bluuebunny/crossref_metadata_2025_split huggingface dataset:
Causal inference from cross-sectional earth system data with geographical convergent cross mapping
Authors: Gao Bingbo , Yang Jianyu , Chen Ziyue , Sugihara George , Li Manchun , Stein Alfred , Kwan Mei-Po , Wang Jinfeng 
Published: September 2023

AbstractCausal inference in complex systems has been largely promoted by the proposal of some advanced temporal causation models. However, temporal models have serious limitations when time series data are not available or present insignificant variations, which causes a common challenge for earth system science. Meanwhile, there are few spatial causation models for fully exploring the rich spatial cross-sectional data in Earth systems. The generalized embedding theorem proves that observations can be combined together to construct the state space of the dynamic system, and if two variables are from the same dynamic system, they are causally linked. Inspired by this, here we show a Geographical Convergent Cross Mapping (GCCM) model for spatial causal inference with spatial cross-sectional data-based cross-mapping prediction in reconstructed state space. Three typical cases, where clearly existing causations cannot be measured through temporal models, demonstrate that GCCM could detect weak-moderate causations when the correlation is not significant. When the coupling between two variables is significant and strong, GCCM is advantageous in identifying the primary causation direction and better revealing the bidirectional asymmetric causation, overcoming the mirroring effect.
Structure guided mimicry of an essential P. falciparum receptor-ligand complex enhances cross neutralizing antibodies
Authors: Yanik Sean , Venkatesh Varsha , Parker Michelle L. , Ramaswamy Raghavendran , Diouf Ababacar , Sarkar Deepti , Miura Kazutoyo , Long Carole A. , Boulanger Martin J. , Srinivasan Prakash 
Published: September 2023

AbstractInvasion of human erythrocytes by Plasmodium falciparum (Pf) merozoites relies on the interaction between two parasite proteins: apical membrane antigen 1 (AMA1) and rhoptry neck protein 2 (RON2). While antibodies to AMA1 provide limited protection against Pf in non-human primate malaria models, clinical trials using recombinant AMA1 alone (apoAMA1) yielded no protection due to insufficient functional antibodies. Immunization with AMA1 bound to RON2L, a 49-amino acid peptide from its ligand RON2, has shown superior protection by increasing the proportion of neutralizing antibodies. However, this approach relies on the formation of a complex in solution between the two vaccine components. To advance vaccine development, here we engineered chimeric antigens by replacing the AMA1 DII loop, displaced upon ligand binding, with RON2L. Structural analysis confirmed that the fusion chimera (Fusion-FD12) closely mimics the binary AMA1-RON2L complex. Immunization studies in female rats demonstrated that Fusion-FD12 immune sera, but not purified IgG, neutralized vaccine-type parasites more efficiently compared to apoAMA1, despite lower overall anti-AMA1 titers. Interestingly, Fusion-FD12 immunization enhanced antibodies targeting conserved epitopes on AMA1, leading to increased neutralization of non-vaccine type parasites. Identifying these cross-neutralizing antibody epitopes holds promise for developing an effective, strain-transcending malaria vaccine.
DeepSlice: rapid fully automatic registration of mouse brain imaging to a volumetric atlas
Authors: Carey Harry , Pegios Michael , Martin Lewis , Saleeba Chris , Turner Anita J. , Everett Nicholas A. , Bjerke Ingvild E. , Puchades Maja A. , Bjaalie Jan G. , McMullan Simon 
Published: September 2023

AbstractRegistration of data to a common frame of reference is an essential step in the analysis and integration of diverse neuroscientific data. To this end, volumetric brain atlases enable histological datasets to be spatially registered and analyzed, yet accurate registration remains expertise-dependent and slow. In order to address this limitation, we have trained a neural network, DeepSlice, to register mouse brain histological images to the Allen Brain Common Coordinate Framework, retaining registration accuracy while improving speed by >1000 fold.
Decoding the endometrial niche of Asherman’s Syndrome at single-cell resolution
Authors: Santamaria Xavier , Roson Beatriz , Perez-Moraga Raul , Venkatesan Nandakumar , Pardo-Figuerez Maria , Gonzalez-Fernandez Javier , Llera-Oyola Jaime , Fernández Estefania , Moreno Inmaculada , Salumets Andres , Vankelecom Hugo , Vilella Felipe , Simon Carlos 
Published: September 2023

