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Articles 1141 - 1170 of 3231
Full-Text Articles in Data Science
Sox On Tumors, A Comfort Or A Constraint?, Junqing Jiang, Yufei Wang, Mengyu Sun, Xiangyuan Luo, Zerui Zhang, Yijun Wang, Siwen Li, Dian Hu, Jiaqian Zhang, Zhangfan Wu, Xiaoping Chen, Bixiang Zhang, Xiao Xu, Shuai Wang, Shengjun Xu, Wenjie Huang, Limin Xia
Sox On Tumors, A Comfort Or A Constraint?, Junqing Jiang, Yufei Wang, Mengyu Sun, Xiangyuan Luo, Zerui Zhang, Yijun Wang, Siwen Li, Dian Hu, Jiaqian Zhang, Zhangfan Wu, Xiaoping Chen, Bixiang Zhang, Xiao Xu, Shuai Wang, Shengjun Xu, Wenjie Huang, Limin Xia
Faculty, Staff and Student Publications
The sex-determining region Y (SRY)-related high-mobility group (HMG) box (SOX) family, composed of 20 transcription factors, is a conserved family with a highly homologous HMG domain. Due to their crucial role in determining cell fate, the dysregulation of SOX family members is closely associated with tumorigenesis, including tumor invasion, metastasis, proliferation, apoptosis, epithelial-mesenchymal transition, stemness and drug resistance. Despite considerable research to investigate the mechanisms and functions of the SOX family, confusion remains regarding aspects such as the role of the SOX family in tumor immune microenvironment (TIME) and contradictory impacts the SOX family exerts on tumors. This review summarizes …
Transfer Learning In The Era Of Foundational Models: Application To Diagnosis In Rheumatology, Prashant Shekhar
Transfer Learning In The Era Of Foundational Models: Application To Diagnosis In Rheumatology, Prashant Shekhar
Math Department Colloquium Series
Problems with current synovitis grading procedures
- There has been a lack of reliability in grading these images in the medical community due to a lack of universally accepted diagnostic criteria [Momtazmanesh et al., 2022]
- The human/machine variability creates an additional challenge in an efficient automated scoring system [Ranganath et al., 2022]
- There is a lack of consistency between doctors in grading these images [Momtazmanesh et al., 2022]
Transcription Factor Bach1 In Cancer: Roles, Mechanisms, And Prospects For Targeted Therapy, Dian Hu, Zerui Zhang, Xiangyuan Luo, Siwen Li, Junqing Jiang, Jiaqian Zhang, Zhangfan Wu, Yijun Wang, Mengyu Sun, Xiaoping Chen, Bixiang Zhang, Xiao Xu, Shuai Wang, Shengjun Xu, Yufei Wang, Wenjie Huang, Limin Xia
Transcription Factor Bach1 In Cancer: Roles, Mechanisms, And Prospects For Targeted Therapy, Dian Hu, Zerui Zhang, Xiangyuan Luo, Siwen Li, Junqing Jiang, Jiaqian Zhang, Zhangfan Wu, Yijun Wang, Mengyu Sun, Xiaoping Chen, Bixiang Zhang, Xiao Xu, Shuai Wang, Shengjun Xu, Yufei Wang, Wenjie Huang, Limin Xia
Faculty, Staff and Student Publications
Transcription factor BTB domain and CNC homology 1 (BACH1) belongs to the Cap 'n' Collar and basic region Leucine Zipper (CNC-bZIP) family. BACH1 is widely expressed in mammalian tissues, where it regulates epigenetic modifications, heme homeostasis, and oxidative stress. Additionally, it is involved in immune system development. More importantly, BACH1 is highly expressed in and plays a key role in numerous malignant tumors, affecting cellular metabolism, tumor invasion and metastasis, proliferation, different cell death pathways, drug resistance, and the tumor microenvironment. However, few articles systematically summarized the roles of BACH1 in cancer. This review aims to highlight the research status …
Patient And Dentist Perspectives On Collecting Patient Reported Outcomes After Painful Dental Procedures In The National Dental Pbrn, Elsbeth Kalenderian, Sayali Tungare, Urvi Mehta, Sharmeen Hamid, Rahma Mungia, Alfa-Ibrahim Yansane, David Holmes, Kim Funkhouser, Ana M Ibarra-Noriega, Janelle Urata, D Brad Rindal, Heiko Spallek, Joel White, Muhammad F Walji
Patient And Dentist Perspectives On Collecting Patient Reported Outcomes After Painful Dental Procedures In The National Dental Pbrn, Elsbeth Kalenderian, Sayali Tungare, Urvi Mehta, Sharmeen Hamid, Rahma Mungia, Alfa-Ibrahim Yansane, David Holmes, Kim Funkhouser, Ana M Ibarra-Noriega, Janelle Urata, D Brad Rindal, Heiko Spallek, Joel White, Muhammad F Walji
Faculty, Staff and Student Publications
BACKGROUND: Dental Patient Reported Outcomes (PROs) relate to a dental patient's subjective experience of their oral health. How practitioners and patients value PROs influences their successful use in practice.
