bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gut Microbiota and Autoimmune Diseases: Mechanisms, Treatment, Challenges, and Future Recommendations
Authors: Sadeghpour Heravi Fatemah 
Published: January 2024

Abstract
Purpose of Review
This review provides an overview of the role of dysbiosis (imbalanced gut microbiota) in the maintenance of host homeostasis and immune function and summarizes recent evidence connecting gut microbiota dysbiosis to the development of autoimmune diseases (ADs) (such as rheumatoid arthritis, type 1 diabetes, systemic lupus erythematosus, multiple sclerosis, spondyloarthritis, and irritable bowel syndrome). The potential mechanisms that underlie the host-microbiota interaction are also discussed to evaluate the manipulation of the gut microbiota as a potential therapeutic approach to managing ADs. Additionally, this review addresses current challenges in gut microbiota-host research and provides future recommendations.

Recent Findings
Recent findings suggested that the pathogenesis of ADs appears to be multifaceted involving both genetic and environmental factors. Dysbiosis or imbalanced gut microbiota has been increasingly identified as one of the main environmental factors that can modulate immune responses and contribute to the development of ADs.

Summary
New research has highlighted the significance of gut microbial dysbiosis in the etiology of numerous diseases. Understanding the relationship between the gut microbiota and the host, however, goes beyond taxonomic concerns, demanding multidisciplinary efforts to design new therapeutic approaches that take individual variances into account.
The efficacy and safety of hydroxychloroquine versus leflunomide in patients with IgA nephropathy: a single-center experience
Authors: He Wei-jie , Wang Juan , Liu Nan , Li Gu-yue , Zhu Xin-wang , Yao Li , Liu Lin-lin 
Published: January 2024

Abstract
Purpose
To date, our understanding of IgA nephropathy (IgAN) pathophysiology has remained incomplete; therefore, treatment remains largely empiric, and the efficacy and safety of immunosuppressants remain controversial. We aimed to assess the efficacy and safety of hydroxychloroquine and leflunomide therapy in a retrospective cohort of patients with IgAN.

Methods
We screened the IgAN registration database in our department, and a total of 159 kidney patients with biopsy-confirmed IgAN were enrolled, with 57 patients receiving hydroxychloroquine plus a renin-angiotensin system inhibitor (hydroxychloroquine group), 52 patients receiving leflunomide plus a renin-angiotensin system inhibitor (leflunomide group), and 50 patients receiving only a renin-angiotensin system inhibitor (renin-angiotensin system inhibitor-only group). Changes in proteinuria, hematuria, and the estimated glomerular filtration rate (eGFR), as well as adverse events, were analyzed during the follow-up period.

Results
At the end of 6-month follow-up, proteinuria significantly decreased by 70.36 (57.54, 79.33)%, 57.29 (46.79, 67.29)% and 41.20 (25.76, 48.94)% in the hydroxychloroquine, leflunomide and renin-angiotensin system inhibitor-only groups, respectively, compared to baseline (all P values < 0.001). Hematuria significantly decreased by 71.07 (56.48, 82.47)% in the leflunomide group (P < 0.001). The eGFR improved by 3.72 ± 2.97%, 3.16 ± 2.00% and 1.91 ± 2.41%, respectively, in the hydroxychloroquine, leflunomide and renin-angiotensin system inhibitor-only groups, but without statistical significance. No serious adverse events occurred during the follow-up period.

Conclusion
Both hydroxychloroquine combined with a renin-angiotensin system inhibitor and leflunomide combined with a renin-angiotensin system inhibitor were more effective than a renin-angiotensin system inhibitor alone in improving proteinuria in IgAN patients. Hydroxychloroquine was more effective in reducing proteinuria, and leflunomide showed superiority in reducing hematuria. Our results need to be verified in large-scale randomized controlled trials.

