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Articles 421 - 450 of 13246
Full-Text Articles in Physical Sciences and Mathematics
Decentralized Science (Desci): A New Paradigm For Diverse And Sustainable Scientific Development, Feiyue Wang, Wenwen Ding
Decentralized Science (Desci): A New Paradigm For Diverse And Sustainable Scientific Development, Feiyue Wang, Wenwen Ding
Bulletin of Chinese Academy of Sciences (Chinese Version)
The rise of artificial intelligence for science (AI4S) has made it particularly important and urgent to ensure the openness, fairness, impartiality, diversity, and sustainability of scientific systems. This is significant to the discourse power and leadership of countries in global innovation and industrial revolution, and also affects the security, stability, and sustainable development of a community with a shared future for mankind. To address these challenges, AI4S needs to adopt new scientific organizational and operational methods. Decentralized science (DeSci) has emerged to vitalize AI4S and provide strong support, effectively addressing issues such as information silos, biases, unfair distribution, and monopolies …
Determining The Ideal Concentrations Of Ethanol And Propylene Glycol In Ethosomes For Transdermal Delivery Of Vitamin D3, Rebecca Conner
Determining The Ideal Concentrations Of Ethanol And Propylene Glycol In Ethosomes For Transdermal Delivery Of Vitamin D3, Rebecca Conner
Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity
Vitamin D3 is an important chemical in the human body, however, many Americans have low levels of this vitamin. There are plenty of oral supplementations for Vitamin D3 deficiency, but those of older age and busy schedules may struggle to meet the minimum requirement. A recently developed ethosomal transmembrane delivery system (Touitou, 2000), similar to liposomes but also containing ethanol, allows users to apply a gel dermally and have the desired drug or active ingredient reach the bloodstream faster. However, there is considerable variation in the concentration of ethanol and permeation enhancers used. Using an affordable method to …
Would You Choose The Same Nationality If You Were Born Again?, Keito Kono, Logan Bowerman
Would You Choose The Same Nationality If You Were Born Again?, Keito Kono, Logan Bowerman
Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity
Nationality is an important element in the formation of identity, but this brings up a question; that is whether people are proud of their nationality. Thus, we decided to investigate how many people would prefer to have the same nationality if they were born again. This survey is important because it could provide an opportunity to recognize people's interest in other countries and their patriotism
The Relationship Between Pets Owned And Gender Amongst College Students, Eman Asghar, Bryce Camuso, Josh Feirick
The Relationship Between Pets Owned And Gender Amongst College Students, Eman Asghar, Bryce Camuso, Josh Feirick
Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity
There is a gap between the number of men and women that own dogs. The Mintel Press Team states that "71% of men aged 18-44 own a dog compared to 60% of their female counterparts" (Mintel Press Team, 2016, para: 1). While this statistic includes people who are college-aged, it does not mention college students specifically. Thus, research into the relationship between pets owned and gender amongst college students is an important topic that warrants looking into.
The Knowledge Of One's Blood Type, Mackenzie Degroft, Ethan Hall, Scarlet Morillo
The Knowledge Of One's Blood Type, Mackenzie Degroft, Ethan Hall, Scarlet Morillo
Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity
An experiment of sample surveys of undergraduate students' knowledge of their blood type.
