bluuebunny/crossref_metadata_2025_split huggingface dataset:
Melatonin ameliorates disease severity in a mouse model of multiple sclerosis by modulating the kynurenine pathway
Authors: Jand Yahya , Ghahremani Mohammad Hossein , Ghanbari Amir , Ejtemaei-Mehr Shahram , Guillemin Gilles J. , Ghazi-Khansari Mahmoud 
Published: September 2022

AbstractMelatonin (MT), a neurohormone with immunomodulatory properties, is one of the metabolites produced in the brain from tryptophan (TRP) that has already strong links with the neuropathogenesis of Multiple sclerosis (MS). However, the exact molecular mechanisms behind that are not fully understood. There is some evidence showing that MS and MT are interconnected via different pathways: Relapses of MS has a direct correlation with a low level of MT secretion and a growing body of evidence suggest that MT be therapeutic in Experimental Autoimmune Encephalomyelitis (EAE, a recognise animal model of MS) severity. Previous studies have demonstrated that the kynurenine pathway (KP), the main pathway of TRP catabolism, plays a key role in the pathogenesis of MS in humans and in EAE. The present study aimed to investigate whether MT can improve clinical signs in the EAE model by modulating the KP. C57BL/6 mice were induced with EAE and received different doses of MT. Then the onset and severity of EAE clinical symptoms were recorded. Two biological factors, aryl hydrocarbon receptor (AhR) and NAD+ which closely interact in the KP were also assessed. The results indicated that MT treatment at all tested doses significantly decrease the EAE clinical scores and the number of demyelinating plaques. Furthermore, MT treatment reduced the mRNA expression of the KP regulatory enzyme indoleamine 2,3-dioxygenase 1(IDO-1) and other KP enzymes. We also found that MT treatment reduces the mRNA expression of the AhR and inhibits the enzyme Nicotinamide N-Methyltransferase (Nnmt) overexpression leading to an increase in NAD+ levels. Collectively, this study suggests that MT treatment may significantly attenuates the severity of EAE by altering the KP, AhR and NAD+ metabolism.
Complete chloroplast genome structure of four Ulmus species and Hemiptelea davidii and comparative analysis within Ulmaceae species
Authors: Liu Yichao , Li Yongtan , Feng Shuxiang , Yan Shufang , Wang Jinmao , Huang Yinran , Yang Minsheng 
Published: September 2022

AbstractIn this study, the chloroplast (cp) genomes ofHemiptelea davidii,Ulmus parvifolia,Ulmus lamellosa,Ulmus castaneifolia, andUlmus pumila‘zhonghuajinye’ were spliced, assembled and annotated using the Illumina HiSeq PE150 sequencing platform, and then compared to the cp genomes of otherUlmusand Ulmaceae species. The results indicated that the cp genomes of the five sequenced species showed a typical tetrad structure with full lengths ranging from 159,113 to 160,388 bp. The large single copy (LSC), inverted repeat (IR), and small single copy (SSC) lengths were in the range of 87,736–88,466 bp, 26,317–26,622 bp and 18,485–19,024 bp, respectively. A total of 130–131 genes were annotated, including 85–86 protein-coding genes, 37 tRNA genes and eight rRNA genes. The GC contents of the five species were similar, ranging from 35.30 to 35.62%. Besides, the GC content was different in different region and the GC content in IR region was the highest. A total of 64-133 single sequence repeat (SSR) loci were identified among all 21 Ulmaceae species. The (A)nand (T)ntypes of mononucleotide were highest in number, and the lengths were primarily distributed in 10–12 bp, with a clear AT preference. A branch-site model and a Bayes Empirical Bayes analysis indicated that therps15andrbcLhad the positive selection sites. Besides, the analysis of mVISTA and sliding windows got a lot of hotspots such astrnH/psbA,rps16/trnQ,trnS/trnG,trnG/trnRandrpl32/trnL, which could be utilized as potential markers for the species identification and phylogeny reconstruction withinUlmusin the further studies. Moreover, the evolutionary tree of Ulmaceae species based on common protein genes, whole cp genome sequences and common genes in IR region of the 23 Ulmaceae species were constructed using the ML method. The results showed that these Ulmaceae species were divided into two branches, one that includedUlmus,ZelkovaandHemiptelea, among whichHemipteleawas the first to differentiate and one that includedCeltis,Trema,Pteroceltis,GironnieraandAphananthe. Besides, these variations found in this study could be used for the classification, identification and phylogenetic study ofUlmusspecies. Our study provided important genetic information to support further investigations into the phylogenetic development and adaptive evolution ofUlmusand Ulmaceae species.
Identification of potential modulators of IFITM3 by in-silico modeling and virtual screening
Authors: Tiwari Vikas , Viswanath Shruthi 
Published: September 2022

