Comparison of hyperpronation and supination‑flexion techniques in children presented to emergency department with painful pronation

Context: Radial head subluxation, also known as ‘pulled elbow’, ‘dislocated elbow’ or ‘nursemaid’s elbow’, is one of the most common upper extremity injuries in young children and a common reason to visit Emergency Department (ED).Aim: To compare supination of the wrist followed by flexion of the elbow (the traditional reduction technique) to hyperpronation of the wrist in the reduction of radial head subluxations (nursemaid’s elbow) maneuvers in children presented to ED with painful pronation and to determine which method is less painful by children.Settings and Design: This prospective randomize study involved a consecutive sampling of children between 1‑5 year old who were presented to the ED with painful pronation.Materials and Methods: The initial procedure was repeated if baseline functioning did not return 20 minutes after the initial reduction attempt. Failure of that technique 30 minutes after the initial reduction attempt resulted in a cross‑over to the alternate method of reduction.Statistical analysis used: Datas were analyzed using SPSS for Windows 16.0. Mean, standard deviation, independent samples t test, Chi‑square test, and paired t test were used in the assessment of pain scores before and after reduction.Results: When pain scores before and after reduction were compared between groups to determine which technique is less painful by children, no significant difference was found between groups.Conclusions: It was found that in the reduction of radial head subluxations, the hyperpronation technique is more effective in children who were presented to ED with painful pronation compared with supination‑flexion. However, there was no significant difference between these techniques in terms of pain.Key words: Child, emergency department, nursemaid’s elbow, pain, pulled elbo

Regularity of the Solutions to SPDEs in Metric Measure Spaces

In this paper we study the regularity of non-linear parabolic PDEs and stochastic PDEs on metric measure spaces admitting heat kernel estimates. In particular we consider mild function solutions to abstract Cauchy problems and show that the unique solution is Hölder continuous in time with values in a suitable fractional Sobolev space. As this analysis is done via a-priori estimates, we can apply this result to stochastic PDEs on metric measure spaces and solve the equation in a pathwise sense for almost all paths. The main example of noise term is of fractional Brownian type and the metric measure spaces can be classical as well as given by various fractal structures. The whole approach is low dimensional and works for spectral dimensions less than 4

Reversible hydration of CH(3)NH(3)Pbl(3) in films, single crystals, and solar cells

Solar cells composed of methylammonium lead iodide perovskite (MAPI) are notorious for their sensitivity to moisture. We show that (i) hydrated crystal phases are formed when MAPI is exposed to water vapor at room temperature and (ii) these phase changes are fully reversed when the material is subsequently dried. The reversible formation of CH3NH3PbI3·H2O followed by (CH3NH3)4PbI6·2H2O (upon long exposure times) was observed using time-resolved XRD and ellipsometry of thin films prepared using “solvent engineering”, single crystals, and state-of-the-art solar cells. In contrast to water vapor, the presence of liquid water results in the irreversible decomposition of MAPI to form PbI2. MAPI changes from dark brown to transparent on hydration; the precise optical constants of CH3NH3PbI3·H2O formed on single crystals were determined, with a bandgap at 3.1 eV. Using the single-crystal optical constants and thin-film ellipsometry measurements, the time-dependent changes to MAPI films exposed to moisture were modeled. The results suggest that the monohydrate phase forms independent of the depth in the film, suggesting rapid transport of water molecules along grain boundaries. Vapor-phase hydration of an unencapsulated solar cell (initially Jsc ≈ 19 mA cm–2 and Voc ≈ 1.05 V at 1 sun) resulted in more than a 90% drop in short-circuit photocurrent and ∼200 mV loss in open-circuit potential; however, these losses were fully reversed after the device was exposed to dry nitrogen for 6 h. Hysteresis in the current–voltage characteristics was significantly increased after this dehydration, which may be related to changes in the defect density and morphology of MAPI following recrystallization from the hydrate. Based on our observations, we suggest that irreversible decomposition of MAPI in the presence of water vapor only occurs significantly once a grain has been fully converted to the monohydrate phase

