bluuebunny/crossref_metadata_2025_split huggingface dataset:
A descriptive analysis of postmarketing requirement studies and clinical trials
Authors: Choi Lauren , Etchey Beverly , Billings Monisha , Lee Cathryn , Weil Kathleen M. , Boxwell Debra , Edelberg Helen 
Published: November 2023

AbstractPurposeUnder the Food and Drug Administration Amendments Act of 2007 (FDAAA), the FDA has the authority to require applicants to conduct postmarketing studies or clinical trials. These postmarketing requirements (PMRs) provide additional data on the safety of the drug product. The purpose of the study was to conduct a descriptive analysis of FDAAA PMRs and the resulting regulatory actions.MethodsThis study evaluated FDAAA PMRs established between 2013 and 2019. We used the Medical Dictionary for Regulatory Activities (MedDRA) to map preferred terms (PTs) for serious risks associated with the PMRs. Relevant documents available in the FDA's document archiving, reporting, and regulatory tracking system (DARRTS), including but not limited to internal letters and reviews, documents submitted by applicants, and publicly available data sources were assessed for data collection of study elements.ResultsOf the 1079 new FDAAA PMRs established between January 01, 2013, and December 31, 2019, 82% (n = 884) were associated with new drug applications (NDAs) and 18% (n = 195) with biologic license applications (BLAs). Most PMRs were established at the time of drug approval (73%, n = 789) compared to post‐approval (27%, n = 290). The majority of PMRs had an open status (59%, n = 639) and 41% (n = 440) were closed. The median time from the PMR establishment date to submission of the results to the FDA was 690 days (interquartile range [IQR]: 748 days) for 167 completed clinical trials and 483 days (IQR: 603 days) for 241 completed studies. Approximately 53% (180/339) of fulfilled FDAAA PMRs resulted in labeling changes.ConclusionsFDAAA PMRs are useful in informing postmarket safety of drugs. Most FDAAA PMRs were established at the time of drug approval, reflecting safety signals identified during the review of the marketing application, and over half of fulfilled FDAAA PMRs resulted in regulatory action.
Preparation of water swellable rubber from epoxidized natural rubber and sodium acrylate by in‐situ polymerization: Effect of vulcanization system, epoxide, and dicumyl peroxide, and sodium acrylate content
Authors: Srichan Sansanee , Prasertsri Sarawut , Phansroy Nichanan , Chutinantakul Phongsathon , Charoenrach Wattapon , Sri‐ang Ambhol , Tongsuphun Mak , Janthaduang Romrun , Boonyod Saowaluk , Katuengngnan Kavichat , Saengsuwan Sayant , Khawdas Wichean , Vudjung Chaiwute 
Published: November 2023

AbstractWater swellable rubber (WSR) was prepared from epoxidized natural rubber (ENR) and sodium acrylate (NaAA) by in‐situ polymerization using sulfur and dicumyl peroxide (DCP) as a vulcanizing agent and an initiator, respectively. The ENR, NaAA, and other additives were mixed in an internal mixer and a two‐roll mill. The effect of the vulcanization system, epoxide, and DCP, and NaAA content on the vulcanization, physical, and mechanical properties of WSR were investigated in this research. As the results, the scorch and curing time of WSR compounded with ENR 25 and vulcanized with a mixture of sulfur‐peroxided or mixed vulcanization system were less than other systems. Furthermore, the scorch and curing time decreased with the increase in DCP content. The WSR with ENR 50 vulcanized with DCP (1.5 phr) in the mixing system provided the highest tensile strength. However, the volume change of WSR with the mixing system (WSR/M) was lower than the WSR cured with peroxide (WSR/P). For WSR/P, the tensile strength, hardness, and volume change in water increased with increasing DCP, and NaAA content, while the elongation at break decreased. These results suggest that WSR has the potential for diverse applications, including waterproofing and sealing solutions in civil construction projects.Highlights
Water swellable rubber (WSR) was prepared from epoxidized natural rubber (ENR) and sodium acrylate (NaAA) by in‐situ polymerization using sulfur and dicumyl peroxide (DCP) as a vulcanizing agent and an initiator.
The scorch and curing time of WSR compounded with ENR 25 and vulcanized with a mixed vulcanization system were less than those of other systems.
During the vulcanization process, ENR 50 can be generated by the ring‐opening of the adjacent epoxide groups more than ENR 25, and the self‐crosslink of ENR 50 was higher than ENR 25.
Water swelling and volume change of WSR tended to decrease with increasing epoxide, and DCP content, whereas those properties increased with increasing NaAA content.
Tensile strength, elongation at break, and hardness of WSR with the mixing system (WSR/M) were higher than those of WSR with the peroxide system (WSR/P).
Swelling and volume change of WSR/P were higher than those of WSR/M.
Preparation of fluorinated poly(aryl ether) with high dimensional stability and high temperature resistance by photo‐thermal dual crosslinking reaction
Authors: Wang Zhaoyang , Yang Huawei , Zhang Wenqing , Wang Baotieliang , Qi Yonggang , Zou Jiawei 
Published: November 2023