AbstractIFITM3 is a transmembrane protein that confers innate immunity. It has been established to restrict entry of multiple viruses. Overexpression of IFITM3 has been shown to be associated with multiple cancers, implying IFITM3 to be good therapeutic target. The regulation of IFITM3 activity is mediated by multiple post-translational modifications (PTM). In this study, we have modelled the structure of IFITM3, consistent with experimental predictions on its membrane topology. MD simulation in membrane-aqueous environment revealed the stability of the model. Ligand binding sites on the IFITM3 surface were predicted and it was observed that the best site includes important residues involved in PTM and has good druggable score. Molecular docking was performed using FDA approved ligands and natural ligands from Super Natural II database. The ligands were re-ranked by calculating binding free energy. Select docking complexes were simulated again to substantiate the binding between ligand and IFITM3. We observed that known drugs like Eluxadoline and natural products like SN00224572 and Parishin A have good binding affinity against IFITM3. These ligands form persistent interactions with key lysine residues (Lys83, Lys104) and hence can potentially alter the activity of IFITM3. The results of this computational study can provide a starting point for experimental investigations on IFITM3 modulators.
Microfluidic microwave biosensor based on biomimetic materials for the quantitative detection of glucose
Authors: Zhang Mengqi , Yang Xiaojun , Ren Mengna , Mao Sui , Dhakal Rajendra , Kim Nam-Young , Li Yuanyue , Yao Zhao 
Published: September 2022

AbstractThis paper presents a microwave microfluidic biosensor for monitoring blood glucose levels. The glucose sensor is a triple ring microstrip patch antenna integrated with a biomimetic microfluidic device capable of measuring a fixed volume of glucose solution. The sensor was utilized to detect 50–500 mg/dL glucose solutions. The interaction of the glucose solution with the electromagnetic field on the patch's surface influences both the resonance frequency and the magnitude of reflection coefficient. The results indicate that the microfluidic device can reduce experimental error and enhance the correlation between glucose concentration, resonant frequency, and reflection coefficient. Finally, the microfluidic sensor had a sensitivity of 0.25 MHz/(mg/dL), a detection limit as low as 7.7 mg/dL, and correlation coefficients of resonance frequency and reflection coefficient with a glucose concentration of 0.996 and 0.984, respectively. The experiment on the sensor's stability verifies the sensor's excellent stability and rapid response (~ 150 ms). Consequently, the device can be used to differentiate the concentration of glucose solutions, as well as to detect blood glucose levels at an early stage.
Estimating leaf area index of maize using UAV-based digital imagery and machine learning methods
Authors: Du Liping , Yang Huan , Song Xuan , Wei Ning , Yu Caixia , Wang Weitong , Zhao Yun 
Published: September 2022

AbstractLeaf area index (LAI) is a fundamental indicator of crop growth status, timely and non-destructive estimation of LAI is of significant importance for precision agriculture. In this study, a multi-rotor UAV platform equipped with CMOS image sensors was used to capture maize canopy information, simultaneously, a total of 264 ground‐measured LAI data were collected during a 2-year field experiment. Linear regression (LR), backpropagation neural network (BPNN), and random forest (RF) algorithms were used to establish LAI estimation models, and their performances were evaluated through 500 repetitions of random sub-sampling, training, and testing. The results showed that RGB-based VIs derived from UAV digital images were strongly related to LAI, and the grain-filling stage (GS) of maize was identified as the optimal period for LAI estimation. The RF model performed best at both whole period and individual growth stages, with the highest R2(0.71–0.88) and the lowest RMSE (0.12–0.25) on test datasets, followed by the BPNN model and LR models. In addition, a smaller 5–95% interval range of R2and RMSE was observed in the RF model, which indicated that the RF model has good generalization ability and is able to produce reliable estimation results.
Pbx(OH)y cluster formation and anomalous thermal behaviour in STI framework-type zeolites
Authors: Cametti Georgia , Roos Diana P. , Prieur Damien , Scheinost Andreas C. , Churakov Sergey V. 
Published: September 2022

