bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lewy bodies, iron, inflammation and neuromelanin: pathological aspects underlying Parkinson’s disease
Authors: Riederer Peter , Nagatsu Toshiharu , Youdim Moussa B. H. , Wulf Max , Dijkstra Johannes M. , Sian-Huelsmann Jeswinder 
Published: April 2023

AbstractSince the description of some peculiar symptoms by James Parkinson in 1817, attempts have been made to define its cause or at least to enlighten the pathology of “Parkinson’s disease (PD).” The vast majority of PD subtypes and most cases of sporadic PD share Lewy bodies (LBs) as a characteristic pathological hallmark. However, the processes underlying LBs generation and its causal triggers are still unknown. ɑ-Synuclein (ɑ-syn, encoded by the SNCA gene) is a major component of LBs, and SNCA missense mutations or duplications/triplications are causal for rare hereditary forms of PD. Thus, it is imperative to study ɑ-syn protein and its pathology, including oligomerization, fibril formation, aggregation, and spreading mechanisms. Furthermore, there are synergistic effects in the underlying pathogenic mechanisms of PD, and multiple factors—contributing with different ratios—appear to be causal pathological triggers and progression factors. For example, oxidative stress, reduced antioxidative capacity, mitochondrial dysfunction, and proteasomal disturbances have each been suggested to be causal for ɑ-syn fibril formation and aggregation and to contribute to neuroinflammation and neural cell death. Aging is also a major risk factor for PD. Iron, as well as neuromelanin (NM), show age-dependent increases, and iron is significantly increased in the Parkinsonian substantia nigra (SN). Iron-induced pathological mechanisms include changes of the molecular structure of ɑ-syn. However, more recent PD research demonstrates that (i) LBs are detected not only in dopaminergic neurons and glia but in various neurotransmitter systems, (ii) sympathetic nerve fibres degenerate first, and (iii) at least in “brain-first” cases dopaminergic deficiency is evident before pathology induced by iron and NM. These recent findings support that the ɑ-syn/LBs pathology as well as iron- and NM-induced pathology in “brain-first” cases are important facts of PD pathology and via their interaction potentiate the disease process in the SN. As such, multifactorial toxic processes posted on a personal genetic risk are assumed to be causal for the neurodegenerative processes underlying PD. Differences in ratios of multiple factors and their spatiotemporal development, and the fact that common triggers of PD are hard to identify, imply the existence of several phenotypical subtypes, which is supported by arguments from both the “bottom-up/dual-hit” and “brain-first” models. Therapeutic strategies are necessary to avoid single initiation triggers leading to PD.
Unique immune and inflammatory cytokine profiles may define long COVID syndrome
Authors: Allan-Blitz Lao-Tzu , Akbari Omid , Kojima Noah , Saavedra Edwyn , Chellamuthu Prithivi , Denny Nicholas , MacMullan Melanie A. , Hess Victoria , Shacreaw Maria , Brobeck Matthew , Turner Frederick , Slepnev Vladimir I. , Ibrayeva Albina , Klausner Jeffrey D. 
Published: April 2023

Abstract
Purpose
Long COVID is estimated to occur in 5–10% of individuals after acute SARS-CoV-2 infection. However, the pathophysiology driving the disease process is poorly understood.

Methods
We evaluated urine and plasma inflammatory and immune cytokine profiles in 33 individuals with long COVID compared to 33 who were asymptomatic and recovered, and 34 without prior infection.

Results
Mean urinary leukotriene E4 was significantly elevated among individuals with long COVID compared to asymptomatic and recovered individuals (mean difference 774.2 pg/mL; SD 335.7) and individuals without prior SARS-CoV-2 infection (mean difference 503.1 pg/ml; SD 467.7). Plasma chemokine ligand 6 levels were elevated among individuals with long COVID compared to individuals with no prior SARS-CoV-2 infection (mean difference 0.59 units; SD 0.42). We found no significant difference in angiotensin-converting enzyme 2 antibody levels. Plasma tumor necrosis factor receptor-associated factor 2 (TRAF2) levels were reduced among individuals with long COVID compared to individuals who were asymptomatic and recovered (mean difference = 0.6 units, SD 0.46). Similarly, the mean level of Sarcoma Homology 2-B adapter protein 3 was 3.3 units (SD 1.24) among individuals with long COVID, lower than 4.2 units (SD 1.1) among individuals with recovered, asymptomatic COVID.

