bluuebunny/crossref_metadata_2025_split huggingface dataset:
PDE12 in type 1 diabetes
Authors: Tekin Hasim , Josefsen Knud , Krogvold Lars , Dahl-Jørgensen Knut , Gerling Ivan , Pociot Flemming , Buschard Karsten 
Published: October 2022

AbstractType 1 diabetes (T1D) incidence is increased after COVID-19 infection in children under 18 years of age. Interferon-α-activated oligoadenylate synthetase and downstream RNAseL activation degrade pathogen RNA, but can also damage host RNA when RNAseL activity is poorly regulated. One such regulator is PDE12 which degrades 2′-5′ oligoadenylate units, thereby decreasing RNAseL activity. We analyzed PDE12 expression in islets from non-diabetic donors, individuals with newly (median disease duration 35 days) and recently (5 years) diagnosed T1D, and individuals with type 2 diabetes (T2D). We also analyzed PDE12 single-nucleotide polymorphisms (SNPs) relative to T1D incidence. PDE12 expression was decreased in individuals with recently diagnosed T1D, in three of five individuals with newly diagnosed T1D, but not in individuals with T2D. Two rare PDE12 SNPs were found to have odds ratios of 1.80 and 1.74 for T1D development. We discuss whether decreased PDE12 expression after COVID-19 infection might be part of the up to 2.5-fold increase in T1D incidence.
Design and characterization of an urea-bridged PMO supporting Cu(II) nanoparticles as highly efficient heterogeneous catalyst for synthesis of tetrazole derivatives
Authors: Valiey Ehsan , Dekamin Mohammad G. 
Published: October 2022

AbstractIn this work, a new periodic mesoporous organosilica with urea-bridges produced by the reaction of (3-aminopropyl)triethoxysilane and toluene-2,4-diisocyanate (APS-TDU-PMO) is introduced. The obtained APS-TDU-PMO was found to be an appropriate support for loading of Cu(II) nanoparticles to afford supramolecular Cu@APS-TDU-PMO nanocomposite. Uniformity and mesoporosity of both synthesized nanomaterials including APS-TDU-PMO and Cu@APS-TDU-PMO were proved by different spectroscopic, microscopic or analytical techniques including FTIR, EDX, XRD, FESEM, TEM, BET, TGA and DTA. Furthermore, the prepared Cu@APS-TDU-PMO nanomaterial was also used, as a heterogeneous and recyclable catalyst, for the synthesis of tetrazole derivatives through cascade condensation, concerted cycloaddition and tautomerization reactions. Indeed, the main advantages of this Cu@APS-TDU-PMO is its simple preparation and high catalytic activity as well as proper surface area which enable it to work under solvent-free conditions. Also, the introduced Cu@APS-TDU-PMO heterogeneous catalyst showed good stability and reusability for six consecutive runs to address more green chemistry principles.
DeepLPI: a novel deep learning-based model for protein–ligand interaction prediction for drug repurposing
Authors: Wei Bomin , Zhang Yue , Gong Xiang 
Published: October 2022

AbstractThe substantial cost of new drug research and development has consistently posed a huge burden for both pharmaceutical companies and patients. In order to lower the expenditure and development failure rate, repurposing existing and approved drugs by identifying interactions between drug molecules and target proteins based on computational methods have gained growing attention. Here, we propose the DeepLPI, a novel deep learning-based model that mainly consists of ResNet-based 1-dimensional convolutional neural network (1D CNN) and bi-directional long short term memory network (biLSTM), to establish an end-to-end framework for protein–ligand interaction prediction. We first encode the raw drug molecular sequences and target protein sequences into dense vector representations, which go through two ResNet-based 1D CNN modules to derive features, respectively. The extracted feature vectors are concatenated and further fed into the biLSTM network, followed by the MLP module to finally predict protein–ligand interaction. We downloaded the well-known BindingDB and Davis dataset for training and testing our DeepLPI model. We also applied DeepLPI on a COVID-19 dataset for externally evaluating the prediction ability of DeepLPI. To benchmark our model, we compared our DeepLPI with the baseline methods of DeepCDA and DeepDTA, and observed that our DeepLPI outperformed these methods, suggesting the high accuracy of the DeepLPI towards protein–ligand interaction prediction. The high prediction performance of DeepLPI on the different datasets displayed its high capability of protein–ligand interaction in generalization, demonstrating that the DeepLPI has the potential to pinpoint new drug-target interactions and to find better destinations for proven drugs.
Experimental and TDDFT materials simulation of thermal characteristics and entropy optimized of Williamson Cu-methanol and Al2O3-methanol nanofluid flowing through solar collector
Authors: Jamshed Wasim , Eid Mohamed R. , Al-Hossainy Ahmed F. , Raizah Zehba , Tag El Din El Sayed M. , Sajid Tanveer 
Published: October 2022

