Retraction notice to "The wastewater microbiome: A novel insight for COVID-19 surveillance" [Sci. Total Environ. 764 (2021) 142867].
Explore the source record for details and available documents.
Published Erratum↗
Biomedical subjects
Steven Roberts
Publications and source records attributed to Steven Roberts.
The wastewater microbiome: A novel insight for COVID-19 surveillance.
Wastewater-Based Epidemiology is a tool to face and mitigate COVID-19 outbreaks by evaluating conditions in a specific community. This study aimed to analyze the microbiome profiles using nanopore technology for full-length 16S rRNA sequencing in wastewater samples collected from a penitentiary (P), a residential care home (RCH), and a quarantine or health care facilities (HCF). During the study, the wastewater samples from the RCH and the P were negative for SARS-CoV-2 based on qPCRs, except during the fourth week when was detected. Unexpectedly, the wastewater microbiome from RCH and P prior to week four was correlated with the samples collected from the HCF, suggesting a core bacterial community is expelled from the digest tract of individuals infected with SARS-CoV-2. The microbiota of wastewater sample positives for SARS-CoV-2 was strongly associated with enteric bacteria previously reported in patients with risk factors for COVID-19. We provide novel evidence that the wastewater microbiome associated with gastrointestinal manifestations appears to precede the SARS-CoV-2 detection in sewage. This finding suggests that the wastewaters microbiome can be applied as an indicator of community-wide SARS-CoV-2 surveillance.
COVID-19↗
Retracted: Factors affecting hospital readmission rates for breast cancer patients in Western Australia.
By this notice, the Editor and the Publisher of the Journal of Surgical Oncology retract from publication the following article: "Factors Affecting Hospital Readmission Rates for Breast Cancer Patients in Western Australia," Michael A. Martin, Ramona Meyricke, Terry O'Neill, and Steven Roberts, Journal of Surgical Oncology, Published online January 17, 2007, DOI: 10.1002/jso.20742. The article has been formally deemed a duplicate submission. The Editor and the Publisher of the Journal of Surgical Oncology regret the occurrence of this unfortunate incident.
breast cancer↗
Breast-conserving surgery versus mastectomy for survival from breast cancer: the Western Australian experience.
BACKGROUND: The focus of this study was the relative survival rates of breast cancer patients whose treatment was breast-conserving surgery compared with that of mastectomy, adjusting for tumor size and nodal status because these factors may be intrinsically associated with mastectomy being the treatment of choice. Patient age was also accounted for in the model. By adjusting for these factors, we mitigate them as confounders of treatment choice in assessing effects on survival rates. METHODS: Data were sourced from linked administrative data from the Western Australian Department of Health Record Linkage Unit. The data consisted of linked records containing the diagnosis, subsequent hospital admission, and death records of about 3000 women diagnosed with cancer in Western Australia between 1 January 1995 and 31 December 1999. Cox proportional hazards regression was used to investigate survival outcomes of breast-conserving surgery compared with that of mastectomy, adjusting for tumor size, nodal status, and subject age. RESULTS: The hazard of death is reduced by a factor of about one half for subjects whose treatment was breast-conserving surgery over treatment by mastectomy. Furthermore, the hazard of death increases substantially for subjects with nodal involvement over subjects for whom there has been no identified spread to regional lymph nodes. Hazard of death increases as both age and tumor size increase. CONCLUSIONS: Western Australian breast cancer patients treated with breast-conserving surgery have improved survival outcomes over those treated with mastectomy, after allowing for tumor size, patient age, and lymph node involvement.
Aged↗
The question of nonlinearity in the dose-response relation between particulate matter air pollution and mortality: can Akaike's Information Criterion be trusted to take the right turn?
