Cognitive behavioural therapy (CBT) for anxiety in people with dementia: study protocol for a randomised controlled trial

Background Many people with dementia experience anxiety, which can lead to decreased independence, relationship difficulties and increased admittance to care homes. Anxiety is often treated with antipsychotic medication, which has limited efficacy and serious side effects. Cognitive behavioural therapy (CBT) is widely used to treat anxiety in a range of populations, yet no RCTs on CBT for anxiety in dementia exist. This study aims to develop a CBT for anxiety in dementia manual and to determine its feasibility in a pilot RCT. Methods/design Phase I involves the development of a CBT for anxiety in dementia manual, through a process of (1) focus groups, (2) comprehensive literature reviews, (3) expert consultation, (4) a consensus conference and (5) field testing. Phase II involves the evaluation of the manual with 50 participants with mild to moderate dementia and anxiety (and their carers) in a pilot, two-armed RCT. Participants will receive either ten sessions of CBT or treatment as usual. Primary outcome measures are anxiety and costs. Secondary outcome measures are participant quality of life, behavioural disturbance, cognition, depression, mood and perceived relationship with the carer, and carer mood and perceived relationship with the person with dementia. Measures will be administered at baseline, 15 weeks and 6 months. Approximately 12 qualitative interviews will be used to gather service-users' perspectives on the intervention. Discussion This study aims to determine the feasibility of CBT for people with anxiety and dementia and provide data on the effect size of the intervention in order to conduct a power analysis for a definitive RCT. The manual will be revised according to qualitative and quantitative findings. Its publication will enable its availability throughout the NHS and beyond. Trial registration ISRCTN6480685

Strengthening the Reporting of Observational Studies in Epidemiology for Newborn Infection (STROBE-NI): an extension of the STROBE statement for neonatal infection research.

Neonatal infections are estimated to account for a quarter of the 2·8 million annual neonatal deaths, as well as approximately 3% of all disability-adjusted life-years. Despite this burden, few data are available on incidence, aetiology, and outcomes, particularly regarding impairment. We aimed to develop guidelines for improved scientific reporting of observational neonatal infection studies, to increase comparability and to strengthen research in this area. This checklist, Strengthening the Reporting of Observational Studies in Epidemiology for Newborn Infection (STROBE- NI), is an extension of the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) statement. STROBE-NI was developed following systematic reviews of published literature (1996-2015), compilation of more than 130 potential reporting recommendations, and circulation of a survey to relevant professionals worldwide, eliciting responses from 147 professionals from 37 countries. An international consensus meeting of 18 participants (with expertise in infectious diseases, neonatology, microbiology, epidemiology, and statistics) identified priority recommendations for reporting, additional to the STROBE statement. Implementation of these STROBE-NI recommendations, and linked checklist, aims to improve scientific reporting of neonatal infection studies, increasing data utility and allowing meta-analyses and pathogen-specific burden estimates to inform global policy and new interventions, including maternal vaccines

Streptococcus pneumoniae Serotype-2 Childhood Meningitis in Bangladesh: A Newly Recognized Pneumococcal Infection Threat

BACKGROUND: Streptococcus pneumoniae is a leading cause of meningitis in countries where pneumococcal conjugate vaccines (PCV) targeting commonly occurring serotypes are not routinely used. However, effectiveness of PCV would be jeopardized by emergence of invasive pneumococcal diseases (IPD) caused by serotypes which are not included in PCV. Systematic hospital based surveillance in Bangladesh was established and progressively improved to determine the pathogens causing childhood sepsis and meningitis. This also provided the foundation for determining the spectrum of serotypes causing IPD. This article reports an unprecedented upsurge of serotype 2, an uncommon pneumococcal serotype, without any known intervention. METHODS AND FINDINGS: Cases with suspected IPD had blood or cerebrospinal fluid (CSF) collected from the beginning of 2001 till 2009. Pneumococcal serotypes were determined by capsular swelling of isolates or PCR of culture-negative CSF specimens. Multicenter national surveillance, expanded from 2004, identified 45,437 patients with suspected bacteremia who were blood cultured and 10,618 suspected meningitis cases who had a lumber puncture. Pneumococcus accounted for 230 culture positive cases of meningitis in children <5 years. Serotype-2 was the leading cause of pneumococcal meningitis, accounting for 20.4% (45/221; 95% CI 15%-26%) of cases. Ninety eight percent (45/46) of these serotype-2 strains were isolated from meningitis cases, yielding the highest serotype-specific odds ratio for meningitis (29.6; 95% CI 3.4-256.3). The serotype-2 strains had three closely related pulsed field gel electrophoresis types. CONCLUSIONS: S. pneumoniae serotype-2 was found to possess an unusually high potential for causing meningitis and was the leading serotype-specific cause of childhood meningitis in Bangladesh over the past decade. Persisting disease occurrence or progressive spread would represent a major potential infection threat since serotype-2 is not included in PCVs currently licensed or under development

Non-linear Autoregressive Neural Networks to Forecast Short-Term Solar Radiation for Photovoltaic Energy Predictions

