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Article: Yifei Xuanfei Jiangzhuo Chinese bioformulation improves cognitive function in a murine model of vascular dementia - the implication of PI3K/AKT and Erk signalling pathway.

Chen, W / Wu, L / Jiang, L F / Hu, Y Q / Zhai, Y / Li, J H / Wu, Y / Tang, N

Journal of biological regulators and homeostatic agents

2020 Volume 34, Issue 6, Page(s) 2177–2183

MeSH term(s)	Animals ; Asian Continental Ancestry Group ; Cognition ; Dementia, Vascular/drug therapy ; Disease Models, Animal ; Drugs, Chinese Herbal ; Humans ; MAP Kinase Signaling System ; Mice ; Phosphatidylinositol 3-Kinases/genetics ; Proto-Oncogene Proteins c-akt/genetics
Chemical Substances	Drugs, Chinese Herbal ; yifei xuanfei jiangzhuo ; Proto-Oncogene Proteins c-akt (EC 2.7.11.1)
Language	English
Publishing date	2020-11-12
Publishing country	Italy
Document type	Letter
ZDB-ID	639196-5
ISSN	1724-6083 ; 0393-974X
ISSN (online)	1724-6083
ISSN	0393-974X
DOI	10.23812/20-310-L
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Article: [Impacts of yishen jiangzhuo granule on B lymphocytes and regulatory T-lymphocytes in patients with chronic renal insufficiency].

Zheng, Jing / Lin, Shang-zhong / Chen, Xue-lan

Zhongguo Zhong xi yi jie he za zhi Zhongguo Zhongxiyi jiehe zazhi = Chinese journal of integrated traditional and Western medicine

2011 Volume 31, Issue 1, Page(s) 37–40

Abstract: Objective: To explore the impacts of Yishen Jiangzhuo Granule (YJG) on peripheral blood B-cells ...

Abstract	Objective: To explore the impacts of Yishen Jiangzhuo Granule (YJG) on peripheral blood B-cells and regulatory T-cells (Treg) in patients with chronic renal insufficiency (CRI). Methods: Fifty-three CRI patients were randomly assigned to two groups, the control group and the YJG group. Before and after treatment, the following parameters in blood were detected: the peripheral Treg, percentage (CD19+), activation rate (CD19+ CD69+) and apoptotic rate (AV) of B-lymphocyte by flow cytometry; cytokines (IL-6 and IL-10) by CBA stream protein analyzing system; high sensitivity C-reactive protein (hs-CRP) by scattering turbidimetric analysis; homocysteine (Hcy) by end-point method; hemoglobin (HGB) content by Beckman-Coulter hemo-analyser; blood contents of Ca, phosphate (P), blood urea nitrogen (BUN), creatinine (SCr) and plasma albumin (Alb) by automatic biochemical analyser; and urinary contents of creatinine (UCr) by inverse HPLC. Then the product of calcium-phosphate (Ca x P) was calculated based on blood contents of Ca2 and P and the clearance rate of endogenous creatinine (CCr) was calculated based on blood BUN and SCr. Results: After treatment CD19+ and CCr significantly increased (P < 0.01), but AV and SCr decreased in both groups (P < 0.01), with the changes in the YJG group were more significant than those in the control group (P < 0.05); levels of CD19+ CD69+, Treg, IL-6, IL-10, CRP, BUN, P and Ca x P showed no significant change (P > 0.05); levels of Ca2+, HGB and Alb increased as well as of Hcy in both groups (P < 0.05). Correlation analysis: There were negative correlation in CD19+ with AV and Hcy; Alb with AV and Hcy; CCr with CRP, SCr and BUN, while positive correlation existed in SCr with CRP and BUN; and CRP with BUN. Conclusions: YJG can improve renal function, and delay the progress of renal failure, and it also shows the regulatory effect on B lymphocytes by lowering the apoptosis rate and improving the percentage of CD19+ in patients.
MeSH term(s)	Adult ; Aged ; B-Lymphocytes/metabolism ; Drugs, Chinese Herbal/therapeutic use ; Female ; Humans ; Kidney Failure, Chronic/drug therapy ; Kidney Failure, Chronic/metabolism ; Male ; Middle Aged ; Phytotherapy ; T-Lymphocytes, Regulatory/metabolism
Chemical Substances	Drugs, Chinese Herbal ; yishen
Language	Chinese
Publishing date	2011-01
Publishing country	China
Document type	English Abstract ; Journal Article ; Randomized Controlled Trial ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	1195456-5
ISSN	1003-5370
ISSN	1003-5370
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Article ; Online: Data-driven mechanistic framework with stratified immunity and effective transmissibility for COVID-19 scenario projections.