Graphical abstract
Modelling sludge dewatering in treatment reed bed considering sludge deposit formation
Authors: Huong Yu Zhe , Tan Yee Yong , Tang Fu Ee , Saptoro Agus 
Published: January 2024

AbstractThe accumulation of sludge deposits is a crucial factor in the dewatering efficiency of sludge treatment reed bed (STRB). This paper presents an improved one-dimensional process-based mathematical model to simulate the dewatering mechanism in STRBs, in which the compressible cake filtration (CCF) theory was implemented to simulate the sludge deposits accumulation on the surface of the reed bed, while the varying sludge deposit thickness was accounted for using the moving mesh method. The proposed model also included the dual porosity variably saturated flow model and the Penman–Monteith equation to describe the dewatering through gravity drainage and evapotranspiration, respectively. The results from the model were validated with experimental data from laboratory-scale STRBs treating septage. The simulation results showed that considering the sludge deposit layer as a specific flow resistance effectively avoids the overprediction of water infiltration rate in the reed bed. The predicted results showed excellent agreement with the actual data, where only five cases of the root mean square error were above 10% compared to the average effluent flux. Further, the effect of evapotranspiration was found to be insignificant within a short-term simulation. The consideration of the influence of sludge deposit formation on drainage dewatering using the CCF model and moving mesh model has delivered a more robust simulation for sludge dewatering in STRBs, and the proposed model is capable of facilitating the understanding of the interactions between the sludge dewatering in STRB with respect to the bed characteristics, hydraulic load, and solid load.
Association Between Socioeconomic Position and Depression, Anxiety and Eating Disorders in University Students: A Systematic Review
Authors: Mac-Ginty Scarlett , Lira Daniela , Lillo Ignacio , Moraga Esteban , Cáceres Cesar , Araya Ricardo , Prina Matthew 
Published: January 2024

AbstractThe high prevalence of mental disorders in university students emphasizes the need to explore contributing factors. While socioeconomic position affects mental health in the general population, it is crucial to investigate if the same applies to university students. MEDLINE-Ovid, Embase-Ovid and PsycINFO databases were searched. All original peer-reviewed observational studies quantifying the association between socioeconomic position and depression, anxiety or eating disorders were included without language or date restrictions. After initial screening, eligible studies were selected, data was extracted using a spreadsheet, and their quality was assessed with the Newcastle–Ottawa scale. The results were synthesized narratively. Seventy-eight of 20,465 records identified were included. Most studies were published in English and originated from high and upper-middle-income countries. The most common socioeconomic indicators were family socioeconomic status/class, financial stress, and parental education. Most studies found a positive association between socioeconomic indicators and depressive and anxiety symptoms, but not eating disorders. The quality of the studies was mixed, with a small proportion using validated measurement tools and appropriate sample sizes. This study highlights the importance of measuring socioeconomic position accurately and applying new methods that can reveal the causal pathways and interactions of multiple identities that shape mental health disparities for the university student population.Preregistration A protocol for this review was registered in PROSPERO (CRD42022247394).
Development and Validation of a Simple Tool for Predicting Pandemic-Related Psychological Distress Among Health Care Workers
Authors: Adorjan Kristina , Dong Mark Sen , Wratil Paul R. , Schmacke Niklas A. , Weinberger Tobias , Steffen Julius , Osterman Andreas , Choukér Alexander , Mueller Tonina T. , Jebrini Tarek , Wiegand Hauke Felix , Tüscher Oliver , Lieb Klaus , Hornung Veit , Falkai Peter , Klein Matthias , Keppler Oliver T. , Koutsouleris Nikolaos 
Published: January 2024

