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Abstract Understanding the association between dipstick-detected proteinuria and oculomotor cranial nerve palsy (CNP) could have significant implications for understanding the mechanism of CNP development and for developing preventive strategies against CNP development in patients with proteinuria. This study aimed to determine the relationship between dipstick-determined proteinuria and ocular motor CNP using National Sample Cohort (NSC) database from Korea’s National Health Insurance Service (NHIS). A nationwide population-based cohort study was conducted using data from the NSC database of Korea’s NHIS. These data were collected from 2009 to 2018. A one-year time lag was established to prevent a situation in which the causal link was inverted. Participants aged 20 years or more who were diagnosed with proteinuria in 2009 were included. Individuals with specific pre-existing CNP, missing data, and those who were newly diagnosed with CNP or who died within one year of being tested were excluded. The study population was classified into six groups according to the degree of proteinuria (negative, trace, or between 1 + and 4 +) based on the urine dipstick test. A Cox proportional hazard regression analysis was performed to determine the linkage between the degree of proteinuria and ocular motor CNP. A total of 5,807 (0.14% of subjects) with ocular motor CNP were assigned to the ocular motor CNP group and 4,047,205 subjects were assigned to the control group. After full adjustment of comorbidities, hazard ratios (HRs) for 1 + , 2 + , 3 + and 4 + proteinuria groups were 1.449 (95% confidence interval [CI] 1.244–1.687), 2.081 (1.707–2.538), 1.96 (1.322–2.904), and 3.011 (1.507–6.014), respectively, for developing ocular motor CNP compared to the proteinuria-negative group. In subgroup analysis, the HR of patients with proteinuria for the development of ocular motor CNP was higher in the younger age group (less than 40 years) (P = 0.0242) and the group with DM (P = 0.04). Our population-based cohort study demonstrated a significant association between proteinuria and the incidence of CNP, suggesting that urine protein level could be a new clinical marker for predicting the development of CNP.

Abstract Introduction Otoscopes and otomicroscopes are the most commonly used instruments for visualizing the ear. Digital otoscopy (DO) could be used to improve diagnostics in primary health care by utilizing image enlargement. The aim of the study was to explore the possibilities of DO in remote consultations. Materials and Methods Based on real‐life referrals, 45 otologic outpatients were recruited. DO was performed followed by an attending otologist's appointment, serving as the gold standard. Twenty‐four patient cases were analyzed on a digital platform as remote consultation cases containing the given referral information supplemented with DO videos (DOVs). A total of 71 evaluations were performed by five otologists. The quality of the DOVs, their suitability for remote consultations, the accuracy of diagnoses and the usefulness of remote consultations were determined. Results The average DOV quality was judged to be 7.4 ± 0.3 (mean ± standard error of the mean; scale of 1–10). The diagnosis was correct in 79% of the cases. In 59% of the patients, the otologists considered that remote consultation could have replaced an in‐person visit. Conclusions In our simulated remote consultation setup, DOV quality was sufficient for diagnostic purposes, DO improved diagnostics and treatment planning in most cases and could be used to reduce the need for in‐person visits. DO‐aided remote consultation may improve diagnostics and access to care. Level of evidence: 3.

Matter with a high energy density (> [10.sup.5] joules per [cm.sup.3]) is prevalent throughout the Universe, being present in all types of stars (1) and towards the centre of the giant planets (2,3); it is also relevant for inertial confinement fusion (4). Its thermodynamic and transport properties are challenging to measure, requiring the creation of sufficiently long-lived samples at homogeneous temperatures and densities (5,6). With the advent of the Linac Coherent Light Source (LCLS) X-ray laser (7), high-intensity radiation (>[10.sup.17] watts per [cm.sup.2], previously the domain of optical lasers) can be produced at X-ray wavelengths. The interaction of single atoms with such intense X-rays has recently been investigated (8). An understanding of the contrasting case of intense X-ray interaction with dense systems is important from a fundamental viewpoint and for applications. Here we report the experimental creation of a solid-density plasma at temperatures in excess of [10.sup.6] kelvin on inertial-confinement time-scales using an X-ray free-electron laser. We discuss the pertinent physics of the intense X-ray-matter interactions, and illustrate the importance of electron-ion collisions. Detailed simulations of the interaction process conducted with a radiative-collisional code show good qualitative agreement with the experimental results. We obtain insights into the evolution of the charge state distribution of the system, the electron density and temperature, and the timescales of collisional processes. Our results should inform future high-intensity X-ray experiments involving dense samples, such as X-ray diffractive imaging of biological systems, material science investigations, and the study of matter in extreme conditions., The experiment was performed at the LCLS soft X-ray materials science instrument (SXR), where a 1.0-µm-thick aluminium (Al) foil was irradiated with 80-fs X-ray pulses at photon energies in the [...]

The snow water equivalent (SWE) of a snowpack represents the amount of water it contains. SWE retrieval with passive microwave remote sensing techniques is notably affected by snow metamorphism. The effective snow grain size (effGS) described in the GlobSnow methodology can be retrieved over areas where prior snow depth data are available. However, this dependency on the availability of prior knowledge results in increased retrieval uncertainty in areas where such information is unavailable. In this work, we proposed a new method to predict the effGS using a random forest (RF) model. The results indicated that the geographical location, orographic effects, and seasonal characteristics are important for retrieving the effGS, and they are important components of the kriging interpolation of the daily effGS in the GlobSnow methodology, resulting in spatial and temporal autocorrelation phenomena. We assessed the performances of snow depth priors from either station measurements or gridded products in predicting effGS and found that the RF model is promising for effGS prediction even without snow depth priors. The application of spatially independent verification and 10-fold cross-validation (10-CV) techniques revealed that the effGS estimates generally agreed with GlobSnow reference data over Eurasia, with overall unbiased root mean square error (unRMSE) values of 0.15.0.18 mm, but high errors were observed over North America due to terrain variability and heterogeneous forest cover, with overall unRMSE values ranging from 0.22.0.31 mm. Compared to the GlobSnow methodology, the proposed method does not rely on ground-based prior information, and improved computational efficiency can be achieved.