Conclusion
Our findings suggest that further studies should be conducted to evaluate the role of leukotriene E4 as a potential biomarker for a diagnostic test. Furthermore, based on reductions in TRAF2, long COVID may be driven in part by impaired TRAF2-dependent immune-mediated inflammation and potentially immune exhaustion.
General patterns of beavers’ selective foraging: how to evaluate the effects of a re-emerging driver of vegetation change along Central European small watercourses
Authors: Juhász Erika , Molnár Zsolt , Bede-Fazekas Ákos , Biró Marianna 
Published: April 2023

AbstractAlong small watercourses, the growth and renewal of native willows and poplars (Salicaceae species) are hindered by the effects of past and recent man-made landscape alteration and climate change, while the selective foraging of the beaver (Castor fiber) is also becoming an increasingly important driver. Knowledge about foraging decisions can refine predictions about vegetational processes and help to develop better nature conservation and forest management strategies. We surveyed the woody plant supply (13,304 units) and its utilization by the beaver at 11 study sites along Central European small watercourses, at two fixed distances from the water. We collected information about the taxon, trunk diameter, and type of utilization (cutting, carving, debarking) of each unit. We built (generalized) linear mixed models aimed at answering questions regarding taxon and diameter preference, their interrelatedness, and their importance in foraging decisions. All of the factors examined had a significant effect on foraging decisions. Utilization was mostly explained by the taxon, with Salicaceae species being generally preferred and utilized in all diameter classes with a high ratio. Several further genera were frequently utilized (mainly Cornus and Ulmus), while others were almost completely avoided (including invasive Amorpha and Robinia). The beavers preferred units with a diameter of 5–9 cm. The type of utilization depended primarily on diameter class. Because native softwoods are the most affected by beaver impact, regardless of trunk diameter, their survival and regrowth should be consciously supported by increasing the water table and improving hydrological conditions.
Parameterizing the cost function of dynamic time warping with application to time series classification
Authors: Herrmann Matthieu , Tan Chang Wei , Webb Geoffrey I. 
Published: April 2023

AbstractDynamic time warping (DTW) is a popular time series distance measure that aligns the points in two series with one another. These alignments support warping of the time dimension to allow for processes that unfold at differing rates. The distance is the minimum sum of costs of the resulting alignments over any allowable warping of the time dimension. The cost of an alignment of two points is a function of the difference in the values of those points. The original cost function was the absolute value of this difference. Other cost functions have been proposed. A popular alternative is the square of the difference. However, to our knowledge, this is the first investigation of both the relative impacts of using different cost functions and the potential to tune cost functions to different time series classification tasks. We do so in this paper by using a tunable cost function $$\lambda _{\gamma }$$

λ
γ

with parameter $$\gamma $$
γ
. We show that higher values of $$\gamma $$
γ
place greater weight on larger pairwise differences, while lower values place greater weight on smaller pairwise differences. We demonstrate that training $$\gamma $$
γ
significantly improves the accuracy of both the $${ DTW }$$

DTW

nearest neighbor and Proximity Forest classifiers.
Design Fire Methodology for Vehicle Spaces Onboard Ships
Authors: Koromila Ioanna A. , Spyrou Kostas J. 
Published: April 2023

AbstractThe purpose of this paper is to contribute towards establishing procedures of assessment of the fire safety of Ro–Ro ship cargo spaces, by employing suitable design fires. Data collected from fire experiments involving vehicles are utilized in order to deduce representative heat release rates for common types of passenger cars and heavy goods vehicles (HGVs). An existing mathematical scheme for generating parametric heat release rate curves is extended for handling vehicle fire scenarios. The methodology is demonstrated through a case study. In particular, the Fire Dynamics Simulator (FDS) code is used for investigating fire propagation on the vehicle deck of a Ro–Ro ship, initiated from a single HGV. On this deck are assumed to be transported a combination of cars and HGVs. The evolution of the fire is assessed assuming different ventilation conditions. The circumstances for spreading to adjacent vehicles are examined. Human survivability and the time that the deck remains accessible are evaluated by considering the International Maritime Organization (IMO) life safety performance criteria.
Inhibition of p38 ameliorates axonal loss with modulation of autophagy in TNF-induced optic nerve damage
Authors: Sase Kana , Tsukahara Chihiro , Fujita Naoki , Arizono Ibuki , Otsubo Mizuki , Kitaoka Yasushi 
Published: April 2023

Abstract
Purpose
A relationship between p38 and autophagy remains debated. The aim of the current study is to investigate whether an inhibitor of p38 prevents axon loss induced by TNF and whether it affects autophagy.