AbstractAsherman’s Syndrome is characterized by intrauterine adhesions or scarring, which cause infertility, menstrual abnormalities, and recurrent pregnancy loss. The pathophysiology of this syndrome remains unknown, with treatment restricted to recurrent surgical removal of intrauterine scarring, which has limited success. Here, we decode the Asherman’s Syndrome endometrial cell niche by analyzing data from over 200,000 cells with single-cell RNA-sequencing in patients with this condition and through in vitro analyses of Asherman’s Syndrome patient-derived endometrial organoids. Our endometrial atlas highlights the loss of the endometrial epithelium, alterations to epithelial differentiation signaling pathways such as Wnt and Notch, and the appearance of characteristic epithelium expressing secretory leukocyte protease inhibitor during the window of implantation. We describe syndrome-associated alterations in cell-to-cell communication and gene expression profiles that support a dysfunctional pro-fibrotic, pro-inflammatory, and anti-angiogenic environment.
The CBL1/9-CIPK1 calcium sensor negatively regulates drought stress by phosphorylating the PYLs ABA receptor
Authors: You Zhang , Guo Shiyuan , Li Qiao , Fang Yanjun , Huang Panpan , Ju Chuanfeng , Wang Cun 
Published: September 2023

AbstractThe stress hormone, Abscisic acid (ABA), is crucial for plants to respond to changes in their environment. It triggers changes in cytoplasmic Ca2+ levels, which activate plant responses to external stresses. However, how Ca2+ sensing and signaling feeds back into ABA signaling is not well understood. Here we reveal a calcium sensing module that negatively regulates drought stress via modulating ABA receptor PYLs. Mutants cbl1/9 and cipk1 exhibit hypersensitivity to ABA and drought resilience. Furthermore, CIPK1 is shown to interact with and phosphorylate 7 of 14 ABA receptors at the evolutionarily conserved site corresponding to PYL4 Ser129, thereby suppressing their activities and promoting PP2C activities under normal conditions. Under drought stress, ABA impedes PYLs phosphorylation by CIPK1 to respond to ABA signaling and survive in unfavorable environment. These findings provide insights into a previously unknown negative regulatory mechanism of the ABA signaling pathway, which is mediated by CBL1/9-CIPK1-PYLs, resulting in plants that are more sensitive to drought stress. This discovery expands our knowledge about the interplay between Ca2+ signaling and ABA signaling.
Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells
Authors: Gayoso Adam , Weiler Philipp , Lotfollahi Mohammad , Klein Dominik , Hong Justin , Streets Aaron , Theis Fabian J. , Yosef Nir 
Published: September 2023

AbstractRNA velocity has been rapidly adopted to guide interpretation of transcriptional dynamics in snapshot single-cell data; however, current approaches for estimating RNA velocity lack effective strategies for quantifying uncertainty and determining the overall applicability to the system of interest. Here, we present veloVI (velocity variational inference), a deep generative modeling framework for estimating RNA velocity. veloVI learns a gene-specific dynamical model of RNA metabolism and provides a transcriptome-wide quantification of velocity uncertainty. We show that veloVI compares favorably to previous approaches with respect to goodness of fit, consistency across transcriptionally similar cells and stability across preprocessing pipelines for quantifying RNA abundance. Further, we demonstrate that veloVI’s posterior velocity uncertainty can be used to assess whether velocity analysis is appropriate for a given dataset. Finally, we highlight veloVI as a flexible framework for modeling transcriptional dynamics by adapting the underlying dynamical model to use time-dependent transcription rates.
EzMechanism: an automated tool to propose catalytic mechanisms of enzyme reactions
Authors: Ribeiro Antonio J. M. , Riziotis Ioannis G. , Tyzack Jonathan D. , Borkakoti Neera , Thornton Janet M. 
Published: September 2023

