bluuebunny/crossref_metadata_2025_split huggingface dataset:
Variation of char reactivity during catalytic gasification with CO2 : comparison among catalytic gasification by ion-exchangeable Na, Ca, and Na/Ca mixture
Authors: Chen Xiye , Zhang Linyao , Xing Chang , Liu Li , Jiao Zixin , Yang Chunhui , Du Changshuai , Qiu Penghua 
Published: June 2022

Abstract
Reactivity is an important indicator to evaluate the gasification performance, and it is also the key to design and optimize the gasification process. The type and activity of the catalyst have great impacts on the gasification reactivity of the char. In this study, the catalytic behavior of ion-exchangeable Na and Ca during CO2 gasification process and the influence mechanism of ion-exchangeable Na and Ca on the gasification reactivity of coal char were researched. The results indicated that the reactivity of Ca-Char was greater than that of Na-Char. The inactivation of Ca was mainly due to the loss and the dispersion deterioration of Ca. The increase of CO2 concentration can not only significantly increase the catalytic activity of Na and Ca, but also enhance the sustainability of Na catalytic activity. The interaction between Na and Ca had inhibition effects on the reactivity of char during CO2 gasification. The higher the ratio of Ca-Char, the more significant the inhibition effects.
Predicting hepatotoxicity associated with low-dose methotrexate using machine learning
Authors: Hu Qiaozhi , Wang Hualing , Xu Ting 
Published: June 2022

Abstract
Purpose
An accurate prediction of the hepatotoxicity associated with low-dose methotrexate can provide evidence for a reasonable treatment choice. This study aimed to develop a machine learning-based prediction model to predict hepatotoxicity associated with low-dose methotrexate and explore the associated risk factors.
Methods
Eligible patients with immune system disorders, who received low-dose methotrexate at West China Hospital between January 1, 2018, and December 31, 2019, were enrolled. A retrospective review of the included patients was conducted. Risk factors were selected from multiple patient characteristics, including demographics, admissions, and treatments. Eight algorithms, including eXtreme Gradient Boosting (XGBoost), AdaBoost, CatBoost, Gradient Boosting Decision Tree (GBDT), Light Gradient Boosting Machine (LightGBM), Tree-based Pipeline Optimization Tool (TPOT), Random Forest (RF), and Artificial Neural Network (ANN), were used to establish the prediction model.
Results
A total of 782 patients were included, and hepatotoxicity was detected in 35.68% (279/782) of the patients. The Random Forest model with the best predictive capacity was chosen to establish the prediction model (receiver operating characteristic curve 0.97, accuracy 64.33%, precision 50.00%, recall 32.14%, and F1 39.13%). Among the 15 risk factors, the highest score was a body mass index of 0.237, followed by age (0.198), the number of drugs (0.151), and the number of comorbidities (0.144). These factors demonstrated their importance in predicting hepatotoxicity associated with low-dose methotrexate.
Conclusion
Using machine learning, this novel study established a predictive model for low-dose methotrexate-related hepatotoxicity. The model can improve medication safety in patients taking methotrexate in clinical practice.
Biotransformation of standard antibiotics by Pleurotus ostreatus mushroom and in vitro antibacterial activity of resulted metabolites
Authors: Matinde Raphael , Sempombe Joseph , Mugoyela Veronica , Nyakirang’ani Nzagi , Kaale Eliangiringa , Masota Nelson E. , Makoye Paul Malaba 
Published: June 2022

Abstract
Background: Research and development of the new antibacterial agents are among the strategized measures to combat antimicrobial resistance (AMR). In the recent decades, biotransformation has been demonstrated as an alternative and effective approach for scavenging the new molecules. There is a high probability of obtaining active metabolites through biotransformation of known compounds possessing antibacterial activities. This study intended to search for new compounds by biotransformation of ceftriaxone and ciprofloxacin antibiotics using Pleurotus ostreatus mushroom.Method: Pleurotus ostreatus mushroom culture was incorporated with antibiotics and incubated for 12 days. The mixture was extracted and analysed by using Thin layer Chromatography (TLC) method to identify newly formed compounds. The TLC chromatograms were then subjected to agar overly bioautography to determine antibacterial activity of the new compounds. Results: Ceftriaxone and Ciprofloxacin antibiotics were metabolized by P. ostreatus to possibly new metabolites. The TLC analysis indicated that ceftriaxone was metabolized to give three new spots and ciprofloxacin gave only one new spot which infer the formation of new compounds from biotransformation by P. ostreatus mushroom. Bioautography showed the new spots from biotransformation of ceftriaxone to be active against S. aureus both standard and clinical isolates as well as active against methicillin resistant Staphylococcus aureus strains. The new spot from biotransformation of ciprofloxacin was only active to standard of E. coli.Conclusion: P. ostreatus mushroom has the potential to bio transform ceftriaxone and ciprofloxacin giving antibacterial active metabolites. This shows biotransformation can be considered an alternative tool for searching of new drugs.
The effects of chronic Nanoselenium treatment on sciatic nerve injury: Behavioral and Biochemical Responses
Authors: Saffarpour Sepideh , Rahimi Behnaz , Janzadeh Atousa , Hosseni Elnaz , Tehran Pargol Sadeghi , Nasirinezhad Farinaz 
Published: June 2022

