bluuebunny/crossref_metadata_2025_split huggingface dataset:
Insight into binding of endogenous neurosteroid ligands to the sigma-1 receptor
Authors: Fu Chunting , Xiao Yang , Zhou Xiaoming , Sun Ziyi 
Published: July 2024

AbstractThe sigma-1 receptor (σ1R) is a non-opioid membrane receptor, which responds to a diverse array of synthetic ligands to exert various pharmacological effects. Meanwhile, candidates for endogenous ligands of σ1R have also been identified. However, how endogenous ligands bind to σ1R remains unknown. Here, we present crystal structures of σ1R from Xenopus laevis (xlσ1R) bound to two endogenous neurosteroid ligands, progesterone (a putative antagonist) and dehydroepiandrosterone sulfate (DHEAS) (a putative agonist), at 2.15-3.09  Å resolutions. Both neurosteroids bind to a similar location in xlσ1R mainly through hydrophobic interactions, but surprisingly, with opposite binding orientations. DHEAS also forms hydrogen bonds with xlσ1R, whereas progesterone interacts indirectly with the receptor through water molecules near the binding site. Binding analyses are consistent with the xlσ1R-neurosteroid complex structures. Furthermore, molecular dynamics simulations and structural data reveal a potential water entry pathway. Our results provide insight into binding of two endogenous neurosteroid ligands to σ1R.
Neuroprosthetic contact lens enabled sensorimotor system for point-of-care monitoring and feedback of intraocular pressure
Authors: Liu Weijia , Du Zhijian , Duan Zhongyi , Li La , Shen Guozhen 
Published: July 2024

AbstractThe wearable contact lens that continuously monitors intraocular pressure (IOP) facilitates prompt and early-state medical treatments of oculopathies such as glaucoma, postoperative myopia, etc. However, either taking drugs for pre-treatment or delaying the treatment process in the absence of a neural feedback component cannot realize accurate diagnosis or effective treatment. Herein, a neuroprosthetic contact lens enabled sensorimotor system is reported, which consists of a smart contact lens with Ti3C2Tx Wheatstone bridge structured IOP strain sensor, a Ti3C2Tx temperature sensor and an IOP point-of-care monitoring/display system. The point-of-care IOP monitoring and warning can be realized due to the high sensitivity of 12.52 mV mmHg−1 of the neuroprosthetic contact lens. In vivo experiments on rabbit eyes demonstrate the excellent wearability and biocompatibility of the neuroprosthetic contact lens. Further experiments on a living rate in vitro successfully mimic the biological sensorimotor loop. The leg twitching (larger or smaller angles) of the living rat was demonstrated under the command of motor cortex controlled by somatosensory cortex when the IOP is away from the normal range (higher or lower).
ABE-ultramax for high-efficiency biallelic adenine base editing in zebrafish
Authors: Qin Wei , Liang Fang , Lin Sheng-Jia , Petree Cassidy , Huang Kevin , Zhang Yu , Li Lin , Varshney Pratishtha , Mourrain Philippe , Liu Yanmei , Varshney Gaurav K. 
Published: July 2024

AbstractAdvancements in CRISPR technology, particularly the development of base editors, revolutionize genetic variant research. When combined with model organisms like zebrafish, base editors significantly accelerate and refine in vivo analysis of genetic variations. However, base editors are restricted by protospacer adjacent motif (PAM) sequences and specific editing windows, hindering their applicability to a broad spectrum of genetic variants. Additionally, base editors can introduce unintended mutations and often exhibit reduced efficiency in living organisms compared to cultured cell lines. Here, we engineer a suite of adenine base editors (ABEs) called ABE-Ultramax (Umax), demonstrating high editing efficiency and low rates of insertions and deletions (indels) in zebrafish. The ABE-Umax suite of editors includes ABEs with shifted, narrowed, or broadened editing windows, reduced bystander mutation frequency, and highly flexible PAM sequence requirements. These advancements have the potential to address previous challenges in disease modeling and advance gene therapy applications.
Illuminating the dark space of neutral glycosphingolipidome by selective enrichment and profiling at multi-structural levels
Authors: Wang Zidan , Zhang Donghui , Wu Junhan , Zhang Wenpeng , Xia Yu 
Published: July 2024

