Exhaled VOC detection in lung cancer screening: a comprehensive meta-analysis.

BACKGROUND: Lung cancer (LC), characterized by high incidence and mortality rates, presents a significant challenge in oncology. Despite advancements in treatments, early detection remains crucial for improving patient outcomes. The accuracy of screening for LC by detecting volatile organic compounds (VOCs) in exhaled breath remains to be determined. METHODS: Our systematic review, following PRISMA guidelines and analyzing data from 25 studies up to October 1, 2023, evaluates the effectiveness of different techniques in detecting VOCs. We registered the review protocol with PROSPERO and performed a systematic search in PubMed, EMBASE and Web of Science. Reviewers screened the studies' titles/abstracts and full texts, and used QUADAS-2 tool for quality assessment. Then performed meta-analysis by adopting a bivariate model for sensitivity and specificity. RESULTS: This study explores the potential of VOCs in exhaled breath as biomarkers for LC screening, offering a non-invasive alternative to traditional methods. In all studies, exhaled VOCs discriminated LC from controls. The meta-analysis indicates an integrated sensitivity and specificity of 85% and 86%, respectively, with an AUC of 0.93 for VOC detection. We also conducted a systematic analysis of the source of the substance with the highest frequency of occurrence in the tested compounds. Despite the promising results, variability in study quality and methodological challenges highlight the need for further research. CONCLUSION: This review emphasizes the potential of VOC analysis as a cost-effective, non-invasive screening tool for early LC detection, which could significantly improve patient management and survival rates.

Environmental pollution and social factors as contributors to preterm birth in Fresno County.

BACKGROUND: Environmental pollution exposure during pregnancy has been identified as a risk factor for preterm birth. Most studies have evaluated exposures individually and in limited study populations. METHODS: We examined the associations between several environmental exposures, both individually and cumulatively, and risk of preterm birth in Fresno County, California. We also evaluated early (< 34 weeks) and spontaneous preterm birth. We used the Communities Environmental Health Screening Tool and linked hospital discharge records by census tract from 2009 to 2012. The environmental factors included air pollution, drinking water contaminants, pesticides, hazardous waste, traffic exposure and others. Social factors, including area-level socioeconomic status (SES) and race/ethnicity were also evaluated as potential modifiers of the relationship between pollution and preterm birth. RESULTS: In our study of 53,843 births, risk of preterm birth was associated with higher exposure to cumulative pollution scores and drinking water contaminants. Risk of preterm birth was twice as likely for those exposed to high versus low levels of pollution. An exposure-response relationship was observed across the quintiles of the pollution burden score. The associations were stronger among early preterm births in areas of low SES. CONCLUSIONS: In Fresno County, we found multiple pollution exposures associated with increased risk for preterm birth, with higher associations among the most disadvantaged. This supports other evidence finding environmental exposures are important risk factors for preterm birth, and furthermore the burden is higher in areas of low SES. This data supports efforts to reduce the environmental burden on pregnant women.

Diabetes mellitus and long-term mortality of ovarian cancer patients. A systematic review and meta-analysis of 12 cohort studies.

Ovarian cancer (OC) is the sixth most common cancer among women, and its prognosis is not favorable. Diabetes mellitus (DM) is hypothesized to be associated with a higher mortality in ovarian cancer patients, but evidence is inconsistent. Thus, we aim to investigate if DM is associated with the long-term all-cause and long-term cancer-specific mortality in ovarian cancer patients by synthesizing available epidemiologic evidences. We used 4 electronic databases (PubMed, EMBASE, Web of Science, and Scopus) to search for eligible articles. Title/abstract screening, full-text review, data extraction, and quality assessment were performed by reviewers independently. In meta-analysis, studies reporting risk ratio (RR) or hazard ratio that investigated the association between DM and mortality of OC patients were synthesized by a random-effect model. Subgroup and sensitivity analyses were performed by certain stratification or restrictive rules. Publication bias was assessed by funnel plots and Egger test. Statistical heterogeneity was evaluated by the I-squared value and a chi-squared test for the Cochrane Q statistic. Twelve cohort studies involving 14 outcome measures were included. In overall meta-analysis, the synthesized RR for all-cause mortality was 1.44 (95% CI 1.16-1.79) without substantial statistical heterogeneity (PCochrane  = .145, I2  = 34.1%); the synthesized RR for cancer-specific mortality was 1.44 (95% CI 1.08-1.93) with substantial heterogeneity (PCochrane  < .001, I2  = 90.1%). No publication bias was observed. Our results suggest DM is associated with a higher all-cause and cancer-specific mortality in ovarian cancer patients. Future studies should be done to examine the association between type 1 DM and ovarian cancer mortality.