METHODS: Semi-structured interviews were conducted with 22 practitioners and 32 patients who provided feedback on using a mobile health (mHealth) platform to collect the pain experience after dental procedures. A themes analysis was conducted to identify implementation barriers and facilitators.
RESULTS: Five themes were uncovered: (1) Sense of Better Care. (2) Tailored Follow-up based on the dental procedure and patient's pain experience. (3) Effective Messaging and Alerts. (4) Usable Digital Platform. …
The Hsp90-Myc-Cdk9 Network Drives Therapeutic Resistance In Mantle Cell Lymphoma, Fangfang Yan, Vivian Jiang, Alexa Jordan, Yuxuan Che, Yang Liu, Qingsong Cai, Yu Xue, Yijing Li, Joseph Mcintosh, Zhihong Chen, Jovanny Vargas, Lei Nie, Yixin Yao, Heng-Huan Lee, Wei Wang, Johnnelson R Bigcal, Maria Badillo, Jitendra Meena, Christopher Flowers, Jia Zhou, Zhongming Zhao, Lukas M Simon, Michael Wang
The Hsp90-Myc-Cdk9 Network Drives Therapeutic Resistance In Mantle Cell Lymphoma, Fangfang Yan, Vivian Jiang, Alexa Jordan, Yuxuan Che, Yang Liu, Qingsong Cai, Yu Xue, Yijing Li, Joseph Mcintosh, Zhihong Chen, Jovanny Vargas, Lei Nie, Yixin Yao, Heng-Huan Lee, Wei Wang, Johnnelson R Bigcal, Maria Badillo, Jitendra Meena, Christopher Flowers, Jia Zhou, Zhongming Zhao, Lukas M Simon, Michael Wang
Faculty, Staff and Student Publications
Brexucabtagene autoleucel CAR-T therapy is highly efficacious in overcoming resistance to Bruton's tyrosine kinase inhibitors (BTKi) in mantle cell lymphoma. However, many patients relapse post CAR-T therapy with dismal outcomes. To dissect the underlying mechanisms of sequential resistance to BTKi and CAR-T therapy, we performed single-cell RNA sequencing analysis for 66 samples from 25 patients treated with BTKi and/or CAR-T therapy and conducted in-depth bioinformatics™ analysis. Our analysis revealed that MYC activity progressively increased with sequential resistance. HSP90AB1 (Heat shock protein 90 alpha family class B member 1), a MYC target, was identified as early driver of CAR-T resistance. CDK9 …
Session 8: Machine Learning Based Behavior Of Non-Opec Global Supply In Crude Oil Price Determinism, Mofe Jeje
Session 8: Machine Learning Based Behavior Of Non-Opec Global Supply In Crude Oil Price Determinism, Mofe Jeje
SDSU Data Science Symposium
Abstract
While studies on global oil price variability, occasioned by OPEC crude oil supply, is well documented in energy literature; the impact assessment of non-OPEC global oil supply on price variability, on the other hand, has not received commensurate attention. Given this gap, the primary objective of this study, therefore, is to estimate the magnitude of oil price determinism that is explained by the share of non-OPEC’s global crude oil supply. Using secondary sources of data collection method, data for target variable will be collected from the US Federal Reserve, as it relates to annual crude oil price variability, while …
Principal Component Analysis With Application To Credit Card Data, Eleanor Cain, Semhar Michael, Gary Hatfield
Principal Component Analysis With Application To Credit Card Data, Eleanor Cain, Semhar Michael, Gary Hatfield
SDSU Data Science Symposium
