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Identifying routes of transmission among hospitalized patients during a healthcare-associated outbreak can be tedious, particularly among patients with complex hospital stays and multiple exposures. Data mining of the electronic health record (EHR) has the potential to rapidly identify common exposures among patients suspected of being part of an outbreak.
We retrospectively analyzed 9 hospital outbreaks that occurred during 2011–2016 and that had previously been characterized both according to transmission route and by molecular characterization of the bacterial isolates. We determined (1) the ability of data mining of the EHR to identify the correct route of transmission, (2) how early the correct route was identified during the timeline of the outbreak, and (3) how many cases in the outbreaks could have been prevented had the system been running in real time.
Correct routes were identified for all outbreaks at the second patient, except for one outbreak involving >1 transmission route that was detected at the eighth patient. Up to 40 or 34 infections (78% or 66% of possible preventable infections, respectively) could have been prevented if data mining had been implemented in real time, assuming the initiation of an effective intervention within 7 or 14 days of identification of the transmission route, respectively.
Data mining of the EHR was accurate for identifying routes of transmission among patients who were part of the outbreak. Prospective validation of this approach using routine whole-genome sequencing and data mining of the EHR for both outbreak detection and route attribution is ongoing.
In 2011 the Incidence Assay Critical Path Working Group reviewed the current state of HIV incidence assays and helped to determine a critical path to the introduction of an HIV incidence assay. At that time the Consortium for Evaluation and Performance of HIV Incidence Assays (CEPHIA) was formed to spur progress and raise standards among assay developers, scientists and laboratories involved in HIV incidence measurement and to structure and conduct a direct independent comparative evaluation of the performance of 10 existing HIV incidence assays, to be considered singly and in combinations as recent infection test algorithms. In this paper we report on a new framework for HIV incidence assay evaluation that has emerged from this effort over the past 5 years, which includes a preliminary target product profile for an incidence assay, a consensus around key performance metrics along with analytical tools and deployment of a standardized approach for incidence assay evaluation. The specimen panels for this evaluation have been collected in large volumes, characterized using a novel approach for infection dating rules and assembled into panels designed to assess the impact of important sources of measurement error with incidence assays such as viral subtype, elite host control of viraemia and antiretroviral treatment. We present the specific rationale for several of these innovations, and discuss important resources for assay developers and researchers that have recently become available. Finally, we summarize the key remaining steps on the path to development and implementation of reliable assays for monitoring HIV incidence at a population level.
We used data from the Genitourinary Medicine Clinic Activity Dataset (GUMCAD) over a 3-year period (2009–2011) to investigate the distribution and risk factors of Trichomonas vaginalis infection in England. Socio-demographic and clinical risk factors associated with a diagnosis of T. vaginalis were explored using multivariable logistic regression. Rates of T. vaginalis infection were highest in London and the West Midlands. For men and women, T. vaginalis infection was significantly associated with: older age compared to those aged 20–24 years, non-white ethnicity (in particular black Caribbean and black ‘other’ ethnic groups), and birth in the Caribbean vs. birth in the UK. Current gonorrhoea or chlamydia infection was associated with a diagnosis of T. vaginalis in women. Further research is required to assess the public health impact and cost-effectiveness of introducing targeted screening for women at high risk of infection in areas of higher prevalence.
We discuss the optimal detection of point sources from multiwavelength imaging data using an approach, referred to as MDET, which requires no prior knowledge of the source spectrum. MDET may be regarded as a somewhat more general version of the so-called ‘chi-squared’ technique. We describe the theoretical basis of the technique, and show examples of its performance with four-channel infrared broadband imaging data from the WISE mission. We also discuss the potential benefits of applying it to the multifrequency data cubes of the ASKAP surveys, and suggest that it could increase the detection sensitivity of searches for neutral hydrogen emission at moderately high redshifts.
In this work we present an experimental study where energetic ions were produced in an underdense 2.5 × 1019 cm−3 plasma created by a 50 fs Ti:Sapphire laser with 5 TWs of power. The plasma comprises 95% He and 5% N2 gases. Ionization-induced trapping of nitrogen K-shell electrons in the laser-induced wakefield generates an electron beam with a mean energy of 40 MeV and ~1 nC of charge. Some of the helium ions at the wake–vacuum interface are accelerated with a measured minimum ion energy of He1+ ions of 1.2 MeV and He2+ ions of 4 MeV. The physics of the interaction is studied with 2D particle-in-cell simulations. These reveal the formation of an ion filament on the axis of the plasma due to space charge attraction of the wakefield-accelerated high-charge electron bunch. Some of these high-energy electrons escape the plasma to form a sheath at the plasma–vacuum boundary that accelerates some of the ions in the filament in the forward direction. Electrons with energy less than the sheath potential cannot escape and return to the plasma boundary in a vortex-like motion. This in turn produces a time-varying azimuthal magnetic field, which generates a longitudinal electric field at the interface that further accelerates and collimates the ions.