A methodology for exploring biomarker--phenotype associations: application to flow cytometry data and systemic sclerosis clinical manifestations.

BACKGROUND: This work seeks to develop a methodology for identifying reliable biomarkers of disease activity, progression and outcome through the identification of significant associations between high-throughput flow cytometry (FC) data and interstitial lung disease (ILD) - a systemic sclerosis (SSc, or scleroderma) clinical phenotype which is the leading cause of morbidity and mortality in SSc. A specific aim of the work involves developing a clinically useful screening tool that could yield accurate assessments of disease state such as the risk or presence of SSc-ILD, the activity of lung involvement and the likelihood to respond to therapeutic intervention. Ultimately this instrument could facilitate a refined stratification of SSc patients into clinically relevant subsets at the time of diagnosis and subsequently during the course of the disease and thus help in preventing bad outcomes from disease progression or unnecessary treatment side effects. The methods utilized in the work involve: (1) clinical and peripheral blood flow cytometry data (Immune Response In Scleroderma, IRIS) from consented patients followed at the Johns Hopkins Scleroderma Center. (2) machine learning (Conditional Random Forests - CRF) coupled with Gene Set Enrichment Analysis (GSEA) to identify subsets of FC variables that are highly effective in classifying ILD patients; and (3) stochastic simulation to design, train and validate ILD risk screening tools. RESULTS: Our hybrid analysis approach (CRF-GSEA) proved successful in predicting SSc patient ILD status with a high degree of success (>82% correct classification in validation; 79 patients in the training data set, 40 patients in the validation data set). CONCLUSIONS: IRIS flow cytometry data provides useful information in assessing the ILD status of SSc patients. Our new approach combining Conditional Random Forests and Gene Set Enrichment Analysis was successful in identifying a subset of flow cytometry variables to create a screening tool that proved effective in correctly identifying ILD patients in the training and validation data sets. From a somewhat broader perspective, the identification of subsets of flow cytometry variables that exhibit coordinated movement (i.e., multi-variable up or down regulation) may lead to insights into possible effector pathways and thereby improve the state of knowledge of systemic sclerosis pathogenesis.

The Structure, Pathogenicity and Immunogenicity of Two Virion Fractions Harvested from Cell Cultures Infected with the CA16 Virus.

OBJECTIVES: To investigate the biological characteristics of the two types of virion fractions of Coxsackievirus A 16 (CA16), which include the real virion fraction and pseudo-virion fraction in their structure, pathogenicity and immunogenicity. METHODS: We obtained the two CA16 virion fractions by density gradient centrifugation. The morphology of virion fractions was analyzed by electron microscopy, while the antigenic characteristics and immunogenicity of two virion fractions were determined by ELISA, SDS-PAGE, Western blot, qRT-PCR, and the mouse model of immune response. RESULTS: The two virion fractions contained the major viral antigen components in their structures, showed similar pathogenicity in a neonatal murine model and were capable of inducing an effective primary immune response in adult mice, regardless of the essential distinction between the two virion fractions, which was the cleavage of VP0 to VP2 and VP4. CONCLUSIONS: The two CA16 virion fractions showed antigenicity and immunogenicity with inducing a specific immune response in animals.

Catalytic 1,1-diazidation of alkenes.

Compared to well-developed catalytic 1,2-diazidation of alkenes to produce vicinal diazides, the corresponding catalytic 1,1-diazidation of alkenes to yield geminal diazides has not been realized. Here we report an efficient approach for catalytic 1,1-diazidation of alkenes by redox-active selenium catalysis. Under mild conditions, electron-rich aryl alkenes with Z or E or Z/E mixed configuration can undergo migratory 1,1-diazidation to give a series of functionalized monoalkyl or dialkyl geminal diazides that are difficult to access by other methods. The method is also effective for the construction of polydiazides. The formed diazides are relatively safe by TGA-DSC analysis and impact sensitivity tests, and can be easily converted into various valuable molecules. In addition, interesting reactivity that geminal diazides give valuable molecules via the geminal diazidomethyl moiety as a formal leaving group in the presence of Lewis acid is disclosed. Mechanistic studies revealed that a selenenylation-deselenenylation followed by 1,2-aryl migration process is involved in the reactions, which provides a basis for the design of new reactions.