Principal Component Analysis (PCA) is a type of dimension reduction technique used in data analysis to process the data before making a model. In general, dimension reduction allows analysts to make conclusions about large data sets by reducing the number of variables while retaining as much information as possible. Using the numerical variables from a data set, PCA aims to compute a smaller set of uncorrelated variables, called principal components, that account for a majority of the variability from the data. The purpose of this poster is to understand PCA as well as perform PCA on a large sample credit …
Predicting Crop Yield Using Remote Sensing Data, Mary Row, Jung-Han Kimn, Hossein Moradi
Predicting Crop Yield Using Remote Sensing Data, Mary Row, Jung-Han Kimn, Hossein Moradi
SDSU Data Science Symposium
Accurate crop yield predictions can help farmers make adjustments or changes in their farming practices to optimize their harvest. Remote sensing data is an inexpensive approach to collecting massive amounts of data that could be utilized for predicting crop yield. This study employed linear regression and spatial linear models were used to predict soybean yield with data from Landsat 8 OLI. Each model was built using only spectral bands of the satellite, only vegetation indices, and both spectral bands and vegetation indices. All analysis was based on data collected from two fields in South Dakota from the 2019 and 2021 …
Session 6: Model-Based Clustering Analysis On The Spatial-Temporal And Intensity Patterns Of Tornadoes, Yana Melnykov, Yingying Zhang, Rong Zheng
Session 6: Model-Based Clustering Analysis On The Spatial-Temporal And Intensity Patterns Of Tornadoes, Yana Melnykov, Yingying Zhang, Rong Zheng
SDSU Data Science Symposium
Tornadoes are one of the nature’s most violent windstorms that can occur all over the world except Antarctica. Previous scientific efforts were spent on studying this nature hazard from facets such as: genesis, dynamics, detection, forecasting, warning, measuring, and assessing. While we want to model the tornado datasets by using modern sophisticated statistical and computational techniques. The goal of the paper is developing novel finite mixture models and performing clustering analysis on the spatial-temporal and intensity patterns of the tornadoes. To analyze the tornado dataset, we firstly try a Gaussian distribution with the mean vector and variance-covariance matrix represented as …
Dynamic Prognosis Prediction For Patients On Dapt After Drug-Eluting Stent Implantation: Model Development And Validation, Fang Li, Laila Rasmy, Yang Xiang, Jingna Feng, Ahmed Abdelhameed, Xinyue Hu, Zenan Sun, David Aguilar, Abhijeet Dhoble, Jingcheng Du, Qing Wang, Shuteng Niu, Yifang Dang, Xinyuan Zhang, Ziqian Xie, Yi Nian, Jianping He, Yujia Zhou, Jianfu Li, Mattia Prosperi, Jiang Bian, Degui Zhi, Cui Tao
Dynamic Prognosis Prediction For Patients On Dapt After Drug-Eluting Stent Implantation: Model Development And Validation, Fang Li, Laila Rasmy, Yang Xiang, Jingna Feng, Ahmed Abdelhameed, Xinyue Hu, Zenan Sun, David Aguilar, Abhijeet Dhoble, Jingcheng Du, Qing Wang, Shuteng Niu, Yifang Dang, Xinyuan Zhang, Ziqian Xie, Yi Nian, Jianping He, Yujia Zhou, Jianfu Li, Mattia Prosperi, Jiang Bian, Degui Zhi, Cui Tao
Faculty, Staff and Student Publications
BACKGROUND: The rapid evolution of artificial intelligence (AI) in conjunction with recent updates in dual antiplatelet therapy (DAPT) management guidelines emphasizes the necessity for innovative models to predict ischemic or bleeding events after drug-eluting stent implantation. Leveraging AI for dynamic prediction has the potential to revolutionize risk stratification and provide personalized decision support for DAPT management.
