bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lymphocyte-to-monocyte ratio is a short-term predictive marker of ulcerative colitis after induction of advanced therapy
Authors: Ishida Natsuki , Asai Yusuke , Miyazu Takahiro , Tamura Satoshi , Tani Shinya , Yamade Mihoko , Iwaizumi Moriya , Hamaya Yasushi , Osawa Satoshi , Furuta Takahisa , Sugimoto Ken 
Published: June 2022

AbstractAdvanced therapies for patients with mild-to-severe ulcerative colitis (UC) may result in treatment failure. We examined whether the lymphocyte-to-monocyte ratio (L/M ratio) could predict the failure of advanced therapies. This retrospective, observational, cohort study included 73 patients who were treated with advanced therapies at the Hamamatsu University School of Medicine (Shizuoka, Japan) between February 2011 and November 2020. The patients were divided into the non-failure and failure groups, and their leukocyte counts and ratios before induction were examined. Univariate and multivariate analyses were performed to identify the prognostic factors. Advanced therapies failed within 3 months in 15 (20.5%) patients. Only the L/M ratio was significantly lower in the failure group than in the non-failure group (P = 0.004). Receiver-operating characteristic (ROC) curve analysis revealed that an L/M ratio of ≤3.417 was predictive of treatment failure; the area under the curve (AUC) was 0.747 (95% CI, 0.620–0.874). Kaplan–Meier analysis revealed that the failure-free rate was significantly lower in the group with an L/M ratio of ≤3.417 than in the group with an L/M ratio of &gt;3.417 (log-rank test P = 0.002). Cox proportional hazard regression analysis identified an L/M ratio of ≤3.417 as an independent risk factor for failure within 3 months after the induction of advanced therapies. Furthermore, ROC analysis of patients who did not receive immunomodulators also revealed that the cut-off L/M ratio was 3.417 and the AUC was 0.796 (95% CI, 0.666–0.925). In patients receiving advanced therapies for active UC, the L/M ratio can predict treatment failure within 3 months. L/M ratios could facilitate the transition from advanced therapies to subsequent treatments.
Profiles in Dementia-Related Anxiety: A Latent Profile Analysis
Authors: Maxfield Molly , Pituch Keenan A 
Published: June 2022

Abstract

Objectives
Dementia-related anxiety (DRA) is the concern about current or future cognitive decline and potential diagnosis of Alzheimer’s disease or related dementias (ADRD). Existing research suggests that DRA likely develops due to diverse reasons (e.g., family ADRD history, self-perceived risk, and health-related anxiety), and approaches to managing DRA likely differ as well (e.g., future planning). This study aimed to identify profiles in DRA.

Method
In a cross-sectional study, a convenience sample of U.S. adults ranging in age from 18 to 82 (N = 492, Mage = 49.25, standard deviation [SDage] = 15.43) completed online assessments of characteristics associated with DRA. Latent profile analysis was used to uncover distinct DRA profiles and promote understanding of individual characteristics associated with varying levels of DRA; multinomial regression assessed if the profiles are further distinguished by covariates.

Results
The resulting four-profile model reveals profile differences are largely due to DRA, self-perceived ADRD risk, and preparedness for future care needs; health-related anxiety, age, ADRD exposure, and anticipated ADRD stigma contribute to profile differences as well. Profiles of the youngest and oldest groups reported the lowest and highest levels of preparedness for future care, along with the lowest DRA and self-perceived risk. Several covariates, particularly those assessing general psychological functioning, were also related to profile membership.