Abstract
BackgroundNanoselenium as a free radical scavenger suggested being a neuroprotective agent in some neuronal diseases. As the neuropathic pain could be a consequence of a defect in antioxidant defenses and changes in oxidative stress parameters, the present study was planned to investigate the effect of nanoselenium particles on pain-related behaviors and spinal antioxidant defense parameters in the sciatic nerve injury model.MethodsAdult male albino Wistar rats (n = 32) were randomly allocated to the four experimental groups: Control group, Neuropathy group with Chronic constriction injury of the sciatic nerve (CCI), CCI +nanoselenium, CCI+ vehicle. CCI model achieved to origin neuropathic pain symptoms. Nanoselenium or vehicle was injected intraperitoneally for 14 days. The behavioral evaluation was carried out to assess the pain threshold by the radiant heat and von Frey tests. Malondialdehyde (MAD), Superoxide Dismutase (SOD) levels, and catalase activity in the spinal cord were evaluated to investigate the possible relation.Results Our data displayed that CCI triggered neuropathic pain-related behaviors in rats. Chronic treatment with nanoselenium meaningfully improved pain threshold (P < 0.001; F=37.86, F = 29. 82), and decreased the level of MDA (P < 0.01; F = 33.16) and increased the SOD level (P < 0.001; F =13.43) and catalase activity (P<0.05;F=10.17) in the spinal cord of CCI rats.ConclusionChronic nanoselenium treatment can improve pain-related behavior and is associated with a reduction in MDA level and increasing in SOD level and catalase activity in the spinal cord of the CCI rats. Nanoselenium provides a therapeutic alternative for the treatment of neuropathic pain by alteration in lipid peroxidation and antioxidant defense system factors.
Effect of lunch with different calorie and nutrient balances on dinner-induced postprandial glucose variability
Authors: Kuwahara Mai , Kim Hyeon-Ki , Furutani Akiko , Mineshita Yui , Nakaoka Takashi , Shibata Shigenobu 
Published: June 2022

Abstract
Aim: This study aimed to examine the effect of lunches with different calorie intakes (Study 1) and nutrient balances (Study 2) on dinner-induced postprandial glucose fluctuation.Methods: Energy trial (Study 1): Thirteen healthy young participants (n = 10 men, n = 3 women) were investigated to determine the effects of different caloric intakes at lunch on glucose level variability. The study comprised four trials (no lunch, low lunch, standard lunch, and high-energy lunch). Energy balance trial (Study 2): Fourteen healthy young adults (n = 8 men, n = 6 women) were investigated to determine the effect of different nutrient balances during lunch on glucose level variability. The study consisted of four trials (standard, protein-rich, fat-rich, and carbohydrate-rich). In Studies 1 and 2, each trial was spaced at least one day apart, and breakfast and dinner were tested as meals. The mealtimes for each trial were then aligned. Continuous glucose monitoring (CGM) was used to assess the blood glucose fluctuations.Results: Study 1: The no-lunch and low-energy lunch trials had significantly higher values in the incremental area under the curve (iAUC) of postprandial blood glucose at dinner compared to the standard and high-energy lunch trials (P < 0.01, P < 0.05 vs none), (respectively, P < 0.01 vs low-energy trial). Study 2: A significantly higher postprandial blood glucose iAUC for dinner was found in the fat-rich trial than that in the protein-rich and standard trials, respectively (P < 0.05).Conclusions: Our findings indicate that skipping lunch and low-calorie or high-lipid intake increased postprandial blood glucose levels after dinner.
Feasibility of conducting HIV prevention trials among key populations in Nairobi, Kenya
Authors: Mutisya Elizabeth Mueni , Muturi-Kioi Vincent , Abaasa Andrew , Nyasani Delvin , Kabuti Rhoda W. , Lunani Laura , Kotikot Timothy , Mundia Moses , Mutua Gaudensia , Ombati Geoffrey , Nduta Hannah , Price Matt A , Kimani Joshua , Anzala Aggrey Omu 
Published: June 2022

