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Your search keyword '"Sherianne Yen Tze Tan"' showing total 2 results
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2 results on '"Sherianne Yen Tze Tan"'

1. Community hospitals of the future: the role of community hospitals to mitigate health system burden in Singapore

Author

Chuan De Foo, Hui Xiang Chia, Sherianne Yen Tze Tan, Yi Feng Lai, Jia En Joy Khoo, Shi Yun Tee, Cher Wee Lim, and Ken Wah Teo

Subjects
community hospital, right-site, chronic disease, health policy, health system reform, Medicine
Abstract

In Singapore, an ageing population with increasing chronic disease burden and complex social circumstances have strained the healthcare system. For the health system to run more efficiently, patients should be appropriately sited according to their medical needs. In Singapore, community hospitals serve as an intermediate inpatient facility managing patients with sub-acute and rehabilitation care needs. Our policy brief uncovers the gaps in transforming community hospital care models and offers actionable steps to unlock the community hospital chokepoints in Singapore's health system. The future community hospitals can accommodate higher acuity but medically stable patients, while patients who do not require inpatient rehabilitation care can be appropriately sited to community partners, if policy, resourcing and technology factors are addressed. An evidence-based, stepwise approach involving all stakeholders will be required to pilot and evaluate new models before large-scale change.

Published
2024
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2. LSTrAP-Crowd: Prediction of novel components of bacterial ribosomes with crowd-sourced analysis of RNA sequencing data

Author

Benedict Hew, Qiao Wen Tan, William Goh, Jonathan Wei Xiong Ng, Kenny Koh, Ryan Chieh Feng Rugdee, Zheng Kai Teng, Jun Xiong Tan, Xi Yei, Qing Rong Tan, Ifa Syafiqah Binte Sulaiman, Seo Min Li Gilia, Erielle Marie Fajardo Villanueva, Son Thanh Nguyen, Dhira Anindya Putri, Jovi Tan Siying, Teo Yong Ren Johanan, Jia Wei Tan, Koh Shao Ning, null Gladys, Wei Wen Ong, Jia Rong Moo, Jace Koh, Pei Xuan Lim, Shook Wei Teoh, Pravin Tamilselvam, Harvard Hui, Yi Xuan Chua, Yook Kit Ow Yeong, Tay Jian Hua, Ming Jun Chong, Yu Wei Sho, Bridget Jing Xing Tang, Carissa Yuwono Kwantalalu, Nur Afiqah Binte Mohammad Rizal, Wei Heng Tan, Lim Shan Chun, Sherianne Yen Tze Tan, Tan Jia Ying, Audrey Michelle Luminary, Lim Jia Jia, null Jolyn, Vanessa Lunardi, Ann Don Low, M K Abdul Rahim, Lin Ming, Joseph JQ Ng, Han Tsou, Cheryl Lim Jiayi, Teffarina Tay Hui Wen, Valerie Teo Fang Wei, Tan You Sheng Justin, Shellia Oktavina, Aaminatul Khalishah Binte Roslan, Natasha Cassandra Chee, Zoe Chen Hui Xin, Nhi Uyen Le Nguyen, Tristy Abigayle Marta, Poh Jia’En, Ang Wei Ying, Alena Tay Qi Ye, Chiu Wei Yeow Emile, Wong Xanaz, Xylon Wei Rui Lee, Wong Pei Wen Kelly, Zhe Jun Tan, Vishalini Val R, Rayna Yip, Cherlyn Chua, Kai Lun Boon, Sriya Mulupuri, Lim Yuen Shan, Samantha Chee Suhui, Amanda Crystal Lee Wei Jin, Siew Choo Tey, Qi Ying Neo, Chan Yi Hue, Phua Tian Xin, Ana Ho Sze Qi, Edbert E. Rodrigues, Chan Mu En, Dynn Sim, Marcus Chee, Abigail Ho, Ang Wen hui, Bertrand Wong, Margaret X Zhao, Er Kian Ching Gabbie, Deng Zheyun Grace, Xin Yi Tan, Melissa Foong, Lim Qin Rui Rachel, Alyssa Jiaqi Lim, Seow Jia Xuan, Rinta P. Reji, Devika Menon, Ong Xuan Xuan, null Nicole, Ravi Keerthana, Min Jia Wong, Zachary J D’Rozario, Shing Yee Lim, Nicholas Lee, Ying Ni, Ying Lian, Jing Wen Poh, Ming Jern Adrian Lee, Pravenah Ravi Chandran, Jia Xin Ngiaw, Herman Foo, Joash Poon, Tong Ling Chan, Perry Ng, Ashlyn Xuanqi Ng, Zhen Ying Ong, Lee Wan Xuan Trena, Lim Shi Min Kristy, Yu Xuan Thng, Ong Si Yi Shirley, Sau Thi Chu, Shu Hua Samantha Lim, Jun Sheng Ho, Celest Lixuan Phang, Victoria Toh Le Yi, Peiran Ng, Seetoh Wei Song, Manessa Nah Shue Ern, and Marek Mutwil

Subjects
Transcriptome, Antibiotic resistance, biology, Gene expression, Protein biosynthesis, RNA, Computational biology, biology.organism_classification, Ribosome, Gene, Bacteria
Abstract

Bacterial resistance to antibiotics is a growing problem that is projected to cause more deaths than cancer in 2050. Consequently, novel antibiotics are urgently needed. Since more than half of the available antibiotics target the bacterial ribosomes, proteins that are involved in protein synthesis are thus prime targets for the development of novel antibiotics. However, experimental identification of these potential antibiotic target proteins can be labor-intensive and challenging, as these proteins are likely to be poorly characterized and specific to few bacteria. In order to identify these novel proteins, we established a Large-Scale Transcriptomic Analysis Pipeline in Crowd (LSTrAP-Crowd), where 285 individuals processed 26 terabytes of RNA-sequencing data of the 17 most notorious bacterial pathogens. In total, the crowd processed 26,269 RNA-seq experiments and used the data to construct gene co-expression networks, which were used to identify more than a hundred uncharacterized genes that were transcriptionally associated with protein synthesis. We provide the identity of these genes together with the processed gene expression data. The data can be used to identify other vulnerabilities or bacteria, while our approach demonstrates how the processing of gene expression data can be easily crowdsourced.

Published
2020
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