bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Phase 1 Study to Evaluate the Pharmacokinetic Drug‐Drug Interaction Between Islatravir and Methadone in Participants on Stable Methadone Therapy
Authors: Matthews Randolph P. , Ankrom Wendy , Handy Whitney , Patel Munjal , Matthews Catherine , Xu Zhiqing , Gravesande Kezia , Searle Shawn , Schwartz Howard , Stoch S. Aubrey , Iwamoto Marian 
Published: December 2024

AbstractIslatravir is a nucleoside reverse transcriptase translocation inhibitor in development for the treatment of HIV‐1. People living with HIV‐1 receiving methadone maintenance therapy may benefit from islatravir. This study was designed to evaluate single‐dose islatravir on steady‐state methadone pharmacokinetics. A nonrandomized, open‐label study (NCT04568603) was conducted and included adult participants receiving methadone therapy. Participants received their standard methadone therapy and a single oral dose of islatravir 60 mg concomitantly. Blood samples were collected to determine methadone and islatravir pharmacokinetics. Fourteen participants aged 26‐63 years were enrolled; 13 completed the study. The geometric mean ratios for methadone area under the concentration‐time curve from time 0 to 24 hours (AUC0‐24), maximum plasma concentration (Cmax), and concentration at 24 hours (C24) were 1.03, 1.01, and 1.07, respectively. Similar effects were seen for the R‐ and S‐enantiomer of methadone (R‐methadone: AUC0‐24, 1.03; Cmax, 1.02; and C24, 1.06; S‐methadone: AUC0‐24, 1.03; Cmax, 1.01; and C24, 1.08). For islatravir, based on a comparison with historical data, the geometric mean ratios for AUC0‐inf and Cmax were 1.18 and 0.86, respectively. Coadministration of a single dose of islatravir and methadone was generally well tolerated. Single‐dose islatravir did not affect steady‐state methadone pharmacokinetics in a clinically meaningful way.
Isolation and Molecular Profiling of Nuclei of Specific Neuronal Types from Human Cerebral Cortex and Striatum
Authors: Pressl Christina , Baffuto Matthew , Darnell Paul , Wang Cuidong , Carroll Thomas S. , Heintz Nathaniel , Mätlik Kert 
Published: December 2024

AbstractMost pathological conditions of the central nervous system do not affect all cell types to the same extent. Delineation of molecular events underlying disease symptoms, including genetic, epigenetic, and transcriptional changes, thus relies on the ability to characterize a specific cell type separately from others. We have developed a methodology for the collection of nuclear RNA and genomic DNA of specific cell types from frozen post‐mortem striatum and cerebral cortex. This allows deep transcriptomic profiling of specific cell populations and characterization of their genomes and epigenetic properties. The method is based on the purification of cell nuclei, followed by fluorescence‐activated sorting of nuclei (FANS) labeled with nucleic acid probes or antibodies binding to targets present in specific cell types. The protocol describes in detail the procedure for isolating and labeling neuronal and glial nuclei from human brain tissue, the steps that can be taken to extract RNA and genomic DNA, a way to combine the procedure with ATAC‐seq to yield information about chromatin accessibility, as well as computational measures for assessing the quality of cell type‐specific RNA‐seq and ATAC‐seq datasets. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC.Basic Protocol 1: Tissue homogenization, isolation of cell nuclei by ultracentrifugation and formaldehyde‐fixationBasic Protocol 2: Antibody‐based labeling and isolation of nuclei of specific neocortical neuron typesSupport Protocol 1: Generation of ATAC‐seq libraries from the nuclei of specific neuron types of the cerebral cortexBasic Protocol 3: Nucleic acid hybridization‐based labeling and isolation of nuclei of specific striatal projection neuron typesAlternate Protocol 1: Labeling and isolation of nuclei of specific striatal interneuron typesSupport Protocol 2: Generation of ATAC‐seq libraries from the nuclei of specific striatal neuron typesBasic Protocol 4: Extraction of genomic DNA and nuclear RNA and preparation of sequencing librariesBasic Protocol 5: Processing and quality control of FANS‐seq and ATAC‐seq data
The impacts of artificial intelligence literacy, green absorptive capacity, and green information system on green innovation
Authors: Cheng Jie , Xu Nai Ru , Khan Noor Ullah , Singh Harcharanjit Singh Mahinder 
Published: December 2024