Abstract
ObjectiveTo assess the feasibility of conducting HIV prevention trials among key populations in Nairobi, Kenya.BackgroundHIV prevention trials require the inclusion of those at high risk of HIV infection and their informed decision to take part and remain in the clinical trial to the end is crucial. In Kenya key populations including men who have sex with men (MSM) and female sex workers (FSW) are, disproportionately, at high risk of HIV infection when compared to the general population. Few trials testing biomedical prevention products against HIV have enrolled Kenyan FSW and MSM. MethodsWe performed simulated vaccine efficacy trial (SiVET) using licensed hepatitis B vaccines as substitutes for a HIV vaccine candidate and included randomization for those immune to hep B. The SiVET was an observational study designed to mimic the rigors of a clinical trial; we assessed HIV risk, provided risk counselling and prevention tools and performed HIV testing at baseline and periodically until the end of the trial. MSM and FSW were enrolled at a ratio of 4:1. Volunteers were assigned to either hepatitis B vaccine or placebo. ResultsRecruitment took approximately 24 months between Sep 2015 and Sep 2017. Of the 368 volunteers screened, 250 (200 MSM and 50 FSW) were enrolled. Reasons for exclusion at screening included: being positive for HIV (n=7), hepatitis (n = 14), other pre-existing medical conditions (n=41), eligible but chose not to enrol (n=47). Most of the volunteers adhered to study procedures and attended their study visits within the study window. These include volunteers who received the second vaccination 244 (98%), the third vaccination 228 (91%) and, the final study visit 217 (87%). The reasons volunteers discontinued from the study early included: relocation and loss to follow up (n=14). A total of 8 cases of HIV infection were observed in 174.5 Person Years at Risk (PYAR), all among MSM, including 5 seroconversions identified at the last study visit, for a HIV incidence of 4.58 cases/ 100 PYAR, among MSM enrolled in the study. ConclusionOur findings suggest that it is possible to conduct HIV prevention trials among key populations in Nairobi with a good adherence to a vaccine efficacy trial schedule. Despite HIV prevention efforts, we also noted a high incidence of HIV infection. This demonstrates the need for effective HIV prevention products in these populations.
Ethnobotanical indices on wound healing medicinal plants in the villages of Gwadabawa/Illela towns of Sokoto State, Northwest Nigeria
Authors: Mathias Sylvester Nefai , Mshelia Halilu Emmanuel , Gaize Tijani Rabiu 
Published: June 2022

Abstract
Background
An ethnomedical survey was undertaken in the Gwadabawa/Illela village communities of Sokoto, Northwestern Nigeria to identify and record information on medicinal plants used for treating wounds and fungal related ailment.
Methods
Traditional Medical Practitioners (TMP’s) and other inhabitants both young and adults were interviewed using semi-structured questionnaires complimented by a voice recording device and an open-ended conversation. Field trips were made to the sites where TMP’s or other informants harvest plants.
Results
The survey identified and recorded 40 plants species from 38 genera and 18 families, used for treating wounds and wound related ailments in Gwadabawa/Illela village communities. Among the 40 species, dicots were represented by 38 species belonging to 38 genera and 16 families, while monocots were two species belonging to two genera and two families. Combretaceae and Fabaceae were the dominant families and contributed to wound healing with 7 species each. Life forms, in term of plants habit/habitat showed a record of trees (20 species), shrubs (12 species) and herb (8 species). Only one climber specie was recorded. Plant part use against their therapeutic indications showed that stembark was the most used plant part in 15 preparations with 37.5% to treat wounds, closely followed by the leaves in 12 preparations with 30.0%, the root and whole plant were reportedly use in five and four preparations with 12.5%, and 10% respectively. Fruit and flower were the least used parts in two and one preparation constituting 5.0% and 2.5% respectively. The informants prepared and prescribed the medicine mainly in the form of powder (70.0%), followed by some form of extraction (12.5%), and sap-juice or latex (10.0%), while the lowest preparation form was recorded for paste and oil (0.5% each). The major method of medicinal administration/ route of application was by spraying topically (65.0%), while other description included the use of oil to apply topically (27.5%) as well as washing and drunk (12.5%). Concoction mixtures recorded some 30–40% mode of preparation as against the use of a single plant, which constitute about 60%. Ethnobotanical indices showed Acacia nilotica as having the highest with a use value of UV: 0.27, (with 8 use reports) and a citation frequency/relative importance index of CF: 11.8, RI: 0.56, while the lowest recoded indices of 0.03 UV and 1.5 CF and 0.07 RI was recorded for some of the other plants in comparison.
Conclusions
There is still a deep reliance on the use of the surveyed plant medicines for wound healing by the people, due to the high level of successes recorded by the informants following traditional practices/applications. Hence, a wholistic or selective scientific study is imminent from the established data base of this research.
Anti-dissipative strategies towards more efficient solar energy conversion
Authors: Cotic Agustina , Cerfontaine Simon , Slep Leonardo , Elias Benjamin , Troian-Gautier Ludovic , Cadranel Alejandro 
Published: June 2022