Discussion
The resulting profiles point to several factors associated with elevated anxiety about ADRD, which do not fully match the risk factors for ADRD.
Bayesian tomography with prior-knowledge-based parametrization and surrogate modelling
Authors: Meles Giovanni Angelo , Linde Niklas , Marelli Stefano 
Published: June 2022

SUMMARYWe present a Bayesian tomography framework operating with prior-knowledge-based parametrization that is accelerated by surrogate models. Standard high-fidelity forward solvers (e.g. finite-difference time-domain schemes) solve wave equations with natural spatial parametrizations based on fine discretization. Similar parametrizations, typically involving tens of thousand of variables, are usually employed to parametrize the subsurface in tomography applications. When the data do not allow to resolve details at such finely parametrized scales, it is often beneficial to instead rely on a prior-knowledge-based parametrization defined on a lower dimension domain (or manifold). Due to the increased identifiability in the reduced domain, the concomitant inversion is better constrained and generally faster. We illustrate the potential of a prior-knowledge-based approach by considering ground penetrating radar (GPR) traveltime tomography in a crosshole configuration with synthetic data. An effective parametrization of the input (i.e. the permittivity distributions determining the slowness field) and compression in the output (i.e. the traveltime gathers) spaces are achieved via data-driven principal component decomposition based on random realizations of the prior Gaussian-process model with a truncation determined by the performances of the standard solver on the full and reduced model domains. To accelerate the inversion process, we employ a high-fidelity polynomial chaos expansion (PCE) surrogate model. We investigate the impact of the size of the training set on the performance of the PCE and show that a few hundreds design data sets is sufficient to provide reliable Markov chain Monte Carlo inversion at a fraction of the cost associated with a standard approach involving a fine discretization and physics-based forward solvers. Appropriate uncertainty quantification is achieved by reintroducing the truncated higher order principle components in the original model space after inversion on the manifold and by adapting a likelihood function that accounts for the fact that the truncated higher order components are not completely located in the null space.
The Spring-Mass Model and Other Reductionist Models of Bipedal Locomotion on Inclines
Authors: Selvitella Alessandro Maria , Foster Kathleen Lois 
Published: June 2022

Abstract
The spring-mass model is a model of locomotion aimed at giving the essential mathematical laws of the trajectory of the center of mass of an animal during bouncing gaits, such as hopping (one-dimensional) and running (two-dimensional). This reductionist mechanical system has been extensively investigated for locomotion over horizontal surfaces, whereas it has been largely neglected on other ecologically relevant surfaces, including inclines. For example, how the degree of inclination impacts the dynamics of the center of mass of the spring-mass model has not been investigated thoroughly. In this work, we derive a mathematical model which extends the spring-mass model to inclined surfaces. Among our results, we derive an approximate solution of the system, assuming a small angular sweep of the limb and a small spring compression during stance, and show that this approximation is very accurate, especially for small inclinations of the ground. Furthermore, we derive theoretical bounds on the difference between the Lagrangian and Lagrange equations of the true and approximate systems, and discuss locomotor stability questions of the approximate solutions. We test our models through a sensitivity analysis using parameters relevant to the locomotion of bipedal animals (quail, pheasant, guinea fowl, turkey, ostrich, and humans) and compare our approximate solution to the numerically derived solution of the exact system. We compare the two-dimensional spring-mass model on inclines with the one-dimensional spring-mass model to which it reduces under the limit of no horizontal velocity; we compare the two-dimensional spring-mass model on inclines with the inverted pendulum model on inclines towards which it converges in the case of high stiffness-to-mass ratio. We include comparisons with historically prevalent no-gravity approximations of these models, as well. The insights we have gleaned through all these comparisons and the ability of our approximation to replicate some of the kinematic changes observed in animals moving on different inclines (e.g., reduction in vertical oscillation of the center of mass and decreased stride length) underline the valuable and reasonable contributions that very simple, reductionist models, like the spring-mass model, can provide.
Capturing High Resolution Plant Movement in the Field
Authors: Heuschele D J , Furuta D , Smith K P , Marchetto P 
Published: June 2022