AbstractCurrent investigation emphasizes the evaluation of entropy in a porous medium of Williamson nanofluid (WNF) flow past an exponentially extending horizontal plate featuring Parabolic Trough Solar Collector (PTSC). Two kinds of nanofluids such as copper-methanol (Cu-MeOH) and alumina-methanol (Al2O3-MeOH) were tested, discussed and plotted graphically. The fabricated nanoparticles are studied using different techniques, including TDDFT/DMOl3 method as simulated and SEM measurements as an experimental method. The centroid lengths of the dimer are 3.02 Å, 3.27 Å, and 2.49 Å for (Cu-MeOH), (Al2O3-MeOH), and (Cu-MeOH-αAl-MOH), respectively. Adequate similarity transformations were applied to convert the partial differential equation (PDEs) into nonlinear ordinary differential equations (ODEs) with the corresponding boundary constraints. An enhancement in Brinkmann and Reynolds numbers increases the overall system entropy. WNF parameter enhances the heat rate in PTSC. The thermal efficiency gets elevated for Cu-MeOH than that of Al2O3-MeOH among 0.8% at least and 6.6% in maximum for varying parametric values.
Integrating Internet multisource big data to predict the occurrence and development of COVID-19 cryptic transmission
Authors: Gao Chengcheng , Zhang Rui , Chen Xicheng , Yao Tianhua , Song Qiuyue , Ye Wei , Li PengPeng , Wang Zhenyan , Yi Dong , Wu Yazhou 
Published: October 2022

AbstractWith the recent prevalence of COVID-19, cryptic transmission is worthy of attention and research. Early perception of the occurrence and development risk of cryptic transmission is an important part of controlling the spread of COVID-19. Previous relevant studies have limited data sources, and no effective analysis has been carried out on the occurrence and development of cryptic transmission. Hence, we collect Internet multisource big data (including retrieval, migration, and media data) and propose comprehensive and relative application strategies to eliminate the impact of national and media data. We use statistical classification and regression to construct an early warning model for occurrence and development. Under the guidance of the improved coronavirus herd immunity optimizer (ICHIO), we construct a “sampling-feature-hyperparameter-weight” synchronous optimization strategy. In occurrence warning, we propose an undersampling synchronous evolutionary ensemble (USEE); in development warning, we propose a bootstrap-sampling synchronous evolutionary ensemble (BSEE). Regarding the internal training data (Heilongjiang Province), the ROC-AUC of USEE3 incorporating multisource data is 0.9553, the PR-AUC is 0.8327, and the R2 of BSEE2 fused by the “nonlinear + linear” method is 0.8698. Regarding the external validation data (Shaanxi Province), the ROC-AUC and PR-AUC values of USEE3 were 0.9680 and 0.9548, respectively, and the R2 of BSEE2 was 0.8255. Our method has good accuracy and generalization and can be flexibly used in the prediction of cryptic transmission in various regions. We propose strategy research that integrates multiple early warning tasks based on multisource Internet big data and combines multiple ensemble models. It is an extension of the research in the field of traditional infectious disease monitoring and has important practical significance and innovative theoretical value.
Computer vision in surgery: from potential to clinical value
Authors: Mascagni Pietro , Alapatt Deepak , Sestini Luca , Altieri Maria S. , Madani Amin , Watanabe Yusuke , Alseidi Adnan , Redan Jay A. , Alfieri Sergio , Costamagna Guido , Boškoski Ivo , Padoy Nicolas , Hashimoto Daniel A. 
Published: October 2022