AbstractImproving the dimensional stability is significant for fluorinated poly(aryl ether) (FPAE). In this work, zirconium tungstate (ZrW2O8) with negative thermal expansion (NTE) modified by thiol groups is successfully obtained by surface modification with 3‐(trimethoxysilyl)‐1‐propanethiol. Then, the dispersion of ZrW2O8 is improved and a certain crosslinked structure is formed by click reaction between thiols on the surface of ZrW2O8 and allyl groups on the backbone of FPAE. On this basis, the residual allyl groups on the FPAE can undergo addition reaction under heating conditions to further form crosslinked structure. Due to the introduction of photo‐thermal dual crosslinked structure, the dimensional stability of FPAE is significantly improved, and the coefficient of thermal expansion decreased by 64.3% compared to the unoptimized samples. Meanwhile, the dielectric properties are characterized with dielectric constant and dissipation factor of 3.70 and 0.008 at 1 kHz. Finally, the prepared film is used to assemble triboelectric nanogenerators, where the short‐circuit current, open‐circuit voltage and transferred charge is 3 μA, 30 V, and 10 nC, respectively. Crosslinked FPAE with high dimensional stability and high temperature resistance are successfully gained by avoiding the complexity of monomer synthesis and realizing higher performance with the same inorganic filler loading.Highlights
Dual crosslinked structure is built by photo‐thermal dual crosslinking reaction.
ZrW2O8 gains homogeneous dispersion in polymer matrix by photo‐crosslinking reaction.
Introducing ZrW2O8 and dual crosslinked structure raises dimensional stability of film.
Precursor deconvolution error estimation: The missing puzzle piece in false discovery rate in top‐down proteomics
Authors: Jeong Kyowon , Kaulich Philipp T. , Jung Wonhyeuk , Kim Jihyung , Tholey Andreas , Kohlbacher Oliver 
Published: November 2023

AbstractTop‐down proteomics (TDP) directly analyzes intact proteins and thus provides more comprehensive qualitative and quantitative proteoform‐level information than conventional bottom‐up proteomics (BUP) that relies on digested peptides and protein inference. While significant advancements have been made in TDP in sample preparation, separation, instrumentation, and data analysis, reliable and reproducible data analysis still remains one of the major bottlenecks in TDP. A key step for robust data analysis is the establishment of an objective estimation of proteoform‐level false discovery rate (FDR) in proteoform identification. The most widely used FDR estimation scheme is based on the target‐decoy approach (TDA), which has primarily been established for BUP. We present evidence that the TDA‐based FDR estimation may not work at the proteoform‐level due to an overlooked factor, namely the erroneous deconvolution of precursor masses, which leads to incorrect FDR estimation. We argue that the conventional TDA‐based FDR in proteoform identification is in fact protein‐level FDR rather than proteoform‐level FDR unless precursor deconvolution error rate is taken into account. To address this issue, we propose a formula to correct for proteoform‐level FDR bias by combining TDA‐based FDR and precursor deconvolution error rate.
Self‐healing polymers for soft actuators and robots
Authors: Qiu Xiaoyan , Zhang Xinxing 
Published: November 2023

