bluuebunny/crossref_metadata_2025_split huggingface dataset:
α1,3-fucosylation of MEST promotes invasion potential of cytotrophoblast cells by activating translation initiation
Authors: Wang Hao , Cui Xinyuan , Wang Luyao , Fan Ningning , Yu Ming , Qin Huamin , Liu Shuai , Yan Qiu 
Published: October 2023

AbstractEmbryo implantation into the uterus is the gateway for successful pregnancy. Proper migration and invasion of embryonic trophoblast cells are the key for embryo implantation, and dysfunction causes pregnancy failure. Protein glycosylation plays crucial roles in reproduction. However, it remains unclear whether the glycosylation of trophoblasts is involved in trophoblast migration and invasion processes during embryo implantation failure. By Lectin array, we discovered the decreased α1,3-fucosylation, especially difucosylated Lewis Y (LeY) glycan, in the villus tissues of miscarriage patients when compared with normal pregnancy women. Downregulating LeY biosynthesis by silencing the key enzyme fucosyltransferase IV (FUT4) inhibited migration and invasion ability of trophoblast cells. Using proteomics and translatomics, the specific LeY scaffolding glycoprotein of mesoderm-specific transcript (MEST) with glycosylation site at Asn163 was identified, and its expression enhanced migration and invasion ability of trophoblast cells. The results also provided novel evidence showing that decreased LeY modification on MEST hampered the binding of MEST with translation factor eIF4E2, and inhibited implantation-related gene translation initiation, which caused pregnancy failure. The α1,3-fucosylation of MEST by FUT4 may serve as a new biomarker for evaluating the functional state of pregnancy, and a target for infertility treatment.
MetaCC allows scalable and integrative analyses of both long-read and short-read metagenomic Hi-C data
Authors: Du Yuxuan , Sun Fengzhu 
Published: October 2023

AbstractMetagenomic Hi-C (metaHi-C) can identify contig-to-contig relationships with respect to their proximity within the same physical cell. Shotgun libraries in metaHi-C experiments can be constructed by next-generation sequencing (short-read metaHi-C) or more recent third-generation sequencing (long-read metaHi-C). However, all existing metaHi-C analysis methods are developed and benchmarked on short-read metaHi-C datasets and there exists much room for improvement in terms of more scalable and stable analyses, especially for long-read metaHi-C data. Here we report MetaCC, an efficient and integrative framework for analyzing both short-read and long-read metaHi-C datasets. MetaCC outperforms existing methods on normalization and binning. In particular, the MetaCC normalization module, named NormCC, is more than 3000 times faster than the current state-of-the-art method HiCzin on a complex wastewater dataset. When applied to one sheep gut long-read metaHi-C dataset, MetaCC binning module can retrieve 709 high-quality genomes with the largest species diversity using one single sample, including an expansion of five uncultured members from the order Erysipelotrichales, and is the only binner that can recover the genome of one important species Bacteroides vulgatus. Further plasmid analyses reveal that MetaCC binning is able to capture multi-copy plasmids.
Distinct and targetable role of calcium-sensing receptor in leukaemia
Authors: Pereira Raquel S. , Kumar Rahul , Cais Alessia , Paulini Lara , Kahler Alisa , Bravo Jimena , Minciacchi Valentina R. , Krack Theresa , Kowarz Eric , Zanetti Costanza , Godavarthy Parimala Sonika , Hoeller Fabian , Llavona Pablo , Stark Tabea , Tascher Georg , Nowak Daniel , Meduri Eshwar , Huntly Brian J. P. , Münch Christian , Pampaloni Francesco , Marschalek Rolf , Krause Daniela S. 
Published: October 2023