Abstract
In natural and artificial photosynthesis, light absorption and catalysis are separate processes linked together by exergonic electron transfer. This leads to free energy losses between the initial excited state, formed after light absorption, and the catalytic center formed after the electron transfer cascade. Additional deleterious processes, such as internal conversion and vibrational relaxation, also dissipate as much as 20-30 % of the absorbed photon energy. Minimization of these energy losses, a holy-grail in solar energy conversion and solar fuels production, is a challenging task, because excited states are usually strongly coupled which results in negligible kinetic barriers and very fast dissipation. Here we show that topological control of oligomeric {Ru(bpy)3} chromophores resulted in small excited-state electronic couplings, leading to activation barriers for internal conversion of around 2000 cm–1 and effectively slowing down dissipation. Two types of excited states are populated upon visible light excitation, i.e. a bridging-ligand centered metal-to-ligand charge transfer (MLCTLm), and a 2,2’-bipyridine-centered MLCT (MLCTbpy), which lies 800-1400 cm–1 higher in energy. As a proof-of-concept, bimolecular electron transfer with tri-tolylamine as electron donor was performed, which mimics catalyst activation by sacrificial electron donors in typical photocatalytic schemes. Both excited states were efficiently quenched by tri-tolylamine and produced the corresponding bpy•– and Lm•– centered reduced complexes, as confirmed by transient absorption spectroscopy. This efficiently generated two distinct reduced photosensitizers with different reducing abilities, i.e. –0.93 V and –0.79 V vs NHE for bpy•– and Lm•–, respectively. Hence, this novel strategy not only allows to trap higher energy excited states, before internal conversion and vibrational relaxation set in, saving between 110 and 170 meV and but also leads in fine to 140 meV more potent reductant for energy conversion schemes and solar fuels production. These results lay the first stone for anti-dissipative energy conversion schemes which, in bimolecular electron transfer reactions, harnesses the excess energy saved by controlling dissipative conversion pathways.
D - Spectrum of Hyper-Dumbbell graph
Authors: Kaliyaperumal Sakthidevi , Desikan Kalyani 
Published: June 2022

Abstract
﻿A new class of graphs called dumbbell graphs denoted as DB (Wm,n) on 2(m+n) vertices is obtained by connecting m - vertices at the centres of the two generalized wheel graphs Wm,n, m ≥2, n ≥3 through m - edges. In this paper, we have extended this class of graphs to form Hyper-Dumbbell graph and also obtained its the distance spectrum, distance Laplacian spectrum and distance signless Laplacian spectrum.
Axonal degeneration in the anterior insular cortex in Parkinson’s disease and Dementia with Lewy bodies: more than just an α-synuclein story
Authors: Fathy Yasmine Y. , Jonkman Laura E. , Bol John J. , Timmermans Evelien , Jonker Allert J. , Rozemuller Annemieke J.M. , de Berg Wilma DJ van 
Published: June 2022