AbstractIn the contemporary digital landscape, the focus of manufacturing companies on green innovation has garnered attention in the business and academic realms. Nonetheless, the existing research system for manufacturers lacks a systematic study on how artificial intelligence literacy may bolster green innovation efforts. This study endeavors to construct a theoretical framework for artificial intelligence literacy, green information system, green absorptive capacity, and green innovation with respect to the dynamic capability theory and conducting empirical analysis utilizing survey data obtained from 288 ISO14001 manufacturing firms in Malaysia. The findings revealed that artificial intelligence literacy is a significant determinator of green absorptive capacity, the positive outcome of green absorptive capacity is green innovation, and the positive link between artificial intelligence literacy and green absorptive capacity is moderated by green information system. However, artificial intelligence literacy didn't exhibit a direct relationship with green innovation, even when considering green absorptive capacity as a mediator. These results not only offer compelling insights into the link between artificial intelligence literacy and green innovation, but also hold significant implications for academic research and policymaking concerning sustainable development and cleaner manufacturing production.
Upcycling Graphite from Spent Li‐Ion Battery with SiOx via Mechano‐Chemical Process as Next‐Generation Anode for Li‐Ion Capacitors
Authors: Akshay Manohar , Ulaganathan Mani , Lee Yun‐Sung , Aravindan Vanchiappan 
Published: December 2024

AbstractHybrid supercapacitors such as Lithium‐ion capacitors (LICs) are one of the most modern energy storage devices of great research interest. The hybridization of the battery‐type anode with the capacitive‐type cathode brings out the synergic effect of enhanced energy density, power capability, long cycle life, and wide operating temperature. Herein, we introduce a simultaneous alloying‐intercalation process from the recovered graphite: silicon monoxide (RG: SiOx) composite as a negative electrode for the LIC applications with the activated carbon (AC) as a counter electrode. The RG from spent lithium‐ion batteries is mixed with commercially available SiOx by scalable mechano‐chemical process, i. e., planetary ball‐milling, to obtain a high‐performance composite with various ratios. The LIC is assembled with an electrochemically prelithiated anode (LixSi + LiC6 + Li2O) and paired with AC under balanced mass loading conditions. The LIC delivered a maximum energy density of 218 Wh kg−1 and power density of 8.45 kW kg−1 with an ultra‐long cycling life of over 20,000 cycles. Remarkably, the energy densities such as 208.7 and 201.4 Wh kg−1 are observed at various temperature conditions like 10 and 40 °C, respectively, with excellent capacity retention characteristics.
Multifunctional Heterogeneous Cobalt Catalyst for the One‐Pot Synthesis of Benzimidazoles by Reductive Coupling of Dinitroarenes with Aldehydes in Water
Authors: del Río‐Rodríguez José Luis , Gutiérrez‐Tarriño Silvia , Chinchilla Lidia E. , Holgado Juan Pedro , Villar‐García Ignacio J. , Pérez‐Dieste Virginia , Calvino Jose J. , Oña‐Burgos Pascual 
Published: December 2024

AbstractThe endeavor of sustainable chemistry has led to significant advancements in green methodologies aimed at minimizing environmental impact while maximizing efficiency. Herein, a straightforward synthesis of benzimidazoles by reductive coupling of o‐dinitroarenes with aldehydes is reported for the first time in aqueous media while using a non‐noble metal catalyst. This work demonstrates that the combination of nitrogen and phosphorous ligands in the synthesis of supported heteroatom‐incorporated Co nanoparticles is crucial for obtaining the desired benzimidazoles. The process achieves >99 % conversion, >99 % chemoselectivity and stability for the reduction of dinitroarenes using water as the solvent and hydrogen as the reductant under mild reaction conditions. The robustness of the catalyst has been investigated using several advanced techniques such as HRTEM, HAADF‐STEM, XEDS, EELS, and NAP‐XPS. In fact, we have shown that the introduction of N and P dopants prevents metal leaching and the sintering of the cobalt nanoparticles. Finally, to explore the general catalytic performance, a wide range of substituted dinitroarenes and benzaldehydes were evaluated, yielding benzimidazoles with competitive and scalable results, including MBIB (94 % yield), which is a compound of pharmaceutical interest.
IGBT Junction Temperature Estimation Based on External Parameters of Multiple Drive Devices in Practical Industrial Scenario
Authors: Su Chenglang , Jiang Wei , Huang Zhicong 
Published: December 2024

