bluuebunny/crossref_metadata_2025_split huggingface dataset:
The herbicide glyphosate inhibits hippocampal long-term potentiation and learning through activation of pro-inflammatory signaling
Authors: Izumi Yukitoshi , O’Dell Kazuko A. , Zorumski Charles F. 
Published: October 2023

AbstractGlyphosate, a herbicide marketed as Roundup, is widely used but there are concerns this exposure could impair cognitive function. In the CA1 region of rat hippocampal slices, we investigated whether glyphosate alters synaptic transmission and long-term potentiation (LTP), a cellular model of learning and memory. Our hypothesis is that glyphosate alters neuronal function and impairs LTP induction via activation of pro-inflammatory processes. Roundup depressed excitatory synaptic potentials(EPSPs) in a dose-dependent manner with complete suppression at 2000 mg/L. At concentrations ≤ 20 mg/L Roundup did not affect basal transmission, but 4 mg/L Roundup administered for 30 min inhibited LTP induction. Acute administration of 10–100 μM glyphosate also inhibited LTP induction. Minocycline, an inhibitor of microglial activation, and TAK-242, an inhibitor of toll-like receptor 4 (TLR4), both overcame the inhibitory effects of 100 µM glyphosate. Similarly, lipopolysaccharide from Rhodobacter sphaeroides (LPS-RS), a different TLR4 antagonist, overcame the inhibitory effects. In addition, ISRIB (integrated stress response inhibitor) and quercetin, an inhibitor of endoplasmic reticulum stress, overcame the inhibitory effects. We also observed that in vivo glyphosate injection (16.9 mg/kg i.p.) impaired one-trial inhibitory avoidance learning. This learning deficit was overcome by TAK-242. These observations indicate that glyphosate can impair cognitive function through pro-inflammatory signaling in microglia.
An interpretable framework for sleep posture change detection and postural inactivity segmentation using wrist kinematics
Authors: Elnaggar Omar , Arelhi Roselina , Coenen Frans , Hopkinson Andrew , Mason Lyndon , Paoletti Paolo 
Published: October 2023

AbstractSleep posture and movements offer insights into neurophysiological health and correlate with overall well-being and quality of life. Clinical practices utilise polysomnography for sleep assessment, which is intrusive, performed in unfamiliar environments, and requires trained personnel. While sensor technologies such as actigraphy are less invasive alternatives, concerns about their reliability and precision in clinical practice persist. Moreover, the field lacks a universally accepted algorithm, with methods ranging from raw signal thresholding to data-intensive classification models that may be unfamiliar to medical staff. This paper proposes a comprehensive framework for objectively detecting sleep posture changes and temporally segmenting postural inactivity using clinically relevant joint kinematics, measured by a custom-made wearable sensor. The framework was evaluated on wrist kinematic data from five healthy participants during simulated sleep. Intuitive three-dimensional visualisations of kinematic time series were achieved through dimension reduction-based preprocessing, providing an out-of-the-box framework explainability that may be useful for clinical monitoring and diagnosis. The proposed framework achieved up to 99.2% F1-score and 0.96 Pearson’s correlation coefficient for posture detection and inactivity segmentation respectively. This work paves the way for reliable home-based sleep movement analysis, serving patient-centred longitudinal care.
Synthesis of novel coumarin-based thiosemicarbazones and their implications in diabetic management via in-vitro and in-silico approaches
Authors: Zahra Syeda Bakhtawar , Ullah Saeed , Halim Sobia Ahsan , Waqas Muhammad , Huda Noor Ul , Khan Ajmal , Binsaleh Ammena Y. , El-kott Attalla F. , Hussain Javid , Al-Harrasi Ahmed , Shafiq Zahid 
Published: October 2023