AbstractFor the first time, the structural investigation of a Pb-exchanged zeolite (Pb13.4(OH)10Al17.4Si54.6O144 ∙38H2O) with STI framework type, revealed a highly unusual and intriguing sudden volume increase under continuous heating. Understanding the fundamental mechanisms leading to such an unusual behaviour is essential for technological applications and interpretation of chemical bonding in zeolites. The dehydration was tracked in situ from 25 to 450 °C by single crystal X-ray diffraction, infrared and X-ray absorption spectroscopy. Further interpretation of the experimental observations was supported by ab initio molecular dynamics simulations. Initially, Pb-STI unit-cell volume contracts (ΔV = − 3.5%) from 25 to 100 °C. This agrees with the trend observed in STI zeolites. Surprisingly, at 125 °C, the framework expanded (ΔV =  + 2%), adopting a configuration, which resembles that of the room temperature structure. Upon heating, the structure loses H2O but no de-hydroxylation occurred. The key mechanism leading to the sudden volume increase was found to be the formation of Pbx(OH)y clusters, which prevent the shrinking of the channels, rupture of the tetrahedral bonds and occlusion of the pores. This zeolite has therefore an increased thermal stability with respect to other STI metal-exchanged zeolites, with important consequences on its applications.
A nationwide cohort study of the association of benzodiazepines with SARS-CoV-2 infection and clinical outcomes
Authors: Park Hye Yoon , Kwon Junhyun , An Suk Kyoon , Park Eun-Cheol 
Published: September 2022

AbstractThe evidence for the impact of benzodiazepine (BZD) use on infection or clinical outcomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is limited. We evaluated the association of BZD use with SARS-CoV-2 infection and the clinical outcomes of coronavirus disease 2019 (COVID-19) using a nationwide COVID-19 database from South Korea. This nationwide cohort study was performed using the COVID-19 database from the Health Insurance Review and Assessment Service of Korea, and SARS-CoV-2 positivity was investigated according to BZD use. SARS-CoV-2-positive adult patients were assessed in three groups, those who needed hospitalization, those with severe symptoms requiring intensive care, and those who died. A multivariate logistic regression model was used for all the analyses. After adjusting for potential confounding factors, there was no association between BZD use and SARS-CoV-2 positivity. SARS-CoV-2-positive patients with BZD use showed an increased risk of need for hospitalization from COVID-19 compared to those without BZD use (odds ratio [OR]: 1.33, 95% confidence interval [CI] 1.07–1.65). In addition, there was a higher risk for long-term users (OR: 2.64, 95% CI 1.08–6.47). Chronic BZD use contributed to a higher risk of the need for hospitalization among COVID-19 patients, whereas BZD use did not increase the risk of SARS-CoV-2 test positivity, severe outcomes, or mortality.
Trajectories of adolescent perceived stress and symptoms of depression and anxiety during the COVID-19 pandemic
Authors: van Loon Amanda W. G. , Creemers Hanneke E. , Vogelaar Simone , Saab Nadira , Miers Anne C. , Westenberg P. Michiel , Asscher Jessica J. 
Published: September 2022

AbstractAdolescents might be particularly affected by the drastic social changes as a consequence of the COVID-19 pandemic, given the increased stress-sensitivity and importance of the social environment in this developmental phase. In order to examine heterogeneity during the pandemic, the current study aimed to identify whether subgroups of adolescents could be distinguished based on their levels of perceived stress and symptoms of depression and anxiety. In addition, we examined which prepandemic factors predicted these trajectories. Adolescents were assessed before the pandemic (N = 188, Mage = 13.49, SD = 0.81) and at three timepoints during the pandemic (i.e., eight, ten, and 15 months after the start of the pandemic in the Netherlands). Results showed no support for distinct trajectories of perceived stress, adolescents experienced stable moderate levels during the pandemic. In contrast, results showed three trajectories for depression and anxiety. The majority of adolescents reported stable low or moderate levels and one small subgroup reported high levels of depression and anxiety that decreased during the pandemic. Certain prepandemic factors predicted higher initial levels of stress and symptoms of depression and anxiety during the pandemic. To support adolescents with prepandemic vulnerabilities, strategies could be developed, for instance enhancing adolescents’ social support.
Comparison of two injectable anaesthetic protocols in Egyptian fruit bats (Rousettus aegyptiacus) undergoing gonadectomy
Authors: Amari Martina , Brioschi Federica Alessandra , Rabbogliatti Vanessa , Di Cesare Federica , Pecile Alessandro , Giordano Alessia , Moretti Pierangelo , Magnone William , Bonato Francesco , Ravasio Giuliano 
Published: September 2022