A Statistical Study Into The Number Of Hours Students At Harrisburg University Spend On Social Media, Nabeel Hakeem-Olowu, Samantha Weaver, Kyla Lea
A Statistical Study Into The Number Of Hours Students At Harrisburg University Spend On Social Media, Nabeel Hakeem-Olowu, Samantha Weaver, Kyla Lea
Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity
The aim of the study is to examine the number of hours that Harrisburg University students spent on social media during their spare time. The purpose of the study is to raise awareness among students about the possible negative impacts of excessive social media usage on their academic performance, social interactions, and sleep duration. Additionally, the study explored the relationship between social media use and academic performance. To collect data, we surveyed one hundred and fifty students from Harrisburg University. The survey consisted of questions related to the number of hours spent on social media during spare time. The respondents …
Data Sharing And Ontology Use Among Agricultural Genetics, Genomics, And Breeding Databases And Resources Of The Agbiodata Consortium, Jennifer L. Clarke, Laurel D. Cooper, Monica F. Poelchau, Tanya Z. Berardini, Justin Elser, Andrew D. Farmer, Stephen Ficklin, Sunita Kumari, Marie-Angélique Laporte, Rex T. Nelson, Rie Sadohara, Peter Selby, Anne E. Thessen, Brandon Whitehead, Taner Z. Sen
Data Sharing And Ontology Use Among Agricultural Genetics, Genomics, And Breeding Databases And Resources Of The Agbiodata Consortium, Jennifer L. Clarke, Laurel D. Cooper, Monica F. Poelchau, Tanya Z. Berardini, Justin Elser, Andrew D. Farmer, Stephen Ficklin, Sunita Kumari, Marie-Angélique Laporte, Rex T. Nelson, Rie Sadohara, Peter Selby, Anne E. Thessen, Brandon Whitehead, Taner Z. Sen
Department of Statistics: Faculty Publications
Over the last couple of decades, there has been a rapid growth in the number and scope of agricultural genetics, genomics and breeding databases and resources. The AgBioData Consortium (https://www.agbiodata.org/) currently represents 44 databases and resources (https://www.agbiodata.org/databases) covering model or crop plant and animal GGB data, ontologies, pathways, genetic variation and breeding platforms (referred to as ‘databases’ throughout). One of the goals of the Consortium is to facilitate FAIR (Findable, Accessible, Interoperable, and Reusable) data management and the integration of datasets which requires data sharing, along with structured vocabularies and/or ontologies. Two AgBioData working groups, focused on Data Sharing and …
Repurposing The Fda-Approved Anthelmintic Pyrvinium Pamoate For Pancreatic Cancer Treatment: Study Protocol For A Phase I Clinical Trial In Early-Stage Pancreatic Ductal Adenocarcinoma, Francesca M. Ponzini, Christopher W. Schultz, Benjamin E. Leiby, Shawnna Cannaday, T. Yeo, James Posey, Wilbur B. Bowne, Charles Yeo, Jonathan R. Brody, Harish Lavu, Avinoam Nevler
Repurposing The Fda-Approved Anthelmintic Pyrvinium Pamoate For Pancreatic Cancer Treatment: Study Protocol For A Phase I Clinical Trial In Early-Stage Pancreatic Ductal Adenocarcinoma, Francesca M. Ponzini, Christopher W. Schultz, Benjamin E. Leiby, Shawnna Cannaday, T. Yeo, James Posey, Wilbur B. Bowne, Charles Yeo, Jonathan R. Brody, Harish Lavu, Avinoam Nevler
Department of Surgery Faculty Papers
BACKGROUND: Recent reports of the utilisation of pyrvinium pamoate (PP), an FDA-approved anti-helminth, have shown that it inhibits pancreatic ductal adenocarcinoma (PDAC) cell growth and proliferation in-vitro and in-vivo in preclinical models. Here, we report about an ongoing phase I open-label, single-arm, dose escalation clinical trial to determine the safety and tolerability of PP in PDAC surgical candidates.
METHODS AND ANALYSIS: In a 3+3 dose design, PP is initiated 3 days prior to surgery. The first three patients will be treated with the initial dose of PP at 5 mg/kg orally for 3 days prior to surgery. Dose doubling will …
Assessment Of First-Phase Covid-19 Pandemic In Europe Using Hierarchical Clustering Based On Principal Components Analysis, Sanjay Kumar, Evrim Oral
Assessment Of First-Phase Covid-19 Pandemic In Europe Using Hierarchical Clustering Based On Principal Components Analysis, Sanjay Kumar, Evrim Oral
School of Public Health Faculty Publications
It is of great interest for researchers to assess the COVID-19 pandemic in Europe. Grouping of COVID-19-affected regions is an effective way to monitor and optimize planning to combat the disease. This paper applied hierarchical clustering based on principal components analysis (HCPCA) to COVID-19 data from affected European countries. Considering several attribute indices, we obtained a new set of indicators using principal components analysis to aggregate and reduce the dimension of attribute indices of affected countries. Further, we obtained groups of affected countries subject to their similarity using hierarchical clustering to the reduced observations of new attributes indices of these …