AbstractGlycosphingolipids (GSLs) are essential components of cell membranes, particularly enriched in the nervous system. Altered molecular distributions of GSLs are increasingly associated with human diseases, emphasizing the significance of lipidomic profiling. Traditional GSL analysis methods are hampered by matrix effect from phospholipids and the difficulty in distinguishing structural isomers. Herein, we introduce a highly sensitive workflow that harnesses magnetic TiO2 nanoparticle-based selective enrichment, charge-tagging Paternò–Büchi reaction, and liquid chromatography-tandem mass spectrometry. This approach enables mapping over 300 distinct GSLs in brain tissues by defining sugar types, long chain bases, N-acyl chains, and the locations of desaturation and hydroxylation. Relative quantitation of GSLs across multiple structural levels provides evidence of dysregulated gene and protein expressions of FA2H and CerS2 in human glioma tissue. Based on the structural features of GSLs, our method accurately differentiates human glioma with/without isocitrate dehydrogenase genetic mutation, and normal brain tissue.
Capillary compression induced outstanding n-type thermoelectric power factor in CNT films towards intelligent temperature controller
Authors: Wang Hong , Li Kuncai , Hao Xin , Pan Jiahao , Zhuang Tiantian , Dai Xu , Wang Jing , Chen Bin , Chong Daotong 
Published: July 2024

AbstractOne-dimensional carbon nanotubes are promising candidates for thermoelectrics because of their excellent electrical and mechanical properties. However, the large n-type power factor remains elusive in macroscopic carbon nanotubes films. Herein, we report an outstanding n-type power factor of 6.75 mW m−1 K−2 for macroscopic carbon nanotubes films with high electrical and thermal conductivity. A high-power density curl-able thermoelectric generator is fabricated with the obtained carbon nanotubes films, which exhibits a high normalized power output density of 2.75 W m−1 at a temperature difference of 85 K. The value is higher than that of previously reported flexible all-inorganic thermoelectric generators (<0.3 W m−1). An intelligent temperature controller with automated temperature-controlling ability is fabricated by assembling these thermoelectric generators, which demonstrates the potential application of the carbon nanotubes films in automated thermal management of electronic devices where requires a large thermoelectric power factor and a large thermal conductivity simultaneously.
quantms: a cloud-based pipeline for quantitative proteomics enables the reanalysis of public proteomics data
Authors: Dai Chengxin , Pfeuffer Julianus , Wang Hong , Zheng Ping , Käll Lukas , Sachsenberg Timo , Demichev Vadim , Bai Mingze , Kohlbacher Oliver , Perez-Riverol Yasset 
Published: July 2024

AbstractThe volume of public proteomics data is rapidly increasing, causing a computational challenge for large-scale reanalysis. Here, we introduce quantms (https://quant,ms.org/), an open-source cloud-based pipeline for massively parallel proteomics data analysis. We used quantms to reanalyze 83 public ProteomeXchange datasets, comprising 29,354 instrument files from 13,132 human samples, to quantify 16,599 proteins based on 1.03 million unique peptides. quantms is based on standard file formats improving the reproducibility, submission and dissemination of the data to ProteomeXchange.
Temporal-spatial cross attention network for recognizing imagined characters
Authors: Xu Mingyue , Zhou Wenhui , Shen Xingfa , Qiu Junping , Li Dingrui 
Published: July 2024

AbstractPrevious research has primarily employed deep learning models such as Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs) for decoding imagined character signals. These approaches have treated the temporal and spatial features of the signals in a sequential, parallel, or single-feature manner. However, there has been limited research on the cross-relationships between temporal and spatial features, despite the inherent association between channels and sampling points in Brain-Computer Interface (BCI) signal acquisition, which holds significant information about brain activity. To address the limited research on the relationships between temporal and spatial features, we proposed a Temporal-Spatial Cross-Attention Network model, named TSCA-Net. The TSCA-Net is comprised of four modules: the Temporal Feature (TF), the Spatial Feature (SF), the Temporal-Spatial Cross (TSCross), and the Classifier. The TF combines LSTM and Transformer to extract temporal features from BCI signals, while the SF captures spatial features. The TSCross is introduced to learn the correlations between the temporal and spatial features. The Classifier predicts the label of BCI data based on its characteristics. We validated the TSCA-Net model using publicly available datasets of handwritten characters, which recorded the spiking activity from two micro-electrode arrays (MEAs). The results showed that our proposed TSCA-Net outperformed other comparison models (EEG-Net, EEG-TCNet, S3T, GRU, LSTM, R-Transformer, and ViT) in terms of accuracy, precision, recall, and F1 score, achieving 92.66$$\%$$
%
, 92.77$$\%$$
%
, 92.70$$\%$$
%
, and 92.58$$\%$$
%
, respectively. The TSCA-Net model demonstrated a 3.65$$\%$$
%
to 7.49$$\%$$
%
improvement in accuracy over the comparison models.
Incidence, identification and antibiotic resistance of Salmonella spp. in the well waters of Tadla Plain, Morocco
Authors: Hafiane Fatima Zahra , Tahri Latifa , El Jarmouni Mohamed , Reyad Ahmed M. , Fekhaoui Mohammed , Mohamed Mohamed O. , Abdelrahman Ehab A. , Rizk Samar H. , El-Sayyad Gharieb S. , Elkhatib Walid F. 
Published: July 2024

