bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using Deep Learning to Model the Groundwater Tracer Radon in Coastal Waters
Authors: McKenzie Tristan , Dulai Henrietta , Lee Jonghyun , Dimova Natasha T. , Santos Isaac R. , Zhang Bo , Burnett William 
Published: March 2023

AbstractSubmarine groundwater discharge (SGD) is an important driver of coastal biogeochemical budgets worldwide. Radon (222Rn) has been widely used as a natural geochemical tracer to quantify SGD, but field measurements are time consuming and costly. Here, we use deep learning to predict coastal seawater radon in SGD‐impacted regions. We hypothesize that deep learning could resolve radon trends and enable preliminary insights with limited field observations of groundwater tracers. Two deep learning models were trained on global coastal seawater radon observations (n = 39,238) with widely available inputs (e.g., salinity, temperature, water depth). The first model used a one‐dimensional convolutional neural network (1D‐CNN‐RNN) framework for site‐specific gap filling and producing short‐term future predictions. A second model applied a fully connected neural network (FCNN) framework to predict radon across geographically and hydrologically diverse settings. Both models can predict observed radon concentrations with r2 > 0.76. Specifically, the FCNN model offers a compelling development because synthetic radon tracer data sets can be obtained using only basic water quality and meteorological parameters. This opens opportunities to attain radon data from regions with large data gaps, such as the Global South and other remote locations, allowing for insights that can be used to predict SGD and plan field experiments. Overall, we demonstrate how field‐based measurements combined with big‐data approaches such as deep learning can be utilized to assess radon and potentially SGD beyond local scales.
Investigating brain aging trajectory deviations in different brain regions of individuals with schizophrenia using multimodal magnetic resonance imaging and brain-age prediction: a multicenter study
Authors: Zhu Jun-Ding , Wu Yung-Fu , Tsai Shih-Jen , Lin Ching-Po , Yang Albert C. 
Published: March 2023

AbstractAlthough many studies on brain-age prediction in patients with schizophrenia have been reported recently, none has predicted brain age based on different neuroimaging modalities and different brain regions in these patients. Here, we constructed brain-age prediction models with multimodal MRI and examined the deviations of aging trajectories in different brain regions of participants with schizophrenia recruited from multiple centers. The data of 230 healthy controls (HCs) were used for model training. Next, we investigated the differences in brain age gaps between participants with schizophrenia and HCs from two independent cohorts. A Gaussian process regression algorithm with fivefold cross-validation was used to train 90, 90, and 48 models for gray matter (GM), functional connectivity (FC), and fractional anisotropy (FA) maps in the training dataset, respectively. The brain age gaps in different brain regions for all participants were calculated, and the differences in brain age gaps between the two groups were examined. Our results showed that most GM regions in participants with schizophrenia in both cohorts exhibited accelerated aging, particularly in the frontal lobe, temporal lobe, and insula. The parts of the white matter tracts, including the cerebrum and cerebellum, indicated deviations in aging trajectories in participants with schizophrenia. However, no accelerated brain aging was noted in the FC maps. The accelerated aging in 22 GM regions and 10 white matter tracts in schizophrenia potentially exacerbates with disease progression. In individuals with schizophrenia, different brain regions demonstrate dynamic deviations of brain aging trajectories. Our findings provided more insights into schizophrenia neuropathology.
A sensitive and reproducible qRT-PCR assay detects physiological relevant trace levels of FMR1 mRNA in individuals with Fragile X syndrome
Authors: Straub Devan , Schmitt Lauren M. , Boggs Anna E. , Horn Paul S. , Dominick Kelli C. , Gross Christina , Erickson Craig A. 
Published: March 2023