Methods
Rats were given intravitreal injection of TNF, TNF plus SB203580, a p38 inhibitor, or SB203580 alone. Immunoblot analysis was performed to examine p62 expression which is a marker of autophagic flux and LC3-II expression which is an autophagy marker in optic nerves 1 week after intravitreal injection. Morphometric analysis of axons was performed to evaluate the effects of SB203580 against TNF-induced optic nerve damage 2 weeks after intravitreal injection. Immunohistochemical analysis was performed to evaluate the expressions of LC3, neurofilament, phosphorylated p38 and p62 in the optic nerve.

Results
Quantification of axon number showed that TNF-induced axon loss was significantly protected by SB203580. Immunoblot analysis showed that the increase of p62 induced by TNF was totally eliminated by SB203580, and the SB203580 alone injection decreased the expression of p62. The level of LC3-II was significantly upregulated in the TNF plus SB203580 group compared with the TNF alone group, and the SB203580 alone injection increased the expression of LC3-II. Immunohistochemical analysis showed that LC3 immunoreactivity was found in the neurofilament positive fibers and that these immunoreactivities were enhanced by SB203580. Some colocalizations of p-p38 and p62 were observed in the TNF-treated optic nerve.

Conclusion
These results suggest that inhibition of p38 exerts axonal protection with upregulated autophagy in TNF-induced optic nerve damage.
Analysis of (sub-)Riemannian PDE-G-CNNs
Authors: Bellaard Gijs , Bon Daan L. J. , Pai Gautam , Smets Bart M. N. , Duits Remco 
Published: April 2023

AbstractGroup equivariant convolutional neural networks (G-CNNs) have been successfully applied in geometric deep learning. Typically, G-CNNs have the advantage over CNNs that they do not waste network capacity on training symmetries that should have been hard-coded in the network. The recently introduced framework of PDE-based G-CNNs (PDE-G-CNNs) generalizes G-CNNs. PDE-G-CNNs have the core advantages that they simultaneously (1) reduce network complexity, (2) increase classification performance, and (3) provide geometric interpretability. Their implementations primarily consist of linear and morphological convolutions with kernels. In this paper, we show that the previously suggested approximative morphological kernels do not always accurately approximate the exact kernels accurately. More specifically, depending on the spatial anisotropy of the Riemannian metric, we argue that one must resort to sub-Riemannian approximations. We solve this problem by providing a new approximative kernel that works regardless of the anisotropy. We provide new theorems with better error estimates of the approximative kernels, and prove that they all carry the same reflectional symmetries as the exact ones. We test the effectiveness of multiple approximative kernels within the PDE-G-CNN framework on two datasets, and observe an improvement with the new approximative kernels. We report that the PDE-G-CNNs again allow for a considerable reduction of network complexity while having comparable or better performance than G-CNNs and CNNs on the two datasets. Moreover, PDE-G-CNNs have the advantage of better geometric interpretability over G-CNNs, as the morphological kernels are related to association fields from neurogeometry.
Maximum Principle for Stochastic Control of SDEs with Measurable Drifts
Authors: Menoukeu-Pamen Olivier , Tangpi Ludovic 
Published: April 2023

AbstractIn this paper, we consider stochastic optimal control of systems driven by stochastic differential equations with irregular drift coefficient. We establish a necessary and sufficient stochastic maximum principle. To achieve this, we first derive an explicit representation of the first variation process (in the Sobolev sense) of the controlled diffusion. Since the drift coefficient is not smooth, the representation is given in terms of the local time of the state process. Then we construct a sequence of optimal control problems with smooth coefficients by an approximation argument. Finally, we use Ekeland’s variational principle to obtain an approximating adjoint process from which we derive the maximum principle by passing to the limit. The work is notably motivated by the optimal consumption problem of investors paying wealth tax.
Outcomes of science-industry collaboration: factors and interdependencies
Authors: Cantner Uwe , Kalthaus Martin , Yarullina Indira 
Published: April 2023

