Spectrum of topics for world congresses and other activities of the International Society for Physical and Rehabilitation Medicine (ISPRM) : a first proposal

Background: One of the objectives of the International Society for Physical and Rehabilitation Medicine is to improve the continuity of World Congresses. This requires the development of an abstract topic list for use in congress announcements and abstract submissions. Methods: An abstract topic list was developed on the basis of the definitions of human functioning and rehabilitation research, which define 5 main areas of research (biosciences in rehabilitation, biomedical rehabilitation sciences and engineering, clinical Physical and Rehabilitation Medicine (PRM) sciences, integrative rehabilitation sciences, and human functioning sciences). For the abstract topic list, these research areas were grouped according to the proposals of congress streams. In a second step, the first version of the list was systematically compared with the topics of the 2003 ISPRM World Congress. Results: The resulting comprehensive abstract topic list contains 5 chapters according to the definition of human functioning and rehabilitation research. Due to the high significance of clinical research, clinical PRM sciences were placed at the top of the list, comprising all relevant health conditions treated in PRM services. For congress announcements a short topic list was derived. Discussion: The ISPRM topic list is sustainable and covers a full range of topics. It may be useful for congresses and elsewhere in structuring research in PRM

Identification and prediction of Parkinson's disease subtypes and progression using machine learning in two cohorts.

The clinical manifestations of Parkinson's disease (PD) are characterized by heterogeneity in age at onset, disease duration, rate of progression, and the constellation of motor versus non-motor features. There is an unmet need for the characterization of distinct disease subtypes as well as improved, individualized predictions of the disease course. We used unsupervised and supervised machine learning methods on comprehensive, longitudinal clinical data from the Parkinson's Disease Progression Marker Initiative (n = 294 cases) to identify patient subtypes and to predict disease progression. The resulting models were validated in an independent, clinically well-characterized cohort from the Parkinson's Disease Biomarker Program (n = 263 cases). Our analysis distinguished three distinct disease subtypes with highly predictable progression rates, corresponding to slow, moderate, and fast disease progression. We achieved highly accurate projections of disease progression 5 years after initial diagnosis with an average area under the curve (AUC) of 0.92 (95% CI: 0.95 ± 0.01) for the slower progressing group (PDvec1), 0.87 ± 0.03 for moderate progressors, and 0.95 ± 0.02 for the fast-progressing group (PDvec3). We identified serum neurofilament light as a significant indicator of fast disease progression among other key biomarkers of interest. We replicated these findings in an independent cohort, released the analytical code, and developed models in an open science manner. Our data-driven study provides insights to deconstruct PD heterogeneity. This approach could have immediate implications for clinical trials by improving the detection of significant clinical outcomes. We anticipate that machine learning models will improve patient counseling, clinical trial design, and ultimately individualized patient care

Identification of genes associated with platinum drug sensitivity and resistance in human ovarian cancer cells

Platinum-based chemotherapeutic regimens are ultimately unsuccessful due to intrinsic or acquired drug resistance. Understanding the molecular basis for platinum drug sensitivity/resistance is necessary for the development of new drugs and therapeutic regimens. In an effort to identify such determinants, we evaluated the expression of approximately 4000 genes using cDNA microarray screening in a panel of 14 unrelated human ovarian cancer cell lines derived from patients who were either untreated or treated with platinum-based chemotherapy. These data were analysed relative to the sensitivities of the cells to four platinum drugs (cis-diamminedichloroplatinum (cisplatin), carboplatin, DACH-(oxalato)platinum (II) (oxaliplatin) and cis-diamminedichloro (2-methylpyridine) platinum (II) (AMD473)) as well as the proliferation rate of the cells. Correlation analysis of the microarray data with respect to drug sensitivity and resistance revealed a significant association of Stat1 expression with decreased sensitivity to cisplatin (r=0.65) and AMD473 (r=0.76). These results were confirmed by quantitative RT–PCR and Western blot analyses. To study the functional significance of these findings, the full-length Stat1 cDNA was transfected into drug-sensitive A2780 human ovarian cancer cells. The resulting clones that exhibited increased Stat1 expression were three- to five-fold resistant to cisplatin and AMD473 as compared to the parental cells. The effect of inhibiting Jak/Stat signalling on platinum drug sensitivity was investigated using the Janus kinase inhibitor, AG490. Pretreatment of platinum-resistant cells with AG490 resulted in significant increased sensitivity to AMD473, but not to cisplatin or oxaliplatin. Overall, the results indicate that cDNA microarray analysis may be used successfully to identify determinants of drug sensitivity/resistance and future functional studies of other candidate genes from this database may lead to an increased understanding of the drug resistance phenotype

How achievable are COVID-19 clinical trial recruitment targets? A UK observational cohort study and trials registry analysis