Abstract
Background
Axons, crucial for impulse transmission and cellular trafficking, are thought to be primary targets of neurodegeneration in Parkinson’s disease (PD) and Dementia with Lewy bodies (DLB). Axonal degeneration occurs early, preceeding and exceeding neuronal loss, and contributes to the spread of pathology, yet is poorly described outside the nigrostriatal circuitry. The insula, a cortical brain hub, was recently discovered as highly vulnerable to pathology and plays a role in cognitive deficits in PD and DLB. The aim of this study was to evaluate morphological features and burden of proteinopathy and axonal degeneration in the anterior insular sub-regions in PD, PD with dementia (PDD), and DLB.
Methods
α-Synuclein (α-syn), phosphorylated (p-)tau, and amyloid-β pathology load were evaluated in the anterior insula (agranular and dysgranular) subregions of brain donors (n = 27). Axonal loss was evaluated using modified Bielschowsky silver staining and quantified using stereology. Cytoskeletal damage was comprehensively studied using immunofluorescent multi-labelling and 3D confocal laser-scanning microscopy.
Results
Compared to PD(D), DLB showed significantly higher α-syn and p-tau pathology load, argyrophilic grains, and most severe axonal loss, particularly in the anterior agranular insula. Alternatively, the dysgranular insula showed a significant higher load of amyloid-β pathology. Using mixed model analysis, p-tau contributed most to axonal loss in the DLB group, highest in the anterior agranular insula. Neurofilament and myelin showed degenerative changes including swellings, demyelination, and detachment of the axon-myelin unit.
Conclusions
Our results highlight the selective vulnerability of the anterior agranular insular sub-region to various converging pathologies, leading to impaired axonal integrity in PD(D) and DLB, disrupting its functional properties and potentially contributing to cognitive, emotional, and autonomic deficits.
Propagation of Vortex Gaussian Beam in Atmospheric Blustery and Evaluation of the BER for Laser gradient Launching
Authors: Khamees Hussein Thary , Sameen Esraa Zuhair 
Published: June 2022

Abstract
In this paper, its enhancement of the Virtual digital message classifications, appreciation of its informal user interface design language, and outstanding information conception abilities. Unity of the most common reproduction responsibilities in digital communications is to assess the bit error rate (BER) of dial-up connection. The Formulation of the scintillation index obsessed on BER of Vortex Gaussian beam in a blustery atmosphere and originate by exploitation of the Huygens Fresnel Process to usage this structure and assess the normal bit error rate (BER), therefore it applies the ITU-R Method to find the Kolmogorov of structure constant parameter and Random Phase Screen Method. The scintillation index leaders of a multimode of Vortex Gaussian beam smooth, and used topological charge, by used zenith angle is started from zero to nighty degree. Furthermore, the typical signal-to-noise ratio (SNR) which is related to the scintillation index as against the BER is calculated via the log-normal method of the beam order. and it’s circulated in gradient path, which is presented for some parameters like it, source sizes, focal lengths and used unique wavelength, λ = 1.35μm. According to the one desired wavelength distribution is dealt with theoretically, the outcomes of BER Guesstimate were starting to the increased value of source size, the structure is better-quality and scintillation index, BER and the some of the factors are decreased the value of BER and enhanced the optical communication system.
A Novel Ultrasound Image Diagnosis Method for Thyroid Nodules
Authors: Zheng Zhiqiang , Su Tianyi , Wang Yuhe , Weng Zhi , Chai Jun , Bu Wenjin , Xu Jinjin , Chen Jiarui 
Published: June 2022

Abstract
The incidence of thyroid nodules is increasing year by year. Accurate determination of benign and malignant nodules is an important basis for formulating treatment plans. Ultrasonography is the most widely used in the diagnosis of benign and malignant nodules, but manual diagnosis is highly subjective, and the rate of missed diagnosis and misdiagnosis is high. To improve the accuracy of clinical diagnosis, this paper proposes a new diagnostic model based on deep learning. The diagnostic model adopts the diagnosis strategy of Localization-Classification. First, the distribution law of nodule size and nodule aspect ratio is obtained through data statistics, the multi-scale localization network structure is a priori designed, and the nodule aspect ratio is obtained from the positioning results. Then, the uncropped ultrasound image and the nodule area image are correspondingly input into the two-way classification network, and the improved attention mechanism is used to enhance the feature extraction, and finally, the deep features, the shallow features, and the nodule aspect ratio are fused, input the fully connected layer to complete the classification of benign and malignant nodules. The experimental data set is 4021 ultrasound images, each image is marked under the guidance of doctors, and the ratio of the training set, validation set, and test set is close to 3:1:1. The experimental results show that the accuracy of the multi-scale localization network reaches 93.74%, and the accuracy, specificity, and sensitivity of the classification network reach 86.34%, 81.29%, and 90.48%, respectively. Compared with the champion model of the TNSCUI 2020 classification competition, the accuracy rate is 1.52 points higher. Therefore, the network model proposed in this paper can effectively diagnose benign and malignant thyroid nodules.