AbstractWe aimed to develop a simple predictive model that enables health care workers (HCWs) to self-assess pandemic-related psychological distress in order to assist them to find psychological support to avert adverse distress-related outcomes. In a pilot study, we recruited and followed longitudinally 220 HCWs at the Hospital of the Ludwig Maximilian University Munich (H-LMU) during the first wave of the COVID-19 pandemic (March–July 2020). In this sample, we evaluated whether a machine-learning model with sociodemographic, epidemiological, and psychological data could predict levels of pandemic-related psychological distress. To maximise clinical utility, we derived a brief, 10-variable model to monitor distress risk and inform about the use of individualised preventive interventions. The validity of the model was assessed in a subsequent cross-sectional study cohort (May–August 2020) consisting of 7554 HCWs at the H-LMU who were assessed for depressiveness after the first wave of the pandemic.The model predicted psychological distress at 12 weeks with a balanced accuracy (BAC) of 75.0% (sensitivity, 73.2%; specificity, 76.8%) and an increase in prognostic certainty of 41%. In the derivation cohort, the brief model maintained a BAC of 75.6% and predicted depressiveness (P < .001), resilience (p.001), and coping (p < .001). Furthermore, it accurately stratified HCWs’ psychological trajectories of global and affective burden as well as behavioural adaptation over the 12-week follow-up period. Our clinically scalable, 10-variable model predicts individual COVID-19 pandemic-related psychological distress outcomes. HCWs may use our associated predictive tool to monitor personal and team-based risk and learn about risk preventive interventions based on an intuitive risk stratification.
Deep learning in terrestrial conservation biology
Authors: Barta Zoltán 
Published: January 2024

AbstractBiodiversity is being lost at an unprecedented rate on Earth. As a first step to more effectively combat this process we need efficient methods to monitor biodiversity changes. Recent technological advance can provide powerful tools (e.g. camera traps, digital acoustic recorders, satellite imagery, social media records) that can speed up the collection of biological data. Nevertheless, the processing steps of the raw data served by these tools are still painstakingly slow. A new computer technology, deep learning based artificial intelligence, might, however, help. In this short and subjective review I oversee recent technological advances used in conservation biology, highlight problems of processing their data, shortly describe deep learning technology and show case studies of its use in conservation biology. Some of the limitations of the technology are also highlighted.
The effect of a hiding space on the behaviour and heart rate variability of dairy calves during temporary separation from the dam
Authors: Spitzer Hannah B , Meagher Rebecca K , Lynne O’Sullivan M , Montelpare William , Gordon Miriam B , McKenna Shawn LB , Proudfoot Kathryn L 
Published: January 2024

Abstract
In natural settings, newborn calves hide for several days before joining the herd. It is unclear whether dairy calves housed indoors would show similar hiding behaviour. This study aimed to describe the use of an artificial hide provided to calves during temporary separation from the dam and assess the effect it has on lying and sleep-like behaviour, as well as heart rate variability (HRV). Twenty-eight cow-calf pairs were randomly assigned to having a hide (n = 14), or no hide (n = 14). Hide use (n = 14), as well as lying and sleep-like behaviour (n = 28), were recorded continuously via video camera during the first hour after the dam was removed for morning milking on day three to seven. Heart rate and R-R intervals were recorded using Polar equine monitors for a subsample of 12 calves (n = 6 per treatment) on day six. Descriptive statistics were calculated for hide use. Wilcoxon Signed Rank tests were used to evaluate whether having a hide affected lying and sleep-like behaviours as well as HRV. Hide use decreased over days and was highly variable between calves. Lying behaviour did not differ between treatments. Duration of sleep-like behaviour was higher for calves without a hide compared to those with a hide. Calves with a hide tended to show signs of higher HRV and parasympathetic activity compared to calves without a hide. Results suggest that providing a hiding space to young calves may be beneficial during periods when the cow is removed from the pen for milking.
Repeated risky choices become more consistent with themselves but not expected value, with no effect of matched trial order
Authors: Spicer Jake , Mullett Timothy L. , Sanborn Adam N. 
Published: January 2024