OBJECTIVES: To analyse enrolment to interventional trials during the first wave of the COVID-19 pandemic in England and describe the barriers to successful recruitment in the circumstance of a further wave or future pandemics. DESIGN: We analysed registered interventional COVID-19 trial data and concurrently did a prospective observational study of hospitalised patients with COVID-19 who were being assessed for eligibility to one of the RECOVERY, C19-ACS or SIMPLE trials. SETTING: Interventional COVID-19 trial data were analysed from the clinicaltrials.gov and International Standard Randomized Controlled Trial Number databases on 12 July 2020. The patient cohort was taken from five centres in a respiratory National Institute for Health Research network. Population and modelling data were taken from published reports from the UK government and Medical Research Council Biostatistics Unit. PARTICIPANTS: 2082 consecutive admitted patients with laboratory-confirmed SARS-CoV-2 infection from 27 March 2020 were included. MAIN OUTCOME MEASURES: Proportions enrolled, and reasons for exclusion from the aforementioned trials. Comparisons of trial recruitment targets with estimated feasible recruitment numbers. RESULTS: Analysis of trial registration data for COVID-19 treatment studies enrolling in England showed that by 12 July 2020, 29 142 participants were needed. In the observational study, 430 (20.7%) proceeded to randomisation. 82 (3.9%) declined participation, 699 (33.6%) were excluded on clinical grounds, 363 (17.4%) were medically fit for discharge and 153 (7.3%) were receiving palliative care. With 111 037 people hospitalised with COVID-19 in England by 12 July 2020, we determine that 22 985 people were potentially suitable for trial enrolment. We estimate a UK hospitalisation rate of 2.38%, and that another 1.25 million infections would be required to meet recruitment targets of ongoing trials. CONCLUSIONS: Feasible recruitment rates, study design and proliferation of trials can limit the number, and size, that will successfully complete recruitment. We consider that fewer, more appropriately designed trials, prioritising cooperation between centres would maximise productivity in a further wave

Cluster Lenses

Clusters of galaxies are the most recently assembled, massive, bound structures in the Universe. As predicted by General Relativity, given their masses, clusters strongly deform space-time in their vicinity. Clusters act as some of the most powerful gravitational lenses in the Universe. Light rays traversing through clusters from distant sources are hence deflected, and the resulting images of these distant objects therefore appear distorted and magnified. Lensing by clusters occurs in two regimes, each with unique observational signatures. The strong lensing regime is characterized by effects readily seen by eye, namely, the production of giant arcs, multiple-images, and arclets. The weak lensing regime is characterized by small deformations in the shapes of background galaxies only detectable statistically. Cluster lenses have been exploited successfully to address several important current questions in cosmology: (i) the study of the lens(es) - understanding cluster mass distributions and issues pertaining to cluster formation and evolution, as well as constraining the nature of dark matter; (ii) the study of the lensed objects - probing the properties of the background lensed galaxy population - which is statistically at higher redshifts and of lower intrinsic luminosity thus enabling the probing of galaxy formation at the earliest times right up to the Dark Ages; and (iii) the study of the geometry of the Universe - as the strength of lensing depends on the ratios of angular diameter distances between the lens, source and observer, lens deflections are sensitive to the value of cosmological parameters and offer a powerful geometric tool to probe Dark Energy. In this review, we present the basics of cluster lensing and provide a current status report of the field.Comment: About 120 pages - Published in Open Access at: http://www.springerlink.com/content/j183018170485723/ . arXiv admin note: text overlap with arXiv:astro-ph/0504478 and arXiv:1003.3674 by other author

Resonant Photonic States in Coupled Heterostructure Photonic Crystal Waveguides

In this paper, we study the photonic resonance states and transmission spectra of coupled waveguides made from heterostructure photonic crystals. We consider photonic crystal waveguides made from three photonic crystals A, B and C, where the waveguide heterostructure is denoted as B/A/C/A/B. Due to the band structure engineering, light is confined within crystal A, which thus act as waveguides. Here, photonic crystal C is taken as a nonlinear photonic crystal, which has a band gap that may be modified by applying a pump laser. We have found that the number of bound states within the waveguides depends on the width and well depth of photonic crystal A. It has also been found that when both waveguides are far away from each other, the energies of bound photons in each of the waveguides are degenerate. However, when they are brought close to each other, the degeneracy of the bound states is removed due to the coupling between them, which causes these states to split into pairs. We have also investigated the effect of the pump field on photonic crystal C. We have shown that by applying a pump field, the system may be switched between a double waveguide to a single waveguide, which effectively turns on or off the coupling between degenerate states. This reveals interesting results that can be applied to develop new types of nanophotonic devices such as nano-switches and nano-transistors

A Search for Dark Higgs Bosons

Recent astrophysical and terrestrial experiments have motivated the proposal of a dark sector with GeV-scale gauge boson force carriers and new Higgs bosons. We present a search for a dark Higgs boson using 516 fb-1 of data collected with the BABAR detector. We do not observe a significant signal and we set 90% confidence level upper limits on the product of the Standard Model-dark sector mixing angle and the dark sector coupling constant.Comment: 7 pages, 5 postscript figures, published version with improved plots for b/w printin

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

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