AbstractConcerns about challenges with water availability in the Tadla Plain region of Morocco have grown as a result of groundwater contamination brought on by human activity, climate change, and insufficient groundwater management. The objective of the study is to measure the number of resistant bacteria in the groundwater of Beni Moussa and Beni Aamir, as well as to evaluate the level of water pollution in this area. 200 samples were therefore gathered from 43 wells over the course of four seasonal campaigns in 2017 and 2018. Additionally, the samples were examined to determine whether Salmonella species were present and if they were resistant to the 16 antibiotics that were tested. Salmonella spp. have been identified in 31 isolated strains in total, accounting for 18.02% of all isolated strains. Data on antibiotic resistance show that 58.1% of Salmonella spp. strains are multidrug-resistant (MDR); 38.7% of Salmonella strains are tolerant to at least six antibiotics, 19.4% to at least nine antibiotics, 9.7% to four to seven antibiotics, 6.5% to at least eleven antibiotics, and the remaining 3.2% to up to twelve antibiotics. A considerable level of resistance to cefepime (61.29%), imipenem (54.84%), ceftazidime (45.16%), ofloxacin (70.97%), and ertapenem (74.19%) was found in the data. Consequently, it is important to monitor and regulate the growth of MDR in order to prevent the groundwater's quality from declining.
Trajectories and revolutions in popular melody based on U.S. charts from 1950 to 2023
Authors: Hamilton Madeline , Pearce Marcus 
Published: July 2024

AbstractIn the past century, the history of popular music has been analyzed from many different perspectives, with sociologists, musicologists and philosophers all offering distinct narratives characterizing the evolution of popular music. However, quantitative studies on this subject began only in the last decade and focused on features extracted from raw audio, which limits the scope to low-level components of music. The present study investigates the evolution of a more abstract dimension of popular music, specifically melody, using a new dataset of popular melodies spanning from 1950 to 2023. To identify "melodic revolutions", changepoint detection was applied to a multivariate time series comprising features related to the pitch and rhythmic structure of the melodies. Two major revolutions in 1975 and 2000 and one smaller revolution in 1996, characterized by significant decreases in complexity, were located. The revolutions divided the time series into three eras, which were modeled separately with autoregression, linear regression and vector autoregression. Linear regression of autoregression residuals underscored inter-feature relationships, which become stronger in post-2000 melodies. The overriding pattern emerging from these analyses shows decreasing complexity and increasing note density in popular melodies over time, especially since 2000.
A national survey on assessment of knowledge, perceptions, practice, and barriers among hospital pharmacists towards medication reconciliation in United Arab Emirates
Authors: Farajallah Alaa , Zainal Hadzliana , Palaian Subish , Alomar Muaed 
Published: July 2024

AbstractMedication reconciliation (MedRec) helps prevent medication errors. This cross-sectional, nationwide study assessed the knowledge, perceptions, practice, and barriers toward MedRec amongst hospital pharmacy practitioners in the United Arab Emirates. A total of 342 conveniently chosen stratified hospital pharmacists responded to the online survey (88.6% response rate). Mann–Whitney U test and Kruskal–Wallis test were applied at alpha = 0.05 and post hoc analysis was performed using Bonferroni test. The overall median knowledge score was 9/12 with IQR (9–11) with higher levels among clinical pharmacists (p < 0.001) and previously trained pharmacists (p < 0.001). Of the respondents, 35.09% (n = 120) practiced MedRec for fewer than five patients per week despite having a strong perception of their role in this process. The overall median perception score was 32.5/35 IQR (28–35) with higher scores among clinical pharmacists (p < 0.001) and those who attended previous training or workshops (p < 0.001). The median barrier score was 24/30 with an IQR (21–25), where lack of training and knowledge were the most common barriers. Results showed that pharmacists who did not attend previous training or workshops on MedRec had higher barrier levels than those who attended (p = 0.012). This study emphasizes the significance of tackling knowledge gaps, aligning perceptions with practice, and suggesting educational interventions.
Potential therapeutic biomolecules of hymenopteran venom against SARS-CoV-2 from Egyptian patients
Authors: Abd El Maksoud Eman A. , Rady Magda H. , Mahmoud Ahmed Gad Taha , Hamza Dalia , Seadawy Mohamed G. , Essa Eman. E. 
Published: July 2024

