Background Emergence of the novel 2009 influenza A H1N1 virus in California led to an evaluation of hospital respiratory protection programs (RPPs) and practices by the California Department of ...Public Health during the 2009-2010 influenza season. Methods Onsite evaluation of 16 hospitals consisted of interviews with managers and health care workers about RPPs and practices, review of written RPPs, and limited observations of personnel using respirators. Data were analyzed using descriptive statistics. Results All hospitals had implemented policies requiring the minimum use of N95 filtering facepiece respirators when working with patients with H1N1 virus infection; 95.5% of health care workers (n = 199) reported they would wear at least this level of protection when in close contact with a patient with confirmed or suspected H1N1 virus infection. However, evaluation of written RPPs indicated deficiencies in required areas, most commonly in recordkeeping, designation of a program administrator, program evaluation, employee training, and fit testing procedures. Conclusions Health care workers were aware of respiratory protection required when providing care for patients with confirmed or suspected H1N1 virus infection. Hospitals should improve written RPPs, fully implement written procedures, and conduct periodic program evaluation to ensure effectiveness of respirator use for health care worker protection. Increased accessibility of resources tailored for hospital respirator program administrators may be helpful.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Epileptic seizure prediction has steadily evolved from its conception in the 1970s, to proof-of-principle experiments in the late 1980s and 1990s, to its current place as an area of vigorous, ...clinical and laboratory investigation. As a step toward practical implementation of this technology in humans, we present an individualized method for selecting electroencephalogram (EEG) features and electrode locations for seizure prediction focused on precursors that occur within ten minutes of electrographic seizure onset. This method applies an intelligent genetic search process to EEG signals simultaneously collected from multiple intracranial electrode contacts and multiple quantitative features derived from these signals. The algorithm is trained on a series of baseline and preseizure records and then validated on other, previously unseen data using split sample validation techniques. The performance of this method is demonstrated on multiday recordings obtained from four patients implanted with intracranial electrodes during evaluation for epilepsy surgery. An average probability of prediction (or block sensitivity) of 62.5% was achieved in this group, with an average block false positive (FP) rate of 0.2775 FP predictions/h, corresponding to 90.47% specificity. These findings are presented as an example of a method for training, testing and validating a seizure prediction system on data from individual patients. Given the heterogeneity of epilepsy, it is likely that methods of this type will be required to configure intelligent devices for treating epilepsy to each individual's neurophysiology prior to clinical deployment.
Whilst holding great promise for low noise, ease of operation and networking,
useful photonic quantum computing has been precluded by the need for
beyond-state-of-the-art components, manufactured by ...the millions. Here we
introduce a manufacturable platform for quantum computing with photons. We
benchmark a set of monolithically-integrated silicon photonics-based modules to
generate, manipulate, network, and detect photonic qubits, demonstrating
dual-rail photonic qubits with $99.98\% \pm 0.01\%$ state preparation and
measurement fidelity, Hong-Ou-Mandel quantum interference between independent
photon sources with $99.50\%\pm0.25\%$ visibility, two-qubit fusion with
$99.22\%\pm0.12\%$ fidelity, and a chip-to-chip qubit interconnect with
$99.72\%\pm0.04\%$ fidelity, not accounting for loss. In addition, we preview a
selection of next generation technologies, demonstrating low-loss silicon
nitride waveguides and components, fabrication-tolerant photon sources,
high-efficiency photon-number-resolving detectors, low-loss chip-to-fiber
coupling, and barium titanate electro-optic phase shifters.
ABSTRACT
CD8 T cells drive the protective immune response to lymphocytic choriomeningitis virus (LCMV) infection and are thus a determining force in the selection of viral variants. To examine how ...escape mutations affect the presentation and recognition of overlapping T-cell epitopes, we isolated an LCMV variant that is not recognized by T-cell receptor (TCR)-transgenic H-2D
b
-restricted LCMV GP33-41-specific cytotoxic T lymphocytes (CTL). The variant virus carried a single-amino-acid substitution (valine to alanine) at position 35 of the viral glycoprotein. This region of the LCMV glycoprotein encodes both the D
b
-restricted GP33-43 epitope and a second epitope (GP34-42) presented by the K
b
molecule. We determined that the V-to-A CTL escape mutant failed to induce a D
b
GP33-43-specific CTL response and that D
b
-restricted GP33-43-specific CTL induced by the wild-type LCMV strain were unable to kill target cells infected with the variant LCMV strain. In contrast, the K
b
-restricted response was much less affected. We found that the V-to-A substitution severely impaired peptide binding to D
b
but not to K
b
molecules. Strikingly, the V-to-A mutation did not change any of the anchor residues, and the dramatic effect on binding was therefore unexpected. The strong decrease in D
b
binding explains why the variant virus escapes the D
b
GP33-43-specific response but still elicits the K
b
-restricted response. These findings also illustrate that mutations within regions encoding overlapping T-cell epitopes can differentially affect the presentation and recognition of individual epitopes.
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