AbstractDiabetes mellitus has a high prevalence rate and it has been deemed a severe chronic metabolic disorder with long-term complications. This research aimed to identify compounds that could potentially inhibit the vital metabolic enzyme α-glucosidase and thereby exert an anti-hyperglycemic effect. The main goal was to establish an effective approach to control diabetes. To proceed with this study, a series of novel coumarin-derived thiosemicarbazones 3a–3m was synthesized and examined using a variety of spectroscopic methods. Moreover, all the compounds were subjected to α-glucosidase inhibition bioassay to evaluate their antidiabetic potential. Fortunately, all the compounds exhibited several folds potent α-glucosidase inhibitory activities with IC50 values ranging from 2.33 to 22.11 µM, in comparison to the standard drug acarbose (IC50 = 873.34 ± 1.67 µM). The kinetic studies of compound 3c displayed concentration-dependent inhibition. Furthermore, the binding modes of these molecules were elucidated through a molecular docking strategy which depicted that the thiosemicarbazide moiety of these molecules plays a significant role in the interaction with different residues of the α-glucosidase enzyme. However, their conformational difference is responsible for their varied inhibitory potential. The molecular dynamics simulations suggested that the top-ranked compounds (3c, 3g and 3i) have a substantial effect on the protein dynamics which alter the protein function and have stable attachment in the protein active pocket. The findings suggest that these molecules have the potential to be investigated further as novel antidiabetic medications.
Testosterone promotes dominance behaviors in the Ultimatum Game after players’ status increases
Authors: Inoue Yukako , Burriss Robert P. , Hasegawa Toshikazu , Kiyonari Toko 
Published: October 2023

AbstractAlthough testosterone is generally considered to promote dominance behaviors, in humans it fosters behaviors appropriate to achieving and maintaining social status, contingent upon the situation. Recent cross-sectional studies, such as Inoue et al. (Sci Rep 7:5335, 2017), have shown that dominance behaviors induced by testosterone are modulated by high status. Yet, it remains ambiguous whether a rise in social status within real-world social groups reshapes the relationship between testosterone and dominance behavior. To investigate this longitudinal question, we added a second wave to Inoue et al.’s study, collecting further data after an interval of 2 years. Members of a university rugby team that adheres to a rigid hierarchical order rooted in seniority played the Ultimatum Game with teammates and provided saliva for assays of testosterone and cortisol. Our analysis reveals that individuals with higher baseline salivary testosterone levels exhibited more dominance as their position in the hierarchy increased according to their seniority.
Evaluating the performance of generative adversarial network-synthesized periapical images in classifying C-shaped root canals
Authors: Yang Sujin , Kim Kee-Deog , Ariji Eiichiro , Takata Natsuho , Kise Yoshitaka 
Published: October 2023

AbstractThis study evaluated the performance of generative adversarial network (GAN)-synthesized periapical images for classifying C-shaped root canals, which are challenging to diagnose because of their complex morphology. GANs have emerged as a promising technique for generating realistic images, offering a potential solution for data augmentation in scenarios with limited training datasets. Periapical images were synthesized using the StyleGAN2-ADA framework, and their quality was evaluated based on the average Frechet inception distance (FID) and the visual Turing test. The average FID was found to be 35.353 (± 4.386) for synthesized C-shaped canal images and 25.471 (± 2.779) for non C-shaped canal images. The visual Turing test conducted by two radiologists on 100 randomly selected images revealed that distinguishing between real and synthetic images was difficult. These results indicate that GAN-synthesized images exhibit satisfactory visual quality. The classification performance of the neural network, when augmented with GAN data, showed improvements compared with using real data alone, and could be advantageous in addressing data conditions with class imbalance. GAN-generated images have proven to be an effective data augmentation method, addressing the limitations of limited training data and computational resources in diagnosing dental anomalies.
Viral load of Torquetenovirus correlates with Sano’s score and levels of total bilirubin and aspartate aminotransferase in Kawasaki disease
Authors: Spezia Pietro Giorgio , Matsudaira Kazunari , Filippini Fabio , Miyamura Takako , Okada Keiko , Nagao Yoshiro , Ishida Takafumi , Sano Tetsuya , Pistello Mauro , Maggi Fabrizio , Hara Junichi 
Published: October 2023