AbstractThe therapeutic potential of insect-derived bioactive molecules as anti-SARS-CoV-2 agents has shown promising results. Hymenopteran venoms, notably from Apis mellifera (honeybee) and Vespa orientalis (oriental wasp), were examined for the first time in an in vitro setting for their potential anti-COVID-19 activity. This assessment utilized an immunodiagnostic system to detect the SARS-CoV-2 nucleocapsid antigen titer reduction. Further analyses, including cytotoxicity assays, plaque reduction assays, and in silico docking-based screening, were performed to evaluate the efficacy of the most potent venom. Results indicated that bee and wasp venoms contain bioactive molecules with potential therapeutic effects against SARS-CoV-2.Nevertheless, the wasp venom exhibited superior efficacy compared to bee venom, achieving a 90% maximal (EC90) concentration effect of antigen depletion at 0.184 mg/mL, in contrast to 2.23 mg/mL for bee venom. The cytotoxicity of the wasp venom was assessed on Vero E6 cells 48 h post-treatment using the MTT assay. The CC 50 of the cell growth was 0.16617 mg/mL for Vero E6 cells. The plaque reduction assay of wasp venom revealed 50% inhibition (IC50) at a 0.208 mg/mL concentration. The viral count at 50% inhibition was 2.5 × 104 PFU/mL compared to the initial viral count of 5 × 104 PFU/mL. In silico data for the wasp venom revealed a strong attraction to binding sites on the ACE2 protein, indicating ideal interactions. This substantiates the potential of wasp venom as a promising viral inhibitor against SARS-CoV-2, suggesting its consideration as a prospective natural preventive and curative antiviral drug. In conclusion, hymenopteran venoms, particularly wasp venom, hold promise as a source of potential therapeutic biomolecules against SARS-CoV-2. More research and clinical trials are needed to evaluate these results and investigate their potential for translation into innovative antiviral therapies.
Pharmacokinetic and molecular docking studies to pyrimidine drug using Mn3O4 nanoparticles to explore potential anti-Alzheimer activity
Authors: Shehab Wesam S. , Haikal Hend A. , Elsayed Doaa A. , EL-Farargy Ahmed F. , El-Gazzar Abdel-Rahman B. A. , El-Bassyouni Gehan T. , Mousa Sahar M. 
Published: July 2024

AbstractAlzheimer disease (AD) is the cause of dementia and accounts for 60–80% cases. Tumor Necrosis Factor-alpha (TNF-α) is a multifunctional cytokine that provides resistance to infections, inflammation, and cancer. It developed as a prospective therapeutic target against multiple autoimmune and inflammatory disorders. Cholinergic insufficiency is linked to Alzheimer's disease, and several cholinesterase inhibitors have been created to treat it, including naturally produced inhibitors, synthetic analogs, and hybrids. In the current study, we tried to prepared compounds may also support the discovery and development of novel therapeutic and preventative drugs for Alzheimer's using manganese tetroxide nanoparticles (Mn3O4-NPs) as a catalyst to generate compounds with excellent reaction conditions. The Biginelli synthesis yields 4-(4-cyanophenyl)-6-oxo-2-thioxohexahydropyrimidine-5-carbonitrile when the 4-cyanobenzaldehyde, ethyl cyanoacetate, and thiourea were coupled with Mn3O4-NPs to produce compound 1. This multi-component method is non-toxic, safe, and environmentally friendly. The new approach reduced the amount of chemicals used and preserved time. Compound 1 underwent reactions with methyl iodide, acrylonitrile, chloroacetone, ethyl chloroacetate, and chloroacetic acid/benzaldehyde, each of the synthetized compounds was docked with TNF-α converting enzyme. These compounds may also support the discovery and development of novel therapeutic and preventative drugs for Alzheimer's disease. The majority of the produced compounds demonstrated pharmacokinetic features, making them potentially attractive therapeutic candidates for Alzheimer's disease treatment.
A contextual-based approach for sarcasm detection
Authors: Helal Nivin A. , Hassan Ahmed , Badr Nagwa L. , Afify Yasmine M. 
Published: July 2024