Porebski, Przemyslaw / Venkatramanan, Srinivasan / Adiga, Aniruddha / Klahn, Brian / Hurt, Benjamin / Wilson, Mandy L / Chen, Jiangzhuo / Vullikanti, Anil / Marathe, Madhav / Lewis, Bryan

Epidemics

2024 Volume 47, Page(s) 100761

Abstract: Scenario-based modeling frameworks have been widely used to support policy-making at state and federal levels in the United States during the COVID-19 response. While custom-built models can be used to support one-off studies, sustained updates to ... ...

Abstract	Scenario-based modeling frameworks have been widely used to support policy-making at state and federal levels in the United States during the COVID-19 response. While custom-built models can be used to support one-off studies, sustained updates to projections under changing pandemic conditions requires a robust, integrated, and adaptive framework. In this paper, we describe one such framework, UVA-adaptive, that was built to support the CDC-aligned Scenario Modeling Hub (SMH) across multiple rounds, as well as weekly/biweekly projections to Virginia Department of Health (VDH) and US Department of Defense during the COVID-19 response. Building upon an existing metapopulation framework, PatchSim, UVA-adaptive uses a calibration mechanism relying on adjustable effective transmissibility as a basis for scenario definition while also incorporating real-time datasets on case incidence, seroprevalence, variant characteristics, and vaccine uptake. Through the pandemic, our framework evolved by incorporating available data sources and was extended to capture complexities of multiple strains and heterogeneous immunity of the population. Here we present the version of the model that was used for the recent projections for SMH and VDH, describe the calibration and projection framework, and demonstrate that the calibrated transmissibility correlates with the evolution of the pathogen as well as associated societal dynamics.
Language	English
Publishing date	2024-03-21
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2467993-8
ISSN	1878-0067 ; 1755-4365
ISSN (online)	1878-0067
ISSN	1755-4365
DOI	10.1016/j.epidem.2024.100761
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Article: Differential Impact of Social Distancing on COVID-19 Spread in the U.S.: By Rurality and Social Vulnerability.

Pilehvari, Asal / You, Wen / Chen, Jiangzhuo / Krulick, John / Venkatramanan, Srini / Marathe, Achla

Research square

2021

Abstract: Background: To quantify lessons learned to better prepare for similar pandemic crisis in the future, we assess the overall impact of social distancing on the daily growth rate of COVID-19 infections in the U.S. during the initial phase of the pandemic ... ...

Abstract	Background: To quantify lessons learned to better prepare for similar pandemic crisis in the future, we assess the overall impact of social distancing on the daily growth rate of COVID-19 infections in the U.S. during the initial phase of the pandemic and the impacts' heterogeneity by urbanity and social vulnerability of the counties. The initial phase is chosen to purposely identify the essential and largest impact of the first-line of defense measure for similar pandemic: social distancing. Methods: Spatial Durbin models with county fixed effects were used to account for spatial dependencies and identify spatial spillover effects and spatial heterogeneity. Results: Besides the substantial curve flattening effects of social distancing, our results show significant spillover effects induced by neighboring counties' social distancing levels even in the absence of significant within-county effects. Urban and areas with high social vulnerability are the ones benefit the most from social distancing and high level of compliance is needed. Moderate level is enough in reaching the peak marginal impact in rural and areas with low social vulnerability.
Language	English
Publishing date	2021-09-14
Publishing country	United States
Document type	Preprint
DOI	10.21203/rs.3.rs-798357/v1
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Article ; Online: COVID's collateral damage: likelihood of measles resurgence in the United States.