AbstractOver the years, hundreds of enzyme reaction mechanisms have been studied using experimental and simulation methods. This rich literature on biological catalysis is now ripe for use as the foundation of new knowledge-based approaches to investigate enzyme mechanisms. Here, we present a tool able to automatically infer mechanistic paths for a given three-dimensional active site and enzyme reaction, based on a set of catalytic rules compiled from the Mechanism and Catalytic Site Atlas, a database of enzyme mechanisms. EzMechanism (pronounced as ‘Easy’ Mechanism) is available to everyone through a web user interface. When studying a mechanism, EzMechanism facilitates and improves the generation of hypotheses, by making sure that relevant information is considered, as derived from the literature on both related and unrelated enzymes. We validated EzMechanism on a set of 62 enzymes and have identified paths for further improvement, including the need for additional and more generic catalytic rules.
Time-resolved cryo-EM (TR-EM) analysis of substrate polyubiquitination by the RING E3 anaphase-promoting complex/cyclosome (APC/C)
Authors: Bodrug Tatyana , Welsh Kaeli A. , Bolhuis Derek L. , Paulаkonis Ethan , Martinez-Chacin Raquel C. , Liu Bei , Pinkin Nicholas , Bonacci Thomas , Cui Liying , Xu Pengning , Roscow Olivia , Amann Sascha Josef , Grishkovskaya Irina , Emanuele Michael J. , Harrison Joseph S. , Steimel Joshua P. , Hahn Klaus M. , Zhang Wei , Zhong Ellen D. , Haselbach David , Brown Nicholas G. 
Published: September 2023

AbstractSubstrate polyubiquitination drives a myriad of cellular processes, including the cell cycle, apoptosis and immune responses. Polyubiquitination is highly dynamic, and obtaining mechanistic insight has thus far required artificially trapped structures to stabilize specific steps along the enzymatic process. So far, how any ubiquitin ligase builds a proteasomal degradation signal, which is canonically regarded as four or more ubiquitins, remains unclear. Here we present time-resolved cryogenic electron microscopy studies of the 1.2 MDa E3 ubiquitin ligase, known as the anaphase-promoting complex/cyclosome (APC/C), and its E2 co-enzymes (UBE2C/UBCH10 and UBE2S) during substrate polyubiquitination. Using cryoDRGN (Deep Reconstructing Generative Networks), a neural network-based approach, we reconstruct the conformational changes undergone by the human APC/C during polyubiquitination, directly visualize an active E3–E2 pair modifying its substrate, and identify unexpected interactions between multiple ubiquitins with parts of the APC/C machinery, including its coactivator CDH1. Together, we demonstrate how modification of substrates with nascent ubiquitin chains helps to potentiate processive substrate polyubiquitination, allowing us to model how a ubiquitin ligase builds a proteasomal degradation signal.
Impact of elastic substrate on the dynamic heterogeneity of WC256 Walker carcinosarcoma cells
Authors: Mielnicka Aleksandra , Kołodziej Tomasz , Dziob Daniel , Lasota Sławomir , Sroka Jolanta , Rajfur Zenon 
Published: September 2023

AbstractCellular heterogeneity is a phenomenon in which cell populations are composed of subpopulations that vary in their behavior. Heterogeneity is particularly pronounced in cancer cells and can affect the efficacy of oncological therapies. Previous studies have considered heterogeneity dynamics to be indicative of evolutionary changes within subpopulations; however, these studies do not consider the short-time morphological plasticity of cells. Physical properties of the microenvironment elasticity have also been poorly investigated within the context of cellular heterogeneity, despite its role in determining cellular behavior. This article demonstrates that cellular heterogeneity can be highly dynamic and dependent on the micromechanical properties of the substrate. During observation, migrating Walker carcinosarcoma WC256 cells were observed to belong to different subpopulations, in which their morphologies and migration strategies differed. Furthermore, the application of an elastic substrate (E = 40 kPa) modified three aspects of cellular heterogeneity: the occurrence of subpopulations, the occurrence of transitions between subpopulations, and cellular migration and morphology. These findings provide a new perspective in the analysis of cellular heterogeneity, whereby it may not be a static feature of cancer cell populations, instead varying over time. This helps further the understanding of cancer cell behavior, including their phenotype and migration strategy, which may help to improve cancer therapies by extending their suitability to investigate tumor heterogeneity.
Synthesis and in situ oxidation of copper micro- and nanoparticles by arc discharge plasma in liquid
Authors: Zhakypov Alibek S. , Nemkayeva Renata R. , Yerlanuly Yerassyl , Tulegenova Malika A. , Kurbanov Beibarys Y. , Aitzhanov Madi B. , Markhabayeva Aiymkul A. , Gabdullin Maratbek T. 
Published: September 2023