Catalytic Enantioselective Construction of Chiral γ-Azido Nitriles through Nitrile Group-Promoted Electrophilic Reaction of Alkenes.

An efficient approach for the construction of enantioenriched γ-azido nitriles through the chiral sulfide-catalyzed asymmetric electrophilic thioazidation of allylic nitriles is disclosed. A wide range of electron-deficient and -rich aryl, heterocyclic aryl, and alkyl substituents are suitable on the substrates of allylic nitriles. The regio-, enantio-, and diastereoselectivities of the reactions are excellent. As versatile platform molecules, the obtained chiral γ-azido nitriles can be easily converted into high-value-added chiral molecules that are not easily accessed by other methods. Control experiments revealed that the allylic nitrile group is important for control of the reactivity and enantioselectivity of the reaction leading to a broad substrate scope.

Drinking water contaminants in California and hypertensive disorders in pregnancy.

Environmental pollutants have been associated with hypertensive disorders in pregnancy including gestational hypertension, preeclampsia, and eclampsia, though few have focused on drinking water contamination. Water pollution can be an important source of exposures that may contribute to adverse pregnancy outcomes. METHODS: We linked water quality data on 13 contaminants and two violations from the California Communities Environmental Health Screening Tool to birth records from vital statistics and hospital discharge records (2007-2012) to examine the relationship between drinking water contamination and hypertensive disorders in pregnancy. We examined contaminants in single- and multipollutant models. Additionally, we examined if the relationship between water contamination and hypertensive disorders in pregnancy differed by neighborhood poverty, individual socioeconomic status, and race/ethnicity. RESULTS: Arsenic, nitrate, trihalomethane, hexavalent chromium, and uranium were detected in a majority of water systems. Increased risk of hypertensive disorders in pregnancy was modestly associated with exposure to cadmium, lead, trihalomethane, and hexavalent chromium in drinking water after adjusting for covariates in single pollutant models with odds ratios ranging from 1.01 to 1.08. In multipollutant models, cadmium was consistent, lead and trihalomethane were stronger, and additional contaminants were associated with hypertensive disorders in pregnancy including trichloroethylene, 1,2-Dibromo-3-chloropropane, nitrate, and tetrachloroethylene. Other contaminants either showed null results or modest inverse associations. The relationship between water contaminants and hypertensive disorders in pregnancy did not differ by neighborhood poverty. CONCLUSIONS: We found increased risk of hypertensive disorders in pregnancy associated with exposure to several contaminants in drinking water in California. Results for cadmium, lead, trihalomethane, and hexavalent chromium were robust in multipollutant models.

Heightened susceptibility: A review of how pregnancy and chemical exposures influence maternal health.

Pregnancy is a unique period when biological changes can increase sensitivity to chemical exposures. Pregnant women are exposed to multiple environmental chemicals via air, food, water, and consumer products, including flame retardants, plasticizers, and pesticides. Lead exposure increases risk of pregnancy-induced hypertensive disorders, although women's health risks are poorly characterized for most chemicals. Research on prenatal exposures has focused on fetal outcomes and less on maternal outcomes. We reviewed epidemiologic literature on chemical exposures during pregnancy and three maternal outcomes: preeclampsia, gestational diabetes, and breast cancer. We found that pregnancy can heighten susceptibility to environmental chemicals and women's health risks, although variations in study design and exposure assessment limited study comparability. Future research should include pregnancy as a critical period for women's health. Incorporating biomarkers of exposure and effect, deliberate timing and method of measurement, and consistent adjustment of potential confounders would strengthen research on the exposome and women's health.

gem-Difluoroallylation of Aryl Diazoesters via Catalyst-Free, Blue-Light-Mediated Formal Doyle-Kirmse Reaction.

A first example of low-energy blue-light-mediated formal Doyle-Kirmse reaction for gem-difluoroallylation of aryl diazoesters has been developed. A variety of highly functionalized gem-difluoroallyl containing esters bearing transformable sulfur and bromine groups were efficiently assembled with broad substrate scope under mild, catalyst-free, and additive-free conditions. The reaction represents a practical and environmentally friendly approach for C-CF2 bond formation based on rearrangement strategy, which will find potential applications among drug discovery and development.

