bluuebunny/crossref_metadata_2025_split huggingface dataset:
Role of lung ornithine aminotransferase in idiopathic pulmonary fibrosis: regulation of mitochondrial ROS generation and TGF-β1 activity
Authors: Lee Jong-Uk , Song Ki Sung , Hong Jisu , Shin Hyesun , Park Eunji , Baek Junyeong , Park Shinhee , Baek Ae-Rin , Lee Junehyuk , Jang An Soo , Kim Do Jin , Chin Su Sie , Kim U-Jin , Jeong Sung Hwan , Park Sung-Woo 
Published: February 2024

AbstractIdiopathic pulmonary fibrosis (IPF) is characterized by aberrant lung remodeling and the excessive accumulation of extracellular matrix (ECM) proteins. In a previous study, we found that the levels of ornithine aminotransferase (OAT), a principal enzyme in the proline metabolism pathway, were increased in the lungs of patients with IPF. However, the precise role played by OAT in the pathogenesis of IPF is not yet clear. The mechanism by which OAT affects fibrogenesis was assessed in vitro using OAT-overexpressing and OAT-knockdown lung fibroblasts. The therapeutic effects of OAT inhibition were assessed in the lungs of bleomycin-treated mice. OAT expression was increased in fibrotic areas, principally in interstitial fibroblasts, of lungs affected by IPF. OAT levels in the bronchoalveolar lavage fluid of IPF patients were inversely correlated with lung function. The survival rate was significantly lower in the group with an OAT level >75.659 ng/mL than in the group with an OAT level ≤75.659 ng/mL (HR, 29.53;p = 0.0008). OAT overexpression and knockdown increased and decreased ECM component production by lung fibroblasts, respectively. OAT knockdown also inhibited transforming growth factor-β1 (TGF)-β1 activity and TGF-β1 pathway signaling. OAT overexpression increased the generation of mitochondrial reactive oxygen species (ROS) by activating proline dehydrogenase. The OAT inhibitor L-canaline significantly attenuated bleomycin-induced lung injury and fibrosis. In conclusion, increased OAT levels in lungs affected by IPF contribute to the progression of fibrosis by promoting excessive mitochondrial ROS production, which in turn activates TGF-β1 signaling. OAT may be a useful target for treating patients with fibrotic lung diseases, including IPF.
Tim4 deficiency reduces CD301b+ macrophage and aggravates periodontitis bone loss
Authors: Wang Ziming , Zeng Hao , Wang Can , Wang Jiaolong , Zhang Jing , Qu Shuyuan , Han Yue , Yang Liu , Ni Yueqi , Peng Wenan , Liu Huan , Tang Hua , Zhao Qin , Zhang Yufeng 
Published: February 2024

AbstractPeriodontitis is a common chronic inflammatory disease that causes the periodontal bone destruction and may ultimately result in tooth loss. With the progression of periodontitis, the osteoimmunology microenvironment in periodontitis is damaged and leads to the formation of pathological alveolar bone resorption. CD301b+ macrophages are specific to the osteoimmunology microenvironment, and are emerging as vital booster for conducting bone regeneration. However, the key upstream targets of CD301b+ macrophages and their potential mechanism in periodontitis remain elusive. In this study, we concentrated on the role of Tim4, a latent upstream regulator of CD301b+ macrophages. We first demonstrated that the transcription level of Timd4 (gene name of Tim4) in CD301b+ macrophages was significantly upregulated compared to CD301b− macrophages via high-throughput RNA sequencing. Moreover, several Tim4-related functions such as apoptotic cell clearance, phagocytosis and engulfment were positively regulated by CD301b+ macrophages. The single-cell RNA sequencing analysis subsequently discovered that Cd301b and Timd4 were specifically co-expressed in macrophages. The following flow cytometric analysis indicated that Tim4 positive expression rates in total macrophages shared highly synchronized dynamic changes with the proportions of CD301b+ macrophages as periodontitis progressed. Furthermore, the deficiency of Tim4 in mice decreased CD301b+ macrophages and eventually magnified alveolar bone resorption in periodontitis. Additionally, Tim4 controlled the p38 MAPK signaling pathway to ultimately mediate CD301b+ macrophages phenotype. In a word, Tim4 might regulate CD301b+ macrophages through p38 MAPK signaling pathway in periodontitis, which provided new insights into periodontitis immunoregulation as well as help to develop innovative therapeutic targets and treatment strategies for periodontitis.
The relationship between balance control and thigh muscle strength and muscle activity in persons with incomplete spinal cord injury
Authors: Wouda Matthijs Ferdinand , Løtveit Marte Fosvold , Bengtson Espen Ingvald , Strøm Vegard 
Published: February 2024

Abstract
Study design
Cross-sectional study.