Thakur, Mugdha / Zhou, Richard / Mohan, Mukundan / Marathe, Achla / Chen, Jiangzhuo / Hoops, Stefan / Machi, Dustin / Lewis, Bryan / Vullikanti, Anil

BMC infectious diseases

2022 Volume 22, Issue 1, Page(s) 743

Abstract: Background: Lockdowns imposed throughout the US to control the COVID-19 pandemic led to a decline in all routine immunizations rates, including the MMR (measles, mumps, rubella) vaccine. It is feared that post-lockdown, these reduced MMR rates will lead ...

Abstract	Background: Lockdowns imposed throughout the US to control the COVID-19 pandemic led to a decline in all routine immunizations rates, including the MMR (measles, mumps, rubella) vaccine. It is feared that post-lockdown, these reduced MMR rates will lead to a resurgence of measles. Methods: To measure the potential impact of reduced MMR vaccination rates on measles outbreak, this research examines several counterfactual scenarios in pre-COVID-19 and post-COVID-19 era. An agent-based modeling framework is used to simulate the spread of measles on a synthetic yet realistic social network of Virginia. The change in vulnerability of various communities to measles due to reduced MMR rate is analyzed. Results: Results show that a decrease in vaccination rate [Formula: see text] has a highly non-linear effect on the number of measles cases and this effect grows exponentially beyond a threshold [Formula: see text]. At low vaccination rates, faster isolation of cases and higher compliance to home-isolation are not enough to control the outbreak. The overall impact on urban and rural counties is proportional to their population size but the younger children, African Americans and American Indians are disproportionately infected and hence are more vulnerable to the reduction in the vaccination rate. Conclusions: At low vaccination rates, broader interventions are needed to control the outbreak. Identifying the cause of the decline in vaccination rates (e.g., low income) can help design targeted interventions which can dampen the disproportional impact on more vulnerable populations and reduce disparities in health. Per capita burden of the potential measles resurgence is equivalent in the rural and the urban communities and hence proportionally equitable public health resources should be allocated to rural regions.
MeSH term(s)	COVID-19/epidemiology ; Child ; Communicable Disease Control ; Humans ; Measles/epidemiology ; Measles/prevention & control ; Measles-Mumps-Rubella Vaccine ; Pandemics ; United States/epidemiology
Chemical Substances	Measles-Mumps-Rubella Vaccine
Language	English
Publishing date	2022-09-20
Publishing country	England
Document type	Journal Article
ZDB-ID	2041550-3
ISSN	1471-2334 ; 1471-2334
ISSN (online)	1471-2334
ISSN	1471-2334
DOI	10.1186/s12879-022-07703-w
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Article ; Online: Feedback Between Behavioral Adaptations and Disease Dynamics

Jiangzhuo Chen / Achla Marathe / Madhav Marathe

Scientific Reports, Vol 8, Iss 1, Pp 1-

2018 Volume 15

Abstract: Abstract We study the feedback processes between individual behavior, disease prevalence, interventions and social networks during an influenza pandemic when a limited stockpile of antivirals is shared between the private and the public sectors. An ... ...

