Midfoot osteoarthritis: potential phenotypes and their associations with demographic, symptomatic and clinical characteristics

Objective: To investigate the demographic, symptomatic, clinical and structural foot characteristics associated with potential phenotypes of midfoot osteoarthritis (OA). Design: Cross-sectional study of 533 community-dwelling adults aged ≥50 years with foot pain in the past year. Health questionnaires and clinical assessments of symptoms, foot structure and function were undertaken. Potential midfoot OA phenotypes were defined by the pattern of radiographic joint involvement affecting either the medial midfoot (talonavicular, navicular-1 st cuneiform, or cuneiform-1 st metatarsal joint), central midfoot (2 nd cuneiform-metatarsal joint), or both medial and central midfoot joints. Multivariable regression models with generalised estimating equations were used to investigate the associations between patterns of midfoot joint involvement and symptomatic, clinical and structural characteristics compared to those with no or minimal midfoot OA. Results: Of 879 eligible feet, 168 had medial midfoot OA, 103 central midfoot OA, 76 both medial and central midfoot OA and 532 no/minimal OA. Having both medial and central midfoot OA was associated with higher pain scores, dorsally-located midfoot pain (OR 2.54, 95%CI 1.45, 4.45), hallux valgus (OR 1.76, 95%CI 1.02, 3.05), flatter foot posture (β 0.44, 95%CI 0.12, 0.77), lower medial arch height (β 0.02, 95%CI 0.01, 0.03) and less subtalar inversion and 1 st MTPJ dorsiflexion. Isolated medial midfoot OA and central midfoot OA had few distinguishing clinical characteristics. Conclusions: Distinct phenotypes of midfoot OA appear challenging to identify, with substantial overlap in symptoms and clinical characteristics. Phenotypic differences in symptoms, foot posture and function were apparent in this study only when both the medial and central midfoot were involved

Long-range temporal correlations in scale-free neuromorphic networks

© 2020 Massachusetts Institute of Technology. Biological neuronal networks are the computing engines of the mammalian brain. These networks exhibit structural characteristics such as hierarchical architectures, small-world attributes, and scale-free topologies, providing the basis for the emergence of rich temporal characteristics such as scale-free dynamics and long-range temporal correlations. Devices that have both the topological and the temporal features of a neuronal network would be a significant step toward constructing a neuromorphic system that can emulate the computational ability and energy efficiency of the human brain. Here we use numerical simulations to show that percolating networks of nanoparticles exhibit structural properties that are reminiscent of biological neuronal networks, and then show experimentally that stimulation of percolating networks by an external voltage stimulus produces temporal dynamics that are self-similar, follow power-law scaling, and exhibit long-range temporal correlations. These results are expected to have important implications for the development of neuromorphic devices, especially for those based on the concept of reservoir computing

The optical microscopy with virtual image breaks a record: 50-nm resolution imaging is demonstrated

We demonstrate a new 'microsphere nanoscope' that uses ordinary SiO2 microspheres as superlenses to create a virtual image of the object in near field. The magnified virtual image greatly overcomes the diffraction limit. We are able to resolve clearly 50-nm objects under a standard white light source in both transmission and reflection modes. The resolution achieved for white light opens a new opportunity to image viruses, DNA and molecules in real time

Atomic Scale Dynamics Drive Brain-like Avalanches in Percolating Nanostructured Networks.

Self-assembled networks of nanoparticles and nanowires have recently emerged as promising systems for brain-like computation. Here, we focus on percolating networks of nanoparticles which exhibit brain-like dynamics. We use a combination of experiments and simulations to show that the brain-like network dynamics emerge from atomic-scale switching dynamics inside tunnel gaps that are distributed throughout the network. The atomic-scale dynamics emulate leaky integrate and fire (LIF) mechanisms in biological neurons, leading to the generation of critical avalanches of signals. These avalanches are quantitatively the same as those observed in cortical tissue and are signatures of the correlations that are required for computation. We show that the avalanches are associated with dynamical restructuring of the networks which self-tune to balanced states consistent with self-organized criticality. Our simulations allow visualization of the network states and detailed mechanisms of signal propagation

