bluuebunny/crossref_metadata_2025_split huggingface dataset:
DPP-4 inhibitors sitagliptin and PF-00734,200 mitigate dopaminergic neurodegeneration, neuroinflammation and behavioral impairment in the rat 6-OHDA model of Parkinson’s disease
Authors: Yu Seong-Jin , Wang Yun , Shen Hui , Bae Eun-Kyung , Li Yazhou , Sambamurti Kumar , Tones Michael A. , Zaleska Margaret M. , Hoffer Barry J. , Greig Nigel H. 
Published: April 2024

AbstractEpidemiological studies report an elevated risk of Parkinson's disease (PD) in patients with type 2 diabetes mellitus (T2DM) that is mitigated in those prescribed dipeptidyl peptidase 4 (DPP-4) inhibitors. With an objective to characterize clinically translatable doses of DPP-4 inhibitors (gliptins) in a well-characterized PD rodent model, sitagliptin, PF-00734,200 or vehicle were orally administered to rats initiated either 7-days before or 7-days after unilateral medial forebrain bundle 6-hydroxydopamine (6-OHDA) lesioning. Measures of dopaminergic cell viability, dopamine content, neuroinflammation and neurogenesis were evaluated thereafter in ipsi- and contralateral brain. Plasma and brain incretin and DPP-4 activity levels were quantified. Furthermore, brain incretin receptor levels were age-dependently evaluated in rodents, in 6-OHDA challenged animals and human subjects with/without PD. Cellular studies evaluated neurotrophic/neuroprotective actions of combined incretin administration. Pre-treatment with oral sitagliptin or PF-00734,200 reduced methamphetamine (meth)-induced rotation post-lesioning and dopaminergic degeneration in lesioned substantia nigra pars compacta (SNc) and striatum. Direct intracerebroventricular gliptin administration lacked neuroprotective actions, indicating that systemic incretin-mediated mechanisms underpin gliptin-induced favorable brain effects. Post-treatment with a threefold higher oral gliptin dose, likewise, mitigated meth-induced rotation, dopaminergic neurodegeneration and neuroinflammation, and augmented neurogenesis. These gliptin-induced actions associated with 70–80% plasma and 20–30% brain DPP-4 inhibition, and elevated plasma and brain incretin levels. Brain incretin receptor protein levels were age-dependently maintained in rodents, preserved in rats challenged with 6-OHDA, and in humans with PD. Combined GLP-1 and GIP receptor activation in neuronal cultures resulted in neurotrophic/neuroprotective actions superior to single agonists alone. In conclusion, these studies support further evaluation of the repurposing of clinically approved gliptins as a treatment strategy for PD.
Segmentation and deep learning to digitalize the kinematics of flow-type landslides
Authors: Choi Clarence E. , Liang Zhengyu 
Published: April 2024

AbstractFlow-type landslides, including subaerial and submarine debris flows, have poor spatiotemporal predictability. Therefore, researchers rely heavily on experimental evidence in revealing complex flow mechanisms and evaluating theoretical models. To measure the velocity field of experimental flows, conventional image analysis tools for measuring soil deformation and hydraulics have been borrowed. However, these tools were not developed for capturing the kinematics of fast-moving soil–water mixtures over complex terrain under non-uniform lighting conditions. In this study, a new framework based on deep learning was used to automatically digitalize the kinematics of experimental flow-type landslides. Captured images were broken into sequences and binarized using a fully convolutional neural network (FCNN). The proposed framework was demonstrated to outperform classic image processing algorithms (e.g., particle image velocimetry, trainable Weka segmentation, and thresholding algorithms) over a wide range of experimental conditions. The FCNN model was even able to process images from consumer-grade cameras under complex shadow, light, and boundary conditions. This feature is most useful for field-scale experimentation. With fewer than 15 annotated training images, the FCNN digitalized experimental flows with an accuracy of 97% in semantic segmentation.
Analysis of genes related to xylem cell wall development based on transcriptomics in Populus alba ‘Berolinensis’ tension wood
Authors: Feng Lin , He Youchao , Li Xu , Zhou Meiqi , Wang Chao 
Published: April 2024