The economical production of flexible, chemically-functionalized carbon nanotube (CNT) electrodes is appealing for the manufacture of electronic textiles with integrated charge storage capability. In this paper, a commercial CNT sheet is treated with 0.02 M potassium permanganate at room temperature to accomplish in-situ deposition of manganese dioxide. The morphology, elemental oxidation states, and crystallinity of the modified CNT sheet are studied using SEM, EDX, XPS, and XRD. Manganese loading is varied from 4 to 20 weight-percent by tuning solution treatment time, and metal oxide hydration state is influenced by thermal annealing at 200 °C. Electrochemical measurements reveal that charge is stored not only via CNT-induced electrical double-layer capacitance, but also through metal oxide-mediated Faradic reactions. The MnO2-decorated CNT sheet exhibits a specific capacitance of 89.6 F/g at 1 A/g, a tenfold enhancement compared to pristine CNT sheet. Overall, this simplified processing approach holds promise for cost-effective incorporation of electrochemical capacitors into functional fabrics for energy-generation applications.
The cognitive profile of early onset Parkinson’s disease (EOPD) has not been clearly defined. Mutations in the parkin gene are the most common genetic risk factor for EOPD and may offer information about the neuropsychological pattern of performance in both symptomatic and asymptomatic mutation carriers. EOPD probands and their first-degree relatives who did not have Parkinson’s disease (PD) were genotyped for mutations in the parkin gene and administered a comprehensive neuropsychological battery. Performance was compared between EOPD probands with (N = 43) and without (N = 52) parkin mutations. The same neuropsychological battery was administered to 217 first-degree relatives to assess neuropsychological function in individuals who carry parkin mutations but do not have PD. No significant differences in neuropsychological test performance were found between parkin carrier and noncarrier probands. Performance also did not differ between EOPD noncarriers and carrier subgroups (i.e., heterozygotes, compound heterozygotes/homozygotes). Similarly, no differences were found among unaffected family members across genotypes. Mean neuropsychological test performance was within normal range in all probands and relatives. Carriers of parkin mutations, whether or not they have PD, do not perform differently on neuropsychological measures as compared to noncarriers. The cognitive functioning of parkin carriers over time warrants further study. (JINS, 2011, 17, 1–10)
Patients who have undergone tracheoesophageal puncture for surgical voice restoration often use unnaturally high oesophageal air pressures during speech. This study examined the effect of high oesophageal air pressure on oesophageal body motility, lower oesophageal sphincter function and dyspeptic symptoms.
Cross-sectional study using several investigative tests of oesophageal function.
Materials and methods:
Sixteen patients who used tracheoesophageal fistula speech underwent several investigations, including: oesophageal manometry, videofluoroscopy, barium swallow, and tracheal pressure measurements during speech. The patients were also asked to complete a dyspepsia questionnaire.
We demonstrated that more than 50 per cent of these patients had subjective or objective disordered oesophageal function. Videofluoroscopy and manometry identified oesophageal dysmotility in the same patients.
Oesophageal function appears to be altered by tracheoesophageal fistula speech. However, our study showed that there is no contraindication to proceeding with tracheoesophageal fistula voicing even in patients with a history of oesophageal dysfunction.
TPF-I capability for planetary signal extraction, including both detection and spectral characterization, can be optimized by taking proper account of instrumental characteristics and astrophysical prior information. We have developed the Point Process Algorithm (PPA), a Bayesian technique for extracting planetary signals using the sine/cosine chopped outputs of a dual nulling interferometer. It is so-called because it represents the system being observed as a set of points in a suitably defined state space, thus providing a natural way of incorporating our prior knowledge of the compact nature of the targets of interest. It can also incorporate the spatial covariance of the exozodi as prior information which could help mitigate against false detections. Data at multiple wavelengths are used simultaneously, taking into account possible spectral variations of the planetary signals. Input parameters include the sigma of measurement noise and the a priori probability of the presence of a planet. The output can be represented as an image of the intensity distribution on the sky, optimized for the detection of point sources. Previous approaches by others to the problem of planet detection for TPF-I have relied on the potentially non-robust identification of peaks in a “dirty” image, usually a correlation map. Tests with synthetic data suggest that the PPA provides greater sensitivity to fainter sources than does the standard approach (correlation map + CLEAN), and will be a useful tool for optimizing the design of TPF-I.