Exploring Parameter Sensitivity Analysis In Mathematical Modeling With Ordinary Differential Equations, Viktoria Savatorova
Exploring Parameter Sensitivity Analysis In Mathematical Modeling With Ordinary Differential Equations, Viktoria Savatorova
CODEE Journal
This paper presents an exploration into parameter sensitivity analysis in mathematical modeling using ordinary differential equations (ODEs). Taking the first steps in understanding local sensitivity analysis through the direct differential method and global sensitivity analysis using metrics like Pearson, Spearman, PRCC, and Sobol’, we provide readers with a basic understanding of parameter sensitivity analysis for mathematical modeling using ODEs. As an illustrative application, the system of differential equations modeling population dynamics of several fish species with harvest considerations is utilized. The results of employing local and global sensitivity analysis are compared, shedding light on the strengths and limitations of each …
Deep Q-Learning Framework For Quantitative Climate Change Adaptation Policy For Florida Road Network Due To Extreme Precipitation, Orhun Aydin
I-GUIDE Forum
Climate change-induced extreme weather and increasing population are increasing the pressure on the global aging road networks. Adaptation requires designing interventions and alterations to the road networks that consider future dynamics of flooding and increased traffic due to the growing population. This paper introduces a reinforcement learning approach to designing interventions for Florida's road network under future traffic and climate projections. Three climate models and a tide and surge model are used to create flooding and coastal inundation projections, respectively. The optimal sequence of decisions for adapting Florida's road network to minimize flooding-related disruptions is solved by using a graph-based …
Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian
Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian
I-GUIDE Forum
Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important because sea-level rise affects millions of people in coastal communities and beyond due to climate change's impacts on polar ice sheets and the ocean. This problem is challenging due to spatial variability and unknowns such as possible tipping points (e.g., collapse of Greenland or West Antarctic ice-shelf), climate feedback loops (e.g., clouds, permafrost thawing), future policy decisions, and human actions. Most existing climate modeling approaches use the same set of weights globally, during either regression or …
A Classical Fall Statistics Problem, Timothy L. Meyer
A Classical Fall Statistics Problem, Timothy L. Meyer
Cornhusker Economics
An evaluation of traditional baseball measures and suggestions for alternatives, centering on statistics related to the offensive quality of a player.
Bayesian Statistical Modeling Of Spatially Resolved Transcriptomics Data, Xi Jiang
Bayesian Statistical Modeling Of Spatially Resolved Transcriptomics Data, Xi Jiang
Statistical Science Theses and Dissertations
Spatially resolved transcriptomics (SRT) quantifies expression levels at different spatial locations, providing a new and powerful tool to investigate novel biological insights. As experimental technologies enhance both in capacity and efficiency, there arises a growing demand for the development of analytical methodologies.
One question in SRT data analysis is to identify genes whose expressions exhibit spatially correlated patterns, called spatially variable (SV) genes. Most current methods to identify SV genes are built upon the geostatistical model with Gaussian process, which could limit the models' ability to identify complex spatial patterns. In order to overcome this challenge and capture more types …
Lightning Forecast From Chaotic And Incomplete Time Series Using Wavelet De-Noising And Spatiotemporal Kriging, Jared K. Nystrom, Raymond Hill, Andrew J. Geyer, Joseph J. Pignatiello Jr., Eric Chicken
Lightning Forecast From Chaotic And Incomplete Time Series Using Wavelet De-Noising And Spatiotemporal Kriging, Jared K. Nystrom, Raymond Hill, Andrew J. Geyer, Joseph J. Pignatiello Jr., Eric Chicken
Faculty Publications
Purpose: Present a method to impute missing data from a chaotic time series, in this case lightning prediction data, and then use that completed dataset to create lightning prediction forecasts.
Design/Methodology/Approach: Using the technique of spatiotemporal kriging to estimate data that is autocorrelated but in space and time. Using the estimated data in an imputation methodology completes a dataset used in lighting prediction.
Findings: The techniques provided prove robust to the chaotic nature of the data, and the resulting time series displays evidence of smoothing while also preserving the signal of interest for lightning prediction.