BMI, Physical Inactivity, and Pap Test Use in Asian Women in the U.S.

INTRODUCTION: In the U.S., limited epidemiologic studies have investigated associations between BMI and physical inactivity and Pap test use among Asian women. The aim was to disentangle associations using data from the Behavioral Risk Factor Surveillance System between 2014 and 2016. METHODS: In the Behavioral Risk Factor Surveillance System, BMI was categorized into four levels (<18.5, 18.5 to <25, 25 to <30, and ≥30) and inactivity was defined as having no physical activity in addition to the individual's regular job during the past month. Analyses were conducted in June 2018. Weighted percentages of covariates were used to descriptively summarize the data. Multivariable logistic regression corrected for sampling weight was used to estimate associations between BMI and inactivity and Pap test use. Subgroup analysis was conducted by income and education. RESULTS: The analysis included 9,424 women and 59.6% of them had their last Pap test within 3 years. OR in the mutually adjusted model suggested underweight (BMI <18.5 compared with normal weight) was inversely associated with Pap test use within the last 3 years (OR=0.56, 95% CI=0.36, 0.88). Inactivity (compared with activity) was not associated with Pap test use within the last 3 years (OR=0.80, 95% CI=0.60, 1.06). Different association patterns of BMI and inactivity were observed by education. CONCLUSIONS: This study suggests that being underweight, rather than overweight or obesity, is associated with a lower rate of Pap test use in U.S. Asian women. Health interventions to facilitate Pap test use in Asian women should explore other potential targets, not aiming to just prevent obesity or change physical inactivity.

Advice and Frequently Asked Questions (FAQs) for Citizen-Science Environmental Health Assessments.

Citizen science provides quantitative results to support environmental health assessments (EHAs), but standardized approaches do not currently exist to translate findings into actionable solutions. The emergence of low-cost portable sensor technologies and proliferation of publicly available datasets provides unparalleled access to supporting evidence; yet data collection, analysis, interpretation, visualization, and communication are subjective approaches that must be tailored to a decision-making audience capable of improving environmental health. A decade of collaborative efforts and two citizen science projects contributed to three lessons learned and a set of frequently asked questions (FAQs) that address the complexities of environmental health and interpersonal relations often encountered in citizen science EHAs. Each project followed a structured step-by-step process in order to compare and contrast methods and approaches. These lessons and FAQs provide advice to translate citizen science research into actionable solutions in the context of a diverse range of environmental health issues and local stakeholders.

Cumulative Risk and Impact Modeling on Environmental Chemical and Social Stressors.

PURPOSE OF REVIEW: The goal of this review is to identify cumulative modeling methods used to evaluate combined effects of exposures to environmental chemicals and social stressors. The specific review question is: What are the existing quantitative methods used to examine the cumulative impacts of exposures to environmental chemical and social stressors on health? RECENT FINDINGS: There has been an increase in literature that evaluates combined effects of exposures to environmental chemicals and social stressors on health using regression models; very few studies applied other data mining and machine learning techniques to this problem. The majority of studies we identified used regression models to evaluate combined effects of multiple environmental and social stressors. With proper study design and appropriate modeling assumptions, additional data mining methods may be useful to examine combined effects of environmental and social stressors.

Meta-Analysis of Maternal and Fetal Transcriptomic Data Elucidates the Role of Adaptive and Innate Immunity in Preterm Birth.

Preterm birth (PTB) is the leading cause of newborn deaths around the world. Spontaneous preterm birth (sPTB) accounts for two-thirds of all PTBs; however, there remains an unmet need of detecting and preventing sPTB. Although the dysregulation of the immune system has been implicated in various studies, small sizes and irreproducibility of results have limited identification of its role. Here, we present a cross-study meta-analysis to evaluate genome-wide differential gene expression signals in sPTB. A comprehensive search of the NIH genomic database for studies related to sPTB with maternal whole blood samples resulted in data from three separate studies consisting of 339 samples. After aggregating and normalizing these transcriptomic datasets and performing a meta-analysis, we identified 210 genes that were differentially expressed in sPTB relative to term birth. These genes were enriched in immune-related pathways, showing upregulation of innate immunity and downregulation of adaptive immunity in women who delivered preterm. An additional analysis found several of these differentially expressed at mid-gestation, suggesting their potential to be clinically relevant biomarkers. Furthermore, a complementary analysis identified 473 genes differentially expressed in preterm cord blood samples. However, these genes demonstrated downregulation of the innate immune system, a stark contrast to findings using maternal blood samples. These immune-related findings were further confirmed by cell deconvolution as well as upstream transcription and cytokine regulation analyses. Overall, this study identified a strong immune signature related to sPTB as well as several potential biomarkers that could be translated to clinical use.