AbstractFragile X syndrome (FXS) is the most common inherited intellectual disability. FXS is caused by a trinucleotide repeat expansion in the 5′ untranslated region of the FMR1 gene, which leads to gene methylation, transcriptional silencing, and lack of expression of Fragile X Messenger Riboprotein (FMRP). Currently available FXS therapies are inefficient, and the disease severity is highly variable, making it difficult to predict disease trajectory and treatment response. We and others have recently shown that a subset of full-mutation, fully-methylated (FM–FM) males with FXS express low amounts of FMRP which could contribute to phenotypic variability. To better understand the underlying mechanisms, we developed a sensitive qRT-PCR assay to detect FMR1 mRNA in blood. This assay reproducibly detects trace amounts of FMR1 mRNA in a subset of FM–FM males, suggesting that current Southern Blot and PCR determination of FM–FM status is not always associated with complete transcriptional silencing. The functional relevance of trace-level FMR1 mRNA is confirmed by showing a positive correlation with cognitive function; however, phenotypic variability is not fully explained by FMR1 expression. These results corroborate the need for better molecular assays for FXS diagnosis and encourage studies to elucidate the factors contributing to the phenotypic variability of FXS.
Benthic jellyfish act as suction pumps to facilitate release of interstitial porewater
Authors: Durieux David M. , Scrogham Gabrielle D. , Fender Christian , Lewis David B. , Deban Stephen M. , Gemmell Brad J. 
Published: March 2023

AbstractUpside-down jellyfish, genus Cassiopea (Péron and Lesueur, 1809), are found in shallow coastal habitats in tropical and subtropical regions circumglobally. These animals have previously been demonstrated to produce flow both in the water column as a feeding current, and in the interstitial porewater, where they liberate porewater at rates averaging 2.46 mL h−1. Since porewater in Cassiopea habitat can be nutrient-rich, this is a potential source of nutrient enrichment in these ecosystems. This study experimentally determines that porewater release by Cassiopea sp. jellyfish is due to suction pumping, and not the Bernoulli effect. This suggests porewater release is directly coupled to bell pulsation rate, and unlike vertical jet flux, should be unaffected by population density. In addition, we show that bell pulsation rate is positively correlated with temperature, and negatively correlated with animal size. As such, we would predict an increase in the release of nutrient-rich porewater during the warm summer months. Furthermore, we show that, at our field site in Lido Key, Florida, at the northernmost limit of Cassiopea range, population densities decline during the winter, increasing seasonal differences in porewater release.
Understanding who talks about what: comparison between the information treatment in traditional media and online discussions
Authors: Schawe Hendrik , Beiró Mariano G. , Alvarez-Hamelin J. Ignacio , Kotzinos Dimitris , Hernández Laura 
Published: March 2023

AbstractWe study the dynamics of interactions between a traditional medium, the New York Times journal, and its followers in Twitter, using a massive dataset. It consists of the metadata of the articles published by the journal during the first year of the COVID-19 pandemic, and the posts published in Twitter by a large set of followers of the @nytimes account along with those published by a set of followers of several other media of different kind. The dynamics of discussions held in Twitter by exclusive followers of a medium show a strong dependence on the medium they follow: the followers of @FoxNews show the highest similarity to each other and a strong differentiation of interests with the general group. Our results also reveal the difference in the attention payed to U.S. presidential elections by the journal and by its followers, and show that the topic related to the “Black Lives Matter” movement started in Twitter, and was addressed later by the journal.
First paleoproteome study of fossil fish otoliths and the pristine preservation of the biomineral crystal host
Authors: Stolarski Jarosław , Drake Jeana , Coronado Ismael , Vieira Ana R. , Radwańska Urszula , Heath-Heckman Elizabeth A. C. , Mazur Maciej , Guo Jinming , Meibom Anders 
Published: March 2023

AbstractOtoliths are calcium carbonate components of the stato-acoustical organ responsible for hearing and maintenance of the body balance in teleost fish. During their formation, control over, e.g., morphology and carbonate polymorph is influenced by complex insoluble collagen-like protein and soluble non-collagenous protein assemblages; many of these proteins are incorporated into their aragonite crystal structure. However, in the fossil record these proteins are considered lost through diagenetic processes, hampering studies of past biomineralization mechanisms. Here we report the presence of 11 fish-specific proteins (and several isoforms) in Miocene (ca. 14.8–14.6 Ma) phycid hake otoliths. These fossil otoliths were preserved in water-impermeable clays and exhibit microscopic and crystallographic features indistinguishable from modern representatives, consistent with an exceptionally pristine state of preservation. Indeed, these fossil otoliths retain ca. 10% of the proteins sequenced from modern counterparts, including proteins specific to inner ear development, such as otolin-1-like proteins involved in the arrangement of the otoliths into the sensory epithelium and otogelin/otogelin-like proteins that are located in the acellular membranes of the inner ear in modern fish. The specificity of these proteins excludes the possibility of external contamination. Identification of a fraction of identical proteins in modern and fossil phycid hake otoliths implies a highly conserved inner ear biomineralization process through time.
The dynamics of novel corona virus disease via stochastic epidemiological model with vaccination
Authors: Ullah Rahman , Al Mdallal Qasem , Khan Tahir , Ullah Roman , Al Alwan Basem , Faiz Faizullah , Zhu Quanxin 
Published: March 2023