Abstract © Emerald Publishing …
The Prevalence Of Burnout In Saudi Arabia Dental Hygienists, Nouf Hamad Aldayel
The Prevalence Of Burnout In Saudi Arabia Dental Hygienists, Nouf Hamad Aldayel
Dental Hygiene Theses & Dissertations
Purpose: The purpose of this pilot study was to assess the prevalence of burnout in Saudi Arabian dental hygienists and identify risk factors associated with burnout. Methods: A descriptive survey design using the Copenhagen Burnout Inventory (CBI) assessed burnout among a convenience sample of n=123 Saudi dental hygienists. The survey was disseminated electronically to 1,000 Saudi Arabian dental hygienists. The CBI measures three subscales: personal, work-related, and client/patient-related burnout on a five-point Likert-type scale. The survey also included six demographic questions, two Likert-type, one “yes/no,” and one openended question, related to burnout. Descriptive statistics, one-way between subject’s ANOVA, independent samples …
Multi-Representation Variational Autoencoder Via Iterative Latent Attention And Implicit Differentiation, Nhu Thuat Tran, Hady Wirawan Lauw
Multi-Representation Variational Autoencoder Via Iterative Latent Attention And Implicit Differentiation, Nhu Thuat Tran, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Variational Autoencoder (VAE) offers a non-linear probabilistic modeling of user's preferences. While it has achieved remarkable performance at collaborative filtering, it typically samples a single vector for representing user's preferences, which may be insufficient to capture the user's diverse interests. Existing solutions extend VAE to model multiple interests of users by resorting a variant of self-attentive method, i.e., employing prototypes to group items into clusters, each capturing one topic of user's interests. Despite showing improvements, the current design could be more effective since prototypes are randomly initialized and shared across users, resulting in uninformative and non-personalized clusters.To fill the gap, …
Dental Hygiene Students Reported Physiological Symptoms Associated With Wearing An N95 Respirator Mask, Peyton Shea Butler
Dental Hygiene Students Reported Physiological Symptoms Associated With Wearing An N95 Respirator Mask, Peyton Shea Butler
Dental Hygiene Theses & Dissertations
Purpose: Physiological symptoms and comfort levels while wearing an N95 respiratory mask has not been examined with dental hygienists. The purpose of this study was to investigate dental hygiene students reported physiological symptoms and comfort perception while wearing an N95 respirator mask during patient care appointments. Methods: After IRB approval (IRB #1987754-2), a 16-item questionnaire was distributed through email to a convenience sample of 65 dental hygiene students. Questions assessed respiratory, dermatologic, cardiac, mask mouth and general physiological symptoms, as well as comfort levels. Additionally, participants were asked to respond to demographic questions and one open ended question inquiring about …
A New Method To Determine The Posterior Distribution Of Coefficient Alpha, John Mart V. Delosreyes
A New Method To Determine The Posterior Distribution Of Coefficient Alpha, John Mart V. Delosreyes
Psychology Theses & Dissertations
There is a focus within the behavioral/social sciences on non-physical, psychological constructs (i.e., constructs). These constructs are indirectly measured using measurement instruments that consist of questions that capture the manifestations of these constructs. The indirect nature of measuring constructs results in a need of ensuring that measurement instruments are reliable. The most popular statistic used to estimate reliability is coefficient alpha as it is easy to compute and has properties that make it desirable to use. Coefficient alpha’s popularity has resulted in a wide breadth of research into its qualities. Notably, research about coefficient alpha’s distribution has led to developments …
Parameter Estimation For Normally Distributed Grouped Data And Clustering Single-Cell Rna Sequencing Data Via The Expectation-Maximization Algorithm, Zahra Aghahosseinalishirazi
Parameter Estimation For Normally Distributed Grouped Data And Clustering Single-Cell Rna Sequencing Data Via The Expectation-Maximization Algorithm, Zahra Aghahosseinalishirazi
Electronic Thesis and Dissertation Repository
The Expectation-Maximization (EM) algorithm is an iterative algorithm for finding the maximum likelihood estimates in problems involving missing data or latent variables. The EM algorithm can be applied to problems consisting of evidently incomplete data or missingness situations, such as truncated distributions, censored or grouped observations, and also to problems in which the missingness of the data is not natural or evident, such as mixed-effects models, mixture models, log-linear models, and latent variables. In Chapter 2 of this thesis, we apply the EM algorithm to grouped data, a problem in which incomplete data are evident. Nowadays, data confidentiality is of …
All-Cause And Opioid-Related Mortality Compared Between Traumatic Spinal Cord Injury And The Us General Population, Jaden Whitehead, Beatrice Ugiliweneza
All-Cause And Opioid-Related Mortality Compared Between Traumatic Spinal Cord Injury And The Us General Population, Jaden Whitehead, Beatrice Ugiliweneza
The Cardinal Edge
Individuals with spinal cord injury (SCI) are susceptible to the misuse of opioids due to the introduction of these substances for pain management. There are very few studies examining the relationship between unintentional deaths caused by opioid usage following spinal cord injury. The objective of this study was to evaluate the trend of opioid-related mortality of individuals with spinal cord injury (SCI) over the years and compare these findings to the mortality rates due to opioid misuse in the general population. In this study, we used data provided by the National Spinal Cord Injury Model Systems (NSCIMS) for SCI 1999-2016 …