AbstractCause of Kawasaki disease (KD) is unknown. KD is often resistant to treatment with intravenous immunoglobulin (IVIG). Sano’s score, which is derived from total bilirubin (TBIL), aspartate aminotransferase (AST) and C-reactive protein (CRP), is predictive of IVIG resistance in Japan. A recent study reported that Torquetenovirus (TTV), especially TTV7, was present at a high viral load in the patients with KD. We used PCR to quantify TTV load and amplicon next generation sequencing to detect individual TTV species. We used serum samples that were collected between 2002 and 2005 from 57 Japanese KD patients before IVIG treatment. Correlations between TTV load and Sano’s score, the biomarkers that constitute this score, and IVIG resistance were examined. TTV load was positively correlated with Sano’s score (P = 0.0248), TBIL (P = 0.0004), and AST (P = 0.0385), but not with CRP (P = 0.6178). TTV load was marginally correlated with IVIG resistance (P = 0.1544). Presence of TTV7 was correlated with total TTV load significantly (P = 0.0231). The correlations between biomarkers for KD and TTV load suggested that TTV may play a role in the pathophysiology of KD. We hypothesize that TTV7 may be associated with a higher total viral load in KD.
Short chain fatty acids facilitate protective immunity by macrophages and T cells during acute fowl adenovirus-4 infection
Authors: Lee Rangyeon , Yoon Byung-Il , Hunter Christopher A. , Kwon Hyuk Moo , Sung Haan Woo , Park Jeongho 
Published: October 2023

AbstractShort chain fatty acids (SCFAs) are major gut metabolites that are involved in the regulation of dysfunction in immune responses, such as autoimmunity and cytokine storm. Numerous studies have reported a protective action of SCFAs against infectious diseases. This study investigated whether SCFAs have protective effect for immunity during fowl adenovirus-4 (FAdV-4) infection. We examined whether SCFA mixture (acetate, propionate, and butyrate) administration could protect against intramuscular challenge of a virulent viral strain. SCFA treatment promoted MHCII-expressing monocytes, the active form of T cells, and effector molecules in both peripheral and lymphoid tissues. It also boosted the production of immune molecules involved in pathogen elimination by intraepithelial lymphocytes and changed the intestinal microbial composition. We suggest that gut metabolites influence the gut microbial environment, and these changes stimulate macrophages and T cells to fight against the intramuscular challenge of FAdV-4.
Empagliflozin induces the transcriptional program for nutrient homeostasis in skeletal muscle in normal mice
Authors: Kawakami Ryo , Matsui Hiroki , Matsui Miki , Iso Tatsuya , Yokoyama Tomoyuki , Ishii Hideki , Kurabayashi Masahiko 
Published: October 2023

AbstractSodium-glucose cotransporter 2 inhibitors (SGLT2i) improve heart failure (HF) outcomes across a range of patient characteristics. A hypothesis that SGLT2i induce metabolic change similar to fasting has recently been proposed to explain their profound clinical benefits. However, it remains unclear whether SGLT2i primarily induce this change in physiological settings. Here, we demonstrate that empagliflozin administration under ad libitum feeding did not cause weight loss but did increase transcripts of the key nutrient sensors, AMP-activated protein kinase and nicotinamide phosphoribosyltransferase, and the master regulator of mitochondrial gene expression, PGC-1α, in quadriceps muscle in healthy mice. Expression of these genes correlated with that of PPARα and PPARδ target genes related to mitochondrial metabolism and oxidative stress response, and also correlated with serum ketone body β-hydroxybutyrate. These results were not observed in the heart. Collectively, this study revealed that empagliflozin activates transcriptional programs critical for sensing and adaptation to nutrient availability intrinsic to skeletal muscle rather than the heart even in normocaloric condition. As activation of PGC-1α is sufficient for metabolic switch from fatigable, glycolytic metabolism toward fatigue-resistant, oxidative mechanism in skeletal muscle myofibers, our findings may partly explain the improvement of exercise tolerance in patients with HF receiving empagliflozin.
Different delocalized ranges in mixed valence cyanido–metal-bridged Fe–Ru–Fe complexes controlled by terminal ligand substitution modification
Authors: Zeng Chen , Xu Qing-Dou , Liu Xiao-Lin , Hu Sheng-Min , Wu Xin-Tao , Sheng Tian-Lu 
Published: October 2023