AbstractDuring the past two years, the novel coronavirus pandemic has dramatically affected the world by producing 4.8 million deaths. Mathematical modeling is one of the useful mathematical tools which has been used frequently to investigate the dynamics of various infectious diseases. It has been observed that the nature of the novel disease of coronavirus transmission differs everywhere, implying that it is not deterministic while having stochastic nature. In this paper, a stochastic mathematical model has been investigated to study the transmission dynamics of novel coronavirus disease under the effect of fluctuated disease propagation and vaccination because effective vaccination programs and interaction of humans play a significant role in every infectious disease prevention. We develop the epidemic problem by taking into account the extended version of the susceptible-infected-recovered model and with the aid of a stochastic differential equation. We then study the fundamental axioms for existence and uniqueness to show that the problem is mathematically and biologically feasible. The extinction of novel coronavirus and persistency are examined, and sufficient conditions resulted from our investigation. In the end, some graphical representations support the analytical findings and present the effect of vaccination and fluctuated environmental variation.
Osteoclastogenesis of human peripheral blood, bone marrow, and cord blood monocytes
Authors: Vuoti Ella , Lehenkari Petri , Tuukkanen Juha , Glumoff Virpi , Kylmäoja Elina 
Published: March 2023

AbstractOsteoclasts are multinucleated bone resorbing cells that can be differentiated from human monocytes in vitro. There are few studies comparing osteoclastogenesis of different monocyte sources. We compared monocytes from human bone marrow (BM), peripheral blood (PB), and umbilical cord blood (CB) and their osteoclastogenic potential by culturing them with RANKL (20 and 80 ng/ml) and M-CSF (10 ng/ml) for 14 days. We also cultured cells without growth factors, as umbilical cord blood monocytes have been reported to be able to fuse spontaneously into osteoclasts. The data was analysed on d4, d8, d11, and d14. After culture with RANKL and M-CSF, all types of cell cultures developed TRACP -positive multinuclear cells that were able to form resorption pits on human bone slices. Only occasional multinuclear cells and small infrequent resorbed areas could be found in PB and CB-derived cultures without growth factors. BM-derived cells formed greater resorption areas than PB- and CB-derived monocytes. The greatest monocyte population in BM samples were intermediate (CD14++CD16+) and in PB and CB classical monocytes (76.3% and 54.4%, respectively). In conclusion, our data demonstrates that bone resorbing osteoclasts can be differentiated from BM, PB and CB. However, the osteoclast precursor origin can affect the osteoclast properties and function.
Intelligent modeling of hydrogen sulfide solubility in various types of single and multicomponent solvents
Authors: Moradkhani M. A. , Hosseini S. H. , Ranjbar K. , Moradi M. 
Published: March 2023

AbstractThis study aims to study the solubility of acid gas, i.e., hydrogen sulfide (H2S) in different solvents. Three intelligent approaches, including Multilayer Perceptron (MLP), Gaussian Process Regression (GPR) and Radial Basis Function (RBF) were used to construct reliable models based on an extensive databank comprising 5148 measured samples from 54 published sources. The analyzed data cover 95 single and multicomponent solvents such as amines, ionic liquids, electrolytes, organics, etc., in broad pressure and temperature ranges. The proposed models require just three simple input variables, i.e., pressure, temperature and the equivalent molecular weight of solvent to determine the solubility. A competitive examination of the novel models implied that the GPR-based one gives the most appropriate estimations with excellent AARE, R2 and RRMSE values of 4.73%, 99.75% and 4.83%, respectively for the tested data. The mentioned intelligent model also performed well in describing the physical behaviors of H2S solubility at various operating conditions. Furthermore, analyzing the William's plot for the GPR-based model affirmed the high reliability of the analyzed databank, as the outlying data points comprise just 2.04% of entire data. In contrast to the literature models, the newly presented approaches proved to be applicable for different types of single and multicomponent H2S absorbers with AAREs less than 7%. Eventually, a sensitivity analysis based on the GPR model reflected the fact that the solvent equivalent molecular weight is the most influential factor in controlling H2S solubility.
Correction of haemorrhagic shock-associated coagulopathy and impaired haemostasis by plasma, prothrombin complex concentrates or an activated protein C-targeted DNA aptamer in mice
Authors: Eltringham-Smith Louise J. , Meixner Scott C. , Pryzdial Edward L. G. , Sheffield William P. 
Published: March 2023