Objectives
A spinal cord injury (SCI) can compromise the ability to maintain sufficient balance control during activities in an upraised position. The objective of the study was to explore the relationship between balance control and muscle strength and muscle activation in the lower extremities in persons with incomplete SCI (iSCI).

Setting
Sunnaas Rehabilitation Hospital, Norway.

Methods
Thirteen men and two women with iSCI and 15 healthy, matched controls were included. Performance of the Berg Balance Scale (BBS) short version (7 items) was used to indicate balance control. Maximal voluntary contraction (MVC) was performed to measure isometric muscle strength in thigh muscles (knee extension/flexion), while surface electromyography (EMG) was measured from M. Vastus Lateralis and M. Biceps Femoris. The relative activation of each muscle during each of the BBS tasks was reported as the percentage of the maximal activation during the MVC (%EMGmax).

Results
The iSCI participants had a significantly lower BBS sum score and up to 40% lower muscle strength in knee- flexion and extension compared to the matched healthy controls. They also exhibited a significantly higher %EMGmax, i.e. a higher muscle activation, during most of the balance tests. Univariate regression analysis revealed a significant association between balance control and mean values of %EMGmax in Biceps Femoris, averaged over the seven BBS tests.

Conclusions
The participants with iSCI had poorer balance control, reduced thigh muscle strength and a higher relative muscle activation in their thigh muscles, during balance-demanding activities.
Involvement of interlukin-17A (IL-17A) gene polymorphism and interlukin-23 (IL-23) level in the development of peri-implantitis
Authors: Talib Ehab Qasim , Taha Ghada Ibrahim 
Published: February 2024

Abstract
Background
Dental implantation has been practiced since ancient times and has gone through several stages. Dentists use dental implants to support dental prostheses such as crowns, bridges, dentures, face prostheses, or as an orthodontic anchor. Thus, the purpose of this study is to detect the role of the immune-genetic variation of IL-17A and related inflammatory cytokine (IL-23) in the initiation and progress of peri implantitis.

Material and methods
This cross-sectional study included 80 subjects (15 peri-implantitis patients, 35 successful implants, and 30 healthy controls); their mean age was (43.91 ± 11.33) years. Blood samples and Peri-implant sulcus fluid (PISF) were collected from all subjects (patients with peri-implantitis, successful implants, and healthy controls) attending the Department of Oral and Maxillofacial Surgery in the Dental College Teaching Hospital, Baghdad University, Baghdad, Iraq. The blood sample detects gene polymorphisms in interleukin-17A by a polymerase chain reaction (PCR). An enzyme-linked immunosorbent assay (ELISA) was carried out to estimate the Peri-implant sulcus fluid (PISF) levels of interleukin-23.

Result
The current study revealed an obvious significant elevation in the mean level of interleukin-23 in the peri-implantitis patient’s group more than its level in the successful implant and control groups (P < 0.05). In addition, the result showed that A/A genotype is associated significantly with peri-implantitis OR (95%confidence interval) =6.9 (1.7121 to 27.4638) folds increase risk of peri-implantitis) (p = 0.0065), while G/A genotype had OR 4.9 (0.9539–24.9394) folds increased risk of peri-implantitis, (p = 0.0572). But it was not statistically significant and G/G genotype had a one-fold increase risk of peri-implantitis.

Conclusion
The increased level of inflammatory cytokine (interleukin-23) might add to the systemic inflammatory burden a predisposing factor, which may lead to impaired osseointegration and subsequent bone loss or implant failure. In addition, IL-17A gene polymorphism may play a role in peri-implant disease susceptibility, especially in persons carrying the rs2275913 A allele at a higher risk of developing peri-implantitits as compared with those carrying the G allele.
Rare disease research workflow using multilayer networks elucidates the molecular determinants of severity in Congenital Myasthenic Syndromes
Authors: Núñez-Carpintero Iker , Rigau Maria , Bosio Mattia , O’Connor Emily , Spendiff Sally , Azuma Yoshiteru , Topf Ana , Thompson Rachel , ’t Hoen Peter A. C. , Chamova Teodora , Tournev Ivailo , Guergueltcheva Velina , Laurie Steven , Beltran Sergi , Capella-Gutiérrez Salvador , Cirillo Davide , Lochmüller Hanns , Valencia Alfonso 
Published: February 2024