Formulation and performance of variational integrators for rotating bodies

Variational integrators are obtained for two mechanical systems whose configuration spaces are, respectively, the rotation group and the unit sphere. In the first case, an integration algorithm is presented for Euler’s equations of the free rigid body, following the ideas of Marsden et al. (Nonlinearity 12:1647–1662, 1999). In the second example, a variational time integrator is formulated for the rigid dumbbell. Both methods are formulated directly on their nonlinear configuration spaces, without using Lagrange multipliers. They are one-step, second order methods which show exact conservation of a discrete angular momentum which is identified in each case. Numerical examples illustrate their properties and compare them with existing integrators of the literature

Switchable pi-coordination and C-H metallation in small-cavity macrocyclic uranium and thorium complexes

New, conformationally restricted ThIV and UIV complexes, [ThCl2(L)] and [UI2(L)], of the small-cavity, dipyrrolide, dianionic macrocycle trans-calix[2]benzene[2]pyrrolide (L)2− are reported and are shown to have unusual κ5:κ5 binding in a bent metallocene-type structure. Single-electron reduction of [UI2(L)] affords [UI(THF)(L)] and results in a switch in ligand binding from κ5-pyrrolide to η6-arene sandwich coordination, demonstrating the preference for arene binding by the electron-rich UIII ion. Facile loss of THF from [UI(THF)(L)] further increases the amount of U–arene back donation. [UI(L)] can incorporate a further UIII equivalent, UI3, to form the very unusual dinuclear complex [U2I4(L)] in which the single macrocycle adopts both κ5:κ5 and η6:κ1:η6:κ1 binding modes in the same complex. Hybrid density functional theory calculations carried out to compare the electronic structures and bonding of [UIIII(L)] and [UIII2I4(L)] indicate increased contributions to the covalent bonding in [U2I4(L)] than in [UI(L)], and similar U–arene interactions in both. MO analysis and QTAIM calculations find minimal U–U interaction in [U2I4(L)]. In contrast to the reducible U complex, treatment of [ThCl2(L)] with either a reductant or non-nucleophilic base results in metallation of the aryl rings of the macrocycle to form the (L−2H)4− tetraanion and two new and robust Th–C bonds in the –ate complexes [K(THF)2ThIV(μ-Cl)(L−2H)]2 and K[ThIV{N(SiMe3)2}(L−2H)]

Next-to-leading order QCD corrections to Higgs boson production in association with a photon via weak-boson fusion at the LHC

Higgs boson production in association with a hard central photon and two forward tagging jets is expected to provide valuable information on Higgs boson couplings in a range where it is difficult to disentangle weak-boson fusion processes from large QCD backgrounds. We present next-to-leading order QCD corrections to Higgs production in association with a photon via weak-boson fusion at a hadron collider in the form of a flexible parton-level Monte Carlo program. The QCD corrections to integrated cross sections are found to be small for experimentally relevant selection cuts, while the shape of kinematic distributions can be distorted by up to 20% in some regions of phase space. Residual scale uncertainties at next-to-leading order are at the few-percent level.Comment: 17 pages, 7 figures, 1 tabl

Neuroimaging of Inflammation in Memory and Related Other Disorders (NIMROD) study protocol: a deep phenotyping cohort study of the role of brain inflammation in dementia, depression and other neurological illnesses