AbstractThis work presents a one-step controlled method for the synthesis of copper oxide nanoparticles using an arc discharge in deionized water without subsequent thermal annealing. The synthesis conditions were varied by changing the arc discharge current from 2 to 4 A. Scanning electron microscopy images of samples synthesized at discharge current of 2 A revealed the formation of tenorite (CuO) nanopetals with an average length of 550 nm and a width of 100 nm, which had a large surface area. Arc discharge synthesis at 3 and 4 A current modes provides the formation of a combination of CuO nanopetals with spherical cuprite (Cu2O) nanoparticles with sizes ranging from 30 to 80 nm. The crystalline phase and elemental composition of the synthesized particles were identified by X-ray diffraction analysis, Raman spectroscopy and Energy dispersive analysis. As the arc discharge current was raised from 2 to 4 A, two notable changes occurred in the synthesized particles: the Cu/O ratio increased, and the particle sizes decreased. At 4 A, the synthesized particles were from 30 to 80 nm in size and had a spherical shape, indicating an increase in the amount of cuprite (Cu2O) phase. The optical band gap of the aqueous solutions of copper oxide particles also increased from 2 to 2.34 eV with increasing synthesis current from 2 to 4 A, respectively. This suggests that the proposed synthesis method can be used to tune the band gap of the final material by controlling the Cu/O ratio through the current of arc discharge. Overall, this work demonstrates a novel approach to the synthesis of copper oxide nanoparticles with controllable CuO/Cu2O/Cu ratios, which has the potential to be useful in a variety of applications, particularly due to the significant enhancement of photocatalytic abilities and widen the working spectral range.
MSFC: a new feature construction method for accurate diagnosis of mass spectrometry data
Authors: Feng Xin , Dong Zheyuan , Li Yingrui , Cheng Qian , Xin Yongxian , Lu Qiaolin , Xin Ruihao 
Published: September 2023

AbstractMass spectrometry technology can realize dynamic detection of many complex matrix samples in a simple, rapid, compassionate, precise, and high-throughput manner and has become an indispensable tool in accurate diagnosis. The mass spectrometry data analysis is mainly to analyze all metabolites in the organism quantitatively and to find the relative relationship between metabolites and physiological and pathological changes. A feature construction of mass spectrometry data (MSFS) method is proposed to construct the features of the original mass spectrometry data, so as to reduce the noise in the mass spectrometry data, reduce the redundancy of the original data and improve the information content of the data. Chi-square test is used to select the optimal non-redundant feature subset from high-dimensional features. And the optimal feature subset is visually analyzed and corresponds to the original mass spectrum interval. Training in 10 kinds of supervised learning models, and evaluating the classification effect of the models through various evaluation indexes. Taking two public mass spectrometry datasets as examples, the feasibility of the method proposed in this paper is verified. In the coronary heart disease dataset, during the identification process of mixed batch samples, the classification accuracy on the test set reached 1.000; During the recognition process, the classification accuracy on the test set advanced to 0.979. On the colorectal liver metastases data set, the classification accuracy on the test set reached 1.000. This paper attempts to use a new raw mass spectrometry data preprocessing method to realize the alignment operation of the raw mass spectrometry data, which significantly improves the classification accuracy and provides another new idea for mass spectrometry data analysis. Compared with MetaboAnalyst software and existing experimental results, the method proposed in this paper has obtained better classification results.
A cross-sectional case–control study on the structural connectome in recovered hospitalized COVID-19 patients
Authors: Lathouwers Elke , Radwan Ahmed , Blommaert Jeroen , Stas Lara , Tassignon Bruno , Allard Sabine D. , De Ridder Filip , De Waele Elisabeth , Hoornaert Nicole , Lacor Patrick , Mertens Rembert , Naeyaert Maarten , Raeymaekers Hubert , Seyler Lucie , Vanbinst Anne-Marie , Van Liedekerke Lien , Van Schependom Jeroen , Van Schuerbeek Peter , Provyn Steven , Roelands Bart , Vandekerckhove Marie , Meeusen Romain , Sunaert Stefan , Nagels Guy , De Mey Johan , De Pauw Kevin 
Published: September 2023