METHODS AND RESULTS: We developed and validated a new AI-based pipeline using retrospective data of drug-eluting stent-treated patients, sourced from the Cerner Health Facts data set (n=98 236) and Optum's de-identified Clinformatics Data Mart Database (n=9978). The 36 months following drug-eluting stent implantation were …
Real-World Trends, Rural-Urban Differences, And Socioeconomic Disparities In Utilization Of Narrow Versus Broad Next-Generation Sequencing Panels, Yiqing Zhao, Anastasios Dimou, Zachary C Fogarty, Jun Jiang, Hongfang Liu, William B Wong, Chen Wang
Real-World Trends, Rural-Urban Differences, And Socioeconomic Disparities In Utilization Of Narrow Versus Broad Next-Generation Sequencing Panels, Yiqing Zhao, Anastasios Dimou, Zachary C Fogarty, Jun Jiang, Hongfang Liu, William B Wong, Chen Wang
Faculty, Staff and Student Publications
UNLABELLED: Advances in genetic technology have led to the increasing use of genomic panels in precision oncology practice, with panels ranging from a couple to hundreds of genes. However, the clinical utilization and utility of oncology genomic panels, especially among vulnerable populations, is unclear. We examined the association of panel size with socioeconomic status and clinical trial matching. We retrospectively identified 9,886 eligible adult subjects in the Mayo Clinic Health System who underwent genomic testing between January 1, 2016 and June 30, 2020. Patient data were retrieved from structured and unstructured data sources of institutional collections, including cancer registries, clinical …
Identification Of New Egfr Inhibitors By Structure-Based Virtual Screening And Biological Evaluation, Shuyi Wang, Xiaotian Xu, Chuxin Pan, Qian Guo, Qinlan Li, Shanhe Wan, Zhonghuang Li, Jiajie Zhang, Xiaoyun Wu
Identification Of New Egfr Inhibitors By Structure-Based Virtual Screening And Biological Evaluation, Shuyi Wang, Xiaotian Xu, Chuxin Pan, Qian Guo, Qinlan Li, Shanhe Wan, Zhonghuang Li, Jiajie Zhang, Xiaoyun Wu
Faculty, Staff and Student Publications
Epidermal growth factor receptor (EGFR) inhibitors have been used in clinical for the treatment of non-small-cell lung cancer for years. However, the emergence of drug resistance continues to be a major problem. To identify potential inhibitors, molecular docking-based virtual screening was conducted on ChemDiv and Enamine commercial databases using the Glide program. After multi-step VS and visual inspection, a total of 23 compounds with novel and varied structures were selected, and the predicted ADMET properties were within the satisfactory range. Further molecular dynamics simulations revealed that the reprehensive compound ZINC49691377 formed a stable complex with the allosteric pocket of EGFR …
Epigenetic Regulation In Cancer, Minzhi Gu, Bo Ren, Yuan Fang, Jie Ren, Xiaohong Liu, Xing Wang, Feihan Zhou, Ruiling Xiao, Xiyuan Luo, Lei You, Yupei Zhao
Epigenetic Regulation In Cancer, Minzhi Gu, Bo Ren, Yuan Fang, Jie Ren, Xiaohong Liu, Xing Wang, Feihan Zhou, Ruiling Xiao, Xiyuan Luo, Lei You, Yupei Zhao
Faculty, Staff and Student Publications
Epigenetic modifications are defined as heritable changes in gene activity that do not involve changes in the underlying DNA sequence. The oncogenic process is driven by the accumulation of alterations that impact genome's structure and function. Genetic mutations, which directly disrupt the DNA sequence, are complemented by epigenetic modifications that modulate gene expression, thereby facilitating the acquisition of malignant characteristics. Principals among these epigenetic changes are shifts in DNA methylation and histone mark patterns, which promote tumor development and metastasis. Notably, the reversible nature of epigenetic alterations, as opposed to the permanence of genetic changes, positions the epigenetic machinery as …
Clustering Of Patients With Heart Disease, Mukadder Cinar
Clustering Of Patients With Heart Disease, Mukadder Cinar
Dissertations, Theses, and Capstone Projects
Heart disease, a leading cause of mortality worldwide, presents complex challenges in public health due to its varied manifestations. Accurate diagnosis and patient stratification are essential for effective management and improved outcomes. In response, this study employed machine learning techniques to analyze heart disease data obtained from UCI Machine Learning Repository, aiming to enhance patient care through advanced data analysis.