Nowadays, green energy is considered as a viable solution to hinder CO2 emissions and greenhouse effects. Indeed, it is expected that Renewable Energy Sources (RES) will cover 40% of the total energy request by 2040. This will move forward decentralized and cooperative power distribution systems also called smart grids. Among RES, solar energy will play a crucial role. However, reliable models and tools are needed to forecast and estimate with a good accuracy the renewable energy production in short-term time periods. These tools will unlock new services for smart grid management. In this paper, we propose an innovative methodology for implementing two different non-linear autoregressive neural networks to forecast Global Horizontal Solar Irradiance (GHI) in short-term time periods (i.e. from future 15 to 120min). Both neural networks have been implemented, trained and validated exploiting a dataset consisting of four years of solar radiation values collected by a real weather station. We also present the experimental results discussing and comparing the accuracy of both neural networks. Then, the resulting GHI forecast is given as input to a Photovoltaic simulator to predict energy production in short-term time periods. Finally, we present the results of this Photovoltaic energy estimation discussing also their accuracy

Characterization of ductal and lobular breast carcinomas using novel prolactin receptor isoform specific antibodies

<p>Abstract</p> <p>Background</p> <p>Prolactin is a polypeptide hormone responsible for proliferation and differentiation of the mammary gland. More recently, prolactin's role in mammary carcinogenesis has been studied with greater interest. Studies from our laboratory and from others have demonstrated that three specific isoforms of the prolactin receptor (PRLR) are expressed in both normal and cancerous breast cells and tissues. Until now, reliable isoform specific antibodies have been lacking. We have prepared and characterized polyclonal antibodies against each of the human PRLR isoforms that can effectively be used to characterize human breast cancers.</p> <p>Methods</p> <p>Rabbits were immunized with synthetic peptides of isoform unique regions and immune sera affinity purified prior to validation by Western blot and immunohistochemical analyses. Sections of ductal and lobular carcinomas were stained with each affinity purified isoform specific antibody to determine expression patterns in breast cancer subclasses.</p> <p>Results</p> <p>We show that the rabbit antibodies have high titer and could specifically recognize each isoform of PRLR. Differences in PRLR isoform expression levels were observed and quantified using histosections from xenografts of established human breast cancer cells lines, and ductal and lobular carcinoma human biopsy specimens. In addition, these results were verified by real-time PCR with isoform specific primers. While nearly all tumors contained LF and SF1b, the majority (76%) of ductal carcinoma biopsies expressed SF1a while the majority of lobular carcinomas lacked SF1a staining (72%) and 27% had only low levels of expression.</p> <p>Conclusions</p> <p>Differences in the receptor isoform expression profiles may be critical to understanding the role of PRL in mammary tumorigenesis. Since these antibodies are specifically directed against each PRLR isoform, they are valuable tools for the evaluation of breast cancer PRLR content and have potential clinical importance in treatment of this disease by providing new reagents to study the protein expression of the human PRLR.</p

Precise measurement of the W-boson mass with the CDF II detector

We have measured the W-boson mass MW using data corresponding to 2.2/fb of integrated luminosity collected in proton-antiproton collisions at 1.96 TeV with the CDF II detector at the Fermilab Tevatron collider. Samples consisting of 470126 W->enu candidates and 624708 W->munu candidates yield the measurement MW = 80387 +- 12 (stat) +- 15 (syst) = 80387 +- 19 MeV. This is the most precise measurement of the W-boson mass to date and significantly exceeds the precision of all previous measurements combined

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

X-ray emission from the Sombrero galaxy: discrete sources

We present a study of discrete X-ray sources in and around the bulge-dominated, massive Sa galaxy, Sombrero (M104), based on new and archival Chandra observations with a total exposure of ~200 ks. With a detection limit of L_X = 1E37 erg/s and a field of view covering a galactocentric radius of ~30 kpc (11.5 arcminute), 383 sources are detected. Cross-correlation with Spitler et al.'s catalogue of Sombrero globular clusters (GCs) identified from HST/ACS observations reveals 41 X-rays sources in GCs, presumably low-mass X-ray binaries (LMXBs). We quantify the differential luminosity functions (LFs) for both the detected GC and field LMXBs, whose power-low indices (~1.1 for the GC-LF and ~1.6 for field-LF) are consistent with previous studies for elliptical galaxies. With precise sky positions of the GCs without a detected X-ray source, we further quantify, through a fluctuation analysis, the GC LF at fainter luminosities down to 1E35 erg/s. The derived index rules out a faint-end slope flatter than 1.1 at a 2 sigma significance, contrary to recent findings in several elliptical galaxies and the bulge of M31. On the other hand, the 2-6 keV unresolved emission places a tight constraint on the field LF, implying a flattened index of ~1.0 below 1E37 erg/s. We also detect 101 sources in the halo of Sombrero. The presence of these sources cannot be interpreted as galactic LMXBs whose spatial distribution empirically follows the starlight. Their number is also higher than the expected number of cosmic AGNs (52+/-11 [1 sigma]) whose surface density is constrained by deep X-ray surveys. We suggest that either the cosmic X-ray background is unusually high in the direction of Sombrero, or a distinct population of X-ray sources is present in the halo of Sombrero.Comment: 11 figures, 5 tables, ApJ in pres