Predictive value of fear avoidance in developing chronic neck pain disability: consequences for clinical decision making

Objective\ud To improve clinical decision making in posttraumatic neck pain by investigating the additional value of fear-avoidance variables in predicting chronic neck pain disability.\ud \ud Design\ud An inception cohort with baseline assessment 1 week posttrauma and outcome assessment 24 weeks posttrauma. Predictive factors include pain intensity, Neck Disability Index (NDI), catastrophizing, fear of movement (Tampa Scale for Kinesiophobia [TSK]), and avoidance muscle behavior.\ud \ud Setting\ud Hospital emergency department of a general hospital.\ud \ud Participants\ud A consecutive sample of 90 people reporting of pain in neck or head region after a motor vehicle collision. Eighty-two subjects (91.1%) of the sample provided 24-week follow-up on the outcome.\ud \ud Interventions\ud Not applicable.\ud \ud Main outcome measure\ud The NDI assessing physical disability of subjects with neck pain.\ud \ud Results\ud By using a combination of the baseline NDI and TSK, it appears to be possible to predict chronic disability with a probability of 54.3% (95% confidence interval [CI], 35.2%–72.3%) after entering the NDI (cutoff, 15) as a first test, and with a probability of 83.3% (95% CI, 70.3%–91.3%) after entering the TSK (cutoff, 40) in a second test.\ud \ud Conclusions\ud A simple rating of baseline neck pain disability within a week of the trauma, separately or in combination with a test for fear of movement, can be used to predict future outcome. Patients showing fear of movement can be offered an intervention that focuses on reduction of this fear.\ud \u

The type I interferon signature in leukocyte subsets from peripheral blood of patients with early arthritis: a major contribution by granulocytes

The type I interferon (IFN) signature in rheumatoid arthritis (RA) has shown clinical relevance in relation to disease onset and therapeutic response. Identification of the cell type(s) contributing to this IFN signature could provide insight into the signature's functional consequences. The aim of this study was to investigate the contribution of peripheral leukocyte subsets to the IFN signature in early arthritis. Blood was collected from 26 patients with early arthritis and lysed directly or separated into peripheral blood mononuclear cells (PBMCs) and polymorphonuclear granulocytes (PMNs). PBMCs were sorted into CD4(+) T cells, CD8(+) T cells, CD19(+) B cells, and CD14(+) monocytes by flow cytometry. Messenger RNA expression of three interferon response genes (IRGs RSAD2, IFI44L, and MX1) and type I interferon receptors (IFNAR1 and IFNAR2) was determined in whole blood and blood cell subsets by quantitative polymerase chain reaction. IRG expression was averaged to calculate an IFN score for each sample. Patients were designated "IFN(high)" (n = 8) or "IFN(low)" (n = 18) on the basis of an IFN score cutoff in whole peripheral blood from healthy control subjects. The difference in IFN score between IFN(high) and IFN(low) patients was remarkably large for the PMN fraction (mean 25-fold) compared with the other subsets (mean 6- to 9-fold), indicating that PMNs are the main inducers of IRGs. Moreover, the relative contribution of the PMN fraction to the whole-blood IFN score was threefold higher than expected from its abundance in blood (p = 0.008), whereas it was three- to sixfold lower for the other subsets (p ≤ 0.063), implying that the PMNs are most sensitive to IFN signaling. Concordantly, IFNAR1 and IFNAR2 were upregulated compared with healthy controls selectively in patient PMNs (p ≤ 0.0077) but not in PBMCs. PMNs are the main contributors to the whole-blood type I IFN signature in patients with early arthritis, which seems due to increased sensitivity of these cells to type I IFN signaling. Considering the well-established role of neutrophils in the pathology of arthritis, this suggests a role of type I IFN activity in the disease as wel

MicroRNAs differentially present in the plasma of HIV elite controllers reduce HIV infection in vitro