AbstractPopulus alba ‘Berolinensis’ is a fast-growing, high-yielding species with strong biotic and abiotic stress resistance, and widely planted for timber, shelter belts and aesthetic purposes. In this study, molecular development is explored and the important genes regulating xylem formation in P. alba ‘Berolinensis’ under artificial bending treatments was identified. Anatomical investigation indicated that tension wood (TW) was characterized by eccentric growth of xylem and was enriched in cellulose; the degree of lignification was lower than for normal wood (NW) and opposite wood (OW). RNA-Seq-based transcriptome analysis was performed using developing xylem from three wood types (TW, OW and NW). A large number of differentially expressed genes (DEGs) were screened and 4889 counted. In GO and KEGG enrichment results, genes involved in plant hormone signal transduction, phenylpropanoid biosynthesis, and cell wall and secondary cell wall biogenesis play major roles in xylem development under artificial bending. Eight expansin (PalEXP) genes were identified from the RNA-seq data; four were differentially expressed during tension wood formation. Phylogenetic analysis indicated that PalEXLB1 belongs to the EXPB subfamily and that the other PalEXPs are members of the EXPA subfamily. A transcriptional regulatory network construction showed 10 transcription factors located in the first and second layers upstream of EXP, including WRKY, ERF and bHLH. RT‒qPCR analysis in leaves, stems and roots combined with transcriptome analysis suggests that PalEXPA2, PalEXPA4 and PalEXPA15 play significant regulatory roles in cell wall formation during tension wood development. The candidate genes involved in xylem cell wall development during tension wood formation marks an important step toward identifying the molecular regulatory mechanism of xylem development and wood property improvement in P. alba ‘Berolinensis’.
Hyperbolic problems with totally characteristic boundary
Authors: Ruan Zhuoping , Witt Ingo 
Published: April 2024

AbstractWe study first-order symmetrizable hyperbolic $$N\times N$$

N
×
N

systems in a spacetime cylinder whose lateral boundary is totally characteristic. In local coordinates near the boundary at $$x=0$$

x
=
0

, these systems take the form $$\begin{aligned} \partial _t u + {{\mathcal {A}}}(t,x,y,xD_x,D_y) u = f(t,x,y), \quad (t,x,y)\in (0,T)\times {{\mathbb {R}}}_+\times {{\mathbb {R}}}^d, \end{aligned}$$

∂
t

u
+
A

(
t
,
x
,
y
,
x

D
x

,

D
y

)

u
=
f

(
t
,
x
,
y
)

,

(
t
,
x
,
y
)

∈

(
0
,
T
)

×

R
+

×

R

d

,

where $${{\mathcal {A}}}(t,x,y,xD_x,D_y)$$

A
(
t
,
x
,
y
,
x

D
x

,

D
y

)

is a first-order differential operator with coefficients smooth up to $$x=0$$

x
=
0

and the derivative with respect to x appears in the combination $$xD_x$$

x

D
x

. No boundary conditions are required in such a situation and corresponding initial-boundary value problems are effectively Cauchy problems. We introduce a certain scale of Sobolev spaces with asymptotics and show that the Cauchy problem for the operator $$\partial _t + {{\mathcal {A}}}(t,x,y,xD_x,D_y)$$

∂
t

+
A

(
t
,
x
,
y
,
x

D
x

,

D
y

)

is well-posed in that scale. More specifically, solutions u exhibit formal asymptotic expansions of the form $$\begin{aligned} u(t,x,y) \sim \sum _{(p,k)} \frac{(-1)^k}{k!}x^{-p} \log ^k \!x \, u_{pk}(t,y) \quad \hbox { as}\ x\rightarrow +0 \end{aligned}$$

u

(
t
,
x
,
y
)

∼

∑

(
p
,
k
)

(
-
1
)

k

k
!

x

-
p

log
k

x

u

pk

(
t
,
y
)

as

x
→
+
0

where $$(p,k)\in {{\mathbb {C}}}\times {{\mathbb {N}}}_0$$

(
p
,
k
)

∈
C
×

N
0

and $$\Re p\rightarrow -\infty $$

ℜ
p
→
-
∞

as $$|p|\rightarrow \infty $$

|
p
|
→
∞

, provided that the right-hand side f and the initial data $$u|_{t=0}$$

u
|

t
=
0

admit asymptotic expansions as $$x \rightarrow +0$$

x
→
+
0

of a similar form, with the singular exponents p and their multiplicities unchanged. In fact, the coefficients $$u_{pk}$$

u

pk

are, in general, not regular enough to write the terms appearing in the asymptotic expansions as tensor products. This circumstance requires an additional analysis of the function spaces. In addition, we demonstrate that the coefficients $$u_{pk}$$

u

pk

solve certain explicitly known first-order symmetrizable hyperbolic systems in the lateral boundary. Especially, it follows that the Cauchy problem for the operator $$\partial _t+{{\mathcal {A}}}(t,x,y,xD_x,D_y)$$