The study began with the application of K-Nearest Neighbors (KNN) classification, which categorized patients into 'Disease' and 'No Disease' groups. This preliminary step provided initial insights into the structure of the dataset. Subsequently, K-means clustering was applied in two rounds, …
What Does One Billion Dollars Look Like?: Visualizing Extreme Wealth, William Mahoney Luckman
What Does One Billion Dollars Look Like?: Visualizing Extreme Wealth, William Mahoney Luckman
Dissertations, Theses, and Capstone Projects
The word “billion” is a mathematical abstraction related to “big,” but it is difficult to understand the vast difference in value between one million and one billion; even harder to understand the vast difference in purchasing power between one billion dollars, and the average U.S. yearly income. Perhaps most difficult to conceive of is what that purchasing power and huge mass of capital translates to in terms of power. This project blends design, text, facts, and figures into an interactive narrative website that helps the user better understand their position in relation to extreme wealth: https://whatdoesonebilliondollarslooklike.website/
The site incorporates …
Making Sense Of Making Parole In New York, Alexandra Mcglinchy
Making Sense Of Making Parole In New York, Alexandra Mcglinchy
Dissertations, Theses, and Capstone Projects
For many individuals incarcerated in New York, the initial step toward freedom begins with an interview with the Board of Parole. This process, however, is frequently a complex and challenging one, characterized by repeated denials and extended incarcerations. The disparity in outcomes – where one individual may receive over 20 denials and another is granted parole on their first attempt – highlights the ambiguity and inconsistency in the parole decision-making process. This project aims to clarify the factors that influence parole decisions by concentrating on measurable variables. These include age, race, duration of sentence served, proportion of sentence served, type …
Modeling Of Covid-19 Clinical Outcomes In Mexico: An Analysis Of Demographic, Clinical, And Chronic Disease Factors, Livia Clarete
Modeling Of Covid-19 Clinical Outcomes In Mexico: An Analysis Of Demographic, Clinical, And Chronic Disease Factors, Livia Clarete
Dissertations, Theses, and Capstone Projects
This study explores COVID-19 clinical outcomes in Mexico, focusing on demographic, clinical, and chronic disease variables to develop predictive models. In the binary classification task, the Ada Boost Classifier distinguishes survivors from non-survivors, with age, sex, ethnicity, and chronic medical conditions influencing outcomes. In multiclass classification, the Gradient Boosting Classifier categorizes patients into outcome groups.