The shape of the dose-response relation between particulate matter air pollution and mortality is crucial for public health assessment, and departures of this relation from linearity could have important regulatory consequences. A number of investigators have studied the shape of the particulate matter-mortality dose-response relation and concluded that the relation could be adequately described by a linear model. Some of these researchers examined the hypothesis of linearity by comparing Akaike's Information Criterion (AIC) values obtained under linear, piecewise linear, and spline alternative models. However, at the current time, the efficacy of the AIC in this context has not been assessed. The authors investigated AIC as a means of comparing competing dose-response models, using data from Cook County, Illinois, for the period 1987-2000. They found that if nonlinearities exist, the AIC is not always successful in detecting them. In a number of the scenarios considered, AIC was equivocal, picking the correct simulated dose-response model about half of the time. These findings suggest that further research into the shape of the dose-response relation using alternative model selection criteria may be warranted.
Aged↗
Mastectomy or breast conserving surgery? Factors affecting type of surgical treatment for breast cancer--a classification tree approach.
BACKGROUND: A critical choice facing breast cancer patients is which surgical treatment--mastectomy or breast conserving surgery (BCS)--is most appropriate. Several studies have investigated factors that impact the type of surgery chosen, identifying features such as place of residence, age at diagnosis, tumor size, socio-economic and racial/ethnic elements as relevant. Such assessment of "propensity" is important in understanding issues such as a reported under-utilisation of BCS among women for whom such treatment was not contraindicated. Using Western Australian (WA) data, we further examine the factors associated with the type of surgical treatment for breast cancer using a classification tree approach. This approach deals naturally with complicated interactions between factors, and so allows flexible and interpretable models for treatment choice to be built that add to the current understanding of this complex decision process. METHODS: Data was extracted from the WA Cancer Registry on women diagnosed with breast cancer in WA from 1990 to 2000. Subjects' treatment preferences were predicted from covariates using both classification trees and logistic regression. RESULTS: Tumor size was the primary determinant of patient choice, subjects with tumors smaller than 20 mm in diameter preferring BCS. For subjects with tumors greater than 20 mm in diameter factors such as patient age, nodal status, and tumor histology become relevant as predictors of patient choice. CONCLUSION: Classification trees perform as well as logistic regression for predicting patient choice, but are much easier to interpret for clinical use. The selected tree can inform clinicians' advice to patients.
Adult↗
A comparison between in vivo radiographic working length determination and measurement after extraction.
The purpose of this study was to compare the difference between the in vivo working length established by viewing a periapical radiograph and the in vitro measurement from the file tip to the apical foramen of the extracted tooth. Twenty-six canals from teeth that had been treatment planned for extraction were accessed under rubber dam isolation. The coronal portion of each canal was flared using Gates Glidden drills, and a K-type file was inserted down the canal until an electronic apex locator indicated that the file had reached the apex. A size 20 K-type file was locked into place with glass ionomer cement at this position. A radiograph was exposed and the tooth was extracted. Each tooth was viewed using a videomicroscope at 30x original magnification, and the distance from the file tip to the most coronal aspect of the major foramen was measured. Six examiners viewed each radiograph and assessed the working length of each canal. Chi(2) analysis of the data revealed a significant difference (p < 0.01) between the estimation of working lengths and the microscopic measurements. The examiners overestimated the distance between the file tip and the apical foramen of the tooth when the file was placed short, and underestimated the distance when the file was placed long. In conclusion, when the file is short it is actually closer to the apical foramen than it appears radiographically; when it is long it is actually longer than it appears radiographically.
Adolescent↗
A comparative photoelastic stress analysis of internal root stresses between RC Prep and saline when applied to the Profile/GT rotary instrumentation system.
The purpose of this study was to measure and compare the amount of stress produced by GT ProFile (GT) and ProFile (PF) rotary files lubricated with either RC Prep (RCP) or saline (S) on the walls of prepared simulated canals. Twenty-four 10-mm long canals with a 10 mm radius of curvature were prepared in PL-2 photoelastic acrylic blocks which were lubricated with either RCP or S. The files were inserted into a Nouvag handpiece mounted to an Instron 4502 universal testing machine and lowered into the canal at a rate of 60 mm/min and a rotational speed of 300 RPM. The following four GTs and four PFs were sequentially introduced into predetermined depths of each canal: 20/.10, 20/.08, 20/.06, 20/.04, 40/.04, 35/.04, 30/.04, and 25/.04. Total areas of stress created by each file were captured by digital video images and measured using Image J software. Statistical analysis of the data was performed using a two-way ANOVA (p < 0.05, n = 24). The GT/RCP group demonstrated a significant average of 64.22% less stress than GT/S group. The PF (25, 30, and 35)/RCP groups demonstrated a significant average of 27.02% less stress than the same S groups. PF (40) produced a negligible amount of stress regardless of the lubricant type. The results reveal that using RCP as a lubricant when instrumenting curved canals with GT and PF results in less stress when compared to saline.