Abstract	Abstract We study the feedback processes between individual behavior, disease prevalence, interventions and social networks during an influenza pandemic when a limited stockpile of antivirals is shared between the private and the public sectors. An economic model that uses prevalence-elastic demand for interventions is combined with a detailed social network and a disease propagation model to understand the feedback mechanism between epidemic dynamics, market behavior, individual perceptions, and the social network. An urban and a rural region are simulated to assess the robustness of results. Results show that an optimal split between the private and public sectors can be reached to contain the disease but the accessibility of antivirals from the private sector is skewed towards the richest income quartile. Also, larger allocations to the private sector result in wastage where individuals who do not need it are able to purchase it but who need it cannot afford it. Disease prevalence increases with household size and total contact time but not by degree in the social network, whereas wastage of antivirals decreases with degree and contact time. The best utilization of drugs is achieved when individuals with high contact time use them, who tend to be the school-aged children of large families.
Keywords	Medicine ; R ; Science ; Q
Subject code	380
Language	English
Publishing date	2018-08-01T00:00:00Z
Publisher	Nature Publishing Group
Document type	Article ; Online
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Article ; Online: A Framework for Discovering Health Disparities among Cohorts in an Influenza Epidemic.

Wang, Lijing / Chen, Jiangzhuo / Marathe, Achla

World wide web

2018 Volume 22, Issue 6, Page(s) 2997–3020

Abstract: Infectious diseases such as Influenza and Ebola pose a serious threat to everyone but certain demographics and cohorts face a higher risk of infection than others. This research provides a computational framework for studying health disparities among ... ...

Abstract	Infectious diseases such as Influenza and Ebola pose a serious threat to everyone but certain demographics and cohorts face a higher risk of infection than others. This research provides a computational framework for studying health disparities among cohorts based on individual level features, such as age, gender, income, etc. We apply this framework to find health disparities among subpopulations in an influenza epidemic and evaluate vaccination prioritization strategies to achieve specific objectives. We explore the heterogeneities in individuals' demographic and socioeconomic attributes as the potential cause of health disparities. An agent-based model is used to simulate an influenza epidemic over a synthetic social contact network of the Montgomery County in Southwest Virginia to identify infected cases which are then labeled with a specific clinical outcome by using a predefined probability distribution based on age and risk level. We divide the population into age and income based cohorts and measure the direct and indirect economic impact of vaccination for each cohort. Simulation-based results find strong health disparities across age and income groups. Various vaccine distribution strategies are considered and outcomes are measured through metrics such as death count, total number of infections, net return per capita, net return per dollar spent and net return per vaccinated person. The results, framework, and methodology developed here can assist public health policy makers in efficiently allocating limited pharmaceutical resources.
Language	English
Publishing date	2018-06-14
Publishing country	United States
Document type	Journal Article
ZDB-ID	2025142-7
ISSN	1573-1413 ; 1386-145X
ISSN (online)	1573-1413
ISSN	1386-145X
DOI	10.1007/s11280-018-0608-8
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Article ; Online: Feedback Between Behavioral Adaptations and Disease Dynamics.

Chen, Jiangzhuo / Marathe, Achla / Marathe, Madhav

Scientific reports

2018 Volume 8, Issue 1, Page(s) 12452

Abstract: We study the feedback processes between individual behavior, disease prevalence, interventions and social networks during an influenza pandemic when a limited stockpile of antivirals is shared between the private and the public sectors. An economic model ...

Abstract	We study the feedback processes between individual behavior, disease prevalence, interventions and social networks during an influenza pandemic when a limited stockpile of antivirals is shared between the private and the public sectors. An economic model that uses prevalence-elastic demand for interventions is combined with a detailed social network and a disease propagation model to understand the feedback mechanism between epidemic dynamics, market behavior, individual perceptions, and the social network. An urban and a rural region are simulated to assess the robustness of results. Results show that an optimal split between the private and public sectors can be reached to contain the disease but the accessibility of antivirals from the private sector is skewed towards the richest income quartile. Also, larger allocations to the private sector result in wastage where individuals who do not need it are able to purchase it but who need it cannot afford it. Disease prevalence increases with household size and total contact time but not by degree in the social network, whereas wastage of antivirals decreases with degree and contact time. The best utilization of drugs is achieved when individuals with high contact time use them, who tend to be the school-aged children of large families.
MeSH term(s)	Antiviral Agents/therapeutic use ; Computer Simulation ; Delivery of Health Care ; Feedback ; Humans ; Income ; Influenza A virus/physiology ; Influenza, Human/drug therapy ; Influenza, Human/epidemiology ; Models, Economic ; Pandemics ; Perception ; Population ; Prevalence ; Private Sector ; Public Sector ; Rural Population ; Social Networking ; United States/epidemiology ; Urban Population
Chemical Substances	Antiviral Agents
Language	English
Publishing date	2018-08-20
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-018-30471-0
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Book ; Online: A Large-Scale Epidemic Simulation Framework for Realistic Social Contact Networks