SynopsisLodging of small grains due to environmental stresses results in yield loss, quality reduction, and difficulties with mechanical harvesting, which lead to economic consequences. New technological discoveries allow for faster and in situ measurements for determining the mechanics of loading stress and plant movement. The overall measurement of plant movement can be a very sophisticated method to mechanically test and predict the behavior of stems when exposed to wind. We investigated the inertial measurement of plants during different magnitude wind events. This type of analysis captures real time quantitative stem behavior during wind events. Using a 1.5 cm2 inertial measurement sensor attached to the upper panicle of a plant, we recorded the ranges and extremes of instantaneous linear acceleration and rotational velocity. When this technology was applied to historically known varieties of different lodging classification, the measurements were able to distinguish between cereal species and differences between movement of lodging susceptible and resistant plants without physical lodging. This type of technology could be used to improve field based lodging models and quantify movement resulting from micro changes in structural and composition of the stem, and to analyze plant movement in natural conditions with a resolution and specificity that has so far been prohibitively expensive and technologically challenging to achieve.
Integrating DNA-Based Prey Occurrence Probability into Stable Isotope Mixing Models
Authors: Hoenig Brandon D , Trevelline Brian K , Latta Steven C , Porter Brady A 
Published: June 2022

SynopsisThe introduction of laboratory methods to animal dietary studies has allowed researchers to obtain results with accuracy and precision, not possible with observational techniques. For example, DNA barcoding, or the identification of prey with taxon-specific DNA sequences, allows researchers to classify digested prey tissues to the species-level, while stable isotope analysis paired with Bayesian mixing models can quantify dietary contributions by comparing a consumer's isotopic values to those derived from their prey. However, DNA-based methods are currently only able to classify, but not quantify, the taxa present in a diet sample, while stable isotope analysis can only quantify dietary taxa that are identified a priori as prey isotopic values are a result of life history traits, not phylogenetic relatedness. Recently, researchers have begun to couple these techniques in dietary studies to capitalize on the reciprocal benefits and drawbacks offered by each approach, with some even integrating DNA-based results directly into Bayesian mixing models as informative priors. As the informative priors used in these models must represent known dietary compositions (e.g., percentages of prey biomasses), researchers have scaled the DNA-based frequency of occurrence of major prey groups so that their normalized frequency of occurrence sums to 100%. Unfortunately, such an approach is problematic as priors stemming from binomial, DNA-based data do not truly reflect quantitative information about the consumer's diet and may skew the posterior distribution of prey quantities as a result. Therefore, we present a novel approach to incorporate DNA-based dietary information into Bayesian stable isotope mixing models that preserves the binomial nature of DNA-based results. This approach uses community-wide frequency of occurrence or logistic regression-based estimates of prey occurrence to dictate the probability that each prey group is included in each mixing model iteration, and, in turn, the probability that each iteration's results are included in the posterior distribution of prey composition possibilities. Here, we demonstrate the utility of this method by using it to quantify the prey composition of nestling Louisiana waterthrush (Parkesia motacilla).
Technical Note: A procedure to place urinary catheters in 1- and 6-week-old preweaned Holstein heifer calves for the in vivo evaluation of intestinal permeability
Authors: Ceja Guadalupe , Boerman Jacquelyn P , Neves Rafael C , Johnson Nicholas S , Schoonmaker Jon P , Jorgensen Matthew W , Johnson Jay S 
Published: June 2022