Acrylic Resins↗
Bootstrap model averaging in time series studies of particulate matter air pollution and mortality.
The consensus from time series studies that have investigated the mortality effects of particulate matter air pollution (PM) is that increases in PM are associated with increases in daily mortality. However, recently concerns have been raised that the observed positive association between PM and mortality may be an artefact of model selection due to multiple hypothesis testing. This problem arises when a number of models are investigated, but only the "best" model is reported and all subsequent inference is based on this model, ignoring the model selection process. In this paper, we introduce the use of the bootstrap as a means of addressing the problems of model selection in PM mortality time series studies. Using the bootstrap to perform inference about the effect of PM on mortality is a process based on a set of models rather than on a single model. It is shown that using the bootstrap to overcome the problems of model selection is competitive with the existing methodology of Bayesian model averaging.
Air Pollutants↗
A new model for investigating the mortality effects of multiple air pollutants in air pollution mortality time-series studies.
Because the U.S. Environmental Protection Agency regulates air pollutants independently, the majority of time-series studies on air pollution and mortality have focused on estimating the adverse health effects of a single pollutant. However, due to the sometimes high correlation between air pollutants, the results from studies that focus on a single air pollutant can be difficult to interpret. In addition, the high correlation between air pollutants can produce problems of interpretation for the standard method of investigating the adverse health effects due to multiple air pollutants. The standard method involves simultaneously including the multiple air pollutants in a single statistical model. Because of this, the development of new models to concurrently estimate the adverse health effects of multiple air pollutants has recently been identified as an important area of future research. In this article, a new model for disentangling the joint effects of multiple air pollutants in air pollution mortality time-series studies is introduced. This new model uses the time-series data to assign each air pollutant a weight that indicates the pollutant's contribution to the air pollution mixture that affects mortality and to estimate the effect of this air pollution mixture on mortality. This model offers an improvement in statistical estimation precision over the standard method. It also avoids problems of interpretation that can occur if the standard method is used. This new model is then illustrated by applying it to time-series data from two U.S. counties.
Air Pollutants↗
Using supervised principal components analysis to assess multiple pollutant effects.
BACKGROUND: Many investigations of the adverse health effects of multiple air pollutants analyze the time series involved by simultaneously entering the multiple pollutants into a Poisson log-linear model. This method can yield unstable parameter estimates when the pollutants involved suffer high intercorrelation; therefore, traditional approaches to dealing with multicollinearity, such as principal component analysis (PCA), have been promoted in this context. OBJECTIVES: A characteristic of PCA is that its construction does not consider the relationship between the covariates and the adverse health outcomes. A refined version of PCA, supervised principal components analysis (SPCA), is proposed that specifically addresses this issue. METHODS: Models controlling for longterm trends and weather effects were used in conjunction with each SPCA and PCA to estimate the association between multiple air pollutants and mortality for U.S. cities. The methods were compared further via a simulation study. RESULTS: Simulation studies demonstrated that SPCA, unlike PCA, was successful in identifying the correct subset of multiple pollutants associated with mortality. Because of this property, SPCA and PCA returned different estimates for the relationship between air pollution and mortality. CONCLUSIONS: Although a number of methods for assessing the effects of multiple pollutants have been proposed, such methods can falter in the presence of high correlation among pollutants. Both PCA and SPCA address this issue. By allowing the exclusion of pollutants that are not associated with the adverse health outcomes from the mixture of pollutants selected, SPCA offers a critical improvement over PCA.