AbstractHaematopoietic stem cells (HSC) reside in the bone marrow microenvironment (BMM), where they respond to extracellular calcium [eCa2+] via the G-protein coupled calcium-sensing receptor (CaSR). Here we show that a calcium gradient exists in this BMM, and that [eCa2+] and response to [eCa2+] differ between leukaemias. CaSR influences the location of MLL-AF9+ acute myeloid leukaemia (AML) cells within this niche and differentially impacts MLL-AF9+ AML versus BCR-ABL1+ leukaemias. Deficiency of CaSR reduces AML leukaemic stem cells (LSC) 6.5-fold. CaSR interacts with filamin A, a crosslinker of actin filaments, affects stemness-associated factors and modulates pERK, β-catenin and c-MYC signaling and intracellular levels of [Ca2+] in MLL-AF9+ AML cells. Combination treatment of cytarabine plus CaSR-inhibition in various models may be superior to cytarabine alone. Our studies suggest CaSR to be a differential and targetable factor in leukaemia progression influencing self-renewal of AML LSC via [eCa2+] cues from the BMM.
Topologically crafted spatiotemporal vortices in acoustics
Authors: Zhang Hongliang , Sun Yeyang , Huang Junyi , Wu Bingjun , Yang Zhaoju , Bliokh Konstantin Y. , Ruan Zhichao 
Published: October 2023

AbstractVortices in fluids and gases have piqued the human interest for centuries. Development of classical-wave physics and quantum mechanics highlighted wave vortices characterized by phase singularities and topological charges. In particular, vortex beams have found numerous applications in modern optics and other areas. Recently, optical spatiotemporal vortex states exhibiting the phase singularity both in space and time have been described. Here, we report the topologically robust generation of acoustic spatiotemporal vortex pulses. We utilize an acoustic meta-grating with broken mirror symmetry which exhibits a topological phase transition with a pair of phase singularities with opposite topological charges emerging in the momentum-frequency domain. We show that these vortices are topologically robust against structural perturbations of the meta-grating and can be employed for the generation of spatiotemporal vortex pulses. Our work paves the way for studies and applications of spatiotemporal structured waves in acoustics and other wave systems.
Improving model fairness in image-based computer-aided diagnosis
Authors: Lin Mingquan , Li Tianhao , Yang Yifan , Holste Gregory , Ding Ying , Van Tassel Sarah H. , Kovacs Kyle , Shih George , Wang Zhangyang , Lu Zhiyong , Wang Fei , Peng Yifan 
Published: October 2023

AbstractDeep learning has become a popular tool for computer-aided diagnosis using medical images, sometimes matching or exceeding the performance of clinicians. However, these models can also reflect and amplify human bias, potentially resulting inaccurate missed diagnoses. Despite this concern, the problem of improving model fairness in medical image classification by deep learning has yet to be fully studied. To address this issue, we propose an algorithm that leverages the marginal pairwise equal opportunity to reduce bias in medical image classification. Our evaluations across four tasks using four independent large-scale cohorts demonstrate that our proposed algorithm not only improves fairness in individual and intersectional subgroups but also maintains overall performance. Specifically, the relative change in pairwise fairness difference between our proposed model and the baseline model was reduced by over 35%, while the relative change in AUC value was typically within 1%. By reducing the bias generated by deep learning models, our proposed approach can potentially alleviate concerns about the fairness and reliability of image-based computer-aided diagnosis.
Dual water-electricity cooperation improves economic benefits and water equality in the Lancang-Mekong River Basin
Authors: Zhang Bingyao , Li Yu , Zhang Chi , Hu Chunhong , Fu Guangtao , Cai Ximing 
Published: October 2023

AbstractTransboundary river cooperation provides an effective pathway to maintain regional security and sustainable development; however, its implementation is a pressing and prominent concern due to lack of appropriate compensation measures and effective incentive strategies. Here we develop a dual water-electricity cooperation (DWEC) framework that combines water and electricity trading to meet the often-conflicting demands of participating countries. The results from the Lancang-Mekong River Basin reveal that substantial benefits in both economic and social aspects can be achieved through coupling regional water and electricity trades. Economic benefits can be obtained by expanding cooperation space and thereby greatly improving the willingness of countries to participate in basin-wide cooperation. Electricity trading plays a key role in loss compensation for water exporters, ensuring no loss for any party and maximizing basin-wide benefits. Furthermore, the DWEC improves regional water use equality, especially in water shortage periods when there is severe competition among water users. The proposed cooperation framework provides a viable way to implement cooperation in transboundary river basins.
Quantum speed limit for complex dynamics
Authors: Zhang Mao , Yu Huai-Ming , Liu Jing 
Published: October 2023