AbstractHundreds of millions of operations are performed worldwide each year, and the rising uptake in minimally invasive surgery has enabled fiber optic cameras and robots to become both important tools to conduct surgery and sensors from which to capture information about surgery. Computer vision (CV), the application of algorithms to analyze and interpret visual data, has become a critical technology through which to study the intraoperative phase of care with the goals of augmenting surgeons’ decision-making processes, supporting safer surgery, and expanding access to surgical care. While much work has been performed on potential use cases, there are currently no CV tools widely used for diagnostic or therapeutic applications in surgery. Using laparoscopic cholecystectomy as an example, we reviewed current CV techniques that have been applied to minimally invasive surgery and their clinical applications. Finally, we discuss the challenges and obstacles that remain to be overcome for broader implementation and adoption of CV in surgery.
Multi-level cellular and functional annotation of single-cell transcriptomes using scPipeline
Authors: Mikolajewicz Nicholas , Gacesa Rafael , Aguilera-Uribe Magali , Brown Kevin R. , Moffat Jason , Han Hong 
Published: October 2022

AbstractSingle-cell RNA-sequencing (scRNA-seq) offers functional insight into complex biology, allowing for the interrogation of cellular populations and gene expression programs at single-cell resolution. Here, we introduce scPipeline, a single-cell data analysis toolbox that builds on existing methods and offers modular workflows for multi-level cellular annotation and user-friendly analysis reports. Advances to scRNA-seq annotation include: (i) co-dependency index (CDI)-based differential expression, (ii) cluster resolution optimization using a marker-specificity criterion, (iii) marker-based cell-type annotation with Miko scoring, and (iv) gene program discovery using scale-free shared nearest neighbor network (SSN) analysis. Both unsupervised and supervised procedures were validated using a diverse collection of scRNA-seq datasets and illustrative examples of cellular transcriptomic annotation of developmental and immunological scRNA-seq atlases are provided herein. Overall, scPipeline offers a flexible computational framework for in-depth scRNA-seq analysis.
Dysregulated transforming growth factor-beta mediates early bone marrow dysfunction in diabetes
Authors: Kum Jina J. Y. , Howlett Christopher J. , Khan Zia A. 
Published: October 2022

AbstractDiabetes affects select organs such as the eyes, kidney, heart, and brain. Our recent studies show that diabetes also enhances adipogenesis in the bone marrow and reduces the number of marrow-resident vascular regenerative stem cells. In the current study, we have performed a detailed spatio-temporal examination to identify the early changes that are induced by diabetes in the bone marrow. Here we show that short-term diabetes causes structural and molecular changes in the marrow, including enhanced adipogenesis in tibiae of mice, prior to stem cell depletion. This enhanced adipogenesis was associated with suppressed transforming growth factor-beta (TGFB) signaling. Using human bone marrow-derived mesenchymal progenitor cells, we show that TGFB pathway suppresses adipogenic differentiation through TGFB-activated kinase 1 (TAK1). These findings may inform the development of novel therapeutic targets for patients with diabetes to restore regenerative stem cell function.
Sterane and hopane biomarkers capture microbial transformations of complex hydrocarbons in young hydrothermal Guaymas Basin sediments
Authors: Mara Paraskevi , Nelson Robert K. , Reddy Christopher M. , Teske Andreas , Edgcomb Virginia P. 
Published: October 2022

AbstractIn Guaymas Basin, organic-rich hydrothermal sediments produce complex hydrocarbon mixtures including saturated, aromatic and alkylated aromatic compounds. We examined sediments from push cores from Guyamas sites with distinct temperature and geochemistry profiles to gain a better understanding on abiotic and biological hydrocarbon alteration. Here we provide evidence for biodegradation of hopanoids, producing saturated hydrocarbons like drimane and homodrimane as intermediate products. These sesquiterpene by-products are present throughout cooler sediments, but their relative abundance is drastically reduced within hotter hydrothermal sediments, likely due to hydrothermal mobilization. Within the sterane pool we detect a trend toward aromatization of steroidal compounds within hotter sediments. The changes in hopane and sterane biomarker composition at different sites reflect temperature-related differences in geochemical and microbial hydrocarbon alterations. In contrast to traditionally observed microbial biodegradation patterns that may extend over hundreds of meters in subsurface oil reservoirs, Guaymas Basin shows highly compressed changes in surficial sediments.
Identification and validation of a genomic mutation signature as a predictor for immunotherapy in NSCLC
Authors: Wang Zemin , Ge You , Li Han , Fei Gaoqiang , Wang Shuai , Wei Pingmin 
Published: October 2022