ABSTRACTThe insulated gate bipolar transistor (IGBT) is one of the most important power semiconductor devices in power electronics and is also prone to failure. High junction temperature and junction temperature fluctuation of IGBT are the main causes of IGBT module aging failure. The high‐precision monitoring of the junction temperature of the IGBT module is a prerequisite for IGBT life prediction, which is crucial for reducing maintenance costs and improving equipment reliability. Therefore, an IGBT junction temperature estimation method based on long short‐term memory (LSTM) neural network and sliding window estimation model is proposed and applied in practical industrial scenarios. This method uses the operating data of the motor drive device in the actual industrial application scenario as the training and test data set and uses the external operating parameters of the IGBT module to estimate the junction temperature of the IGBT module. Compared with the internal operating parameters of the IGBT module based on switching transient, the external operating parameters are easier to collect and process, and more suitable for practical application scenes. A sliding window estimation model is proposed to estimate the junction temperature of the IGBT module. Compared with the point‐to‐point estimation method, the sliding window estimation method can capture the influence of historical operation data better and has a higher capability of time series data estimation. The IGBT junction temperature estimation of sliding windows is realized by the LSTM neural network, which is more suitable for time series estimation in real industrial scenarios. The experimental results show that the estimation accuracy of the sliding window estimation method is better than that of the point‐to‐point estimation method, and the accuracy of the sliding window estimation method based on LSTM is better than that of the sliding window estimation method based on other machine learning models. It proves that the proposed method can better capture the dynamic process of the system and has higher estimation accuracy.
Preoperative susceptibility to developing secondary hyperalgesia is associated with post‐thoracotomy pain at 2 months
Authors: Gousset Solenn , Cappe Maximilien , Lenoir Cedric , Steyaert Arnaud , Lavand'homme Patricia , Mouraux André , Lacroix Valérie , van den Broeke Emanuel N. 
Published: December 2024

AbstractBackgroundIdentifying the subset of patients at risk for developing persistent pain after surgery is clinically important as they could benefit from targeted prevention measures. In this prospective study, we investigated if the preoperative assessment of the individual susceptibility to developing experimentally induced secondary hyperalgesia is associated with post‐thoracotomy pain at 2 months.MethodsForty‐one patients scheduled to undergo a posterolateral thoracotomy were recruited before surgery and followed prospectively for 2 months. The day before surgery, we experimentally induced secondary hyperalgesia at one of the two forearms and measured the change of perception to mechanical pinprick stimuli and the area of hyperalgesia. On postoperative Day 4, Day 15 and at the 2‐month follow‐up, patients were asked about their pain intensity at rest and during coughing and the area of secondary hyperalgesia around the scar as well as the change in perception to mechanical pinprick stimuli was measured.ResultsOf the 41 patients that were recruited only 20 could be analysed. Forty per cent reported pain at the 2‐month follow‐up. All of them reported cough‐evoked pain and 10 per cent also reported pain at rest. A binary logistic regression model with both the magnitude and extent of experimentally induced secondary hyperalgesia was statistically significant (chi‐squared = 12.439, p = 0.002, McFadden R2 = 0.462) and showed excellent discriminative power (AUC = 0.938) for the presence or absence of cough‐evoked pain at the 2 month follow‐up.ConclusionOur findings indicate that the individual susceptibility to developing experimentally induced secondary hyperalgesia preoperatively may identify patients who are potentially vulnerable to develop persistent post‐thoracotomy pain.SignificanceOur data suggests that preoperatively assessed experimentally induced secondary hyperalgesia displays excellent discriminative power for the presence or absence of cough‐evoked pain 2 months after thoracotomy.
Non‐Autoregressive Translation Algorithm Based on LLM Knowledge Distillation in English Corpus
Authors: Ju Fang , Wang Weihui 
Published: December 2024