Investigation of association between environmental and socioeconomic factors and preterm birth in California.

BACKGROUND: Preterm birth (PTB),2 defined as birth at gestational age <37 weeks, is a major public health concern. Infants born prematurely, comprising of about 10% of the US newborns, have elevated risks of neonatal mortality and a wide array of health problems. Although numerous clinical, genetic, environmental and socioeconomic factors have been implicated in PTB, very few studies investigate the impacts of multiple pollutants and social factors on PTB using large scale datasets. OBJECTIVES: To evaluate association between environmental and socioeconomic factors and PTB in California. METHODS: We linked the birth cohort file maintained by the California Office of Statewide Health Planning and Development from 2009 to 2012 years across 1.8 million births and the CalEnviroScreen 3.0 dataset from California Communities Environmental Health Screening Tool at the census tract level for 56 California counties. CalEnviroScreen contains 7 exposure and 5 environmental effects variables that constitute the Pollution Burden variable, and 5 socioeconomic variables. We evaluated relationships between environmental exposures and the risk of PTB using hierarchical clustering analyses and GIS-based visualization. We also used logistic regression to evaluate the relationship between specific pollutant and exposure indicators and PTB, accounted for socio-demographic determinants such as maternal race/ethnicity, maternal age, maternal education and payment of delivery costs. RESULTS: There exists geographic variability in PTB for groups of counties with similar environmental and social exposure profiles. We found an association between Pollution Burden, particulate matter ≤2.5 µm (PM2.5), and Drinking Water Scores and PTB (adjusted odds ratios were 1.03 (95% Confidence Interval (CI): 1.01, 1.04), 1.03 (95% CI: 1.02,1.04), and 1.04 (95% CI: 1.03,1.05), respectively). Additional findings suggest that certain drinking water contaminants such as arsenic and nitrate are associated with PTB in California. CONCLUSIONS: CalEnviroScreen data combined with birth records offer great opportunity for revealing novel exposures and evaluating cumulative exposures related to PTB by providing useful environmental and social information. Certain drinking water contaminants such as arsenic and nitrate are potentially associated with PTB in California and should be investigated further. Small association signals may involve sizeable population impacts.

Associations between socio-demographic characteristics and chemical concentrations contributing to cumulative exposures in the United States.

Association rule mining (ARM) has been widely used to identify associations between various entities in many fields. Although some studies have utilized it to analyze the relationship between chemicals and human health effects, fewer have used this technique to identify and quantify associations between environmental and social stressors. Socio-demographic variables were generated based on U.S. Census tract-level income, race/ethnicity population percentage, education level, and age information from the 2010-2014, 5-Year Summary files in the American Community Survey (ACS) database, and chemical variables were generated by utilizing the 2011 National-Scale Air Toxics Assessment (NATA) census tract-level air pollutant exposure concentration data. Six mobile- and industrial-source pollutants were chosen for analysis, including acetaldehyde, benzene, cyanide, particulate matter components of diesel engine emissions (namely, diesel PM), toluene, and 1,3-butadiene. ARM was then applied to quantify and visualize the associations between the chemical and socio-demographic variables. Census tracts with a high percentage of racial/ethnic minorities and populations with low income tended to have higher estimated chemical exposure concentrations (fourth quartile), especially for diesel PM, 1,3-butadiene, and toluene. In contrast, census tracts with an average population age of 40-50 years, a low percentage of racial/ethnic minorities, and moderate-income levels were more likely to have lower estimated chemical exposure concentrations (first quartile). Unsupervised data mining methods can be used to evaluate potential associations between environmental inequalities and social disparities, while providing support in public health decision-making contexts.

Connecting the Dots: Linking Environmental Justice Indicators to Daily Dose Model Estimates.