Air Pollutants↗
An investigation of distributed lag models in the context of air pollution and mortality time series analysis.
In particulate air pollution mortality time series studies, the particulate air pollution exposure measure used is typically the current day's or the previous day's air pollution concentration or a multi-day moving average air pollution concentration. Distributed lag models (DLMs) that allow for differential air pollution effects that are spread over multiple days are seen as an improvement over using a single- or multi-day moving average air pollution exposure measure. However, at the current time, the statistical properties of DLMs as a measure of air pollution exposure have not been investigated. In this paper, a simulation study is used to investigate the performance of DLMs as a measure of air pollution exposure in comparison with single- and multi-day moving average air pollution exposure measures under various forms for the true effect of air pollution on mortality. The simulation study shows that DLMs offer a more robust measure of the effect of air pollution on mortality and avoid the potential for a large negative bias compared with single- or multi-day moving average air pollution exposure measures. This is important information. In many U.S. cities, particulate air pollution concentrations are observed only once every six days, meaning it is often only possible to use single-day particulate air pollution exposure measures. The results from this paper will help quantify the magnitude of the negative bias that can result from using single-day exposure measures. The implications of this work for future air pollution mortality time series studies are discussed. The data used in this paper are concurrent daily time series of mortality, weather, and particulate air pollution from Cook County, IL, for the period 1987-1994.
Air Pollutants↗
An in vitro evaluation of the cytotoxicity of various endodontic irrigants on human gingival fibroblasts.
The purpose of this study was to measure the cytotoxicity of six endodontic irrigants on cultured gingival fibroblasts using the CyQuant assay. Human gingival fibroblasts were grown in Dulbecco's Modified Eagle Medium (DMEM) containing 10% fetal bovine serum at 37 degrees C and 5% CO(2). At confluence, cells were split, plated in 96-well plates and incubated for 24-h to allow attachment. The following irrigants were tested at various concentrations: Sodium hypochlorite (NaOCl); iodine potassium-iodide (IKI); Betadine scrub (BS); calcium hydroxide [Ca(OH)2]; chlorine dioxide (SCD) and DMEM (positive control). Experimental groups were compared by the logarithmic difference between the clinical and LD50 concentrations of a particular irrigant. The results showed that IKI and Ca(OH)2 were significantly less cytotoxic than SCD, NaOCl, and BS. In conclusion, IKI and Ca(OH)2 are well tolerated by human gingival fibroblasts.
Analysis of Variance↗
An in vitro evaluation of the antibacterial efficacy of chlorine dioxide on E. faecalis in bovine incisors.
This study investigated the ability of chlorine dioxide to eliminate Enterococcus faecalis from dentinal tubules of bovine incisors. Thirty-seven extracted bovine incisor roots were sectioned into seventy-four 5 mm disks. Standardized lumens were filled with either sterile Brain Heart Infusion Broth (contamination controls, n = 10) or BHI containing E. faecalis (1.0 x 10 cfu/ml). Disks were incubated in 5% CO2 at 37 degrees C for 72 h. To simulate endodontic instrumentation the lumens were again enlarged. Sixty disks were randomly divided into four experimental groups and filled with one of the following irrigants: 10% Clidox-S (chlorine dioxide), 13.8% BioClenz (chlorine dioxide), 5.25% Clorox, or saline. The disks were incubated for 30 min and were then frozen, pulverized, serially diluted in phosphate buffered saline, and plated on BHI plates in triplicate. Total colony forming units were counted macroscopically. Statistical analysis of the data was performed with a Kruskal-Wallis one-way ANOVA on ranks (p < 0.05, n = 60). Bacterial counts, expressed in log10 cfu/disk were as follows (">" denotes significant differences): Saline > Clidox-S = BioClenz > Clorox. All negative controls were sterile. Chlorine dioxide and NaOCL were both effective in eliminating E. faecalis from the dentinal disks within 30 min.
Animals↗
Using moving total mortality counts to obtain improved estimates for the effect of air pollution on mortality.