ABSTRACTAlthough significant advancements have been made in the quality of machine translation by large‐scale language models, their high computational costs and resource consumption have hindered their widespread adoption in practical applications. So this research introduces an English corpus‐based machine translation algorithm that leverages knowledge distillation from large language model, with the goal of enhancing translation quality and reducing the computational demands of the model. Initially, we conducted a thorough analysis of the English corpus to identify prevalent language patterns and structures. Following this, we developed a knowledge distillation approach that transfers the translation expertise of a large teacher model to a smaller student model, thereby achieving increased translation accuracy and efficiency. We designed a dynamic temperature hyperparameter distillation strategy that effectively enhances the precision of translations. In the experimental phase, we utilized several standard English corpora to train and assess our algorithm. The findings indicate that, compared to current machine translation systems, our method significantly reduces the need for computational resources while preserving translation quality.
Ultrasonic Assisted Environmentally Friendly Extraction of Natural Dyes From Beta vulgaris for the Coloration of Silk Fabric Using Different Mordants
Authors: Mia Rony , Uddin Tafsir , Mofasser A. Z. M. , Ibn Sayed Nadim , Shamim Al Mojnun , Islam Sanjida , Ohi Khandaker Akil Mahadi , Khan Moonis Ali , Banna Burhan Uddin 
Published: December 2024

ABSTRACTConsidering the indispensability of environmental protection, the utilization of natural ingredients as sustainable and eco‐friendly alternatives to synthetic dyes in fabric dyeing is of great significance. Betacyanins are naturally sourced pigments of red‐violet color that have the propensity to be fixed to mordanted substrates with reasonable permanency. In this study, the betacyanins sourced from beetroot (Beta vulgaris) were used to dye pre‐mordanted silk fabrics employing ultrasonication. In addition, a comparative analysis of the effects of five different mordants such as orange‐peel extracts, lemon peel extracts, tannic acid, ferrous sulfate, and alum on the color strength and fastness of beetroot‐dyed silk fabrics was presented in this research. For the characterization of the extracted dye, undyed, dyed, and mordanted silk fabric, infrared spectroscopy was performed. To observe the interaction of extracted dye and silk fabric, scanning electron microscopy was also accomplished. The outcomes of the characterization validated the successful extraction of dyes from beetroot and dyeing silk fabric with it. The values of color intensity (K/S), CIE L* a* b*, and CIE L* c* h* were measured using a reflectance spectrophotometer. At the same time, dry and wet rubbing and lightfastness ratings of dyed silk fabrics were determined according to the ISO standards. When 5% (o.w.f.) ferrous sulfate was used in pre‐mordanting, the ratings of colorfastness to wash, rub, and light ranged from 4 to 4/5, and the K/S value of the final sample was 4.88, which is higher than the K/S values of any other dyed samples. In contrast, the performance of 5% (o.w.f.) lemon peel extracts as a mordant was remarkably higher than orange peel extracts and even better than alum and tannic acid to some extent. The beetroot‐dyed silk fabric pre‐mordanted with 5% lemon peel exhibited a K/S value of 4.32, and the overall colorfastness rating ranged from 3/4 to 4/5. In conclusion, beetroot extracts hold the promise of being utilized as a sustainable replacement for environmentally harmful synthetic dyestuff in silk dyeing. Furthermore, in silk dyeing with beetroot extract, lemon peel extract is a potent alternative to ferrous sulfate as a mordant.
Intelligent Logistics Warehousing Strategy Based on 5G Network and Cloud Computing in the Era of Big Data
Authors: Wu Yue , Tang Wenting 
Published: December 2024