Interaction imaging with amplitude-dependence force spectroscopy

Knowledge of surface forces is the key to understanding a large number of processes in fields ranging from physics to material science and biology. The most common method to study surfaces is dynamic atomic force microscopy (AFM). Dynamic AFM has been enormously successful in imaging surface topography, even to atomic resolution, but the force between the AFM tip and the surface remains unknown during imaging. Here, we present a new approach that combines high accuracy force measurements and high resolution scanning. The method, called amplitude-dependence force spectroscopy (ADFS) is based on the amplitude-dependence of the cantilever's response near resonance and allows for separate determination of both conservative and dissipative tip-surface interactions. We use ADFS to quantitatively study and map the nano-mechanical interaction between the AFM tip and heterogeneous polymer surfaces. ADFS is compatible with commercial atomic force microscopes and we anticipate its wide-spread use in taking AFM toward quantitative microscopy

Hierarchical Equations of Motion Approach to Quantum Thermodynamics

We present a theoretical framework to investigate quantum thermodynamic processes under non-Markovian system-bath interactions on the basis of the hierarchical equations of motion (HEOM) approach, which is convenient to carry out numerically "exact" calculations. This formalism is valuable because it can be used to treat not only strong system-bath coupling but also system-bath correlation or entanglement, which will be essential to characterize the heat transport between the system and quantum heat baths. Using this formalism, we demonstrated an importance of the thermodynamic effect from the tri-partite correlations (TPC) for a two-level heat transfer model and a three-level autonomous heat engine model under the conditions that the conventional quantum master equation approaches are failed. Our numerical calculations show that TPC contributions, which distinguish the heat current from the energy current, have to be take into account to satisfy the thermodynamic laws.Comment: 9 pages, 4 figures. As a chapter of: F. Binder, L. A. Correa, C. Gogolin, J. Anders, and G. Adesso (eds.), "Thermodynamics in the quantum regime - Recent Progress and Outlook", (Springer International Publishing

Equating scores of the University of Pennsylvania Smell Identification Test and Sniffin' Sticks test in patients with Parkinson's disease

BACKGROUND: Impaired olfaction is an important feature in Parkinson's disease (PD) and other neurological diseases. A variety of smell identification tests exist such as "Sniffin' Sticks" and the University of Pennsylvania Smell Identification Test (UPSIT). An important part of research is being able to replicate findings or combining studies in a meta-analysis. This is difficult if olfaction has been measured using different metrics. We present conversion methods between the: UPSIT, Sniffin' 16, and Brief-SIT (B-SIT); and Sniffin' 12 and Sniffin' 16 odour identification tests. METHODS: We used two incident cohorts of patients with PD who were tested with either the Sniffin' 16 (n = 1131) or UPSIT (n = 980) and a validation dataset of 128 individuals who took both tests. We used the equipercentile and Item Response Theory (IRT) methods to equate the olfaction scales. RESULTS: The equipercentile conversion suggested some bias between UPSIT and Sniffin' 16 tests across the two groups. The IRT method shows very good characteristics between the true and converted Sniffin' 16 (delta mean = 0.14, median = 0) based on UPSIT. The equipercentile conversion between the Sniffin' 12 and 16 item worked well (delta mean = 0.01, median = 0). The UPSIT to B-SIT conversion showed evidence of bias but amongst PD cases worked well (mean delta = -0.08, median = 0). CONCLUSION: We have demonstrated that one can convert UPSIT to B-SIT or Sniffin' 16, and Sniffin' 12 to 16 scores in a valid way. This can facilitate direct comparison between tests aiding future collaborative analyses and evidence synthesis

Latent cluster analysis of ALS phenotypes identifies prognostically differing groups

BACKGROUND Amyotrophic lateral sclerosis (ALS) is a degenerative disease predominantly affecting motor neurons and manifesting as several different phenotypes. Whether these phenotypes correspond to different underlying disease processes is unknown. We used latent cluster analysis to identify groupings of clinical variables in an objective and unbiased way to improve phenotyping for clinical and research purposes. METHODS Latent class cluster analysis was applied to a large database consisting of 1467 records of people with ALS, using discrete variables which can be readily determined at the first clinic appointment. The model was tested for clinical relevance by survival analysis of the phenotypic groupings using the Kaplan-Meier method. RESULTS The best model generated five distinct phenotypic classes that strongly predicted survival (p<0.0001). Eight variables were used for the latent class analysis, but a good estimate of the classification could be obtained using just two variables: site of first symptoms (bulbar or limb) and time from symptom onset to diagnosis (p<0.00001). CONCLUSION The five phenotypic classes identified using latent cluster analysis can predict prognosis. They could be used to stratify patients recruited into clinical trials and generating more homogeneous disease groups for genetic, proteomic and risk factor research

