Miracle-dz/UniFAR-FTUs huggingface dataset:
Predictive values of systemic inflammation biomarkers in proliferative vitreoretinopathy associated with primary rhegmatogenous retinal detachment

ABSTRACT Clinical relevance Proliferative vitreoretinopathy (PVR) is still the leading cause of surgical failure after rhegmatogenous retinal detachment (RRD) repair. The factors that can predict the development of PVR remain to be elucidated. Background This study evaluates the predictive values of the systemic immune-inflammation index, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio in patients with primary RRD with and without PVR. Methods A total of 150 patients with RRD and 51 age- and sex-matched healthy participants were included in the study. Patients who developed PVR within three months after surgery were enrolled as PVR cases (n = 75, Group 1), and those who did not develop PVR were enrolled in RRD without the PVR group (n = 75, Group 2). Ocular examination findings and medical records of all participants were analysed retrospectively. Peripheral blood samples were collected, and systemic immune-inflammation index, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratios were calculated. The systemic immune-inflammation index calculation formula is: (Neutrophil/lymphocyte) × Platelet. Results The median neutrophil-to-lymphocyte ratio and systemic immune-inflammation index levels were significantly higher in Group 1 patients compared to Group 2 and the control groups (p = 0.01, for both). However, the groups were similar regarding median platelet-to-lymphocyte ratio (p = 0.917). The optimal cut-off values of neutrophil-to-lymphocyte ratio and systemic immune-inflammation index were calculated as 1.72 (with 72% sensitivity and 48% specificity) and 407.9 (with 72% sensitivity and 49.3% specificity), respectively, for predicting PVR development in patients with RRD. Conclusion Neutrophil-to-lymphocyte ratio and systemic immune-inflammation index may be useful biomarkers for predicting the risk of PVR development in RRD patients.
Affine Near-Semirings Over Brandt Semigroups

In order to study the structure of A +(B n )—the affine near-semiring over a Brandt semigroup—this work completely characterizes the Green's classes of its semigroup reducts. In this connection, this work classifies the elements of A +(B n ) and reports the size of A +(B n ). Further, idempotents and regular elements of the semigroup reducts of A +(B n ) have also been characterized and studied some relevant semigroups in A +(B n ).
A Systematic Review of the Effect of Hearing Aids on Static and Dynamic Balance in Adults with Hearing Impairment

This preregistered systematic review examined the peer-reviewed scientific literature to determine the effect of hearing aids (HAs) on static and dynamic balance in adults with Hearing Impairment (HI). A search of the English language literature in seven academic databases identified 909 relevant articles published prior to July 2021. Ten articles contained studies that met the inclusion criteria for this review. Seven studies had measured static balance with five reporting improvements and one reporting no changes in balance with HA use. Two studies had measured dynamic balance with both reporting no changes with HA use. One study had measured both dynamic and static balance and reported no changes with HA use. For adults with HI, the evidence was equivocal that amplification from HAs improves balance. High quality studies investigating the effect of HAs on balance in adults with HI are needed given this field is likely to develop in response to the growing population of adults with hearing and balance impairment worldwide.
Loss of autism-candidate CHD8 perturbs neural crest development and intestinal homeostatic balance