Abstract
Currently, the benefits of immune checkpoint inhibitor (ICI) therapy prediction via emerging biomarkers have been identified, and the association between genomic mutation signatures (GMS) and immunotherapy benefits has been widely recognized as well. However, the evidence about non-small cell lung cancer (NSCLC) remains limited. We analyzed 310 immunotherapy patients with NSCLC from the Memorial Sloan Kettering Cancer Center (MSKCC) cohort. Lasso Cox regression was used to construct a GMS, and the prognostic value of GMS could be able to verify in the Rizvi cohort (N=240) and Hellmann cohort (N=75). We further conducted immunotherapy-related characteristics analysis in The Cancer Genome Atlas (TCGA) cohort (N=1052). A total of seven genes (ZFHX3, NTRK3, EPHA7, MGA, STK11, EPHA5, TP53) were identified for GMS model construction. Compared with GMS-high patients, patients with GMS-low had longer overall survival (OS; P&lt;0.001) in the MSKCC cohort and progression-free survival (PFS; P&lt;0.001) in the validation cohort. Multivariate Cox analysis revealed that GMS was an independent predictive factor for NSCLC patients in both the MSKCC and validation cohort. Meanwhile, we found that GMS-low patients reflected enhanced antitumor immunity in TCGA cohort. The results indicated that GMS had not only potential predictive value for the benefit of immunotherapy but also may serve as a potential biomarker to guide clinical ICI treatment decisions for NSCLC.
Integrating Verbal Short-Term Memory Into the Assessment and Treatment of Aphasia
Authors: Sayers Matthew J. , Greenspan Wendy , Martin Nadine 
Published: October 2022

Purpose:Verbal short-term memory (STM) impairment is ubiquitous in people with aphasia, and its severity generally parallels the severity of word processing impairment. In language-based models of STM, verbal STM arises from the activation and maintenance of linguistic representations. Measures of verbal STM can provide insight into the nature of language processing deficits in aphasia and should be a component of comprehensive assessment and treatment plans. Although verbal STM impairment in aphasia is widely studied in the research community, inclusion of verbal STM assessment and treatment in clinical practice remains limited.Method:This tutorial presents a description of language-based models of verbal STM and factors that contribute to performance in verbal STM tasks. We outline a model of verbal STM assessment and intervention that considers two levels of linguistic processing deficits (i.e., semantic vs. phonological), temporal variability in performance and access to representations (activation transmission vs. maintenance), and the effects of memory load. This tutorial presents a practical framework for the integration of measures of verbal STM in both assessment and treatment. Case studies are included to facilitate learning.Conclusions:This tutorial provides clinicians with the theoretical background and practical framework for integration of verbal STM in both treatment and assessment. While the assessment and treatment of verbal STM deficits in aphasia is in the beginning stages of implementation in the clinical setting, it offers a promising avenue for aphasia rehabilitation.
Measuring the orbit shrinkage rate of hot Jupiters due to tides
Authors: Rosário N. M. , Barros S. C. C. , Demangeon O. D. S. , Santos N. C. 
Published: October 2022

Context. A tidal interaction between a star and a close-in exoplanet leads to shrinkage of the planetary orbit and eventual tidal dis- ruption of the planet. Measuring the shrinkage of the orbits will allow for the tidal quality parameter of the star (Q★′) to be measured, which is an important parameter to obtain information about stellar interiors.
Aims. We analyse data from the Transiting Exoplanet Survey Satellite (TESS) for two targets known to host close-in hot Jupiters, which have significant data available and are expected to have a fast decay: WASP-18 and WASP-19. We aim to measure the current limits on orbital period variation and provide new constrains on Q★′ for our targets.
Methods. We modelled the transit shape using all the available TESS observations and fitted the individual transit times of each tran- sit. We used previously published transit times together with our results to fit two models, a constant period model, and a quadratic orbital decay model, using Markov chain Monte Carlo (MCMC) algorithms.
Results. We obtain new constrains on Q★′ for both targets and improve the precision of the known planet parameters with the newest observations from TESS. We find period change rates of (−0.11 ± 0.21) × 10−10 for WASP-18b and (−0.35 ± 0.22) × 10−10 for WASP-19b and we do not find significant evidence of orbital decay in these targets. We obtain new lower limits for Q★′ of (1.42 ± 0.34) × 107 in WASP-18 and (1.26 ± 0.10) × 106 in WASP-19, corresponding to upper limits of the orbital decay rate of −0.45 × 10−10 and −0.71 × 10−10, respectively, with a 95% confidence level. We compare our results with other relevant targets for tidal decay studies.
Conclusions. We find that the orbital decay rate in both WASP-18b and WASP-19b appears to be smaller than the measured orbital decay of WASP-12b. We show that the minimum value of Q★′ in WASP-18 is two orders of magnitude higher than that of WASP-12, while WASP-19 has a minimum value one order of magnitude higher, which is consistent with other similar targets. Further observations are required to constrain the orbital decay of WASP-18 and WASP-19.
Implications of multiwavelength spectrum on cosmic-ray acceleration in blazar TXS 0506+056
Authors: Das Saikat , Gupta Nayantara , Razzaque Soebur 
Published: October 2022