∂
t

+
A

(
t
,
x
,
y
,
x

D
x

,

D
y

)

is well-posed in the scale of standard Sobolev spaces $$H^s((0,T)\times {{\mathbb {R}}}_+^{1+d})$$

H
s

(

(
0
,
T
)

×

R
+

1
+
d

)

.
Cytogenetic and pathologic characterization of MYC-rearranged B-cell lymphomas in pediatric and young adult patients
Authors: Gagnon Marie-France , Bruehl Frido K. , Sill Daniel R. , Meyer Reid G. , Greipp Patricia T. , Hoppman Nicole L. , Xu Xinjie , Baughn Linda B. , Peterson Jess F. , McPhail Ellen D. , Ketterling Rhett P. , King Rebecca L. 
Published: April 2024

AbstractMYC-rearranged B-cell lymphoma (BCL) in the pediatric/young adult (YA) age group differs substantially in disease composition from adult cohorts. However, data regarding the partner genes, concurrent rearrangements, and ultimate diagnoses in these patients is scarce compared to that in adult cohorts. We aimed to characterize the spectrum of MYC-rearranged (MYC-R) mature, aggressive BCL in the pediatric/YA population. A retrospective study of morphologic, immunophenotypic, and fluorescence in situ hybridization (FISH) results of patients age ≤ 30 years with suspected Burkitt lymphoma (BL), diffuse large B-cell lymphoma (DLBCL) or high-grade B-cell lymphoma (HGBCL), and a MYC-R by FISH between 2013–2022 was performed. Two-hundred fifty-eight cases (129 (50%) pediatric (< 18 years) and 129 (50%) YA (18–30 years)) were included. Most MYC-R BCL in pediatric (89%) and YA (66%) cases were BL. While double-hit (DH) cytogenetics (MYC with BCL2 and/or BCL6-R, HGBCL-DH) was rare in the pediatric population (2/129, 2%), HGBCL-DH increased with age and was identified in 17/129 (13%) of YA cases. Most HGBCL-DH had MYC and BCL6-R, while BCL2-R were rare in both groups (3/258, 1%). MYC-R without an IG partner was more common in the YA group (14/116 (12%) vs 2/128 (2%), p = 0.001). The pediatric to YA transition is characterized by decreasing frequency in BL and increasing genetic heterogeneity of MYC-R BCL, with emergence of DH-BCL with MYC and BCL6-R. FISH to evaluate for BCL2 and BCL6 rearrangements is likely not warranted in the pediatric population but should continue to be applied in YA BCL.
The impacts of host association and perturbation on symbiont fitness
Authors: Hoang Kim L. , Salguero-Gómez Roberto , Pike Victoria L. , King Kayla C. 
Published: April 2024

AbstractSymbiosis can benefit hosts in numerous ways, but less is known about whether interactions with hosts benefit symbionts—the smaller species in the relationship. To determine the fitness impact of host association on symbionts in likely mutualisms, we conducted a meta-analysis across 91 unique host-symbiont pairings under a range of spatial and temporal contexts. Specifically, we assess the consequences to symbiont fitness when in and out of symbiosis, as well as when the symbiosis is under suboptimal or varying environments and biological conditions (e.g., host age). We find that some intracellular symbionts associated with protists tend to have greater fitness when the symbiosis is under stressful conditions. Symbionts of plants and animals did not exhibit this trend, suggesting that symbionts of multicellular hosts are more robust to perturbations. Symbiont fitness also generally increased with host age. Lastly, we show that symbionts able to proliferate in- and outside host cells exhibit greater fitness than those found exclusively inside or outside cells. The ability to grow in multiple locations may thus help symbionts thrive. We discuss these fitness patterns in light of host-driven factors, whereby hosts exert influence over symbionts to suit their own needs.
Pediatric congenital pulmonary malformations: key findings at imaging
Authors: Fichera Giulia , Cavaliere Annachiara , Causin Francesco , Zuliani Monica , Bisogno Gianni , Rea Federico , Stramare Roberto , Giraudo Chiara 
Published: April 2024