A combination of zebrafish and transcriptomic analyses revealed the role of the autism-candidate chd8 in the development of the enteric nervous system, serotonin metabolism, and intestinal integrity. Individuals with mutations in CHD8 present with gastrointestinal complaints, yet the underlying mechanisms are understudied. Here, using a stable constitutive chd8 mutant zebrafish model, we found that the loss of chd8 leads to a reduced number of vagal neural crest cells (NCCs), enteric neural and glial progenitors, emigrating from the neural tube, and that their early migration capability was altered. At later stages, although the intestinal colonization by NCCs was complete, we found the decreased numbers of both serotonin-producing enterochromaffin cells and NCC-derived serotonergic neurons, suggesting an intestinal hyposerotonemia in the absence of chd8. Furthermore, transcriptomic analyses revealed an altered expression of key receptors and enzymes in serotonin and acetylcholine signaling pathways. The tissue examination of chd8 mutants revealed a thinner intestinal epithelium accompanied by an accumulation of neutrophils and the decreased numbers of goblet cells and eosinophils. Last, single-cell sequencing of whole intestines showed a global disruption of the immune balance with a perturbed expression of inflammatory interleukins and changes in immune cell clusters. Our findings propose a causal developmental link between chd8, NCC development, intestinal homeostasis, and autism-associated gastrointestinal complaints.
Impact of Fluoxetine on Herbivorous Zooplankton and Planktivorous Fish

The contamination of freshwater environments by pharmaceuticals is a growing problem. Modern healthcare uses nearly 3000 substances, many of which are designed to work at low dosages and act on physiological systems that have been evolutionarily conserved across taxa. Because drugs affect the organisms from different trophic levels, pharmaceutical pollution is likely to disturb species interactions. However, such effects are still only poorly understood. We investigated the impacts of environmentally relevant concentrations of the common drug fluoxetine (Prozac), an increasingly common contaminant of European waters, on predation behavior of crucian carp (Carassius carassius), a common planktivorous European fish, and the somatic growth of its prey, the water flea (Daphnia magna), a widespread planktonic crustacean. We exposed these two organisms to environmentally relevant levels of fluoxetine (360 ng L−1): the fish for 4 weeks and the water fleas for two generations. We tested the growth of the daphnids and the hunting behavior (reaction distance at which fish attacked Daphnia and feeding rate) of the fish under drug contamination. We found that Daphnia exposed to fluoxetine grew larger than a nonexposed cohort. The hunting behavior of C. carassius was altered when they were exposed to the drug; the reaction distance was shorter, and the feeding rate was slower. These effects occurred regardless of Daphnia size and the treatment regime they were subjected to. Our results suggest that contamination of freshwater environments with fluoxetine can disrupt the top‐down ecological control of herbivores by reducing the hunting efficiency of fish and, as a consequence, may lead to increases in cladoceran population numbers. Environ Toxicol Chem 2023;42:385–392. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
Molecular dynamics simulations of single-layer molybdenum disulphide (MoS2): Stillinger-Weber parametrization, mechanical properties, and thermal conductivity

We present a parameterization of the Stillinger-Weber potential to describe the interatomic interactions within single-layer MoS2 (SLMoS2). The potential parameters are fitted to an experimentally obtained phonon spectrum, and the resulting empirical potential provides a good description for the energy gap and the crossover in the phonon spectrum. Using this potential, we perform classical molecular dynamics simulations to study chirality, size, and strain effects on the Young's modulus and the thermal conductivity of SLMoS2. We demonstrate the importance of the free edges on the mechanical and thermal properties of SLMoS2 nanoribbons. Specifically, while edge effects are found to reduce the Young's modulus of SLMoS2 nanoribbons, the free edges also reduce the thermal stability of SLMoS2 nanoribbons, which may induce melting well below the bulk melt temperature. Finally, uniaxial strain is found to efficiently manipulate the thermal conductivity of infinite, periodic SLMoS2.
Relative velocities of inertial particles in turbulent aerosols

We compute the joint distribution of relative velocities and separations of identical inertial particles suspended in randomly mixing and turbulent flows. Our results are obtained by matching asymptotic forms of the distribution. The method takes into account spatial clustering of the suspended particles as well as singularities in their motion (so-called ‘caustics’). It thus takes proper account of the fractal properties of phase space and the distribution is characterised in terms of the corresponding phase-space fractal dimension D2. The method clearly exhibits universal aspects of the distribution (independent of the statistical properties of the flow): at small particle separations R and not too large radial relative speeds |VR|, the distribution of radial relative velocities exhibits a universal power-law form , provided that D2 ≤ d + 1 and that the Stokes number St is large enough for caustics to form. The range in VR over which this power law is valid depends on R, on the Stokes number and upon the nature of the flow. Our results are in good agreement with results of computer simulations of the dynamics of particles suspended in random velocity fields in one and two spatial dimensions with finite correlation times. In the white-noise limit, the results are consistent with those of Gustavsson and Mehlig [Phys. Rev. E84 (2011) 045304].
Targeted inactivation of the Septin2 and Septin9 genes in myelinating Schwann cells of mice