AbstractQuantum speed limit focuses on the minimum time scale for a fixed mission and hence is important in quantum information where fast dynamics is usually beneficial. Most existing tools for the depiction of quantum speed limit are the lower-bound-type tools, which are in fact difficult to reveal the true minimum time, especially for many-body systems or complex dynamics. Therefore, the evaluation of this true minimum time in these scenarios is still an unsolved problem. Hereby we provide the operational definition of quantum speed limit for a general target and propose a three-step (classification-regression-calibration) methodology based on machine learning to evaluate the true minimum time in complex dynamics. Moreover, the analytical expression of the true minimum time is also provided for the time-dependent Hamiltonians with time-independent eigenstates.
Understanding and leveraging phenotypic plasticity during metastasis formation
Authors: Shah Saumil , Philipp Lisa-Marie , Giaimo Stefano , Sebens Susanne , Traulsen Arne , Raatz Michael 
Published: October 2023

AbstractCancer metastasis is the process of detrimental systemic spread and the primary cause of cancer-related fatalities. Successful metastasis formation requires tumor cells to be proliferative and invasive; however, cells cannot be effective at both tasks simultaneously. Tumor cells compensate for this trade-off by changing their phenotype during metastasis formation through phenotypic plasticity. Given the changing selection pressures and competitive interactions that tumor cells face, it is poorly understood how plasticity shapes the process of metastasis formation. Here, we develop an ecology-inspired mathematical model with phenotypic plasticity and resource competition between phenotypes to address this knowledge gap. We find that phenotypically plastic tumor cell populations attain a stable phenotype equilibrium that maintains tumor cell heterogeneity. Considering treatment types inspired by chemo- and immunotherapy, we highlight that plasticity can protect tumors against interventions. Turning this strength into a weakness, we corroborate current clinical practices to use plasticity as a target for adjuvant therapy. We present a parsimonious view of tumor plasticity-driven metastasis that is quantitative and experimentally testable, and thus potentially improving the mechanistic understanding of metastasis at the cell population level, and its treatment consequences.
Proof of concept for a single-dose Group B Streptococcus vaccine based on capsular polysaccharide conjugated to Qβ virus-like particles
Authors: Carboni Filippo , Cozzi Roberta , Romagnoli Giacomo , Tuscano Giovanna , Balocchi Cristiana , Buffi Giada , Bodini Margherita , Brettoni Cecilia , Giusti Fabiola , Marchi Sara , Brogioni Giulia , Brogioni Barbara , Cinelli Paolo , Cappelli Luigia , Nocciolini Chiara , Senesi Silvia , Facciotti Claudia , Frigimelica Elisabetta , Fabbrini Monica , Stranges Daniela , Savino Silvana , Maione Domenico , Adamo Roberto , Wizel Benjamin , Margarit Immaculada , Romano Maria Rosaria 
Published: October 2023

AbstractA maternal vaccine to protect neonates against Group B Streptococcus invasive infection is an unmet medical need. Such a vaccine should ideally be offered during the third trimester of pregnancy and induce strong immune responses after a single dose to maximize the time for placental transfer of protective antibodies. A key target antigen is the capsular polysaccharide, an anti-phagocytic virulence factor that elicits protective antibodies when conjugated to carrier proteins. The most prevalent polysaccharide serotypes conjugated to tetanus or diphtheria toxoids have been tested in humans as monovalent and multivalent formulations, showing excellent safety profiles and immunogenicity. However, responses were suboptimal in unprimed individuals after a single shot, the ideal schedule for vaccination during the third trimester of pregnancy. In the present study, we obtained and optimized self-assembling virus-like particles conjugated to Group B Streptococcus capsular polysaccharides. The resulting glyco-nanoparticles elicited strong immune responses in mice already after one immunization, providing pre-clinical proof of concept for a single-dose vaccine.
Ground truth based comparison of saliency maps algorithms
Authors: Szczepankiewicz Karolina , Popowicz Adam , Charkiewicz Kamil , Nałęcz-Charkiewicz Katarzyna , Szczepankiewicz Michał , Lasota Sławomir , Zawistowski Paweł , Radlak Krystian 
Published: October 2023