Context.The MAGIC collaboration has recently analyzed data from a long-term multiwavelength campaign of theγ-ray blazar TXS 0506+056. In December 2018 it was flaring in the very high-energy (VHE;E >  100 GeV)γ-ray band, but no simultaneous neutrino event was detected.Aims.We modeled the observed spectral energy distribution (SED) using a one-zone leptohadronic emission.Methods.We estimated the neutrino flux through the restriction from the observed X-ray flux on the secondary radiation due to the hadronic cascade, initiated by protons with energyEp ≲ 0.1 EeV. We assumed that ultra-high-energy cosmic rays (UHECRs;E ≳ 0.1 EeV), with the same slope and normalization as the low-energy spectrum, are accelerated in the jet but escape efficiently. We propagate the UHE protons in a random turbulent extragalactic magnetic field (EGMF).Results.The leptonic emission from the jet dominates the GeV range, whereas the cascade emission from CR interactions in the jet contributes substantially to the X-ray and VHE range. The line-of-sight cosmogenicγ-rays from UHECRs produce a hardening in the VHE spectrum. Our model prediction for neutrinos from the jet is consistent with the 7.5-year flux limit by IceCube and shows no variability during the MAGIC campaign. Therefore, we infer that the correlation between GeV-TeVγ-rays and neutrino flare is minimal. The luminosity in CRs limits the cosmogenicγ-ray flux, which in turn bounds the RMS value of the EGMF to ≳10−5nG. The cosmogenic neutrino flux is lower than the IceCube-Gen2 detection potential for 10 yr of observation.Conclusions.Very high-energyγ-ray variability should arise from increased activity inside the jet; thus, detecting steady flux at multi-TeV energies may indicate UHECR acceleration. Upcomingγ-ray imaging telescopes, such as the CTA, will be able to constrain the cosmogenicγ-ray component in the SED of TXS 0506+056.
Total Synthesis of Phellinus ribis Glycans with Immunostimulating Activities by an Orthogonal One-Pot Glycosylation Strategy
Authors: Wan Jie , Wang Leilei , Xiao Guozhi 
Published: October 2022

AbstractA total synthesis of nonasaccharide repeating units and shorter sequences from Phellinus ribis glycans with strong immunostimulating activities was achieved by an orthogonal one-pot glycosylation strategy based on an N-phenyltrifluoroacetimidate glycosylation, a Yu glycosylation, and an ortho-(1-phenylvinyl)benzoate glycosylation. The issues inherent to thioglycosides-based orthogonal one-pot glycosylations, such as aglycone transfer, are eliminated by this one-pot glycosylation strategy, which streamlines the chemical synthesis of glycans.
Synthesis of 1,3-Diaryltriazenes and Azo Dyes from Aryl Amines Using N-Nitrososulfonamides
Authors: Baxter Ryan D. , Yaghoubi Mahshid 
Published: October 2022

AbstractNew methods for the synthesis of 1,3-diaryltriazenes and azo dyes from aryl amines are reported. Both methods involve the formation of aryl diazonium intermediates via the transnitrosation of aryl amines with N-nitrososulfonamides. Each two-step transformation may be performed in one reaction vessel at room temperature with no precautions taken to exclude air or moisture. Several triazene and azo dye structures are reported here for the first time, demonstrating the utility of operating the two-step reaction sequence under mild conditions.