AbstractEven with extensive transfusion support, trauma-induced bleeding often leads to death. Early intervention may improve outcomes, yet which blood products, factor concentrates, or other drugs constitute optimal treatment is unclear. Patients with acute traumatic coagulopathy (ATC), arising from trauma and haemorrhagic shock, have the worst prognosis. Here, multiple interventions were compared in a mouse model of ATC. After the trauma of tissue excision, anaesthetized mice were bled to 35 mm Hg mean arterial pressure, maintained under shock for 60 min, and resuscitated with fluids equal in volume to the shed blood. Resuscitated mice were subjected to liver laceration to test haemostasis and blood loss was quantified. Saline-treated mice lost two- to three-fold more blood than sham-treated animals and were coagulopathic by prothrombin time elevation post- versus pre-procedure. Murine fresh-frozen plasma (mFFP), anti-activated protein C aptamer HS02-52G, or prothrombin complex concentrates eliminated the bleeding diathesis and coagulopathy; fibrinogen, plasminogen activator inhibitor-1, or tranexamic acid ameliorated bleeding or coagulopathy, but not both. HS02-52G and mFFP also eliminated the changes in plasma aPC and tissue plasminogen activator levels observed in saline-treated mice, as judged via microtiter plate biomarker assays. Procoagulant interventions, especially inhibiting aPC, could be beneficial in human ATC.
Presepsin as a diagnostic and prognostic biomarker of severe bacterial infections and COVID-19
Authors: Kyriazopoulou Evdoxia , Leventogiannis Konstantinos , Tavoulareas Georgios , Mainas Efstratios , Toutouzas Konstantinos , Mathas Christos , Prekates Athanassios , Sakka Vissaria , Panagopoulos Periklis , Syrigos Konstantinos , Giamarellos-Bourboulis Evangelos J. 
Published: March 2023

AbstractWe aimed to develop presepsin as a marker of diagnosis of severe infections of either bacterial and viral origin. The derivation cohort was recruited from 173 hospitalized patients with acute pancreatitis or post-operative fever or infection suspicion aggravated by at least one sign of the quick sequential organ failure assessment (qSOFA). The first validation cohort was recruited from 57 admissions at the emergency department with at least one qSOFA sign and the second validation cohort from 115 patients with COVID-19 pneumonia. Presepsin was measured in plasma by the PATHFAST assay. Concentrations more than 350 pg/ml had sensitivity 80.2% for sepsis diagnosis in the derivation cohort (adjusted odds ratio 4.47; p < 0.0001). In the derivation cohort, sensitivity for 28-day mortality prognosis was 91.5% (adjusted odds ratio 6.82; p: 0.001). Concentrations above 350 pg/ml had sensitivity 93.3% for the diagnosis of sepsis in the first validation cohort; this was 78.3% in the second validation cohort of COVID-19 aiming at the early diagnosis of acute respiratory distress syndrome necessitating mechanical ventilation. The respective sensitivity for 28-day mortality was 85.7% and 92.3%. Presepsin may be a universal biomarker for the diagnosis of severe infections of bacterial origin and prediction of unfavorable outcome.
Differentially expressed discriminative genes and significant meta-hub genes based key genes identification for hepatocellular carcinoma using statistical machine learning
Authors: Hasan Md. Al Mehedi , Maniruzzaman Md. , Shin Jungpil 
Published: March 2023