A substituent change from Cp to Cp* in cyanidometal bridged Fe–Ru–Fe complexes makes the one-electron oxidation products not only show a redox site change from Ru to Fe, but also exhibit a delocalization range change from Fe–Ru–Fe to Fe–Ru.
Severe cutaneous adverse reaction to drug excipient following brand-to-generic switch of levetiracetam
Authors: Lim Jo Anne , Jamil Adawiyah , Ramli Nur Amalina , Johar Fatimah Mat , Nor Mokhtar 
Published: October 2023

Abstract

Purpose
Levetiracetam is an antiepileptic drug known for its high tolerability, and severe adverse drug reactions are rare. We report the case of a severe cutaneous adverse drug reaction in a patient who was switched from brand-name to generic levetiracetam.

Summary
A 29-year-old woman undergoing contrast-enhanced computed tomography developed lesions over her trunk starting 6 hours after imaging. Although initially diagnosed as an allergy to the radiocontrast agent, the condition progressively worsened into toxic epidermal necrolysis-drug reaction with eosinophilia and systemic symptoms overlap syndrome, despite adequate hydration and treatment. Investigation of the patient’s medications revealed that she had been switched from brand-name to generic levetiracetam a week before the onset of symptoms. Levetiracetam was immediately discontinued, with the patient recovering after 2 weeks of intensive care. Adverse drug reaction analysis identified excipients in generic levetiracetam as the likely cause of the severe reaction.

Conclusion
This is the first reported case of severe cutaneous drug allergy after a brand-to-generic switch for levetiracetam. Brand-to-generic switches of medications can potentially cause severe allergic reactions due to differences in excipients.
Spatio-temporal expression of candidate genes for nectar spur development in Tropaeolum (Tropaeolaceae: Brassicales)
Authors: Martínez-Salazar Sebastián , Kramer Elena M , González Favio , Pabón-Mora Natalia 
Published: October 2023

Abstract

Background and Aims
Tropaeolaceae (Brassicales) comprise ~100 species native to South and Central America. Tropaeolaceae flowers have a nectar spur, formed by a late expansion and evagination of the fused proximal region of the perianth (i.e. the floral tube). This spur is formed in the domain of the tube oriented towards the inflorescence axis, which corresponds to the adaxial floral region. However, little is known about the molecular mechanisms responsible for the evolution of spurs in Tropaeolaceae.

Methods
In this study, we examined the spatio-temporal expression of genes putatively responsible for differential patterns of cell division between the adaxial and abaxial floral regions in Tropaeolaceae. These genes include previously identified TCP and KNOX transcription factors and the cell division marker HISTONE H4 (HIS4).

Key Results
We found a TCP4 homologue concomitantly expressed with spur initiation and elaboration. Tropaeolaceae possess two TCP4-like (TCP4L) copies, as a result of a Tropaeolaceae-specific duplication. The two copies (TCP4L1 and TCP4L2) in Tropaeolum longifolium show overlapping expression in the epidermis of reproductive apices (inflorescence meristems) and young floral buds, but only TlTCP4L2 shows differential expression in the floral tube at early stages of spur formation, restricted to the adaxial region. This adaxial expression of TlTCP4L2 overlaps with the expression of TlHIS4. Later in development, only TlTCP4L2 is expressed in the nectariferous tissue of the spur.

Conclusions
Based on these results, we hypothesize that Tropaeolaceae TCP4L genes had a plesiomorphic role in epidermal development and that, after gene duplication, TCP4L2 acquired a new function in spur initiation and elaboration. To better understand spur evolution in Tropaeolaceae, it is critical to expand developmental genetic studies to their sister group, the Akaniaceae, which possess simultaneously an independent duplication of TCP4L genes and a spurless floral tube.
Generative models for protein sequence modeling: recent advances and future directions
Authors: Mardikoraem Mehrsa , Wang Zirui , Pascual Nathaniel , Woldring Daniel 
Published: October 2023