AbstractPediatric congenital pulmonary malformations are rare abnormalities which may affect airways, pulmonary parenchyma, and vasculature and diagnostic imaging plays a significant role in their identification and characterization. Although, nowadays, often the diagnosis of this heterogeneous group of malformations is performed prenatally by ultrasound and/or fetal magnetic resonance, after birth, computed tomography represents the main technique. Radiographs are often used as first line diagnostic tool while magnetic resonance demonstrated to be especially beneficial to investigate some malformations such as bronchogenic cysts. Therefore, radiologists should be aware of the main features associated with such alterations to guarantee a prompt diagnosis and, if necessary, guide towards the optimal treatment. Aim of this pictorial review is to provide a comprehensive overview of the typical features of congenital pulmonary malformations at imaging supporting general and pediatric radiologists in the diagnostic process.
Modeling and prediction of tribological properties of copper/aluminum-graphite self-lubricating composites using machine learning algorithms
Authors: Ning Huifeng , Chen Faqiang , Su Yunfeng , Li Hongbin , Fan Hengzhong , Song Junjie , Zhang Yongsheng , Hu Litian 
Published: April 2024

AbstractThe tribological properties of self-lubricating composites are influenced by many variables and complex mechanisms. Data-driven methods, including machine learning (ML) algorithms, can yield a better comprehensive understanding of complex problems under the influence of multiple parameters, typically for how tribological performances and material properties correlate. Correlation of friction coefficients and wear rates of copper/aluminum-graphite (Cu/Al-graphite) self-lubricating composites with their inherent material properties (composition, lubricant content, particle size, processing process, and interfacial bonding strength) and the variables related to the testing method (normal load, sliding speed, and sliding distance) were analyzed using traditional approaches, followed by modeling and prediction of tribological properties through five different ML algorithms, namely support vector machine (SVM), K-Nearest neighbor (KNN), random forest (RF), eXtreme gradient boosting (XGBoost), and least-squares boosting (LSBoost), based on the tribology experimental data. Results demonstrated that ML models could satisfactorily predict friction coefficient and wear rate from the material properties and testing method variables data. Herein, the LSBoost model based on the integrated learning algorithm presented the best prediction performance for friction coefficients and wear rates, with R2 of 0.9219 and 0.9243, respectively. Feature importance analysis also revealed that the content of graphite and the hardness of the matrix have the greatest influence on the friction coefficients, and the normal load, the content of graphite, and the hardness of the matrix influence the wear rates the most.
A real-world exploration into clinical outcomes of direct oral anticoagulant therapy in people with chronic kidney disease: a large hospital-based study
Authors: Nwanosike Ezekwesiri Michael , Merchant Hamid A. , Sunter Wendy , Ansari Muhammad Ayub , Conway Barbara R. , Hasan Syed Shahzad 
Published: April 2024

Abstract
Background
There is limited evidence to support definite clinical outcomes of direct oral anticoagulant (DOAC) therapy in chronic kidney disease (CKD). By identifying the important variables associated with clinical outcomes following DOAC administration in patients in different stages of CKD, this study aims to assess this evidence gap.

Methods
An anonymised dataset comprising 97,413 patients receiving DOAC therapy in a tertiary health setting was systematically extracted from the multidimensional electronic health records and prepared for analysis. Machine learning classifiers were applied to the prepared dataset to select the important features which informed covariate selection in multivariate logistic regression analysis.

Results
For both CKD and non-CKD DOAC users, features such as length of stay, treatment days, and age were ranked highest for relevance to adverse outcomes like death and stroke. Patients with Stage 3a CKD had significantly higher odds of ischaemic stroke (OR 2.45, 95% Cl: 2.10–2.86; p = 0.001) and lower odds of all-cause mortality (OR 0.87, 95% Cl: 0.79–0.95; p = 0.001) on apixaban therapy. In patients with CKD (Stage 5) receiving apixaban, the odds of death were significantly lowered (OR 0.28, 95% Cl: 0.14–0.58; p = 0.001), while the effect on ischaemic stroke was insignificant.

Conclusions
A positive effect of DOAC therapy was observed in advanced CKD. Key factors influencing clinical outcomes following DOAC administration in patients in different stages of CKD were identified. These are crucial for designing more advanced studies to explore safer and more effective DOAC therapy for the population.