Nonparametric Methods For Analysis And Sizing Of Cluster Randomization Trials With Baseline Measurements, Chengchun Yu
Nonparametric Methods For Analysis And Sizing Of Cluster Randomization Trials With Baseline Measurements, Chengchun Yu
Electronic Thesis and Dissertation Repository
Cluster randomization trials are popular in situations where the intervention needs to be implemented at the cluster level, or logistical, financial and/or ethical reason dictates the choice for randomization at the cluster level, or minimization of contamination is needed. It is very common for cluster trials to take measurements before randomization and again at follow-up, resulting in a clustered pretest-posttest design. For continuous outcomes, the cluster-adjusted analysis of covariance approach can be used to adjust for accidental bias and improve efficiency. However, a direct application of this method is nonsensical if the measures are incompatible with an interval scale, yet …
Reu-Deim Classification Of Hispanic Voters In Hispanic Groups Using Name And Zip Code Data In Palm Beach, Florida, Kamila Soto-Ortiz
Reu-Deim Classification Of Hispanic Voters In Hispanic Groups Using Name And Zip Code Data In Palm Beach, Florida, Kamila Soto-Ortiz
Beyond: Undergraduate Research Journal
When it comes to registering to vote, Hispanic voters can only register as “Hispanic” in the “Race/Ethnicity” category, causing difficulties when analyzing voting trends amongst the Hispanic community. Upon the recent idea that not all Hispanic Groups vote the same, the goal is to create a model that can possibly identify a voter’s Hispanic Group with the information provided on the public Florida voter file. This is accomplished using name and zip code data for all voters in Palm Beach, Florida. This paper will explore the model implemented, its findings and limitations. Palm Beach, Florida, is met with low confidence …
Asymptotic Results For Empirical Processes In Informative Model Of Random Censorship From Both Sides, Abdurakhim Abdushukurov, Dilshod Mansurov
Asymptotic Results For Empirical Processes In Informative Model Of Random Censorship From Both Sides, Abdurakhim Abdushukurov, Dilshod Mansurov
Bulletin of National University of Uzbekistan: Mathematics and Natural Sciences
In the paper, the empirical process in informative model of random censorship from both sides is investigated. For it, the limit Gaussian process with mean zero is founded. Under investigating of empirical process, the characterization properties of the considered informative model is used. The properties of the semiparametric estimator by using methods of numerical modeling are discussed.
Sugar-Sweetened Beverages And Artificially Sweetened Beverages Consumption And The Risk Of Nonalcoholic Fatty Liver (Nafld) And Nonalcoholic Steatohepatitis (Nash), Tung Sung Tseng, Wei Ting Lin, Peng Sheng Ting, Chiung Kuei Huang, Po Hung Chen, Gabrielle V. Gonzalez, Hui Yi Lin
Sugar-Sweetened Beverages And Artificially Sweetened Beverages Consumption And The Risk Of Nonalcoholic Fatty Liver (Nafld) And Nonalcoholic Steatohepatitis (Nash), Tung Sung Tseng, Wei Ting Lin, Peng Sheng Ting, Chiung Kuei Huang, Po Hung Chen, Gabrielle V. Gonzalez, Hui Yi Lin
School of Public Health Faculty Publications
Nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) are fast becoming the most common chronic liver disease and are often preventable with healthy dietary habits and weight management. Sugar-sweetened beverage (SSB) consumption is associated with obesity and NAFLD. However, the impact of different types of SSBs, including artificially sweetened beverages (ASBs), is not clear after controlling for total sugar intake and total caloric intake. The aim of this study was to examine the association between the consumption of different SSBs and the risk of NAFLD and NASH in US adults. The representativeness of 3739 US adults aged ≥20 years …
History And Current Status Of Mediterranean Spotted Fever (Msf) In The Crimean Peninsula And Neighboring Regions Along The Black Sea Coast, Muniver T. Gafarova, Marina E. Eremeeva
History And Current Status Of Mediterranean Spotted Fever (Msf) In The Crimean Peninsula And Neighboring Regions Along The Black Sea Coast, Muniver T. Gafarova, Marina E. Eremeeva
Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications
Mediterranean spotted fever (MSF) is a tick-borne rickettsiosis caused by Rickettsia conorii subspecies conorii and transmitted to humans by Rhipicephalus sanguineus ticks. The disease was first discovered in Tunisia in 1910 and was subsequently reported from other Mediterranean countries. The first cases of MSF in the former Soviet Union were detected in 1936 on the Crimean Peninsula. This review summarizes the historic information and main features of MSF in that region and contemporary surveillance and control efforts for this rickettsiosis. Current data pertinent to the epidemiology of the disease, circulation of the ticks and distribution of animal hosts are discussed …
Produção De Artigos Científicos No Estudo Longitudinal De Saúde Do Adulto (Elsa-Brasil), 2011-2023, Arthur Sandi Bauermann, Maria Antônia Mylius De Oliveira, Clara Akemi Basso Aseka, Luiza Dalmolin Beneduzi
Produção De Artigos Científicos No Estudo Longitudinal De Saúde Do Adulto (Elsa-Brasil), 2011-2023, Arthur Sandi Bauermann, Maria Antônia Mylius De Oliveira, Clara Akemi Basso Aseka, Luiza Dalmolin Beneduzi
AMNET Conferencia Internacional
No abstract provided.