The formation of axon‐enwrapping myelin sheaths by oligodendrocytes in the central nervous system involves the assembly of a scaffolding septin filament comprised of the subunits SEPTIN2, SEPTIN4, SEPTIN7 and SEPTIN8. Conversely, in the peripheral nervous system (PNS), myelin is synthesized by a different cell type termed Schwann cells, and it remained unknown if septins also assemble as a multimer in PNS myelin. According to prior proteome analysis, PNS myelin comprises the subunits SEPTIN2, SEPTIN7, SEPTIN8, SEPTIN9, and SEPTIN11, which localize to the paranodal and abaxonal myelin subcompartments. Here, we use the Cre/loxP‐system to delete the Septin9‐gene specifically in Schwann cells, causing a markedly reduced abundance of SEPTIN9 in sciatic nerves, implying that Schwann cells are the main cell type expressing SEPTIN9 in the nerve. However, Septin9‐deficiency in Schwann cells did not affect the abundance or localization of other septin subunits. In contrast, when deleting the Septin2‐gene in Schwann cells the abundance of all relevant septin subunits was markedly reduced, including SEPTIN9. Notably, we did not find evidence that deleting Septin2 or Septin9 in Schwann cells impairs myelin biogenesis, nerve conduction velocity or motor/sensory capabilities, at least at the assessed timepoints. Our data thus show that SEPTIN2 but not SEPTIN9 is required for the formation or stabilization of a septin multimer in PNS myelin in vivo; however, its functional relevance remains to be established.
Behavioral couples therapy for brain injury: single case methodology with bi-phasic design

ABSTRACT Objectives To explore the outcomes of Behavioral Couples Therapy (BCT) for couples with brain injury. Background Brain injury can result in communication, emotional and behavioral disturbances, leading to higher levels of depression, anxiety and relationship distress. Currently, no study has explored the outcomes of BCT in couples impacted by brain injury. Method Four heterosexual couples living with brain injury were seen at a specialist outpatient service, and attended an average of 13 (range 8–25) BCT sessions. Participants with brain injury and their partners completed weekly measures of depression, anxiety, and couple satisfaction throughout baseline, assessment, intervention, and follow-up phases. Data were visually analyzed, and effects examined using reliable change analysis, and between-phase comparison conducted using Tau-U. Results Tau-U analysis demonstrated that both the patient and partner groups experienced significant overall improvement in relationship satisfaction and anxiety. Partners also reported significant reduction in depression scores overall. Reliable change analysis indicated improvement for some individual patients and partners, with effects maintained at follow-up in some cases. Conclusions The results offer promising results regarding the use of BCT for brain injury in increasing relationship satisfaction and reducing psychological distress. Further investigation is warranted.
Recovery of Brain Network Integration and Segregation During the Loss and Recovery of Consciousness Induced by Sevoflurane