AbstractExploring the molecular basis of disease severity in rare disease scenarios is a challenging task provided the limitations on data availability. Causative genes have been described for Congenital Myasthenic Syndromes (CMS), a group of diverse minority neuromuscular junction (NMJ) disorders; yet a molecular explanation for the phenotypic severity differences remains unclear. Here, we present a workflow to explore the functional relationships between CMS causal genes and altered genes from each patient, based on multilayer network community detection analysis of complementary biomedical information provided by relevant data sources, namely protein-protein interactions, pathways and metabolomics. Our results show that CMS severity can be ascribed to the personalized impairment of extracellular matrix components and postsynaptic modulators of acetylcholine receptor (AChR) clustering. This work showcases how coupling multilayer network analysis with personalized -omics information provides molecular explanations to the varying severity of rare diseases; paving the way for sorting out similar cases in other rare diseases.
Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks
Authors: Regazzoni Francesco , Pagani Stefano , Salvador Matteo , Dede’ Luca , Quarteroni Alfio 
Published: February 2024

AbstractPredicting the evolution of systems with spatio-temporal dynamics in response to external stimuli is essential for scientific progress. Traditional equations-based approaches leverage first principles through the numerical approximation of differential equations, thus demanding extensive computational resources. In contrast, data-driven approaches leverage deep learning algorithms to describe system evolution in low-dimensional spaces. We introduce an architecture, termed Latent Dynamics Network, capable of uncovering low-dimensional intrinsic dynamics in potentially non-Markovian systems. Latent Dynamics Networks automatically discover a low-dimensional manifold while learning the system dynamics, eliminating the need for training an auto-encoder and avoiding operations in the high-dimensional space. They predict the evolution, even in time-extrapolation scenarios, of space-dependent fields without relying on predetermined grids, thus enabling weight-sharing across query-points. Lightweight and easy-to-train, Latent Dynamics Networks demonstrate superior accuracy (normalized error 5 times smaller) in highly-nonlinear problems with significantly fewer trainable parameters (more than 10 times fewer) compared to state-of-the-art methods.
Mirror-image ligand discovery enabled by single-shot fast-flow synthesis of D-proteins
Authors: Callahan Alex J. , Gandhesiri Satish , Travaline Tara L. , Reja Rahi M. , Lozano Salazar Lia , Hanna Stephanie , Lee Yen-Chun , Li Kunhua , Tokareva Olena S. , Swiecicki Jean-Marie , Loas Andrei , Verdine Gregory L. , McGee John H. , Pentelute Bradley L. 
Published: February 2024

AbstractWidespread adoption of mirror-image biological systems presents difficulties in accessing the requisite D-protein substrates. In particular, mirror-image phage display has the potential for high-throughput generation of biologically stable macrocyclic D-peptide binders with potentially unique recognition modes but is hindered by the individualized optimization required for D-protein chemical synthesis. We demonstrate a general mirror-image phage display pipeline that utilizes automated flow peptide synthesis to prepare D-proteins in a single run. With this approach, we prepare and characterize 12 D-proteins – almost one third of all reported D-proteins to date. With access to mirror-image protein targets, we describe the successful discovery of six macrocyclic D-peptide binders: three to the oncoprotein MDM2, and three to the E3 ubiquitin ligase CHIP. Reliable production of mirror-image proteins can unlock the full potential of D-peptide drug discovery and streamline the study of mirror-image biology more broadly.
Supernova dust destruction in the magnetized turbulent ISM
Authors: Kirchschlager Florian , Mattsson Lars , Gent Frederick A. 
Published: February 2024