Elite controllers maintain HIV-1 viral loads below the limit of detection. The mechanisms responsible for this phenomenon are poorly understood. As microRNAs (miRNAs) are regulators of gene expression and some of them modulate HIV infection, we have studied the miRNA profile in plasma from HIV elite controllers and chronically infected individuals and compared against healthy donors. Several miRNAs correlate with CD41 T cell count or with the known time of infection. No significant differences were observed between elite controllers and healthy donors; however, 16 miRNAs were different in the plasma of chronic infected versus healthy donors. In addition, levels of hsa-miR-29b-3p, hsa-miR-33a-5p and hsa-miR-146a-5p were higher in plasma from elite controllers than chronic infected and hsa-miR-29b-3p and hsa-miR-33a-5p overexpression significantly reduced the viral production in MT2 and primary T CD41 cells. Therefore, levels of circulating miRNAs might be of diagnostic and/or prognostic value for HIV infection, and hsa-miR-29b-3p and miR-33a-5p may contribute to the design of new anti-HIV drugs.Fil: Reynoso, Rita Paola. University of Natural Resources and Life Sciences; AustriaFil: Laufer, Natalia Lorna. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas en Retrovirus y Sida. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas en Retrovirus y Sida; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Juan A. Fernández"; Argentina. Universidad de Buenos Aires; ArgentinaFil: Hackl, Matthias. University of Natural Resources and Life Sciences; Austria. Tamirna Gmbh; AustriaFil: Skalicky, Susanna. Evercyte Gmbh; AustriaFil: Monteforte, Rossella. University of Natural Resources and Life Sciences; AustriaFil: Turk, Gabriela Julia Ana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas en Retrovirus y Sida. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas en Retrovirus y Sida; Argentina. Universidad de Buenos Aires; ArgentinaFil: Carobene, Mauricio. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas en Retrovirus y Sida. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas en Retrovirus y Sida; ArgentinaFil: Quarleri, Jorge Fabian. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas en Retrovirus y Sida. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas en Retrovirus y Sida; ArgentinaFil: Cahn, Pedro. Fundación Huésped; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Juan A. Fernández"; ArgentinaFil: Werner, Roland. Medizinische Universitat Innsbruck; AustriaFil: Stoiber, Heribert. Medizinische Univesitat Innsbruck; AustriaFil: Grillari Voglauer, Regina. University of Natural Resources and Life Sciences; Austria. Evercyte Gmbh; AustriaFil: Grillari, Johannes. University of Natural Resources and Life Sciences; Austria. Evercyte Gmbh; Austri

The Immigration Laws and Policy in the United States of America

Figure S3. Line plot of the absolute number of cells per lymphocyte subset in 68 non-converting and 17 converting patients with arthralgia. The non-converting patients are depicted from the time point of inclusion. The converting patients are depicted from the time point of conversion and the time before conversion. (TIF 1784 kb

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

The Large Hadron-Electron Collider at the HL-LHC

The Large Hadron-Electron Collider (LHeC) is designed to move the field of deep inelastic scattering (DIS) to the energy and intensity frontier of particle physics. Exploiting energy-recovery technology, it collides a novel, intense electron beam with a proton or ion beam from the High-Luminosity Large Hadron Collider (HL-LHC). The accelerator and interaction region are designed for concurrent electron-proton and proton-proton operations. This report represents an update to the LHeC's conceptual design report (CDR), published in 2012. It comprises new results on the parton structure of the proton and heavier nuclei, QCD dynamics, and electroweak and top-quark physics. It is shown how the LHeC will open a new chapter of nuclear particle physics by extending the accessible kinematic range of lepton-nucleus scattering by several orders of magnitude. Due to its enhanced luminosity and large energy and the cleanliness of the final hadronic states, the LHeC has a strong Higgs physics programme and its own discovery potential for new physics. Building on the 2012 CDR, this report contains a detailed updated design for the energy-recovery electron linac (ERL), including a new lattice, magnet and superconducting radio-frequency technology, and further components. Challenges of energy recovery are described, and the lower-energy, high-current, three-turn ERL facility, PERLE at Orsay, is presented, which uses the LHeC characteristics serving as a development facility for the design and operation of the LHeC. An updated detector design is presented corresponding to the acceptance, resolution, and calibration goals that arise from the Higgs and parton-density-function physics programmes. This paper also presents novel results for the Future Circular Collider in electron-hadron (FCC-eh) mode, which utilises the same ERL technology to further extend the reach of DIS to even higher centre-of-mass energies.Peer reviewe

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Recognition of patients with medically unexplained physical symptoms by family physicians: results of a focus group study

BACKGROUND: Patients with medically unexplained physical symptoms (MUPS) form a heterogeneous group and frequently attend their family physician (FP). Little is known about how FPs recognize MUPS in their patients. We conducted a focus group study to explore how FPs recognize MUPS and whether they recognize specific subgroups of patients with MUPS. Targeting such subgroups might improve treatment outcomes. METHODS: Six focus groups were conducted with in total 29 Dutch FPs. Two researchers independently analysed the data applying the principles of constant comparative analysis in order to detect characteristics to recognize MUPS and to synthesize subgroups. RESULTS: FPs take into account various characteristics when recognizing MUPS in their patients. More objective characteristics were multiple MUPS, frequent and long consultations and many referrals. Subjective characteristics were negative feelings towards patients and the feeling that the FP cannot make sense of the patient's story. Experience of the FP, affinity with MUPS, consultation skills, knowledge of the patient's context and the doctor-patient relationship seemed to influence how and to what extent these characteristics play a role. Based on the perceptions of the FPs we were able to distinguish five subgroups of patients according to FPs: 1) the anxious MUPS patient, 2) the unhappy MUPS patient, 3) the passive MUPS patient, 4) the distressed MUPS patient, and 5) the puzzled MUPS patient. These subgroups were not mutually exclusive, but were based on how explicit and predominant certain characteristics were perceived by FPs. CONCLUSIONS: FPs believe that they can properly identify MUPS in their patients during consultations and five distinct subgroups of patients could be distinguished. If these subgroups can be confirmed in further research, personalized treatment strategies can be developed and tested for their effectiveness