AbstractAdvances in artificial intelligence technology bring a rising demand on stimuli responsive actuating materials and soft actuators. By the virtue of easy deformation and mechanical resilience, polymers with unique properties like shape‐memory, electro/magneto‐active, and thermal/humidity/chemical‐responsiveness have emerged as promising candidates for soft robotics. Damage tolerance or a degree of self‐healing ability improves soft robots endowed with such materials longevity, and provides safeguards for the function and potentially reduce costs. The combination of stimuli‐responsive actuation and self‐healing function involves elaborate supramolecular chemical and physical structure designs, being a challenging topic within the field of soft robotics and thus intriguing wide research interests. This review aims to discuss some highlights in convenient combination of stimuli‐responsive micro‐nanostructures and dynamic bonds chemistry within last 5 years, that further give the actuators recovery of mechanic and function, and improved comprehensive properties. Through a review of the most remarkable paradigms, the order organization of dynamic bonds with liquid crystal mesogenic units, functional micro‐nanofillers, hierarchical gradient interfaces, etc. are outlined. Finally, the perspectives and main challenges of self‐healable actuators are summarized. It is anticipated that this review will provide scientists with insights and guidance for the future innovative research in this field.
Biotin protein ligase as you like it: Either extraordinarily specific or promiscuous protein biotinylation
Authors: Cronan John E. 
Published: November 2023

AbstractBiotin (vitamin H or B7) is a coenzyme essential for all forms of life. Biotin has biological activity only when covalently attached to a few key metabolic enzyme proteins. Most organisms have only one attachment enzyme, biotin protein ligase (BPL), which attaches biotin to all target proteins. The sequences of these proteins and their substrate proteins are strongly conserved throughout biology. Structures of both the biotin ligase‐ and biotin‐acceptor domains of mammals, plants, several bacterial species, and archaea have been determined. These, together with mutational analyses of ligases and their protein substrates, illustrate the exceptional specificity of this protein modification. For example, the Escherichia coli BPL biotinylates only one of the >4000 cellular proteins. Several bifunctional bacterial biotin ligases transcriptionally regulate biotin synthesis and/or transport in concert with biotinylation. The human BPL has been demonstrated to play an important role in that mutations in the BPL encoding gene cause one form of the disease, biotin‐responsive multiple carboxylase deficiency. Promiscuous mutant versions of several BPL enzymes release biotinoyl‐AMP, the active intermediate of the ligase reaction, to solvent. The released biotinoyl‐AMP acts as a chemical biotinylation reagent that modifies lysine residues of neighboring proteins in vivo. This proximity‐dependent biotinylation (called BioID) approach has been heavily utilized in cell biology.
CASP15 cryo‐EM protein and RNA targets: Refinement and analysis using experimental maps
Authors: Mulvaney Thomas , Kretsch Rachael C. , Elliott Luc , Beton Joseph G. , Kryshtafovych Andriy , Rigden Daniel J. , Das Rhiju , Topf Maya 
Published: November 2023

AbstractCASP assessments primarily rely on comparing predicted coordinates with experimental reference structures. However, experimental structures by their nature are only models themselves—their construction involves a certain degree of subjectivity in interpreting density maps and translating them to atomic coordinates. Here, we directly utilized density maps to evaluate the predictions by employing a method for ranking the quality of protein chain predictions based on their fit into the experimental density. The fit‐based ranking was found to correlate well with the CASP assessment scores. Overall, the evaluation against the density map indicated that the models are of high accuracy, and occasionally even better than the reference structure in some regions of the model. Local assessment of predicted side chains in a 1.52 Å resolution map showed that side‐chains are sometimes poorly positioned. Additionally, the top 118 predictions associated with 9 protein target reference structures were selected for automated refinement, in addition to the top 40 predictions for 11 RNA targets. For both proteins and RNA, the refinement of CASP15 predictions resulted in structures that are close to the reference target structure. This refinement was successful despite large conformational changes often being required, showing that predictions from CASP‐assessed methods could serve as a good starting point for building atomic models in cryo‐EM maps for both proteins and RNA. Loop modeling continued to pose a challenge for predictors, and together with the lack of consensus amongst models in these regions suggests that modeling, in combination with model‐fit to the density, holds the potential for identifying more flexible regions within the structure.
Robust multivariate quality control charts for enhanced variability monitoring
Authors: Ali Taha Hussein , Sedeeq Bekhal Samad , Saleh Dlshad Mahmood , Rahim Alan Ghafur 
Published: November 2023