Abstract
Choices made in risky scenarios are considered fundamentally noisy because decisions have often been found to be inconsistent when repeated. Past measures of noise may, however, be confounded by the use of randomized contextual factors that are known to influence choice, in particular, the order of trials. In two experiments, we control trial order to test the extent to which inconsistent choice is attributable to changes in experimental context. Both tasks find strong evidence that trial order has no effect on choice consistency, indicating such experimental factors have little influence on behavior compared with internal noise. Choices also showed an increase in consistency across multiple repetitions, suggesting a fall in noise with experience, but this increase was not associated with any improvement in performance, with choices showing no greater adherence to either expected value or expected utility across repetitions. Instead, choices increasingly adhered to simplistic heuristic decision rules, possibly indicating greater reliance on such strategies as the tasks progressed. These results carry implications for a number of decision-making theories, including true-and-error models, rank-based methods, and strategy shift approaches.
Processing code-blending beyond the lexical level: evidence for a double syntactic derivation?
Authors: Giustolisi Beatrice , Jaber Angélique , Branchini Chiara , Geraci Carlo , Donati Caterina 
Published: January 2024

Abstract
Bimodal bilinguals master languages in two modalities, spoken and signed, and can use them simultaneously due to the independence of the articulators. This behavior, named code-blending, is one of the hallmarks of bimodal bilingualism. Lexical experiments on production and comprehension in American Sign Language/English showed that blending is not cognitively costly and facilitates lexical access. In this work, we replicated the blending advantage in lexical comprehension for hearing bimodal bilinguals with two other language pairs, French Sign Language (LSF)–French and Italian Sign Language (LIS)–Italian, and we explored whether the facilitation is also found at the sentential level. Results show that blended utterances for languages with incongruent word order like LIS–Italian were processed slower than monolingual utterances, while no difference was found when the word orders were congruent (LSF–French). We discuss these findings in light of linguistic theories of syntactic structure derivation in bimodal bilinguals.
Cycling Rates of Particulate Organic Carbon Along the GEOTRACES Pacific Meridional Transect GP15
Authors: Amaral Vinícius J. , Lam Phoebe J. , Marchal Olivier , Kenyon Jennifer A. 
Published: January 2024

AbstractUnderstanding particle cycling processes in the ocean is critical for predicting the response of the biological carbon pump to external perturbations. Here, measurements of particulate organic carbon (POC) concentration in two size fractions (1–51 and >51 μm) from GEOTRACES Pacific meridional transect GP15 are combined with a POC cycling model to estimate rates of POC production, (dis)aggregation, sinking, remineralization, and vertical transport mediated by migrating zooplankton, in the euphotic zone (EZ) and upper mesopelagic zone (UMZ) of distinct environments. We find coherent variations in POC cycling parameters and fluxes throughout the transect. Thus, the settling speed of POC in the >51 μm fraction increased with depth in the UMZ, presumably due to higher particle densities at depth. The settling flux of total POC (>1 μm) out of the EZ was positively correlated with primary production integrated over the EZ; the highest export occurred in the subarctic gyre while the lowest occurred in the subtropical gyres. The ratio of POC settling flux to integrated primary production was low (<5%) along GP15, which suggests an efficient recycling of POC in the EZ in all trophic regimes. Specific rates of POC remineralization did not show clear variations with temperature or dissolved oxygen concentration, that is, POC recycling was apparently controlled by other factors such as microbial colonization and substrate lability. Particle cohesiveness, as approximated by the second‐order rate constant for particle aggregation, was negatively correlated with trophic regime: particles appeared more cohesive in low‐productivity regions than in high‐productivity regions.
Africa's Crustal Architecture Inferred From Probabilistic and Perturbational Inversion of Ambient Noise: ADAMA
Authors: Olugboji Tolulope , Xue Siyu , Legre Jean‐Joel , Tamama Yuri 
Published: January 2024