AbstractHepatocellular carcinoma (HCC) is the most common lethal malignancy of the liver worldwide. Thus, it is important to dig the key genes for uncovering the molecular mechanisms and to improve diagnostic and therapeutic options for HCC. This study aimed to encompass a set of statistical and machine learning computational approaches for identifying the key candidate genes for HCC. Three microarray datasets were used in this work, which were downloaded from the Gene Expression Omnibus Database. At first, normalization and differentially expressed genes (DEGs) identification were performed using limma for each dataset. Then, support vector machine (SVM) was implemented to determine the differentially expressed discriminative genes (DEDGs) from DEGs of each dataset and select overlapping DEDGs genes among identified three sets of DEDGs. Enrichment analysis was performed on common DEDGs using DAVID. A protein-protein interaction (PPI) network was constructed using STRING and the central hub genes were identified depending on the degree, maximum neighborhood component (MNC), maximal clique centrality (MCC), centralities of closeness, and betweenness criteria using CytoHubba. Simultaneously, significant modules were selected using MCODE scores and identified their associated genes from the PPI networks. Moreover, metadata were created by listing all hub genes from previous studies and identified significant meta-hub genes whose occurrence frequency was greater than 3 among previous studies. Finally, six key candidate genes (TOP2A, CDC20, ASPM, PRC1, NUSAP1, and UBE2C) were determined by intersecting shared genes among central hub genes, hub module genes, and significant meta-hub genes. Two independent test datasets (GSE76427 and TCGA-LIHC) were utilized to validate these key candidate genes using the area under the curve. Moreover, the prognostic potential of these six key candidate genes was also evaluated on the TCGA-LIHC cohort using survival analysis.
Quantum asymmetric key crypto scheme using Grover iteration
Authors: Yoon Chun Seok , Hong Chang Ho , Kang Min Sung , Choi Ji-Woong , Yang Hyung Jin 
Published: March 2023

AbstractHere, we propose a quantum asymmetric key cryptography scheme using Grover’s quantum search algorithm. In the proposed scheme, Alice generates a pair of public and private keys, keeps the private keys safe, and only discloses public keys to the outside. Bob uses Alice's public key to send a secret message to Alice and Alice uses her private key to decrypt the secret message. Furthermore, we discuss the safety of quantum asymmetric key encryption techniques based on quantum mechanical properties.
A novel DNA methylation signature to improve survival prediction of progression-free survival for testicular germ cell tumors
Authors: Gao Feng , Xu Qiaoping , Jiang Yingjun , Lu Bingjun 
Published: March 2023

AbstractThis study aimed to develop a nomogram for predicting the progression-free survival (PFS) of testicular germ cell tumors (TGCT) patients based on DNA methylation signature and clinicopathological characteristics. The DNA methylation profiles, transcriptome data, and clinical information of TGCT patients were obtained from the Cancer Genome Atlas (TCGA) database. Univariate Cox, lasso Cox, and stepwise multivariate Cox regression were applied to identify a prognostic CpG sites-derived risk signature. Differential expression analysis, functional enrichment analysis, immunoinfiltration analysis, chemotherapy sensitivity analysis, and clinical feature correlation analysis were performed to elucidate the differences among risk groups. A prognostic nomogram integrating CpG sites-derived risk signature and clinicopathological features was further established and evaluated likewise. A risk score model based on 7 CpG sites was developed and found to exhibit significant differences among different survival, staging, radiotherapy, and chemotherapy subgroups. There were 1452 differentially expressed genes between the high- and low-risk groups, with 666 being higher expressed and 786 being lower expressed. Genes highly expressed were significantly enriched in immune-related biological processes and related to T-cell differentiation pathways; meanwhile, down-regulated genes were significantly enriched in extracellular matrix tissue organization-related biological processes and involved in multiple signaling pathways such as PI3K-AKT. As compared with the low-risk group, patients in the high-risk group had decreased lymphocyte infiltration (including T-cell and B-cell) and increased macrophage infiltration (M2 macrophages). They also showed decreased sensitivity to etoposide and bleomycin chemotherapy. Three clusters were obtained by consensus clustering analysis based on the 7 CpG sites and showed distinct prognostic features, and the risk scores in each cluster were significantly different. Multivariate Cox regression analysis found that the risk scores, age, chemotherapy, and staging were independent prognostic factors of PFS of TGCT, and the results were used to formulate a nomogram model that was validated to have a C-index of 0.812. Decision curve analysis showed that the nomogram model was superior to other strategies in the prediction of PFS of TGCT. In this study, we successfully established CpG sites-derived risk signature, which might serve as a useful tool in the prediction of PFS, immunoinfiltration, and chemotherapy sensitivity for TGCT patients.