AbstractDust in the interstellar medium (ISM) is critical to the absorption and intensity of emission profiles used widely in astronomical observations, and necessary for star and planet formation. Supernovae (SNe) both produce and destroy ISM dust. In particular the destruction rate is difficult to assess. Theory and prior simulations of dust processing by SNe in a uniform ISM predict quite high rates of dust destruction, potentially higher than the supernova dust production rate in some cases. Here we show simulations of supernova-induced dust processing with realistic ISM dynamics including magnetic field effects and demonstrate how ISM inhomogeneity and magnetic fields inhibit dust destruction. Compared to the non-magnetic homogeneous case, the dust mass destroyed within 1 Myr per SNe is reduced by more than a factor of two, which can have a great impact on the ISM dust budget.
Metabolomic profiles of sleep-disordered breathing are associated with hypertension and diabetes mellitus development
Authors: Zhang Ying , Yu Bing , Qi Qibin , Azarbarzin Ali , Chen Han , Shah Neomi A. , Ramos Alberto R. , Zee Phyllis C. , Cai Jianwen , Daviglus Martha L. , Boerwinkle Eric , Kaplan Robert , Liu Peter Y. , Redline Susan , Sofer Tamar 
Published: February 2024

AbstractSleep-disordered breathing (SDB) is a prevalent disorder characterized by recurrent episodic upper airway obstruction. Using data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), we apply principal component analysis (PCA) to seven SDB-related measures. We estimate the associations of the top two SDB PCs with serum levels of 617 metabolites, in both single-metabolite analysis, and a joint penalized regression analysis. The discovery analysis includes 3299 individuals, with validation in a separate dataset of 1522 individuals. Five metabolite associations with SDB PCs are discovered and replicated. SDB PC1, characterized by frequent respiratory events common in older and male adults, is associated with pregnanolone and progesterone-related sulfated metabolites. SDB PC2, characterized by short respiratory event length and self-reported restless sleep, enriched in young adults, is associated with sphingomyelins. Metabolite risk scores (MRSs), representing metabolite signatures associated with the two SDB PCs, are associated with 6-year incident hypertension and diabetes. These MRSs have the potential to serve as biomarkers for SDB, guiding risk stratification and treatment decisions.
Single-atom tailored atomically-precise nanoclusters for enhanced electrochemical reduction of CO2-to-CO activity
Authors: Wang Yi-Man , Yan Fang-Qin , Wang Qian-You , Du Chen-Xia , Wang Li-Ya , Li Bo , Wang Shan , Zang Shuang-Quan 
Published: February 2024

AbstractThe development of facile tailoring approach to adjust the intrinsic activity and stability of atomically-precise metal nanoclusters catalysts is of great interest but remians challenging. Herein, the well-defined Au8 nanoclusters modified by single-atom sites are rationally synthesized via a co-eletropolymerization strategy, in which uniformly dispersed metal nanocluster and single-atom co-entrenched on the poly-carbazole matrix. Systematic characterization and theoretical modeling reveal that functionalizing single-atoms enable altering the electronic structures of Au8 clusters, which amplifies their electrocatalytic reduction of CO2 to CO activity by ~18.07 fold compared to isolated Au8 metal clusters. The rearrangements of the electronic structure not only strengthen the adsorption of the key intermediates *COOH, but also establish a favorable reaction pathway for the CO2 reduction reaction. Moreover, this strategy fixing nanoclusters and single-atoms on cross-linked polymer networks efficiently deduce the performance deactivation caused by agglomeration during the catalytic process. This work contribute to explore the intrinsic activity and stability improvement of metal clusters.
Resonant generation of propagating second-harmonic spin waves in nano-waveguides
Authors: Nikolaev K. O. , Lake S. R. , Schmidt G. , Demokritov S. O. , Demidov V. E. 
Published: February 2024

AbstractGeneration of second-harmonic waves is one of the universal nonlinear phenomena that have found numerous technical applications in many modern technologies, in particular, in photonics. This phenomenon also has great potential in the field of magnonics, which considers the use of spin waves in magnetic nanostructures to implement wave-based signal processing and computing. However, due to the strong frequency dependence of the phase velocity of spin waves, resonant phase-matched generation of second-harmonic spin waves has not yet been achieved in practice. Here, we show experimentally that such a process can be realized using a combination of different modes of nano-sized spin-wave waveguides based on low-damping magnetic insulators. We demonstrate that our approach enables efficient spatially-extended energy transfer between interacting waves, which can be controlled by the intensity of the initial wave and the static magnetic field.
Dendritic mGluR2 and perisomatic Kv3 signaling regulate dendritic computation of mouse starburst amacrine cells
Authors: Acarón Ledesma Héctor , Ding Jennifer , Oosterboer Swen , Huang Xiaolin , Chen Qiang , Wang Sui , Lin Michael Z. , Wei Wei 
Published: February 2024