AbstractEgyptian fruit bats have gained increasing interest being a natural reservoir for emerging zoonotic viruses. Anaesthesia is often required to allow safe handling of bats. We aimed to compare the sedative and cardiopulmonary effects of two balanced anaesthetic protocols in bats undergoing gonadectomy. Group DK (n = 10) received intramuscular dexmedetomidine (40 µg/kg) and ketamine (7 mg/kg), whereas group DBM (n = 10) received intramuscular dexmedetomidine (40 µg/kg), butorphanol (0.3 mg/kg) and midazolam (0.3 mg/kg). Induction time and cardiopulmonary parameters were recorded. If anaesthetic plan was inadequate, isoflurane was titrated-to-effect. At the end of surgery venous blood gas analysis was performed and atipamezole or atipamezole-flumazenil was administered for timed and scored recovery. In DBM group heart rate and peripheral oxygen saturation were significantly higher (p = 0.001;p = 0.003 respectively), while respiratory rate was significantly lower (p = 0.001). All bats required isoflurane supplementation with no significant differences between groups. Induction and recovery times showed no significant differences. In group DK a better recovery was scored (p = 0.034). Sodium and chloride were significantly higher in DBM group (p = 0.001;p = 0.002 respectively). Both anaesthetic protocols were comparable and can be recommended for minor procedures in bats.
Detecting thin adhesive coatings in wood fiber materials with laboratory-based dual-energy computed tomography (DECT)
Authors: Kibleur Pierre , Blykers Benjamin , Boone Matthieu N. , Van Hoorebeke Luc , Van Acker Joris , Van den Bulcke Jan 
Published: September 2022

AbstractThe distribution and good spreading of adhesive resins is critical for the wood-based panels industry. Full 3D non-destructive characterization is necessary, but methods are limited due to the chemical similarities between the resins and the wood fibers. For X-ray microtomography ($$\mu $$
μ
CT), the doping of the resin with a highly attenuating contrast agent is necessary to visualize the resin distribution. However, the attenuation signal remains hard to segment clearly due to partial volume effects in the image, and phase mixing in the material. To help in the identification of the doped resin, dual-energy X-ray CT (DECT) is used to exploit the contrast agent’s K-edge, based on simulations which take into account the polychromatic properties of the X-ray tube and detector response. The contrast agent’s identification with DECT is validated with elemental mapping using scanning electron microscopy combined with energy-dispersive spectroscopy (SEM-EDX) on the surface of a wood-based panel sample, using data fusion between DECT and SEM-EDX. Overall, DECT results here in the first 3D identification of doped resin inside wood fiberboards, guiding the industry’s efforts in further improving the durability of wood-based panels.
Role of oceanic abiotic carbonate precipitation in future atmospheric CO2 regulation
Authors: Bialik Or M. , Sisma-Ventura Guy , Vogt-Vincent Noam , Silverman Jacob , Katz Timor 
Published: September 2022

AbstractThe oceans play a major role in the earth’s climate by regulating atmospheric CO2. While oceanic primary productivity and organic carbon burial sequesters CO2 from the atmosphere, precipitation of CaCO3 in the sea returns CO2 to the atmosphere. Abiotic CaCO3 precipitation in the form of aragonite is potentially an important feedback mechanism for the global carbon cycle, but this process has not been fully quantified. In a sediment-trap study conducted in the southeastern Mediterranean Sea, one of the fastest warming and most oligotrophic regions in the ocean, we quantify for the first time the flux of inorganic aragonite in the water column. We show that this process is kinetically induced by the warming of surface water and prolonged stratification resulting in a high aragonite saturation state (ΩAr ≥ 4). Based on these relations, we estimate that abiotic aragonite calcification may account for 15 ± 3% of the previously reported CO2 efflux from the sea surface to the atmosphere in the southeastern Mediterranean. Modelled predictions of sea surface temperature and ΩAr suggest that this process may weaken in the future ocean, resulting in increased alkalinity and buffering capacity of atmospheric CO2.
A recessive mutation in muscadine grapes causes berry color-loss without influencing anthocyanin pathway
Authors: Ismail Ahmed , Gajjar Pranavkumar , Park Minkyu , Mahboob Abdulla , Tsolova Violeta , Subramanian Jayasankar , Darwish Ahmed G. , El-Sharkawy Islam 
Published: September 2022