A new multicompartmental reaction-diffusion modeling method links transient membrane attachment of E. coli MinE to E-ring formation

Many important cellular processes are regulated by reaction-diffusion (RD) of molecules that takes place both in the cytoplasm and on the membrane. To model and analyze such multicompartmental processes, we developed a lattice-based Monte Carlo method, Spatiocyte that supports RD in volume and surface compartments at single molecule resolution. Stochasticity in RD and the excluded volume effect brought by intracellular molecular crowding, both of which can significantly affect RD and thus, cellular processes, are also supported. We verified the method by comparing simulation results of diffusion, irreversible and reversible reactions with the predicted analytical and best available numerical solutions. Moreover, to directly compare the localization patterns of molecules in fluorescence microscopy images with simulation, we devised a visualization method that mimics the microphotography process by showing the trajectory of simulated molecules averaged according to the camera exposure time. In the rod-shaped bacterium _Escherichia coli_, the division site is suppressed at the cell poles by periodic pole-to-pole oscillations of the Min proteins (MinC, MinD and MinE) arising from carefully orchestrated RD in both cytoplasm and membrane compartments. Using Spatiocyte we could model and reproduce the _in vivo_ MinDE localization dynamics by accounting for the established properties of MinE. Our results suggest that the MinE ring, which is essential in preventing polar septation, is largely composed of MinE that is transiently attached to the membrane independently after recruited by MinD. Overall, Spatiocyte allows simulation and visualization of complex spatial and reaction-diffusion mediated cellular processes in volumes and surfaces. As we showed, it can potentially provide mechanistic insights otherwise difficult to obtain experimentally

The impact of diabetes on multiple avoidable admissions: a cross-sectional study

Background Multiple admissions for ambulatory care sensitive conditions (ACSC) are responsible for an important proportion of health care expenditures. Diabetes is one of the conditions consensually classified as an ACSC being considered a major public health concern. The aim of this study was to analyse the impact of diabetes on the occurrence of multiple admissions for ACSC. Methods We analysed inpatient data of all public Portuguese NHS hospitals from 2013 to 2015 on multiple admissions for ACSC among adults aged 18 or older. Multiple ACSC users were identified if they had two or more admissions for any ACSC during the period of analysis. Two logistic regression models were computed. A baseline model where a logistic regression was performed to assess the association between multiple admissions and the presence of diabetes, adjusting for age and sex. A full model to test if diabetes had no constant association with multiple admissions by any ACSC across age groups. Results Among 301,334 ACSC admissions, 144,209 (47.9%) were classified as multiple admissions and from those, 59,436 had diabetes diagnosis, which corresponded to 23,692 patients. Patients with diabetes were 1.49 times (p < 0,001) more likely to be admitted multiple times for any ACSC than patients without diabetes. Younger adults with diabetes (18–39 years old) were more likely to become multiple users. Conclusion Diabetes increases the risk of multiple admissions for ACSC, especially in younger adults. Diabetes presence is associated with a higher resource utilization, which highlights the need for the implementation of adequate management of chronic diseases policies.NOVASaudeinfo:eu-repo/semantics/publishedVersio

Voxel-wise comparisons of cellular microstructure and diffusion-MRI in mouse hippocampus using 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND)

A key challenge in medical imaging is determining a precise correspondence between image properties and tissue microstructure. This comparison is hindered by disparate scales and resolutions between medical imaging and histology. We present a new technique, 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND), for registering medical images with 3D histology to overcome these limitations. Ex vivo 120 × 120 × 200 μm resolution diffusion-MRI (dMRI) data was acquired at 7 T from adult C57Bl/6 mouse hippocampus. Tissue was then optically cleared using CLARITY and stained with cellular markers and confocal microscopy used to produce high-resolution images of the 3D-tissue microstructure. For each sample, a dense array of hippocampal landmarks was used to drive registration between upsampled dMRI data and the corresponding confocal images. The cell population in each MRI voxel was determined within hippocampal subregions and compared to MRI-derived metrics. 3D-BOND provided robust voxel-wise, cellular correlates of dMRI data. CA1 pyramidal and dentate gyrus granular layers had significantly different mean diffusivity (p > 0.001), which was related to microstructural features. Overall, mean and radial diffusivity correlated with cell and axon density and fractional anisotropy with astrocyte density, while apparent fibre density correlated negatively with axon density. Astrocytes, axons and blood vessels correlated to tensor orientation