AbstractDendritic mechanisms driving input-output transformation in starburst amacrine cells (SACs) are not fully understood. Here, we combine two-photon subcellular voltage and calcium imaging and electrophysiological recording to determine the computational architecture of mouse SAC dendrites. We found that the perisomatic region integrates motion signals over the entire dendritic field, providing a low-pass-filtered global depolarization to dendrites. Dendrites integrate local synaptic inputs with this global signal in a direction-selective manner. Coincidental local synaptic inputs and the global motion signal in the outward motion direction generate local suprathreshold calcium transients. Moreover, metabotropic glutamate receptor 2 (mGluR2) signaling in SACs modulates the initiation of calcium transients in dendrites but not at the soma. In contrast, voltage-gated potassium channel 3 (Kv3) dampens fast voltage transients at the soma. Together, complementary mGluR2 and Kv3 signaling in different subcellular regions leads to dendritic compartmentalization and direction selectivity, highlighting the importance of these mechanisms in dendritic computation.
Integrated analysis of X-ray diffraction patterns and pair distribution functions for machine-learned phase identification
Authors: Szymanski Nathan J. , Fu Sean , Persson Ellen , Ceder Gerbrand 
Published: February 2024

AbstractTo bolster the accuracy of existing methods for automated phase identification from X-ray diffraction (XRD) patterns, we introduce a machine learning approach that uses a dual representation whereby XRD patterns are augmented with simulated pair distribution functions (PDFs). A convolutional neural network is trained directly on XRD patterns calculated using physics-informed data augmentation, which accounts for experimental artifacts such as lattice strain and crystallographic texture. A second network is trained on PDFs generated via Fourier transform of the augmented XRD patterns. At inference, these networks classify unknown samples by aggregating their predictions in a confidence-weighted sum. We show that such an integrated approach to phase identification provides enhanced accuracy by leveraging the benefits of each model’s input representation. Whereas networks trained on XRD patterns provide a reciprocal space representation and can effectively distinguish large diffraction peaks in multi-phase samples, networks trained on PDFs provide a real space representation and perform better when peaks with low intensity become important. These findings underscore the importance of using diverse input representations for machine learning models in materials science and point to new avenues for automating multi-modal characterization.
The impact of heavy metal concentrations on aquatic insect populations in the Asan Wetland of Dehradun, Uttarakhand
Authors: Tabassum Sazia , Kotnala C. B. , Salman Mohammed , Tariq Mohd , Khan Afzal Husain , Khan Nadeem A. 
Published: February 2024

AbstractThis study, centered on the Asan Wetland in Uttarakhand, examines the ecological impact of heavy metals on aquatic insects biodiversity. It highlights the detrimental effects of metals like chromium, mercury, and lead, stemming from natural and anthropogenic sources, on aquatic insects diversity. Aquatic insects, particularly sensitive to water quality, are emphasized as key indicators of environmental health, illustrating the importance of understanding and managing the influences on wetland ecosystems. Wetland ecosystems are vulnerable to various environmental stressors, including pollution from heavy metals. These toxic substances can alter water quality parameters, disrupt nutrient cycling, and negatively impact the biodiversity and ecological balance of the system. This study aimed to evaluate the impact of several heavy metals (namely Cd, As, Cu, Fe, Pb, Ni, Zn, Al, Cr) on the distribution and biodiversity of various aquatic insect species, including Coeleoptera, Diptera, Ephemeroptera, Odonata, Plecoptera, and Trichoptera. The research utilized data collected between November 2021 and October 2022 from specifically chosen sites (S1, S2, S3) within the Asan Wetland in Dehradun, Uttarakhand. After collecting and identifying samples, various statistical (Sorenson, Shannon-Weiner diversity index, Margelef index) and multivariate tests (CCA, PCA, One-way Anova), have been applied to show the effects of these parameters. This study offers significant findings regarding the distribution patterns of heavy metals, the abundance of aquatic insects, and their interconnectedness within the ecosystem of the Asan Wetland. The abundance of aquatic insects, represented by 13 genera belonging to 6 orders, was assessed at three different sites (S1, S2, and S3) within the wetland. It was concluded that the heavy metals concentration and aquatic insects’ density increases and decreases vice-versa in monsoon and winter seasons might be due to unfavourable factors. These findings contribute to the understanding of ecological dynamics and potential impacts of heavy metals on aquatic biota in wetland environments.