Graphical Abstract
Race and indigeneity in human microbiome science: microbiomisation and the historiality of otherness
Authors: Núñez Casal Andrea 
Published: April 2024

AbstractThis article reformulates Stephan Helmreich´s the ¨microbiomisation of race¨ as the historiality of otherness in the foundations of human microbiome science. Through the lens of my ethnographic fieldwork of a transnational community of microbiome scientists that conducted a landmark human microbiome research on indigenous microbes and its affiliated and first personalised microbiome initiative, the American Gut Project, I follow and trace the key actors, experimental systems and onto-epistemic claims in the emergence of human microbiome science a decade ago. In doing so, I show the links between the reinscription of race, comparative research on the microbial genetic variation of human populations and the remining of bioprospected data for personalised medicine. In these unpredictable research movements, the microbiome of non-Western peoples and territories is much more than a side project or a specific approach within the field: it constitutes the nucleus of its experimental system, opening towards subsequent and cumulative research processes and knowledge production in human microbiome science. The article demonstrates that while human microbiome science is articulated upon the microbial ‘makeup’ of non-wester(nised) communities, societies, and locales, its results and therapeutics are only applicable to medical conditions affecting rich nations (i.e., inflammatory, autoimmune, and metabolic diseases). My reformulation of ¨microbiomisation of race¨ as the condition of possibility of human microbiome science reveals that its individual dimension is sustained by microbial DNA data from human populations through bioprospecting practices and gains meaning through personalised medicine initiatives, informal online networks of pseudoscientific and commodified microbial-related evidence.
Hybrid regularization inspired by total variation and deep denoiser prior for image restoration
Authors: Liang Hu , Zhang Jiahao , Wei Daisen , Zhu Jinbo 
Published: April 2024

AbstractImage restoration is a fundamental problem in computer vision, with the goal of restoring high-quality images from degraded low-quality observation images. However, the ill-posedness of restoration problem often leads to artifacts in the results. It inspires us to study the combination of prior, effectively restrict the solution space and improving the quality of the restored image. In this paper, a novel hybrid regularization method for image restoration is proposed, which adopts both internal and external image priors into a unified framework. Specifically, a new hybrid regularization model is designed. The TV model and a deep image denoiser are inserted into the restoration model using the plug-and-play framework, protecting image details while implicitly using external information for deep denoising. Moreover, in order to make the proposed hybrid regularization operable, an adaptive parameter method is proposed to adaptively balance the TV model and learned model in iteration. Experiments show that the proposed method surpasses the performance of existing image restoration techniques.
Category-Level Contrastive Learning for Unsupervised Hashing in Cross-Modal Retrieval
Authors: Xu Mengying , Luo Linyin , Lai Hanjiang , Yin Jian 
Published: April 2024

AbstractUnsupervised hashing for cross-modal retrieval has received much attention in the data mining area. Recent methods rely on image-text paired data to conduct unsupervised cross-modal hashing in batch samples. There are two main limitations for existing models: (1) learning of cross-modal representations is restricted to batches; (2) semantically similar samples may be wrongly treated as negative. In this paper, we propose a novel category-level contrastive learning for unsupervised cross-modal hashing, which alleviates the above problems and improves cross-modal query accuracy. To break the limitation of learning in small batches, a selected memory module is first proposed to take global relations into account. Then, we obtain pseudo labels through clustering and combine the labels with the Hadamard Matrix for category-centered learning. To reduce wrong negatives, we further propose a memory bank to store clusters of samples and construct negatives by selecting samples from different categories for contrastive learning. Extensive experiments show the significant superiority of our approach over the state-of-the-art models on MIRFLICKR-25K and NUS-WIDE datasets.
Computational Thinking During a Short, Authentic, Interdisciplinary STEM Experience for Elementary Students
Authors: Cantlon Jessica F. , Becker Katherine T. , DeLong Caroline M. 
Published: April 2024

AbstractSTEM experiences that capture students’ curiosity have a unique role in inspiring awe in science, enculturing science engagement, and recruiting students to pursue STEM careers. Here, we present a unique interdisciplinary STEM experience for elementary school students that teaches them to write computer code to test primate intelligence at a zoo where they test their code with real monkeys. In a pilot study involving 3rd to 6th grade students, we find that students can acquire “hard skills” in computational thinking during this short-term immersive STEM experience, with a significant increase in accuracy and problem-solving attempts at post-test. Furthermore, students’ interests in animal science, computers, and robots remain stable or even increase following this experience, demonstrating the project’s capacity to blend technical skills with authentic scientific exploration. Teachers’ feedback highlights the positive impact on critical thinking and leadership. This research underscores the potential of free-form, authentic, interdisciplinary STEM experiences to simultaneously nurture computational skills and a passion for science.