ABSTRACTBased on the resource base of “cloud computing,” a super big data storage center was built to exchange data between companies, units, departments and businesses, management, customers and personnel, so as to ensure the timely and accurate reception of all aspects of information. Using radio frequency identification technology, barcode technology, GPS/GIS (Global Positioning System/Geographic Information System) technology, mobile communication technology, and 5G (5th Generation Mobile Communication Technology) network technology, a new business model was realized. At the same time, SOA (Service Oriented Architecture) structure was adopted to combine decentralized business and SOA architecture in the form of loose coupling, and dynamic binding was adopted to realize dynamic access of cloud logistics warehousing platform. Massive data were collected, analyzed, and preprocessed through big data technology and logistics facilities. Real‐time data transmission was realized through 5G network. At the same time, scene acquisition, modeling, analysis, control, feedback, and other technologies were applied to the logistics system to realize the intellectualization of logistics warehousing services. The receiving and sending business process of B2C (Business‐to‐Consumer) e‐commerce enterprises based on “cloud logistics warehousing” is to take the terminal shipper as the seller and the terminal consignee as the buyer. By integrating the information of all links in the logistics process into the “cloud” platform, various stakeholders can conduct information, capital, and other transactions on this platform, thus ensuring the quality of customer logistics services. The advantage of recognized logistics cloud warehouse is that its application value accounts for 43.1%. The scheme proposed in this paper can shorten the storage time of the warehouse, thus speeding up the operation of the warehouse; it can ensure the quality of each link, thus reducing the operating costs of the warehouse; it can increase the use space of the warehouse and save the manpower of the warehouse; it can improve the operation efficiency of the warehouse, thus improving the economic benefits.
Behavioral Alterations in Mice Exposed to Manganese via Drinking Water: Effects of Sex and a Lipopolysaccharide Challenge
Authors: Ludwig Helaina D. , Carpenter Jessica M. , Filipov Nikolay M. 
Published: December 2024

ABSTRACTManganese (Mn) is an essential and important metal; however, overexposures lead to adverse neurological outcomes. Nonoccupational Mn overexposure occurs primarily through consumption of Mn‐contaminated drinking water (DW). Sex differences in terms of nervous and immune systems' responsiveness to excessive Mn in the DW are understudied. Thus, this study investigated behavioral and sex differences in response to Mn DW treatment (0.4 g Mn/L for up to 8 weeks) and a lipopolysaccharide (LPS) challenge of adult C57BL/6 mice with GFP‐tagged monocytes/microglia. After 6 weeks, in motor function tests, Mn exposure resulted in decreased activity and gait deficits. In two different mood tests (open field test [OFT]/elevated zero maze), Mn‐exposed mice exhibited decreased fear/anxiety‐like behavior. Two weeks after behavioral assessment, when mice were challenged with LPS, circulating inflammatory cytokines, and acute phase proteins increased in both sexes. After 8 weeks of Mn exposure, liver and brain Mn levels were increased, but Mn alone did not affect circulating cytokines in either sex. Notably, Mn‐exposed/LPS‐challenged males had potentiated plasma cytokine output, whereas the reverse was seen in females. Males, but not females, continued to exhibit increased fearlessness (i.e., increased OFT center time), even when challenged with LPS. Overall, our results show that Mn DW exposure increases brain Mn levels and it leads to behavioral alterations in both sexes. However, males might be more susceptible to the effect of Mn on mood, and this effect is recalcitrant to an inflammagen challenge. Mn augmented post‐LPS cytokine production only in males, further indicating that important Mn effects are sex‐biased.
MiR‐200a‐3p Attenuates Neuropathic Pain by Suppressing the Bromodomain‐Containing Protein 3‐Nuclear Factor‐κB Pathway
Authors: Deng Chao , Yuan Xuequan , Lin Xuezheng , Liu Sitong 
Published: December 2024

ABSTRACTMicroRNAs (miRNAs) have key roles in the pathological processes of neuropathic pain. Here, our aim was to elucidate the function of miR‐200a‐3p as well as its related regulatory mechanism in neuropathic pain. An animal model of neuropathic pain was established by chronic constriction injury (CCI) induction. The knockdown experiments are performed by injecting a lentiviral construct intrathecally. MiR‐200a‐3p and bromodomain‐containing protein 3 (BRD3) expression in rat spinal cord was determined using RT‐qPCR. The mechanical, thermal, and cold responses in animals were assessed at the indicated time after surgery. The levels of inflammatory cytokines in rat spinal cord were measured by ELISA. The changes in NF‐κB signaling‐related molecules in rat spinal cord were determined using western blot and immunofluorescence. MiR‐200a‐3p was underexpressed in CCI rats in a time‐dependent manner. Overexpression of miR‐200a‐3p decreased mechanical hyperalgesia and thermal sensitivity to attenuate neuropathic pain in rats. BRD3 was targeted by miR‐200a‐3p. Additionally, downregulation of BRD3 inhibited neuropathic pain progression. Moreover, overexpression of BRD3 rescued the effect of miR‐200a‐3p on NF‐κB signaling and neuropathic pain in CCI rats. MiR‐200a‐3p attenuates neuropathic pain via downregulating BRD3 to block NF‐κB signaling.