In many cities of the United States, measurements of ambient particulate matter air pollution (PM) are available only once every 6 days. Time-series studies conducted in these cities that investigate the relationship between mortality and PM are restricted to using a single day's PM as the measure of PM exposure. This is undesirable because current evidence suggests that the effects of PM on mortality are spread over multiple days. And studies have shown that using a single day's PM as the measure of PM exposure can result in estimates that have a large negative bias. In this article, I introduce a new model for estimating the mortality effects of PM when only every-sixth-day PM data are available. This new model uses information available in the daily mortality time series to infer otherwise lost information about the effect of PM on mortality over a period of more than a single day. This new model typically offers an increase in both statistical estimation precision and accuracy compared with existing models.
Aged↗
Mortality displacement and distributed lag models.
Numerous time-series studies have investigated the association between daily mortality and daily ambient particulate air pollution concentrations (PM). The consensus from these studies is that increases in PM are associated with increases in daily mortality. However, it may be that increases in PM only hasten the deaths of individuals in a small, frail subset of the population whose longevity is short even in the absence of particulate air pollution. This hypothesis has been termed mortality displacement or harvesting. Distributed lag models (DLM) have been used to explore mortality effects of air pollution that are spread over multiple days, and DLM coefficients have been proposed as indicators of mortality displacement. We investigate statistical properties of DLM coefficients in the context of mortality displacement using simulation studies with frail population models. Our simulations use actual PM time series, as well as actual weather time series included as confounders. Our simulations show that DLM coefficients can have large bias when the mean lifetime of individuals in the frail subset of the population is more than a few weeks, and that the magnitude of this bias increases as the mean lifetime of individuals in the frail subset of the population increases. We conclude that DLM coefficients may be misleading as an indicator of mortality displacement, in the context of the frail population models that we explored.
Air Pollutants↗
High-resolution fast spin echo imaging of the human brain at 4.7 T: implementation and sequence characteristics.
In this work, a number of important issues associated with fast spin echo (FSE) imaging of the human brain at 4.7 T are addressed. It is shown that FSE enables the acquisition of images with high resolution and good tissue contrast throughout the brain at high field strength. By employing an echo spacing (ES) of 22 ms, one can use large flip angle refocusing pulses (162 degrees ) and a low acquisition bandwidth (50 kHz) to maximize the signal-to-noise ratio (SNR). A new method of phase encode (PE) ordering (called "feathering") designed to reduce image artifacts is described, and the contributions of RF (B(1)) inhomogeneity, different echo coherence pathways, and magnetization transfer (MT) to FSE signal intensity and contrast are investigated. B(1) inhomogeneity is measured and its effect is shown to be relatively minor for high-field FSE, due to the self-compensating characteristics of the sequence. Thirty-four slice data sets (slice thickness = 2 mm; in-plane resolution = 0.469 mm; acquisition time = 11 min 20 s) from normal volunteers are presented, which allow visualization of brain anatomy in fine detail. This study demonstrates that high-field FSE produces images of the human brain with high spatial resolution, SNR, and tissue contrast, within currently prescribed power deposition guidelines.
Adult↗
Interactions between particulate air pollution and temperature in air pollution mortality time series studies.
In many community time series studies on the effect of particulate air pollution on mortality, particulate air pollution is modeled additively. In this study, we investigated the interaction between daily particulate air pollution and daily mean temperature in Cook County, Illinois and Allegheny County, Pennsylvania, using data for the period 1987-1994. This was done through the use of joint particulate air pollution-temperature response surfaces and by stratifying the effect of particulate air pollution on mortality by temperature. Evidence that the effect of particulate air pollution on mortality may depend on temperature is found. However, the results were sensitive to the number of degrees of freedom used in the confounder adjustments, the particulate air pollution exposure measure, and how the effects of temperature on mortality are modeled. The results were less sensitive to the estimation method used--generalized linear models and natural cubic splines or generalized additive models and smoothing splines. The results of this study suggest that in community particulate air pollution mortality time series studies the possibility of an interaction between daily particulate air pollution and daily mean temperature should be considered.
Aged↗