Demographic variables, especially age, are crucial for predicting COVID-19 outcomes for both the binary and multiclass classification tasks. Clinical information about previous conditions, including chronic diseases, also holds relevance, especially diabetes, immunocompromise, and cardiovascular diseases. These insights inform public health measures and healthcare strategies, emphasizing …
Sparse Bayesian Variable Selection In High‐Dimensional Logistic Regression Models With Correlated Priors, Zhuanzhuan Ma, Zifei Han, Souparno Ghosh, Liucang Wu, Min Wang
Sparse Bayesian Variable Selection In High‐Dimensional Logistic Regression Models With Correlated Priors, Zhuanzhuan Ma, Zifei Han, Souparno Ghosh, Liucang Wu, Min Wang
School of Mathematical & Statistical Sciences Faculty Publications
In this paper, we propose a sparse Bayesian procedure with global and local(GL) shrinkage priors for the problems of variable selection and classification in high-dimensional logistic regression models. In particular, we consider two types of GL shrinkage priors for the regression coefficients, the horseshoe (HS)prior and the normal-gamma (NG) prior, and then specify a correlated prior for the binary vector to distinguish models with the same size. The GL priors are then combined with mixture representations of logistic distribution to construct a hierarchical Bayes model that allows efficient implementation of a Markov chain Monte Carlo (MCMC) to generate samples from …
Analyzing The Effects Of Data Variability & Volume On Predicting Particulate Matter (Pm2.5): Insights From A Machine Learning Approach, Jada A. Macharie
Analyzing The Effects Of Data Variability & Volume On Predicting Particulate Matter (Pm2.5): Insights From A Machine Learning Approach, Jada A. Macharie
Theses and Dissertations
Accurately predicting PM2.5 concentrations are imperative to the future of public health and environmental policies. Machine learning models incorporating spatial and temporal datasets to predict PM2.5 are often limited by data availability constraints and poor resolution satellite imagery.
Safety, Immunogenicity, And Mechanism Of A Rotavirus Mrna-Lnp Vaccine In Mice, Chenxing Lu, Yan Li, Rong Chen, Xiaoqing Hu, Qingmei Leng, Xiaopeng Song, Xiaochen Lin, Jun Ye, Jinlan Wang, Jinmei Li, Lida Yao, Xianqiong Tang, Xiangjun Kuang, Guangming Zhang, Maosheng Sun, Yan Zhou, Hongjun Li
Safety, Immunogenicity, And Mechanism Of A Rotavirus Mrna-Lnp Vaccine In Mice, Chenxing Lu, Yan Li, Rong Chen, Xiaoqing Hu, Qingmei Leng, Xiaopeng Song, Xiaochen Lin, Jun Ye, Jinlan Wang, Jinmei Li, Lida Yao, Xianqiong Tang, Xiangjun Kuang, Guangming Zhang, Maosheng Sun, Yan Zhou, Hongjun Li
Faculty, Staff and Student Publications
Rotaviruses (RVs) are a major cause of diarrhea in young children worldwide. The currently available and licensed vaccines contain live attenuated RVs. Optimization of live attenuated RV vaccines or developing non-replicating RV (e.g., mRNA) vaccines is crucial for reducing the morbidity and mortality from RV infections. Herein, a nucleoside-modified mRNA vaccine encapsulated in lipid nanoparticles (LNP) and encoding the VP7 protein from the G1 type of RV was developed. The 5' untranslated region of an isolated human RV was utilized for the mRNA vaccine. After undergoing quality inspection, the VP7-mRNA vaccine was injected by subcutaneous or intramuscular routes into mice. …
The Impact Of Accessible Data On Cyberstalking, Elise Kwan
The Impact Of Accessible Data On Cyberstalking, Elise Kwan
The Journal of Purdue Undergraduate Research
No abstract provided.
Model Selection Through Cross-Validation For Supervised Learning Tasks With Manifold Data, Derek Brown
Model Selection Through Cross-Validation For Supervised Learning Tasks With Manifold Data, Derek Brown
The Journal of Purdue Undergraduate Research
No abstract provided.