Anesthetic-induced loss of consciousness (LOC) has been studied using functional connectivity (FC) and functional network analysis (FNA), manifested as fragmentation of the whole-brain functional network. However, how the fragmented brain networks reversibly recover during the recovery of consciousness (ROC) remains vague. This study aims to investigate the changes in brain network structure during ROC, to better understand the network fragmentation during anesthesia, thus providing insights into consciousness monitoring. We analyzed EEG data recorded from 15 individuals anesthetized by sevoflurane. By investigating the properties of functional networks generated using different brain atlases and performing community detection for functional networks, we explored the changes in brain network structure to understand how fragmented brain networks recover during the ROC. We observed an overall larger FC magnitude during LOC than in the conscious state. The ROC was accompanied by the increasing binary network efficiency, decreasing FC magnitude, and decreasing community similarity with the functional atlas. Furthermore, we observed a negative correlation between modularity and community number ( $\text{p} < 0.001$ and $\textit {BF}_{{10}} >4000$ , linear regression test), in which modularity increased and community number decreased during ROC. Our results show that a larger FC magnitude reveals excessive synchronization of neuronal activities during LOC. The increasing binary network efficiency, decreasing community number, and decreasing community similarity indicate the recovery of functional network integration. The increasing modularity implies the recovery of functional network segregation during ROC. The results suggest the limitation of FC magnitude and modularity in monitoring anesthetized states and the potential of integrated information theory to evaluate consciousness.
The classification of Nichols algebras over groups with finite root system of rank two

We classify all groups G and all pairs (V,W) of absolutely simple Yetter-Drinfeld modules over G such that the support of the direct sum of V and W generates G, the square of the braiding between V and W is not the identity, and the Nichols algebra of the direct sum of V and W admits a finite root system. As a byproduct, we determine the dimensions of such Nichols algebras, and several new families of finite-dimensional Nichols algebras are obtained. Our main tool is the Weyl groupoid of pairs of absolutely simple Yetter-Drinfeld modules over groups.
An update on maternal cardiac hemodynamics in fetal growth restriction and pre‐eclampsia

Pre‐eclampsia and fetal growth restriction (FGR) have been long related to primary placental dysfunction, caused by abnormal trophoblast invasion. Nevertheless, emerging evidence has led to a new hypothesis for the origin of pre‐eclampsia and FGR. Suboptimal maternal cardiovascular adaptation has been shown to result in uteroplacental hypoperfusion, ultimately leading to placental hypoxic damage with secondary dysfunction. In this review, we summarize current evidence on maternal cardiac hemodynamics in FGR and pre‐eclampsia. We also discuss the different approaches for antihypertensive treatment according to the hemodynamic phenotype observed in pre‐eclampsia and FGR.
Copula-like Variational Inference

This paper considers a new family of variational distributions motivated by Sklar's theorem. This family is based on new copula-like densities on the hypercube with non-uniform marginals which can be sampled efficiently, i.e. with a complexity linear in the dimension of state space. Then, the proposed variational densities that we suggest can be seen as arising from these copula-like densities used as base distributions on the hypercube with Gaussian quantile functions and sparse rotation matrices as normalizing flows. The latter correspond to a rotation of the marginals with complexity $\mathcal{O}(d \log d)$. We provide some empirical evidence that such a variational family can also approximate non-Gaussian posteriors and can be beneficial compared to Gaussian approximations. Our method performs largely comparably to state-of-the-art variational approximations on standard regression and classification benchmarks for Bayesian Neural Networks.
The Sloan Digital Sky Survey quasar catalog: ninth data release

We present the Data Release 9 Quasar (DR9Q) catalog from the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey III. The catalog includes all BOSS objects that were targeted as quasar candidates during the survey, are spectrocopically confirmed as quasars via visual inspection, have luminosities Mi[z = 2] 2.15 (61 931) is ~2.8 times larger than the number of z > 2.15 quasars previously known. Redshifts and FWHMs are provided for the strongest emission lines (C iv, C iii], Mg ii). The catalog identifies 7533 broad absorption line quasars and gives their characteristics. For each object the catalog presents five-band (u, g, r, i, z) CCD-based photometry with typical accuracy of 0.03 mag, and information on the morphology and selection method. The catalog also contains X-ray, ultraviolet, near-infrared, and radio emission properties of the quasars, when available, from other large-area surveys. The calibrated digital spectra cover the wavelength region 3600−10 500 A at a spectral resolution in the range 1300 < R < 2500; the spectra can be retrieved from the SDSS Catalog Archive Server. We also provide a supplemental list of an additional 949 quasars that have been identified, among galaxy targets of the BOSS or among quasar targets after DR9 was frozen.
Evolving communities with individual preferences