AbstractCOVID-19 can induce neurological sequelae, negatively affecting the quality of life. Unravelling this illness's impact on structural brain connectivity, white-matter microstructure (WMM), and cognitive performance may help elucidate its implications. This cross-sectional study aimed to investigate differences in these factors between former hospitalised COVID-19 patients (COV) and healthy controls. Group differences in structural brain connectivity were explored using Welch-two sample t-tests and two-sample Mann–Whitney U tests. Multivariate linear models were constructed (one per region) to examine fixel-based group differences. Differences in cognitive performance between groups were investigated using Wilcoxon Rank Sum tests. Possible effects of bundle-specific FD measures on cognitive performance were explored using a two-group path model. No differences in whole-brain structural organisation were found. Bundle-specific metrics showed reduced fiber density (p = 0.012, Hedges’ g = 0.884) and fiber density cross-section (p = 0.007, Hedges’ g = 0.945) in the motor segment of the corpus callosum in COV compared to healthy controls. Cognitive performance on the motor praxis and digit symbol substitution tests was worse in COV than healthy controls (p < 0.001, r = 0.688; p = 0.013, r = 422, respectively). Associations between the cognitive performance and bundle-specific FD measures differed significantly between groups. WMM and cognitive performance differences were observed between COV and healthy controls.
Stem cells-derived exosomes alleviate neurodegeneration and Alzheimer’s pathogenesis by ameliorating neuroinflamation, and regulating the associated molecular pathways
Authors: Khan Muhammad Imran , Jeong Eun Sun , Khan Muhammad Zubair , Shin Jin Hyuk , Kim Jong Deog 
Published: September 2023

AbstractAmyloid beta (Aβ) aggregation and tau hyper phosphorylation (p-tau) are key molecular factors in Alzheimer’s disease (AD). The abnormal formation and accumulation of Aβ and p-tau lead to the formation of amyloid plaques and neurofibrillary tangles (NFTs) which ultimately leads to neuroinflammation and neurodegeneration. β- and γ-secretases produce Aβ peptides via the amyloidogenic pathway, and several kinases are involved in tau phosphorylation. Exosomes, a recently developed method of intercellular communication, derived from neuronal stem cells (NSC-exos), are intriguing therapeutic options for AD. Exosomes have ability to cross the BBB hence highly recommended for brain related diseases and disorders. In the current study, we examined how NSC-exos could protect human neuroblastoma cells SH-SY5Y (ATCC CRL-2266). NSC-exos were derived from Human neural stem cells (ATCC-BYS012) by ultracentrifugation and the therapeutic effects of the NSC-exos were then investigated in vitro. NSC-exos controlled the associated molecular processes to drastically lower Aβ and p-tau. A dose dependent reduction in β- and γ-secretase, acetylcholinesterase, GSK3β, CDK5, and activated α-secretase activities was also seen. We further showed that BACE1, PSEN1, CDK5, and GSK-3β mRNA expression was suppressed and downregulated, while ADAM10 mRNA was increased. NSC- Exos downregulate NF-B/ERK/JNK-related signaling pathways in activated glial cells HMC3 (ATCC-CRL-3304) and reduce inflammatory mediators such iNOS, IL-1β, TNF-α, and IL-6, which are associated with neuronal inflammation. The NSC-exos therapy ameliorated the neurodegeneration of human neuroblastoma cells SH-SY5Y by enhancing viability. Overall, these findings support that exosomes produced from stem cells can be a neuro-protective therapy to alleviate AD pathology.
Dermoscopy of acute radiation-induced dermatitis in patients with head and neck cancers treated with radiotherapy
Authors: Pilśniak Aleksandra , Szlauer-Stefańska Anastazja , Tukiendorf Andrzej , Rutkowski Tomasz , Składowski Krzysztof , Kamińska-Winciorek Grażyna 
Published: September 2023

AbstractHead and neck cancer (HNC) was the seventh most common cancer in the world in 2018. Treatment of a patient may include surgery, radiotherapy (RT), chemotherapy, targeted therapy, immunotherapy, or a combination of these methods. Ionizing radiation used during RT covers relatively large volumes of healthy tissue surrounding the tumor. The acute form of radiation-induced dermatitis (ARD) are skin lesions that appear usually within 90 days of the start of RT. This is a prospective study which compares 2244 dermoscopy images and 374 clinical photographs of irradiated skin and healthy skin of 26 patients at on average 15 time points. Dermoscopy pictures were evaluated independently by 2 blinded physicians. Vessels in reticular distribution, white, yellow or brown scale in a patchy distribution, perifollicular pigmentation and follicular plugs arranged in rosettes were most often observed. For these dermoscopic features, agreement with macroscopic features was observed. Two independent predictors of severe acute toxicity were identified: gender and concurrent chemotherapy. Knowledge of dermoscopic features could help in the early assessment of acute toxicity and the immediate implementation of appropriate therapeutic strategies. This may increase the tolerance of RT in these groups of patients.