$\textit{Introduction}$ Inflammation of the central nervous system is increasingly regarded as having a role in cognitive disorders such as dementia and depression, but it is not clear how such neuroinflammation relates to other aspects of neuropathology (e.g., tau and amyloid pathology) as well as to structural and functional changes in the brain and symptoms (as assessed via MRI and clinical and neuropsychological assessment). This study will explore these pathophysiological mechanisms using positron emission tomography (PET) which allows $\textit{in vivo}$ imaging of inflammation, amyloid and tau deposition, together with neuropsychological profiling, magnetic resonance imaging (MRI) and peripheral biomarker analysis. \textit{Methods & analysis} Using PET imaging of the ligand [11C]PK11195 we will test for increased neuroinflammation $\textit{in vivo}$ in patients with Alzheimer’s disease, Lewy body dementia, frontotemporal dementia, progressive supranuclear palsy, late onset depression and mild cognitive impairment, when compared to healthy controls. We will assess whether areas of inflammatory change are associated with amyloid and tau deposition (assessed using $^{11}$C-labelled Pittsburgh Compound B ([$^{11}$C]PiB) and $^{18}$F-labelled AV-1451 respectively), as well as structural and functional connectivity changes found on MRI. Inflammatory biomarker analysis and immune-phenotyping of peripheral blood monocytes will determine the correlation between central (i.e., neural) and peripheral inflammation. Finally, we will examine whether neuroinflammatory changes seen on PET imaging are associated with global and domain specific cognitive impairments, or predict cognitive decline over 12 months. \textit{Ethics & dissemination} The study protocol was approved by the local ethics committee, East of England - Cambridge Central Research Ethics Committee (reference: 13/EE/0104). The study is also ARSAC approved as part of this process. Data will be disseminated by presentation at national and international conferences and by publication, predominantly in journals of neuroscience as well as clinical neurology and psychiatry. $\textit{Strengths}$ Multimodal deep phenotyping Comparisons between diseases as well as with controls Longitudinal neuropsychology data Comparison of central and peripheral inflammation $\textit{Weaknesses}$ Lack of longitudinal neuroimaging Not a prospective study, unable to assess causationThe study is funded by the UK National Institute of Health Research Cambridge Biomedical Research Unit in Dementia (Project 4 - RNAG/293). JBR is supported by the Wellcome Trust (103838). JPC is supported by the UK National Institute of Health Research Biomedical Research Centre at Cambridge. PVR is supported by the PSP Association

Impact of the June 2018 Saddleworth Moor wildfires on air quality in northern England

The June 2018 Saddleworth Moor fires were some of the largest UK wildfires on record and lasted for approximately three weeks. They emitted large quantities of smoke, trace gases and aerosols which were transported downwind over the highly populated regions of Manchester and Liverpool. Surface observations of PM2.5 indicate that concentrations were 4–5.5 times higher than the recent seasonal average. State-of-the-art satellite measurements of total column carbon monoxide (TCCO) from the TROPOMI instrument on the Sentinel 5—Precursor (S5P) platform, coupled with measurements from a flight of the UK BAe-146–301 research aircraft, are used to quantify the substantial enhancement in emitted trace gases. The aircraft measured plume enhancements with near-fire CO and PM2.5 concentrations >1500 ppbv and >125 μg m−3 (compared to ~100 ppbv and ~5 μg m−3 background concentrations). Downwind fire-plume ozone (O3) values were larger than the near-fire location, indicating O3 production with distance from source. The near-fire O3:CO ratio was (ΔO3/ΔCO) 0.001 ppbv/ppbv, increasing downwind to 0.060–0.105 ppbv/ppbv, suggestive of O3 production enhancement downwind of the fires. Emission rates of CO and CO2 ranged between 1.07 (0.07–4.69) kg s−1 and 13.7 (1.73–50.1) kg s−1, respectively, similar to values expected from a medium sized power station

Infantile zinc deficiency: Association with autism spectrum disorders

Elucidation of the pathogenesis and effective treatment of autism spectrum disorders is one of the challenges today. In this study, we examine hair zinc concentrations for 1,967 children with autistic disorders (1,553 males and 414 females), and show considerable association with zinc deficiency. Histogram of hair zinc concentration was non-symmetric with tailing in lower range, and 584 subjects were found to have lower zinc concentrations than −2 standard deviation level of its reference range (86.3–193ppm). The incidence rate of zinc deficiency in infant group aged 0–3 year-old was estimated 43.5 % in male and 52.5 % in female. The lowest zinc concentration of 10.7 ppm was detected in a 2-year-old boy, corresponding to about 1/12 of the control mean level. These findings suggest that infantile zinc deficiency may epigenetically contribute to the pathogenesis of autism and nutritional approach may yield a novel hope for its treatment and prevention