AbstractIn this research, it was proposed to create three new robust multivariate charts corresponding to the |S|‐ chart, which are robust to outliers, using three methods, an algorithm, namely the Rousseuw and Leroy algorithm, Maronna and Zamar, and the family of ‘concentration algorithms’ by Olive and Hawkins. Then the comparison between the proposed and classical method of the researcher Shewhart depends on the total variance (trace variance matrix), the general variance (determinant of the variance matrix), and the difference between the upper and lower control limits to obtain the most efficient charts against outliers through simulation and real data and using a program in the MATLAB language designed for this purpose. The study concluded that the proposed charts dealt with the problem of the influence of outliers and were more efficient than the classical method, in addition, the proposed robust chart (Orthogonalized Gnanadesikan‐Kettenring) was more efficient than the rest of the proposed charts.
Non‐periodic inspection and replacement policy of system subject to non‐homogeneous gamma degradation process
Authors: Yao Fengming , Hu Jiawen , Li Bo , Liu Hengchang , Gong Feng 
Published: November 2023

AbstractThe non‐homogeneous gamma process can exhibit a convex average trend with a non‐linear shape parameter, providing significant flexibility in fitting an accelerated degradation process. However, few studies have been conducted on the maintenance modeling of systems undergoing a non‐homogeneous gamma degradation process despite its versatility. Meanwhile, most maintenance studies adopt a periodic inspection policy to reveal the degradation level. However, it is reasonable to inspect less frequently when the degradation level of the system is low and to perform inspections more frequently when the degradation level increases. Therefore, we conduct a study on the inspection/replacement policy of systems undergoing a non‐homogeneous gamma degradation process, where three non‐periodic inspection policies are investigated. We formulate the problem as a SMDP framework and present a value iteration algorithm to obtain the optimal action at each decision epoch that minimizes the long‐term average cost. A comprehensive numerical study is provided to illustrate the effectiveness of our proposed model.
Comparative ONIOM modeling of 1,3‐butadiene polymerization using Nd(III) and Gd(III) Ziegler–Natta catalyst systems
Authors: Masliy Alexey N. , Akhmetov Ildar G. , Kuznetsov Andrey M. , Davletbaeva Ilsiya M. 
Published: November 2023

AbstractOn the base of structural and thermodynamic data using modern methods of quantum chemistry, a comparative theoretical study of the elementary acts of initiation and growth of a polymer chain during the polymerization of 1,3‐butadiene was carried out. Ziegler–Natta catalysts based on Nd(III) and Gd(III) were used as polymerization initiators. It was shown that the higher stereospecificity of the action of gadolinium catalytic complexes in comparison with neodymium complexes is due to the increased stability of the anti‐form of the π‐allylic terminal structure of the growing polymer chain, and the reduced activity is due to the higher activation energy of the processes of initiation and chain growth.
Attention mechanism‐based multisensor data fusion neural network for fault diagnosis of autonomous underwater vehicles
Authors: Shi Huaitao , Song Zelong , Bai Xiaotian , Zhang Ke 
Published: November 2023

AbstractThe autonomous underwater vehicle (AUV) frequently operates in harsh underwater environments, and timely fault diagnosis of the AUV can prevent mission failure and equipment loss. Data‐driven methods based on a single data source have been widely utilized for fault diagnosis of the AUV because they do not require the construction of complex mechanism models and have high fault diagnosis accuracy. However, these methods face challenges in accomplishing complex fault diagnosis tasks because the single data source provides very restricted fault features. To address this issue, an attention mechanism‐based multisensor data fusion neural network (MDFNN) for AUV fault diagnosis is proposed in this work. First, a feature extraction layer based on the two‐dimensional (2D) convolutional method with a 1D kernel is introduced to extract features from each sensor data separately, significantly optimizing the model architecture. Second, an efficient channel attention mechanism‐based feature fusion layer is proposed to reassign weights to the features of each sensor data, enabling the model to focus more on crucial features. Finally, the fused features are input to the fully connected layers and softmax layer to realize the fault diagnosis of multisensor data. In the end, the diagnostic performance of the proposed MDFNN is evaluated utilizing real AUV experimental data. The experiment shows that the proposed MDFNN has a very fast convergence speed and 98.37% fault diagnosis accuracy, demonstrating its excellent fault diagnosis performance. The proposed MDFNN provides a generalized and simply structured fault diagnosis framework for the AUV with multiple types of sensor data, providing significant engineering value.
A host‐derived chimeric peptide protects citrus against Huanglongbing without threatening the native microbial community of the phyllosphere
Authors: Choi Jeongyun , Basu Supratim , Thompson Abigail , Otto Kristen , Sineva Elena V. , Kunta Madhurababu , Gupta Goutam , Trivedi Pankaj 
Published: November 2023