Abstract
The widespread adoption of high-throughput omics technologies has exponentially increased the amount of protein sequence data involved in many salient disease pathways and their respective therapeutics and diagnostics. Despite the availability of large-scale sequence data, the lack of experimental fitness annotations underpins the need for self-supervised and unsupervised machine learning (ML) methods. These techniques leverage the meaningful features encoded in abundant unlabeled sequences to accomplish complex protein engineering tasks. Proficiency in the rapidly evolving fields of protein engineering and generative AI is required to realize the full potential of ML models as a tool for protein fitness landscape navigation. Here, we support this work by (i) providing an overview of the architecture and mathematical details of the most successful ML models applicable to sequence data (e.g. variational autoencoders, autoregressive models, generative adversarial neural networks, and diffusion models), (ii) guiding how to effectively implement these models on protein sequence data to predict fitness or generate high-fitness sequences and (iii) highlighting several successful studies that implement these techniques in protein engineering (from paratope regions and subcellular localization prediction to high-fitness sequences and protein design rules generation). By providing a comprehensive survey of model details, novel architecture developments, comparisons of model applications, and current challenges, this study intends to provide structured guidance and robust framework for delivering a prospective outlook in the ML-driven protein engineering field.
Prediction of multi-relational drug–gene interaction via Dynamic hyperGraph Contrastive Learning
Authors: Tao Wen , Liu Yuansheng , Lin Xuan , Song Bosheng , Zeng Xiangxiang 
Published: October 2023

Abstract
Drug–gene interaction prediction occupies a crucial position in various areas of drug discovery, such as drug repurposing, lead discovery and off-target detection. Previous studies show good performance, but they are limited to exploring the binding interactions and ignoring the other interaction relationships. Graph neural networks have emerged as promising approaches owing to their powerful capability of modeling correlations under drug–gene bipartite graphs. Despite the widespread adoption of graph neural network-based methods, many of them experience performance degradation in situations where high-quality and sufficient training data are unavailable. Unfortunately, in practical drug discovery scenarios, interaction data are often sparse and noisy, which may lead to unsatisfactory results. To undertake the above challenges, we propose a novel Dynamic hyperGraph Contrastive Learning (DGCL) framework that exploits local and global relationships between drugs and genes. Specifically, graph convolutions are adopted to extract explicit local relations among drugs and genes. Meanwhile, the cooperation of dynamic hypergraph structure learning and hypergraph message passing enables the model to aggregate information in a global region. With flexible global-level messages, a self-augmented contrastive learning component is designed to constrain hypergraph structure learning and enhance the discrimination of drug/gene representations. Experiments conducted on three datasets show that DGCL is superior to eight state-of-the-art methods and notably gains a 7.6% performance improvement on the DGIdb dataset. Further analyses verify the robustness of DGCL for alleviating data sparsity and over-smoothing issues.
HPTLC Method Development and Validation for the Simultaneous Estimation of Nortriptyline HCl and Pregabalin in their Combined Dosage Form
Authors: Harkhani Hinal , Thummar Kashyap , Chauhan Sanjay , Vadalia Jigna 
Published: October 2023

Abstract
Nortriptyline HCl and pregabalin Tablet is used to treat neuropathic pain as well as mental or mood issues such as sadness, mood, feelings, anxiety and tensions. Very few analytical methods are available for the simultaneous estimation of nortriptyline HCl and pregabalin and no reports has been found for HPTLC method. In the current study, a reliable HPTLC method for the simultaneous measurement of nortriptyline HCl and pregabalin in pure forms and pharmaceutical formulations has been developed with ninhydrine post derivatization of pregabalin. The HPTLC method development was carried using silica gel G60 F254 as stationary phase and acetonitrile: methanol: triethylamine: water: formic acid (7:3:0.3:0.8:0.02 v/v/v/v/v) was used as mobile phase with saturation time of 20 min. The system was found to give a compact band for nortriptyline HCl (Rf = 0.523 ± 0.008) pregabalin (Rf = 0.279 ± 0.005). The developed method was found to be validated as per ICH Q2 (R1) guideline. The peak of nortriptyline HCl and pregabalin showed good linearity over the concentration range of 50–300 ng/band and 350–2250 ng/band, respectively, with a correlation coefficient of ˃0.995. The % recoveries of both drugs were found to be in the range of 98.84–101.87%. Statistical analysis proved that the method is selective, precise, robust and accurate for the estimation of nortriptyline HCl and pregabalin.