Western science.

关键词： Housing health wellbeing policy interventions mātauranga Māori Pasifika

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