AbstractWe analyse the outcomes for scientists from science-industry collaboration projects and study the conditions under which these outcomes emerge. While previous research analyses the motivations for scientists to collaborate and the characteristics of such collaborations, we focus on the generated outcomes. We provide a new conceptualisation of collaboration outcomes and distinguish three different types: scientific outcomes, commercialisable outcomes, and follow-up cooperation. We argue that scientific factors influence the generation of scientific outcomes, and economic factors the generation of commercialisable outcomes, accordingly; interaction factors are proposed to influence the emergence of follow-up cooperation. We further propose that these outcomes depend on each other and hence are co-generated. We test our propositions with survey data from scientists in the German state of Thuringia. We develop novel survey items about characteristics of scientists’ last collaboration with an industry partner and its outcomes. Multivariate probit estimations show that scientific factors positively relate to scientific outcomes, and interaction factors are relevant for follow-up cooperation. However, when it comes to economic factors, we find mixed evidence of their relation to commercialisable outcomes. The outcome interdependence exists between scientific outcomes and the other two types of outcomes but not between commercialisable outcomes and follow-up cooperation. Our results can be used by policymakers and science managers to design and strengthen the support for collaboration projects.
Adaptive cooperative coevolutionary differential evolution for parallel feature selection in high-dimensional datasets
Authors: Firouznia Marjan , Ruiu Pietro , Trunfio Giuseppe A. 
Published: April 2023

AbstractIn many fields, it is a common practice to collect large amounts of data characterized by a high number of features. These datasets are at the core of modern applications of supervised machine learning, where the goal is to create an automatic classifier for newly presented data. However, it is well known that the presence of irrelevant features in a dataset can make the learning phase harder and, most importantly, can lead to suboptimal classifiers. Consequently, it is becoming increasingly important to be able to select the right subset of features. Traditionally, optimization metaheuristics have been used with success in the task of feature selection. However, many of the approaches presented in the literature are not applicable to datasets with thousands of features because of the poor scalability of optimization algorithms. In this article, we address the problem using a cooperative coevolutionary approach based on differential evolution. In the proposed algorithm, parallelized for execution on shared-memory architectures, a suitable strategy for reducing the dimensionality of the search space and adjusting the population size during the optimization results in significant performance improvements. A numerical investigation on some high-dimensional and medium-dimensional datasets shows that, in most cases, the proposed approach can achieve higher classification performance than other state-of-the-art methods.
Recent advances in CAR T-cell therapy for lymphoma in China
Authors: Che Yuxuan , Sun Xiuhua 
Published: April 2023

AbstractLymphoma is a hematologic malignancy which mainly consists of Hodgkin lymphoma (HL) and non-Hodgkin lymphoma (NHL). Although systemic chemotherapy, radiotherapy, and other advanced therapeutics, including rituximab or immune checkpoint inhibitors, have improved the prognosis in recent decades, there are still a number of patients with relapsed or refractory (R/R) lymphoma with a poor prognosis. Chimeric antigen receptor (CAR) T-cell therapy has provided a curative option for patients with relapsed or refractory lymphoma. Numerous clinical trials have been conducted worldwide and presented inspiring results that give insight into this breakthrough therapy. The development of cancer cell therapy in China has been rapid in the past years and dominates the field with the USA. This review aims to summarize the published results of CAR T-cell therapy alone or in combination with other therapies in mainland China, both in R/R NHL and R/R HL.
Bidiagonal factorization of tetradiagonal matrices and Darboux transformations
Authors: Branquinho Amílcar , Foulquié-Moreno Ana , Mañas Manuel 
Published: April 2023