Machine Learning Of Big Data: A Gaussian Regression Model To Predict The Spatiotemporal Distribution Of Ground Ozone, Jerry Gu
The Journal of Purdue Undergraduate Research
Tracking pollution levels on the ground is important to the environment and public health. One of the pollutants of concern is ozone, which, at high concentrations, can cause respiratory and cardiovascular problems. The National Center for Atmospheric Research (NCAR) has published valuable ozone data obtained from ground-based sensors installed at selected locations. Because it is unfeasible to measure the exact ozone levels everywhere at any time, it would be valuable to predict the temporal-spatial distributions of ozone concentration based on existing data. This would help us better understand the patterns and trends in the data and make better decisions to …
A Computational Profile Of Invasive Lionfish In Belize: A New Insight On A Destructive Species, Joshua E. Balan
A Computational Profile Of Invasive Lionfish In Belize: A New Insight On A Destructive Species, Joshua E. Balan
The Journal of Purdue Undergraduate Research
Since their discovery in the region in 2009, invasive Indonesian-native lionfish have been taking over the Belize Barrier Reef. As a result, populations of local species have dwindled as they are either eaten or outcompeted by the invaders. This has led to devastating losses ecologically and economically; massive industries in the local nations, such as fisheries and tourism, have suffered greatly. Attempting to combat this, local organizations, from nonprofits to ecotourism companies, have been manually spear-hunting them on scuba dives to cull the population. One such company, Reef Conservation Institute (ReefCI), operating out of Tom Owens Caye outside of Placencia, …
Dementia Prediction In Older Adults Using Sex-Specific Health Trajectory Clustering, Omar A Ibrahim, Muskan Garg, Sunyang Fu, Maria Vassilaki, Ronald C Petersen, Jennifer St Sauver, Sunghwan Sohn
Dementia Prediction In Older Adults Using Sex-Specific Health Trajectory Clustering, Omar A Ibrahim, Muskan Garg, Sunyang Fu, Maria Vassilaki, Ronald C Petersen, Jennifer St Sauver, Sunghwan Sohn
Faculty, Staff and Student Publications
With increasing number of people living with dementia, the problem of late diagnosis significantly impacts a person's quality of life while early signs of dementia may provide useful insights to facilitate better treatment plans. With time, this progressive neurodegenerative syndrome could progress from mild cognitive impairment to dementia. A pattern of health conditions can be characterized in unsupervised manner to help predict this progress. As a significant extension to our previous work with streaming clustering model, we consider additional information for predicting dementia onset. With empirical observations, we discover the importance of examining sex and age to predict dementia onset. …
Prevention And Potential Treatment Strategies For Respiratory Syncytial Virus, Bo-Wen Sun, Peng-Peng Zhang, Zong-Hao Wang, Xia Yao, Meng-Lan He, Rui-Ting Bai, Hao Che, Jing Lin, Tian Xie, Zi Hui, Xiang-Yang Ye, Li-Wei Wang
Prevention And Potential Treatment Strategies For Respiratory Syncytial Virus, Bo-Wen Sun, Peng-Peng Zhang, Zong-Hao Wang, Xia Yao, Meng-Lan He, Rui-Ting Bai, Hao Che, Jing Lin, Tian Xie, Zi Hui, Xiang-Yang Ye, Li-Wei Wang
Faculty, Staff and Student Publications
Respiratory syncytial virus (RSV) is a significant viral pathogen that causes respiratory infections in infants, the elderly, and immunocompromised individuals. RSV-related illnesses impose a substantial economic burden worldwide annually. The molecular structure, function, and in vivo interaction mechanisms of RSV have received more comprehensive attention in recent times, and significant progress has been made in developing inhibitors targeting various stages of the RSV replication cycle. These include fusion inhibitors, RSV polymerase inhibitors, and nucleoprotein inhibitors, as well as FDA-approved RSV prophylactic drugs palivizumab and nirsevimab. The research community is hopeful that these developments might provide easier access to knowledge and …
Fusionnw, A Potential Clinical Impact Assessment Of Kinases In Pan-Cancer Fusion Gene Network, Chengyuan Yang, Himansu Kumar, Pora Kim