Kitson, Joy / Costello, Ian / Chen, Jiangzhuo / Jiménez, Diego / Hoops, Stefan / Mortveit, Henning / Meneses, Esteban / Yeom, Jae-Seung / Marathe, Madhav V. / Bhatele, Abhinav

2024

Abstract: Global pandemics can wreak havoc and lead to significant social, economic, and personal losses. Preventing the spread of infectious diseases requires implementing interventions at different levels of government, and evaluating the potential impact and ... ...

Abstract	Global pandemics can wreak havoc and lead to significant social, economic, and personal losses. Preventing the spread of infectious diseases requires implementing interventions at different levels of government, and evaluating the potential impact and efficacy of those preemptive measures. Agent-based modeling can be used for detailed studies of epidemic diffusion and possible interventions. We present Loimos, a highly parallel simulation of epidemic diffusion written on top of Charm++, an asynchronous task-based parallel runtime. Loimos uses a hybrid of time-stepping and discrete-event simulation to model disease spread. We demonstrate that our implementation of Loimos is able to scale to large core counts on an HPC system. In particular, Loimos is able to simulate a US-scale synthetic interaction network in an average of 1.497 seconds per simulation day when executed on 16 nodes on Rivanna at the University of Virginia, processing around 428 billion interactions (person-person edges) in under five minutes for an average of 1.4 billion traversed edges per second (TEPS). Comment: 13 pages (including references), 9 figures
Keywords	Computer Science - Distributed ; Parallel ; and Cluster Computing
Publishing date	2024-01-16
Publishing country	us
Document type	Book ; Online
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Article: Data-Driven Modeling for Different Stages of Pandemic Response.

Adiga, Aniruddha / Chen, Jiangzhuo / Marathe, Madhav / Mortveit, Henning / Venkatramanan, Srinivasan / Vullikanti, Anil

Journal of the Indian Institute of Science

2020 Volume 100, Issue 4, Page(s) 901–915

Abstract: Some of the key questions of interest during the COVID-19 pandemic (and all outbreaks) include: where did the disease start, how is it spreading, who are at risk, and how to control the spread. There are a large number of complex factors driving the ... ...

Abstract	Some of the key questions of interest during the COVID-19 pandemic (and all outbreaks) include: where did the disease start, how is it spreading, who are at risk, and how to control the spread. There are a large number of complex factors driving the spread of pandemics, and, as a result, multiple modeling techniques play an increasingly important role in shaping public policy and decision-making. As different countries and regions go through phases of the pandemic, the questions and data availability also change. Especially of interest is aligning model development and data collection to support response efforts at each stage of the pandemic. The COVID-19 pandemic has been unprecedented in terms of real-time collection and dissemination of a number of diverse datasets, ranging from disease outcomes, to mobility, behaviors, and socio-economic factors. The data sets have been critical from the perspective of disease modeling and analytics to support policymakers in real time. In this overview article, we survey the data landscape around COVID-19, with a focus on how such datasets have aided modeling and response through different stages so far in the pandemic. We also discuss some of the current challenges and the needs that will arise as we plan our way out of the pandemic.
Keywords	covid19
Language	English
Publishing date	2020-11-16
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2139553-6
ISSN	0970-4140 ; 0970-4140 ; 0019-4964
ISSN (online)	0970-4140
ISSN	0970-4140 ; 0019-4964
DOI	10.1007/s41745-020-00206-0
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