Many different quantitative techniques have been developed to either assess Environmental Justice (EJ) issues or estimate exposure and dose for risk assessment. However, very few approaches have been applied to link EJ factors to exposure dose estimate and identify potential impacts of EJ factors on dose-related variables. The purpose of this study is to identify quantitative approaches that incorporate conventional risk assessment (RA) dose modeling and cumulative risk assessment (CRA) considerations of disproportionate environmental exposure. We apply the Average Daily Dose (ADD) model, which has been commonly used in RA, to better understand impacts of EJ indicators upon exposure dose estimates and dose-related variables, termed the Environmental-Justice-Average-Daily-Dose (EJ-ADD) approach. On the U.S. nationwide census tract-level, we defined and quantified two EJ indicators (poverty and race/ethnicity) using an EJ scoring method to examine their relation to census tract-level multi-chemical exposure dose estimates. Pollutant doses for each tract were calculated using the ADD model, and EJ scores were assigned to each tract based on poverty- or race-related population percentages. Single- and multiple-chemical ADD values were matched to the tract-level EJ scores to analyze disproportionate dose relationships and contributing EJ factors. We found that when both EJ indicators were examined simultaneously, ADD for all pollutants generally increased with larger EJ scores. To demonstrate the utility of using EJ-ADD on the local scale, we approximated ADD levels of lead via soil/dust ingestion for simulated communities with different EJ-related scenarios. The local-level simulation indicates a substantial difference in exposure-dose levels between wealthy and EJ communities. The application of the EJ-ADD approach can link EJ factors to exposure dose estimate and identify potential EJ impacts on dose-related variables.

Exploring the forest instead of the trees: An innovative method for defining obesogenic and obesoprotective environments.

Past research has assessed the association of single community characteristics with obesity, ignoring the spatial co-occurrence of multiple community-level risk factors. We used conditional random forests (CRF), a non-parametric machine learning approach to identify the combination of community features that are most important for the prediction of obesogenic and obesoprotective environments for children. After examining 44 community characteristics, we identified 13 features of the social, food, and physical activity environment that in combination correctly classified 67% of communities as obesoprotective or obesogenic using mean BMI-z as a surrogate. Social environment characteristics emerged as most important classifiers and might provide leverage for intervention. CRF allows consideration of the neighborhood as a system of risk factors.

The gene expression profile of peripheral blood mononuclear cells from EV71-infected rhesus infants and the significance in viral pathogenesis.

Enterovirus 71 (EV71) is the major pathogen responsible for fatal hand, foot and mouth disease (HFMD). Our previous work reported on an EV71-infected rhesus monkey infant model that presented with histo-pathologic changes of the central nervous system (CNS) and lungs. This study is focused on the correlated modulation of gene expression in the peripheral blood mononuclear cells (PBMCs) from EV71-infected rhesus monkey infants. The expression of more than 500 functional genes associated with multiple pathways was modulated. The expression of genes associated with immune inflammatory responses was up-regulated during the period from days 4 to 10 post-infection. The expression of two genes (TAC1 and IL17A), which play major roles in inflammatory reactions, was remarkably up-regulated during the infection period. Furthermore, a higher expression level of the TAC1 gene was identified in the CNS compared to the lungs, but a high expression level of the IL-17A gene was observed in the lungs and not in the CNS. The results of this study suggest at least two facts about EV71 infection, which are that: the TAC1 gene that encodes substance P and neurokinin-A is present in both PBMCs and the hypothalamus; and the up-regulation of IL-17A is sustained in the peripheral blood.

EV71-infected CD14(+) cells modulate the immune activity of T lymphocytes in rhesus monkeys.

Preliminary studies of the major pathogen enterovirus 71 (EV71), a member of the Picornaviridae family, have suggested that EV71 may be a major cause of fatal hand, foot and mouth disease cases. Currently, the role of the pathological changes induced by EV71 infection in the immunopathogenic response remains unclear. Our study focused on the interaction between this virus and immunocytes and indicated that this virus has the ability to replicate in CD14(+) cells. Furthermore, these EV71-infected CD14(+) cells have the capacity to stimulate the proliferation of T cells and to enhance the release of certain functional cytokines. An adaptive immune response induced by the back-transfusion of EV71-infected CD14(+) cells was observed in donor neonatal rhesus monkeys. Based on these observations, the proposed hypothesis is that CD14(+) cells infected by the EV71 virus might modulate the anti-EV71 adaptive immune response by inducing simultaneous T-cell activation.