AbstractAnthocyanins, a major class of flavonoids, are important pigments of grape berries. Despite the recent discovery of the genetic cause underlying the loss of color, the metabolomic and molecular responses are unknown. Anthocyanin quantification among diverse berry color muscadines suggests that all genotypes could produce adequate anthocyanin quantities, irrespective of berry color. Transcriptome profiling of contrasting color muscadine genotypes proposes a potential deficiency that occurs within the anthocyanin transport and/or degradation mechanisms and might cause unpigmented berries. Genome-wide association studies highlighted a region on chromosome-4, comprising several genes encoding glutathione S-transferases involved in anthocyanin transport. Sequence comparison among genotypes reveals the presence of two GST4b alleles that differ by substituting the conserved amino acid residue Pro171-to-Leu. Molecular dynamics simulations demonstrate that GST4b2–Leu171encodes an inactive protein due to modifications within the H-binding site. Population genotyping suggests the recessive inheritance of the unpigmented trait with a GST4b2/2 homozygous. A model defining colorless muscadines’ response to the mutation stimulus, avoiding the impact of trapped anthocyanins within the cytoplasm is established.
Non-Hermitian skin clusters from strong interactions
Authors: Shen Ruizhe , Lee Ching Hua 
Published: September 2022

AbstractStrong, non-perturbative interactions often lead to new exciting physics, as epitomized by emergent anyons from the Fractional Quantum hall effect. Within the actively investigated domain of non-Hermitian physics, we provide a family of states known as non-Hermitian skin clusters. Taking distinct forms as Vertex, Topological, Interface, Extended and Localized skin clusters, they generically originate from asymmetric correlated hoppings on a lattice, in the strongly interacting limit with quenched single-body energetics. Distinct from non-Hermitian skin modes which accumulate at boundaries, our skin clusters are predominantly translation invariant particle clusters. As purely interacting phenomena, they fall outside the purview of generalized Brillouin zone analysis, although our effective lattice formulation provides alternative analytic and topological characterization. Non-Hermitian skin clusters originate from the fragmentation structure of the Hilbert space and may thus be of significant interest in modern many-body contexts such as the Eigenstate thermalization hypothesis (ETH) and quantum scars.
Short-term local predictions of COVID-19 in the United Kingdom using dynamic supervised machine learning algorithms
Authors: Wang Xin , Dong Yijia , Thompson William David , Nair Harish , Li You 
Published: September 2022

Abstract
Background
Short-term prediction of COVID-19 epidemics is crucial to decision making. We aimed to develop supervised machine-learning algorithms on multiple digital metrics including symptom search trends, population mobility, and vaccination coverage to predict local-level COVID-19 growth rates in the UK.

Methods
Using dynamic supervised machine-learning algorithms based on log-linear regression, we explored optimal models for 1-week, 2-week, and 3-week ahead prediction of COVID-19 growth rate at lower tier local authority level over time. Model performance was assessed by calculating mean squared error (MSE) of prospective prediction, and naïve model and fixed-predictors model were used as reference models. We assessed real-time model performance for eight five-weeks-apart checkpoints between 1st March and 14th November 2021. We developed an online application (COVIDPredLTLA) that visualised the real-time predictions for the present week, and the next one and two weeks.

Results
Here we show that the median MSEs of the optimal models for 1-week, 2-week, and 3-week ahead prediction are 0.12 (IQR: 0.08–0.22), 0.29 (0.19–0.38), and 0.37 (0.25–0.47), respectively. Compared with naïve models, the optimal models maintain increased accuracy (reducing MSE by a range of 21–35%), including May–June 2021 when the delta variant spread across the UK. Compared with the fixed-predictors model, the advantage of dynamic models is observed after several iterations of update.

Conclusions
With flexible data-driven predictors selection process, our dynamic modelling framework shows promises in predicting short-term changes in COVID-19 cases. The online application (COVIDPredLTLA) could assist decision-making for control measures and planning of healthcare capacity in future epidemic growths.