AbstractIntroductionThe application of host‐derived antibacterial peptides has been highlighted as a potential efficacious and safe tool for the treatment of Huanglongbing (HLB), the most devastating disease of citrus. However, pathogenic bacteria such as HLB‐causing Candidatus liberibacter asiaticus (CLas) often develop resistance against the host antibacterial peptides. We showed that chimeras containing two different host antibacterial peptides not only retain antibacterial activity but also overcome bacterial resistance and enhance plant defence responses. Also, chimeric peptides can have an off‐target impact on the structure and function of plant‐associated microbiomes. However, there is a lack of understanding of the impact of the chimeric peptide therapy on the microbial structure in the citrus phyllosphere while reducing the CLas titre. Here, we aim to evaluate the efficacy of a chimeric peptide (UGK17) to reduce CLas titre, inducing plant defence response and impacting the microbiome associated with the citrus phyllosphere.Material and MethodLeaf samples were collected from orange and grapefruit trees in Texas and identified as old and young leaves according to their maturity. We collected three different types of leaves based on their infection and symptoms: healthy, symptomatic (infected with typical symptoms), and asymptomatic (infected without symptoms). In planta assay was performed by dipping the leaves in the 0, 5 and 25 μM of UGK17 solutions for 48 h. The quantifications of CLas titre and pathogenesis‐related (PR) gene expression were done by quantitative polymerase chain reaction (qPCR) and reverse transcription‐qPCR, respectively. Amplicon sequencing was done to evaluate the impact of UGK17 on individual bacterial community structures. In addition, we performed an ex planta assay to assess the effect of UGK17 on the growth of bacterial isolates including Liberibacter crescens instead of unculturable CLas predominant in the phyllosphere.ResultThe UGK17 treatment reduced the CLas titre in both asymptomatic and symptomatic citrus leaves, regardless of the age of the leaves. The UGK17 application augmented the PR gene expression. In ex planta assay, the growth of L. crescens along with four other strains belonging to the family Rhizobiaceae, was significantly inhibited by the UGK17 while the growth of 74 strains were unaffected. Additionally, there was no statistically significant changes in the microbial community structure with UGK17 treatment.ConclusionOur results suggest that the chimeric peptide therapy is a promising solution to combat HLB by targeting mainly Gram‐negative pathogens and enhancing the plant immune responses without impairing the indigenous microbial community in the citrus phyllosphere.
Sustainable development goals: Sustainability reporting challenges in the United Arab Emirates context
Authors: Elrazaz Tariq , Shaker Samaan Ahmed , Elmassri Moataz 
Published: November 2023

AbstractDrawing on legitimacy theory, this study examines the extent of corporate engagement with the sustainable development goals (SDGs) through assessing the corporate disclosure quality of SDG‐related information in a mandated setting environment, focusing on the United Arab Emirates (UAE). Based on corporate sustainability reports for 132 UAE publicly listed companies in years 2020 and 20,221, we use a scoring methodology incorporating the GRI standards related to the economic, environmental and social impacts of corporate operations. Results of the study reveal that UAE companies use mandatory sustainability reports as a legitimacy tool through a symbolic action superficially integrating SDGs targets into their corporate operations and activities. However, in year 2021 the results show that some companies act substantively by adopting substantive organizational structural changes to integrate SDGs in their business operations and reporting behavior. Unlike previous studies, the paper contributes to the literature and practice by examining the corporate disclosure quality of SDGs in a mandated setting environment. This mandatory context offers an opportunity for a comprehensive analysis of company endeavors regarding their symbolic execution aimed at projecting a surface display of commitment to SDGs, versus their substantive implementation, which leads to significant enhancements in corporate sustainability reports. The findings of this study offer valuable practical implications for regulators and policymakers regarding the implementation of mandatory sustainability reporting. While such reporting may not necessarily result in significant changes in terms of integrating SDGs targets into business strategies and operations, it could potentially lead to the adoption of “SDG‐washing” practices by companies.