Abstract
Oral administration of indigestible markers and subsequent urine collection is a useful method to determine in vivo gastrointestinal tract (GIT) permeability in cattle for research purposes. However, urine sampling techniques often rely on total waste collection, which reduces the ability to perform more frequent sampling and obtain accurate volumes and sterile samples. An alternative is urethral catheterization, though the feasibility of this technique has not been thoroughly tested in preweaned Holstein heifer calves. The study objective was to develop a urethral catheter placement procedure in preweaned Holstein heifer calves for continuous and accurate urine collection to evaluate GIT permeability using an indigestible marker. Fifteen Holstein heifer calves had catheters placed at approximately 1 wk (8.0 ± 1.5 d) and 6 wk (40.0 ± 1.5 d) of age. During the procedure, calves were individually housed and restrained. The vulva was sterilized and then a sterile, lubricated speculum was inserted into the vagina. A sterile 0.09 cm diameter guidewire was guided into a lubricated, sterile 10 French Foley catheter. The catheter was inserted at approximately 5 through 7 cm into the urethral opening, guided into the bladder, and the catheter balloon was filled with 10 mL of water. The guidewire was removed, and urine flow confirmed correct placement before a 4-L urinary drainage bag was attached to the catheter. After catheterization (24 h), 1 L of chromium (Cr)-ethylenediaminetetraacetic acid was orally dosed to the calves. Calf health observations were made six times over a 48-h period, and any occurrence of vaginal discharge, tissue discharge in catheter, bleeding, inflammation, or abnormal urine was considered a localized reaction. The proportion of localized reactions for each age group was determined using Microsoft Excel, and the total Cr output was analyzed using PROC GLIMMIX. Localized reactions occurred for 20.0% of the 1-wk-old calves and 13.3% of the 6-wk-old calves. In the first 4 h, urine was collected every 15 min, and there were no overall Cr output differences (P = 0.38; 10.28 ± 3.21 mg Cr) when comparing 1- and 6-wk-old calves. However, 1-wk-old calves tended (P = 0.08) to have greater overall Cr output at 480 min (19.2%) and 1,440 min (41.9%) when compared with 6-wk-old calves. In summary, urinary catheterization is a viable urinary collection method for the determination of in vivo GIT permeability in preweaned Holstein heifer calves.
Human Rights Issues—A Still Neglected Managerial Area in Supply Chains? Study Results of Socially Responsible Companies from Poland
Authors: Rudnicka Agata 
Published: June 2022

AbstractThis article discusses human rights issues in supply chains of socially responsible companies operating in Poland. The issue of human rights in business is gaining importance both in the context of legal regulations and the approach of enterprises. Nevertheless, human rights in supply chains pose many challenges. This issue should be particularly important to companies that have decided to implement social responsibility. Two crucial research questions were asked. First, to what extent do socially responsible companies pay attention to human rights issues in supply chains? Second, if human rights issues are managed in supply chains, how is this done? The main results show that this issue is considered, but it is difficult to unequivocally assess to what extent the subject of human rights is treated strategically as an element of a business case and how far it results from the current need to be adjusted to the present societal expectations. This article outlines the general overview of the situation.
Promotion of nonalcoholic steatohepatitis by RNA N6-methyladenosine reader IGF2BP2 in mice
Authors: Zhou Bing , Luo Yunchen , Ji Nana , Mao Fei , Xiang Liping , Bian Hua , Zheng Ming-Hua , Hu Cheng , Li Yao , Lu Yan 
Published: June 2022

AbstractNonalcoholic steatohepatitis (NASH) has emerged as the major cause of end-stage liver diseases. However, an incomplete understanding of its molecular mechanisms severely dampens the development of pharmacotherapies. In the present study, through systematic screening of genome-wide mRNA expression from three mouse models of hepatic inflammation and fibrosis, we identified IGF2BP2, an N6-methyladenosine modification reader, as a key regulator that promotes NASH progression in mice. Adenovirus or adeno-associated virus-mediated overexpression of IGF2BP2 could induce liver steatosis, inflammation, and fibrosis in mice, at least in part, by increasing Tab2 mRNA stability. Besides, hepatic overexpression of IGF2BP2 mimicked gene expression profiles and molecular pathways of human NASH livers. Of potential clinical significance, IGF2BP2 expression is significantly upregulated in the livers of NASH patients. Moreover, knockdown of IGF2BP2 substantially alleviated liver injury, inflammation, and fibrosis in diet-induced NASH mice. Taken together, our findings reveal an important role of IGF2BP2 in NASH, which may provide a new therapeutic target for the treatment of NASH.
Variability and phase lags of the type-C quasi-periodic oscillation of MAXI J1348–630 with NICER
Authors: Alabarta Kevin , Méndez Mariano , García Federico , Peirano Valentina , Altamirano Diego , Zhang Liang , Karpouzas Konstantinos 
Published: June 2022