The goal of this paper is to provide mathematically rigorous tools for modelling the evolution of a community of interacting individuals. We model the population by a measure space (Ω,F,ν) where ν determines the abundance of individual preferences. The preferences of an individual ω∈Ω are described by a measurable choice X(ω) of a rough path.
Multicenter validation of a machine learning phase space electro-mechanical pulse wave analysis to predict elevated left ventricular end diastolic pressure at the point-of-care

Background Phase space is a mechanical systems approach and large-scale data representation of an object in 3-dimensional space. Whether such techniques can be applied to predict left ventricular pressures non-invasively and at the point-of-care is unknown. Objective This study prospectively validated a phase space machine-learned approach based on a novel electro-mechanical pulse wave method of data collection through orthogonal voltage gradient (OVG) and photoplethysmography (PPG) for the prediction of elevated left ventricular end diastolic pressure (LVEDP). Methods Consecutive outpatients across 15 US-based healthcare centers with symptoms suggestive of coronary artery disease were enrolled at the time of elective cardiac catheterization and underwent OVG and PPG data acquisition immediately prior to angiography with signals paired with LVEDP (IDENTIFY; NCT #03864081). The primary objective was to validate a ML algorithm for prediction of elevated LVEDP using a definition of ≥25 mmHg (study cohort) and normal LVEDP ≤ 12 mmHg (control cohort), using AUC as the measure of diagnostic accuracy. Secondary objectives included performance of the ML predictor in a propensity matched cohort (age and gender) and performance for an elevated LVEDP across a spectrum of comparative LVEDP (<12 through 24 at 1 mmHg increments). Features were extracted from the OVG and PPG datasets and were analyzed using machine-learning approaches. Results The study cohort consisted of 684 subjects stratified into three LVEDP categories, ≤12 mmHg (N = 258), LVEDP 13–24 mmHg (N = 347), and LVEDP ≥25 mmHg (N = 79). Testing of the ML predictor demonstrated an AUC of 0.81 (95% CI 0.76–0.86) for the prediction of an elevated LVEDP with a sensitivity of 82% and specificity of 68%, respectively. Among a propensity matched cohort (N = 79) the ML predictor demonstrated a similar result AUC 0.79 (95% CI: 0.72–0.8). Using a constant definition of elevated LVEDP and varying the lower threshold across LVEDP the ML predictor demonstrated and AUC ranging from 0.79–0.82. Conclusion The phase space ML analysis provides a robust prediction for an elevated LVEDP at the point-of-care. These data suggest a potential role for an OVG and PPG derived electro-mechanical pulse wave strategy to determine if LVEDP is elevated in patients with symptoms suggestive of cardiac disease.
Erratum: COVID-19 and Risk of Oxygen-Dependent Chronic Respiratory Failure: A National Cohort Study

(P, 0.001) for evaluating the relationship between the change in mucus plug score and FEV1% predicted adjusting for age, site, and baseline blood eosinophil count. Because the test of partial correlation is equivalent to the test of regression coefficient in the multivariable model (2, 3), the P value is identical to that of our analysis. Partial correlations are a unitless rescaling of regression coefficients, which can be useful for those preferring to evaluate relationships in the abstract. We felt it was better to use regression coefficients to retain interpretations for actual change in FEV1% predicted, because that was our interest. As Drs. Ikeda and Tomita note, structural equation modeling could provide additional insight in the complex relationships between multiple variables. However, our objective was to understand the relationship between the change in mucus plug score and the change in FEV1% predicted. Multivariable linear regression allowed us to focus on this key relationship without the added complexity of simultaneously modeling multiple relationships between all the variables in the model.