Number Of Regions Created By Random Chords In The Circle, Shi Feng
Number Of Regions Created By Random Chords In The Circle, Shi Feng
Rose-Hulman Undergraduate Mathematics Journal
In this paper we discuss the number of regions in a unit circle after drawing n i.i.d. random chords in the circle according to a particular family of distribution. We find that as n goes to infinity, the distribution of the number of regions, properly shifted and scaled, converges to the standard normal distribution and the error can be bounded by Stein's method for proving Central Limit Theorem.
The Public Health Impact Of Paxlovid Covid-19 Treatment In The United States, Yuan Bai, Zhanwei Du, Lin Wang, Eric H. Y. Lau, Isaac Fung, Petter Holme, Ben Cowling, Alison Galvani, Robert Krug, Lauren Ancel Meyers
The Public Health Impact Of Paxlovid Covid-19 Treatment In The United States, Yuan Bai, Zhanwei Du, Lin Wang, Eric H. Y. Lau, Isaac Fung, Petter Holme, Ben Cowling, Alison Galvani, Robert Krug, Lauren Ancel Meyers
Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications
The antiviral drug Paxlovid has been shown to rapidly reduce viral load. Coupled with vaccination, timely administration of safe and effective antivirals could provide a path towards managing COVID-19 without restrictive non-pharmaceutical measures. Here, we estimate the population-level impacts of expanding treatment with Paxlovid in the US using a multi-scale mathematical model of SARS-CoV-2 transmission that incorporates the within-host viral load dynamics of the Omicron variant. We find that, under a low transmission scenario (Re∼1.2) treating 20% of symptomatic cases would be life and cost saving, leading to an estimated 0.26 (95% CrI: 0.03, 0.59) million hospitalizations averted, 30.61 (95% …
Design, Analysis, And Interpretation Of Treatment Response Heterogeneity In Personalized Nutrition And Obesity Treatment Research, Roger S. Zoh, Bridget H. Esteves, Xiaoxin Yu, Amanda J. Fairchild, Ana I. Vazquez, Andrew G. Chapple, Andrew W. Brown, Brandon George, Derek Gordon, Douglas Landsittel, Gary L. Gadbury, Greg Pavela, Gustavo De Los Campos, Luis M. Mestre, David B. Allison
Design, Analysis, And Interpretation Of Treatment Response Heterogeneity In Personalized Nutrition And Obesity Treatment Research, Roger S. Zoh, Bridget H. Esteves, Xiaoxin Yu, Amanda J. Fairchild, Ana I. Vazquez, Andrew G. Chapple, Andrew W. Brown, Brandon George, Derek Gordon, Douglas Landsittel, Gary L. Gadbury, Greg Pavela, Gustavo De Los Campos, Luis M. Mestre, David B. Allison
School of Public Health Faculty Publications
It is increasingly assumed that there is no one-size-fits-all approach to dietary recommendations for the management and treatment of chronic diseases such as obesity. This phenomenon that not all individuals respond uniformly to a given treatment has become an area of research interest given the rise of personalized and precision medicine. To conduct, interpret, and disseminate this research rigorously and with scientific accuracy, however, requires an understanding of treatment response heterogeneity. Here, we define treatment response heterogeneity as it relates to clinical trials, provide statistical guidance for measuring treatment response heterogeneity, and highlight study designs that can quantify treatment response …