Fusionnw, A Potential Clinical Impact Assessment Of Kinases In Pan-Cancer Fusion Gene Network, Chengyuan Yang, Himansu Kumar, Pora Kim
Faculty, Staff and Student Publications
Kinase fusion genes are the most active fusion gene group in human cancer fusion genes. To help choose the clinically significant kinase so that the cancer patients that have fusion genes can be better diagnosed, we need a metric to infer the assessment of kinases in pan-cancer fusion genes rather than relying on the sample frequency expressed fusion genes. Most of all, multiple studies assessed human kinases as the drug targets using multiple types of genomic and clinical information, but none used the kinase fusion genes in their study. The assessment studies of kinase without kinase fusion gene events can …
Current Status And Applications Of Microbial Chassis Strains For Chinese Biomanufacturing Industry, Guoqiang Chen, Fuqing Wu, Shuang Zheng, Jun Ding, Junting Sheng
Current Status And Applications Of Microbial Chassis Strains For Chinese Biomanufacturing Industry, Guoqiang Chen, Fuqing Wu, Shuang Zheng, Jun Ding, Junting Sheng
Bulletin of Chinese Academy of Sciences (Chinese Version)
Biomanufacturing is an important component of new quality productive forces, representing the commanding height of the new round of technological revolution and serving as a new engine for industrial transformation following information technology. It demonstrates vast application prospects in fields such as renewable energy, advanced materials, biomedicine, green food, and environmental protection. Biomanufacturing utilizes chassis microorganisms similar as “microchip” to produce various bioproducts via processes including chassis design and construction, large-scale cell cultivation, and product purifications. Most chassis microorganisms in biomanufacturing were not domestically identified. This study summarizes the types of common chassis microorganisms both domestically and internationally, as well …
Research Progress In High-Throughput Phenotype Testing Technology And Equipment For Engineering Cells Based On Microfluidics, Shuang Li, Xiaojie Guo, Haibo Chen, Sisi Chen, Xin Da, Zhenghui Li, Qinxiu Liu, Yi Wang, Xinhui Xing, Chong Zhang
Research Progress In High-Throughput Phenotype Testing Technology And Equipment For Engineering Cells Based On Microfluidics, Shuang Li, Xiaojie Guo, Haibo Chen, Sisi Chen, Xin Da, Zhenghui Li, Qinxiu Liu, Yi Wang, Xinhui Xing, Chong Zhang
Bulletin of Chinese Academy of Sciences (Chinese Version)
Engineering cells are a core component of green bio-manufacturing. The efficient testing and acquisition of engineering cells with the desired phenotype is a critical factor in the successful implementation of bio-manufacturing. In recent years, based on microfluidics technologies, non-culture type single-cell phenotype high-throughput test equipment and culture type phenotype high-throughput test equipment for the growth and metabolism of single cell in a bioreactor have been developed such as microdroplet and microchamber, realizing high-throughput, automated, miniaturized, and integrated testing of the phenotypes of engineering cells and providing a powerful tool for the breeding of engineering cells. This review systematically compiles the …
Analysis And Reflections On Key Platform Facilities Construction Of Global Biomanufacturing Industry, Xiaoyan Wu, Fang Chen, Yaoying Shan, Anjing Lu
Analysis And Reflections On Key Platform Facilities Construction Of Global Biomanufacturing Industry, Xiaoyan Wu, Fang Chen, Yaoying Shan, Anjing Lu
Bulletin of Chinese Academy of Sciences (Chinese Version)
Biomanufacturing, an emerging production method, is becoming a significant trend in global economic development and has garnered widespread international attention. Platform facilities are vital to the biomanufacturing industry’s development, serving as both the foundation for technological innovation and the bridge between research outcomes and practical applications. This study analyzes three key types of platform facilities and their operational mechanisms: technology innovation platforms (exemplified by the U.S. Agile BioFoundry), pilot-scale platforms (represented by European Bio Base Europe Pilot Plant), and industry incubation platforms (illustrated by the UK SynbiCITE). Drawing from these successful examples and examining China’s current platform infrastructure, this paper …