AbstractRecently a spectral Favard theorem for bounded banded lower Hessenberg matrices that admit a positive bidiagonal factorization was presented. These type of matrices are oscillatory. In this paper the Lima–Loureiro hypergeometric multiple orthogonal polynomials and the Jacobi–Piñeiro multiple orthogonal polynomials are discussed at the light of this bidiagonal factorization for tetradiagonal matrices. The Darboux transformations of tetradiagonal Hessenberg matrices is studied and Christoffel formulas for the elements of the bidiagonal factorization are given, i.e., the bidiagonal factorization is given in terms of the recursion polynomials evaluated at the origin.
GHRH + arginine test and body mass index: do we need to review diagnostic criteria for GH deficiency?
Authors: Gasco V. , Cuboni D. , Varaldo E. , Bioletto F. , Berton A. M. , Bona C. , Prencipe N. , Ghigo E. , Maccario M. , Grottoli S. 
Published: April 2023

Abstract
Introduction
The proportion of patients with low GH response to provocative tests increases with the number of other pituitary hormone deficiencies, reason why in panhypopituitary patients GH stimulation tests may be unnecessary to diagnose GH deficiency (GHD)

Purpose
To re-evaluate the diagnostic cut-offs of GH response to GHRH + arginine (ARG) test related to BMI, considering the patients’ pituitary function as the gold standard for the diagnosis of GHD.

Methods
The GH responses to GHRH + ARG were studied in 358 patients with history of hypothalamic-pituitary disease. GHD was defined by the presence of at least 3 other pituitary deficits (n = 223), while a preserved somatotropic function was defined by the lack of other pituitary deficits and an IGF-I SDS ≥ 0 (n = 135). The cut-off with the best sensitivity (SE) and specificity (SP), was identified for each BMI category using the ROC curve analysis. To avoid over-diagnosis of GHD we subsequently searched for the cut-offs with a SP ≥ 95%.

Results
The best GH cut-off was 8.0 μg/l (SE 95%, SP 100%) in lean, 7.0 μg/l (SE 97.3%, SP 82.8%) in overweight, and 2.8 μg/l (SE 84.3%, SP 91.7%) in obese subjects. The cut-off with a SP ≥ 95% was 2.6 μg/l (SE 68.5%, SP 96.6%) in overweight and 1.75 μg/l (SE 70.0%, SP 97.2%) in obese subjects.

Conclusions
This is the first study that evaluates the diagnostic cut-offs of GH response to GHRH + ARG related to BMI using a clinical definition of GHD as gold standard. Our results suggest that with this new approach, the GHRH + ARG cut-offs should be revised to avoid GHD over-diagnosis.
Effects of coals microscale structural features on their mechanical properties, propensity to crushing and fine dust formation
Authors: Kossovich Elena , Epshtein Svetlana , Krasilova Vera , Hao Jie , Minin Maxim 
Published: April 2023

AbstractThe work is dedicated to revealing the structural features of coals with different ranks, such as anthracites, metaanthracite and graphite, that determine their ability to crush and form fine dust. For this purpose, a combination of various nanoindentation techniques and Raman spectroscopy was used. The mechanical behavior of the selected coals was investigated by cyclic nanoindentation with increasing peak load and quasi-static loading. The alteration of the mechanical properties was studied by analysis of elastic moduli and damage indices Rw. Three groups of coals were identified based on their propensity to crushing during cyclic nanoindentation. Coals assigned to the first and second groups are characterized by local destruction in the contact zone with the indenter and the formation of a core of crushed material. Coals assigned to the third group are characterized by bulk destruction (outside the zone of contact with the indenter). In general, the ability of coals to fracture under mechanical loading decreases in the series of metamorphism due to microscale compaction of vitrinite matter. In the series of anthracite, metaanthracite and graphite, it is established that the coal matter compaction takes place for the anthracite and metaanthracite, whereas graphite reveals rather different behavior due to abrupt change of its structure. The ratios between the amorphous and crystalline phases of carbon (S) were determined by deconvolution of coals Raman spectra. The propensity of coals to crushing (a damage index Rw) increases with growth of the proportion of amorphous carbon in the coal matter. For the considered coals and metaanthracite, it is established that the proneness to destruction outside the contact zone with the indenter is determined by the ratio of amorphous and crystalline carbon of 1 and higher. When S parameter is lower than 1, the coals are being crushed only in the zone of contact with the indenter.