AbstractAfrica's continental crust hosts a variety of geologic terrains and is crucial for understanding the evolution of its longest‐lived cratons. However, few of its seismological models are yet to incorporate the largest continent‐wide noise dispersion data sets. Here, we report on new insights into Africa's crustal architecture obtained using a new data set and model assessment product, ADAMA, which comprises a large ensemble of short‐period surface wave dispersion measurements: 5–40 s. We construct a continent‐wide model of Africa's Crust Evaluated with ADAMA's Rayleigh Phase maps (ACE‐ADAMA‐RP). Dispersion maps, and uncertainties, are obtained with a probabilistic approach. This model update, and a crustal taxonomy derived from unsupervised machine learning, reveals that the architecture of Africa's crust can be classified into two main types: primitive (C1: faster velocities with little gradients) and modified (C2–C4: slower velocities in the shallow crust with more pronounced gradients). The Archean shields are “primitive,” showing little variation or secular evolution. The basins, orogens, and continental margins are “modified” and retain imprints of surface deformation. The crustal taxonomy is obtained without a‐priori geological information and differs from previous classification schemes. While most of our reported features are robust, probabilistic modeling suggests caution in the quantitative interpretations where illumination is compromised by low‐quality measurements, sparse coverage or both. Future extension of our approach to other complementary seismological and geophysical data sets—for example, multimode earthquake dispersion, receiver functions, gravity, and mineral physics, will enable continent‐wide lithospheric modeling that extends resolution to the upper mantle.
Quasiperiodic Emissions: Fine Structure Corresponding to a Bouncing Wave
Authors: Němec F. , Santolík O. , Hospodarsky G. B. , Kurth W. S. 
Published: January 2024

AbstractQuasiperiodic (QP) emissions are whistler‐mode electromagnetic waves observed in the Earth's inner magnetosphere whose intensity has a nearly periodic time modulation with typical modulation periods on the order of minutes. Some events exhibit, on top of the main modulation period, an additional fine inner modulation with modulation periods on the order of seconds. We use high‐resolution multi‐component electromagnetic wave data obtained by the Van Allen Probes spacecraft to investigate one such event. Detailed wave analysis demonstrates that the fine inner modulation is due to a wave packet bouncing back and forth between the hemispheres. The presence of a density duct is important for the formation of the event, as demonstrated by the increased ratio of wave power propagating away from the equator (a tentative source region) within the duct. The main QP modulation period corresponds to the plasma number density modulation observed just outside the plasmasphere.
Effects of Stratospheric Warming on Ural blocking Events in Winter
Authors: Li Zhihao , Dai Guokun , Mu Mu 
Published: January 2024

AbstractUtilizing the Open Integrated Forecasting System, the responses of Ural blocking (UB) to different stratospheric warming scenarios are investigated. Numerical results show that stratospheric warming with moderate strength in minor patterns prolongs the UB duration and enhances its intensity, while strong stratospheric warming in minor patterns tends to shorten its duration and weaken its intensity, even leading to the collapse of the UB events. Further diagnosis reveals that the planetary wave activity flux propagates downward from the stratosphere to the troposphere after stratospheric warming. Moreover, the convergence of planetary wave activity flux is a key factor for UB enhancement and maintenance. In addition, the weakened meridional temperature gradients, decelerated zonal westerly winds, and a reduced meridional potential vorticity gradient (PVy) result in UB enhancement in response to stratospheric warming with moderate strength. As stratospheric warming strengthens, planetary wave activity flux diverges, westerly winds in the tropospheric mid‐latitudes accelerate and the PVy in the Ural sector enlarges, which further weakens UB. Regarding the stratospheric perturbations in major patterns, they have similar influences on UB events, that is, UB enhances with moderate stratospheric warming and weakens with strong warming. However, the strengthened warming would trigger UB re‐enhancement, which is closely associated with anomalous activities of tropospheric synoptic‐scale waves induced by stratospheric perturbations. These results reveal UB events respond differently to stratospheric warming with various intensities and patterns in the short term, which makes a contribution to understanding stratosphere‐troposphere coupling.