AbstractSarcasm is a perplexing form of human expression that presents distinct challenges in understanding. The problem of sarcasm detection has centered around analyzing individual utterances in isolation which may not provide a comprehensive understanding of the speaker’s sarcastic intent. Our work addresses this problem by exploring and understanding the specific contextual cues that contribute to sarcasm. In this paper, we propose an enhanced approach for sarcasm detection using contextual features. Our methodology involves employing pre-trained transformer models, RoBERTa and DistilBERT, and fine-tuning them on two datasets: the News Headlines and the Mustard datasets. Incorporating contextual information, the proposed approach yielded the best performance, achieving an impressive F1 score of 99% on News Headlines dataset and 90% on Mustard dataset. Moreover, we experimented summarizing the context into a concise short sentence. This enhancement reduced training time by 35.5% of the original time. We further validated the model trained on the News headlines dataset against the Reddit dataset, which resulted in 49% F1 score without context data. However, with the inclusion of context data, the F1 score surged to 75%. Proposed approach enhances the understanding of sarcasm in different contextual settings, enabling more accurate sentiment analysis and better decision-making in various applications.
Effect of herbal irrigants on surface roughness of intraradicular dentin using quantitative method of 3D surface texture analysis
Authors: Sobhy Sabah M. , Abdelfatah Heba , Elgamily Hanaa M. , Mohammed Nesreen Y. 
Published: July 2024

AbstractReplacing the conventional endodontic irrigants with herbal agents could avoid complications associated with using sodium hypochlorite (NaOCl). Endodontic irrigants alter the surface roughness of the dentinal wall surface, which affects sealer mechanical retention. This study aimed to assess the effect of experimental herbal Moringa oleifera and orange peel extract irrigant on intraradicular dentin (IRD) surface roughness using quantitative 3D surface analysis by scanning electron microscopy (SEM) regarding the smear layer assessment. Sixty human root sections were divided into four groups (n = 15): NaOCl combined with 17% ethylenediaminetetraacetic acid (EDTA); negative control (saline); moringa extract (MO); and orange oil (OO). SEM images were assessed quantitatively for surface roughness (Ra) in the coronal, middle, and apical IRD. The data were analysed by Kruskal–Wallis, Friedman, and Dunn’s tests. All groups showed statistically significant differences (P = 0.007). MO exhibited significantly greater Ra values at the coronal, middle, and apical root levels than OO (P = 0.007, 0.009, and 0.046, respectively). There was no significant change in Ra values at various root levels within each group at P = 0.091, 0.819, 0.819, and 0.549 for the EDTA, saline, MO, and OO groups. Considerable (IRD) surface roughness analysis makes Moringa extract a promising herbal endodontic irrigant alternative to the NaOCl plus EDTA regimen.
Multicenter validation study for automated left ventricular ejection fraction assessment using a handheld ultrasound with artificial intelligence
Authors: Kagiyama Nobuyuki , Abe Yukio , Kusunose Kenya , Kato Nahoko , Kaneko Tomohiro , Murata Azusa , Ota Mitsuhiko , Shibayama Kentaro , Izumo Masaki , Watanabe Hiroyuki 
Published: July 2024

AbstractWe sought to validate the ability of a novel handheld ultrasound device with an artificial intelligence program (AI-POCUS) that automatically assesses left ventricular ejection fraction (LVEF). AI-POCUS was used to prospectively scan 200 patients in two Japanese hospitals. Automatic LVEF by AI-POCUS was compared to the standard biplane disk method using high-end ultrasound machines. After excluding 18 patients due to infeasible images for AI-POCUS, 182 patients (63 ± 15 years old, 21% female) were analyzed. The intraclass correlation coefficient (ICC) between the LVEF by AI-POCUS and the standard methods was good (0.81, p < 0.001) without clinically meaningful systematic bias (mean bias -1.5%, p = 0.008, limits of agreement ± 15.0%). Reduced LVEF < 50% was detected with a sensitivity of 85% (95% confidence interval 76%–91%) and specificity of 81% (71%–89%). Although the correlations between LV volumes by standard-echo and those by AI-POCUS were good (ICC > 0.80), AI-POCUS tended to underestimate LV volumes for larger LV (overall bias 42.1 mL for end-diastolic volume). These trends were mitigated with a newer version of the software tuned using increased data involving larger LVs, showing similar correlations (ICC > 0.85). In this real-world multicenter study, AI-POCUS showed accurate LVEF assessment, but careful attention might be necessary for volume assessment. The newer version, trained with larger and more heterogeneous data, demonstrated improved performance, underscoring the importance of big data accumulation in the field.