ABSTRACT
We study the properties of the type-C quasi-periodic oscillation (type-C QPO) of MAXI J1348–630 during its 2019 outburst and reflare with NICER. This is the first time that the evolution of the properties of type-C QPOs is studied during an outburst reflare. We found that the properties of the type-C QPO during the reflare are similar to those of type-C QPOs observed in other black hole systems during outburst. This suggests that the physical processes responsible for type-C QPOs are the same in a reflare and in an outburst. We also found that the full width at half-maximum of a high-frequency broad-band component observed during the reflare changes significantly with energy. We studied the energy-dependent fractional rms amplitude and phase lags of the type-C QPO from 0.5 to 12 keV. We found that the fractional rms amplitude increases up to 2–3 keV and then remains approximately constant above this energy, and the lag spectra of the type-C QPO are hard. We discuss the dependence of the fractional rms amplitude and phase lags with energy in the context of Comptonization as the radiative mechanism driving the QPO rms and lag spectra.
Detection of spatial clustering in the 1000 richest SDSS DR8 redMaPPer clusters with nearest neighbor distributions
Authors: Wang Yunchong , Banerjee Arka , Abel Tom 
Published: June 2022

ABSTRACT
Distances to the k-nearest-neighbor (kNN) data points from volume-filling query points are a sensitive probe of spatial clustering. Here, we present the first application of kNN summary statistics to observational clustering measurement, using the 1000 richest redMaPPer clusters (0.1 ≤ z ≤ 0.3) from the SDSS DR8 catalog. A clustering signal is defined as a difference in the cumulative distribution functions (CDFs) of kNN distances from fixed query points to the observed clusters versus a set of unclustered random points. We find that the k = 1, 2-NN CDFs of redMaPPer deviate significantly from the randoms’ across scales of 35 to 155 Mpc, which is a robust signature of clustering. In addition to kNN, we also measure the two-point correlation function for the same set of redMaPPer clusters versus random points, which shows a noisier and less significant clustering signal within the same radial scales. Quantitatively, the χ2 distribution for both the kNN-CDFs and the two-point correlation function measured on the randoms peak at χ2 ∼ 50 (null hypothesis), whereas the kNN-CDFs (χ2 ∼ 300, p = 1.54 × 10−36) pick up a much more significant clustering signal than the two-point function (χ2 ∼ 100, p = 1.16 × 10−6) when measured on redMaPPer. Finally, the measured 3NN and 4NN CDFs deviate from the predicted k = 3, 4-NN CDFs assuming an ideal Gaussian field, indicating a non-Gaussian clustering signal for redMaPPer clusters, although its origin might not be cosmological due to observational systematics. Therefore, kNN serves as a more sensitive probe of clustering complementary to the two point correlation function, providing a novel approach for constraining cosmology and galaxy–halo connection.
Proximity of exoplanets to first-order mean-motion resonances
Authors: Charalambous C , Teyssandier J , Libert A-S 
Published: June 2022

ABSTRACT
Planetary formation theories and, more specifically, migration models predict that planets can be captured in mean-motion resonances (MMRs) during the disc phase. The distribution of period ratios between adjacent planets shows an accumulation in the vicinity of the resonance, which is not centred on the nominal resonance but instead presents an offset slightly exterior to it. Here, we extend on previous works by thoroughly exploring the effect of different disc and planet parameters on the resonance offset during the disc migration phase. The dynamical study is carried out for several first-order MMRs and for both low-mass Earth-like planets undergoing type-I migration and giant planets evolving under type-II migration. We find that the offset varies with time during the migration of the two-planet system along the apsidal corotation resonance family. The departure from the nominal resonance increases for higher planetary masses and stronger eccentricity damping. In the Earth to super-Earth regime, we find offset values in agreement with the observations when using a sophisticated modelling for the planet–disc interactions, where the damping time-scale depends on the eccentricity. This dependence causes a feedback that induces an increase of the resonance offsets. Regarding giant planets, the offsets of detected planet pairs are well reproduced with a classical K-factor prescription for the planet–disc interactions when the eccentricity damping rate remains low to moderate. In both regimes, eccentricities are in agreement with the observations too. As a result, planet–disc interactions provide a generic channel to generate the offsets found in the observations.