AbstractDeep neural networks (DNNs) have achieved outstanding results in domains such as image processing, computer vision, natural language processing and bioinformatics. In recent years, many methods have been proposed that can provide a visual explanation of decision made by such classifiers. Saliency maps are probably the most popular. However, it is still unclear how to properly interpret saliency maps for a given image and which techniques perform most accurately. This paper presents a methodology to practically evaluate the real effectiveness of saliency map generation methods. We used three state-of-the-art network architectures along with specially prepared benchmark datasets, and we proposed a novel metric to provide a quantitative comparison of the methods. The comparison identified the most reliable techniques and the solutions which usually failed in our tests.
Seasonal variations of functional connectivity of human brains
Authors: Xu Lyuan , Choi Soyoung , Zhao Yu , Li Muwei , Rogers Baxter P. , Anderson Adam , Gore John C. , Gao Yurui , Ding Zhaohua 
Published: October 2023

AbstractSeasonal variations have long been observed in various aspects of human life. While there is an abundance of research that has characterized seasonality effects in, for example, cognition, mood, and behavior, including studies of underlying biophysical mechanisms, direct measurements of seasonal variations of brain functional activities have not gained wide attention. We have quantified seasonal effects on functional connectivity as derived from MRI scans. A cohort of healthy human subjects was divided into four groups based on the seasons of their scanning dates as documented in the image database of the Human Connectome Project. Sinusoidal functions were used as regressors to determine whether there were significant seasonal variations in measures of brain activities. We began with the analysis of seasonal variations of the fractional amplitudes of low frequency fluctuations of regional functional signals, followed by the seasonal variations of functional connectivity in both global- and network-level. Furthermore, relevant environmental factors, including average temperature and daylength, were found to be significantly associated with brain functional activities, which may explain how the observed seasonal fluctuations arise. Finally, topological properties of the brain functional network also showed significant variations across seasons. All the observations accumulated revealed seasonality effects of human brain activities in a resting-state, which may have important practical implications for neuroimaging research.
Effect of polydeoxyribonucleotide on early bone formation in lateral bone augmentation with immediate implant placement: an experimental in vivo study
Authors: Lee Dongseob , Lee Jungwon , Seol Yang-Jo , Lee Yong-Moo , Koo Ki-Tae 
Published: October 2023

AbstractThis study investigated early bone formation using collagenated biphasic calcium phosphate (CBCP) with or without polynucleotide (PDRN). Third (P3) or fourth (P4) premolars of six male beagle dogs were extracted and 5-mm-high dehiscence defects were created, followed by 3D-printed implant placement. The buccal bone defects were grafted with (i) CBCP and collagen membrane or (ii) CBCP soaked in polydeoxyribonucleotide (CBCP/PDRN) and collagen membrane. Samples of the experimental sites were harvested at 2- and 6-weeks post-surgery. The specimens were evaluated with radiologic and histomorphometric analysis. No significant differences were found between the CBCP and CBCP/PDRN groups in the micro-CT analysis at 2 or 6 weeks. No significant differences were observed in bone-to-implant contact (BIC) or bone area fraction occupancy (BAFO) in buccal augmented and lingual non-augmented areas. In the qualitative analysis, the new bone (NB) area and NB proportion in buccal augmented areas showed significantly higher values in the CBCP/PDRN group than in the CBCP group at 2 and 6 weeks. Peri-implant buccal dehiscence defects with immediate 3D-printed implant placement were corrected using a collagen membrane and CBCP or CBCP/PDRN. PDRN might have the potential to facilitate early bone formation with sufficient stability over time in dehiscence defects.
Physics-informed neural network with transfer learning (TL-PINN) based on domain similarity measure for prediction of nuclear reactor transients
Authors: Prantikos Konstantinos , Chatzidakis Stylianos , Tsoukalas Lefteri H. , Heifetz Alexander 
Published: October 2023

AbstractNuclear reactor safety and efficiency can be enhanced through the development of accurate and fast methods for prediction of reactor transient (RT) states. Physics informed neural networks (PINNs) leverage deep learning methods to provide an alternative approach to RT modeling. Applications of PINNs in monitoring of RTs for operator support requires near real-time model performance. However, as with all machine learning models, development of a PINN involves time-consuming model training. Here, we show that a transfer learning (TL-PINN) approach achieves significant performance gain, as measured by reduction of the number of iterations for model training. Using point kinetic equations (PKEs) model with six neutron precursor groups, constructed with experimental parameters of the Purdue University Reactor One (PUR-1) research reactor, we generated different RTs with experimentally relevant range of variables. The RTs were characterized using Hausdorff and Fréchet distance. We have demonstrated that pre-training TL-PINN on one RT results in up to two orders of magnitude acceleration in prediction of a different RT. The mean error for conventional PINN and TL-PINN models prediction of neutron densities is smaller than 1%. We have developed a correlation between TL-PINN performance acceleration and similarity measure of RTs, which can be used as a guide for application of TL-PINNs.
Medial open-wedge high tibial osteotomy for the treatment of degenerative varus knee osteoarthritis in geriatric patients: a retrospective study
Authors: Li Jia , Zhao Feng , Dong Wei , Yu Xiaoguang , Zhu Chaohua , Liu Sen , Jia Guoxing , Liu Guobin 
Published: October 2023

AbstractHTO has proven to be a cost-effective surgical procedure in the treatment of KOA, but few investigations have studied radiological changes and clinical effectiveness of OWHTO in geriatric patients. 76 patients were recruited in this retrospective study. According to the age, patients were divided into two groups (≤ 60, Group “Young”; > 60, Group “Geriatric”). Demographic data, radiological imaging and postoperative complications were analyzed. Kellgren–Lawrence grade (K–L), weight-bearing line ratio (WBLR); posterior tibial slope angle (PTS); American knee score (AKS); Western Ontario and McMaster Universities Arthritis Index (WOMAC) and visual analog scale (VAS) were introduced to estimate the clinical outcome of OWHTO. There were 18 male and 58 female patients in the present study with a mean age of 58.5 ± 9.2 years (ranges from 40 to 82 years); the average age was 51.4 ± 4.1 years and 67.3 ± 4.9 years for group Y and G respectively, 44.7% and 31.5% patients were older than 60 and 65 years. BMI for the 76 patients was 26.6 ± 3.2 kg/m2, and geriatric patients were more likely accompanied by one or more comorbidities (70.6 vs. 45.2%). There were 34 and 42 patients in group Geriatric and group Young respectively, and no significant difference of MPTA, WBLR, PTS and WOMAC, VAS, AKS and ROM between the two group (P > 0.05) were found. After more than a two-year follow-up period, postoperative WBLR, AKS, WOMAC and VAS were much more desired than preoperative, and no significant difference of these variables between the young and geriatric group (P > 0.05), however, elderly patients were more likely to suffer from a longer bone union time. OWHTO can avoid geriatric patients from undergoing secondary knee surgery in the short term, however the survival rate of OWHTO in geriatric patients should be ultimately clarified by different studies.
MALAT1 expression is associated with aggressive behavior in indolent B-cell neoplasms
Authors: Fernández-Garnacho Elena María , Nadeu Ferran , Martín Silvia , Mozas Pablo , Rivero Andrea , Delgado Julio , Giné Eva , López-Guillermo Armando , Duran-Ferrer Martí , Salaverria Itziar , López Cristina , Beà Sílvia , Demajo Santiago , Jares Pedro , Puente Xose S. , Martín-Subero José Ignacio , Campo Elías , Hernández Lluís 
Published: October 2023

AbstractMALAT1 long non-coding RNA has oncogenic roles but has been poorly studied in indolent B-cell neoplasms. Here, MALAT1 expression was analyzed using RNA-seq, microarrays or qRT-PCR in primary samples from clinico-biological subtypes of chronic lymphocytic leukemia (CLL, n = 266), paired Richter transformation (RT, n = 6) and follicular lymphoma (FL, n = 61). In peripheral blood (PB) CLL samples, high MALAT1 expression was associated with a significantly shorter time to treatment independently from other known prognostic factors. Coding genes expressed in association with MALAT1 in CLL were predominantly related to oncogenic pathways stimulated in the lymph node (LN) microenvironment. In RT paired samples, MALAT1 levels were lower, concordant with their acquired increased independency of external signals. Moreover, MALAT1 levels in paired PB/LN CLLs were similar, suggesting that the prognostic value of MALAT1 expression in PB is mirroring expression differences already present in LN. Similarly, high MALAT1 expression in FL predicted for a shorter progression-free survival, in association with expression pathways promoting FL pathogenesis. In summary, MALAT1 expression is related to pathophysiology and more aggressive clinical behavior of indolent B-cell neoplasms. Particularly in CLL, its levels could be a surrogate marker of the microenvironment stimulation and may contribute to refine the clinical management of these patients.