bluuebunny/crossref_metadata_2025_split huggingface dataset:
Composites Based on Nanosilica Filled EPDM/NBR Rubber Blends with better mechanical and swelling resistance properties
Authors: Dhanasekar S , Baskar S , Vishvanathperumal S 
Published: May 2023

AbstractThe main inorganic component of rice husk is silica. Washing the rice husk, followed by combustion and chemical treatment, produced high-surface area amorphous extracted nanosilica (NS) and modified extracted nanosilica (mNS). It was established to reinforce a blend of ethylene-propylene-diene monomer (EPDM) and acrylonitrile-butadiene rubber (NBR) using different amounts of mNS, specifically 2, 4, 6, 8, and 10 phr. The cure properties, mechanical, physical, and swelling resistance examinations of the sulphur-cured nanocomposites were studied. The results showed that while the torques were prolonged with increasing mNS concentration, the optimum cure time (t90) and scorch time (ts2) decreased. The homogeneous distribution of nanosilica particles throughout the rubber matrices was confirmed by the FESEM micrographs. The outcomes guaranteed a discernible improvement in the nanocomposites' examined qualities.
Determination of Essential and Non-Essential Elements in Medicinal Herbs from Brazil Using ICP OES techniques
Authors: Junior João B. Pereira , Carvalho Vanessa S. , Ferreira William Q. , Araujo Rennan G. O. , Ferreira Sérgio L.C. 
Published: May 2023

AbstractThis work aims to present a simple, cost-effective, and environmentally friendly digestion method with diluted HNO3and H2O2for simultaneous determination of As, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, P, Pb, Sr and Zn in medicinal herbs employed inductively coupled plasma optical emission spectrometry (ICP OES). A fractional factorial design uses a multivariate strategy to optimize the experimental parameters of the sample preparation. The application of a multi-response function established the best experimental conditions. After optimized digestion conditions with a final volume of 8.0 mL and 0.1 g of medical herb sample mass in the reaction flask system was of 4.0 mol L-1HNO3concentration, 6.0% (m m-1) H2O2concentration, the temperature of 180°C and digestion time, 120 min, employing a closed block digester. The optimized procedure resulted in low residual carbon content and residual acid acidity concentration, showing good chemical analysis conditions introduced by ICP OES. Accuracy was confirmed through the certified reference materials analysis of tomato leaves (CRM-Agro C1003a), sugar cane leaves (CRM-Agro C1005a), and tea (NCS DC 73351), where agreement ranged from 83 (Sr) to 116% (As), for all analytes. Values obtained of the limit of detection (LOD) and limit of quantification (LOQ) ranged from 0.06 (Cd) to 1.9 (P) mg kg-1and from 0.2 (Cd) to 6.3(P) mg kg-1, respectively. Finally, twenty-seven medicinal herbs samples were used to assess the applicability of the developed procedure. It was obtained from the markets of Salvador (State of Bahia) and Belém (State of Pará), both cities Brazilian. The analyte concentrations in the samples comprised a range of As (< 0.5–2.74 mg kg-1), Ca (0.44–2.96%), Cu (< 2.2–20.3 mg kg-1), Fe (103.7–976 mg kg-1), K (0.102-4.0%), Mg (0.029-0.80%), Mn (8.9–2020 mg kg-1), Na (< 2.0-3.4%), P (< 6.3–0.31%), Sr (19.5–692 mg kg-1), and Zn (3.19–75.7 mg kg-1). Cadmium, Cr, and Pb showed values of concentration below LOQ for the analytical method proposed. Principal component analysis (PCA) was applied to inorganic constituent concentrations data in an attempt to classify the medicinal herbs, being an excellent tool for classifying samples.
Lysergic acid diethylamide stimulates cardiac human H 2 histamine receptors
Authors: Gergs Ulrich , Jacob Hannes , Braekow Pauline , Hofmann Britt , Pockes Steffen , Humphrys Laura J. , Kirchhefer Uwe , Fehse Charlotte , Neumann Joachim 
Published: May 2023

Abstract
Introduction: Lysergic acid diethylamide (LSD) is an artificial hallucinogenic drug. Thus, we hypothesized that LSD might act 5-HT4 serotonin receptors and/or H2 histamine receptors.
Methods: We studied isolated electrically stimulated left atrial preparations, spontaneously beating right atrial preparations, and spontaneously beating Langendorff-perfused hearts from transgenic mice with cardiomyocyte-specific overexpression of the human 5-HT4 receptor (5-HT4-TG) or of the H2-histamine receptor (H2-TG). For comparison, we used wild type littermate mice (WT). Finally, we measured isometric force of contraction in isolated electrically stimulated muscle strips from the human right atrium obtained from patients during bypass surgery.
Results: LSD (up to 10 µM) concentration dependently increased force of contraction and beating rate in left or right atrial preparations from 5-HT4-TG (n=6, p<0.05) as a partial agonist in 5-HT4-TG atrial preparations. The inotropic and chronotropic effects of LSD were antagonized by 10 µM tropisetron in 5-HT4-TG. In contrast, LSD (10 µM) increased force of contraction and beating rate in left or right atrial preparations, from H2-TG as a full agonist. After pre-stimulation with cilostamide (1 µM), LSD (10 µM) increased force of contraction in human atrial preparations (n = 6, p < 0.05). The contractile effects of LSD in human atrial preparations could be antagonized by by 10 µM cimetidine.
Conclusion: LSD leads to H2-histamine receptor mediated cardiac effects in humans.
Significance: LSD is undergoing a revival in clinical studies. New indications for LSD especially in psychiatric patients are being found. Hence, there is a clinical need to understand its cardiac effects and possibly cardiac side effects better. The present work uses a translational approach to address this research need.
Automatic P-phase picking based on machine learning and AIC algorithm and its application in engineering geological hazards warning
Authors: Zhang Yongshu , Li Lianchong , Mu Wenqiang , Wei Tingshuang , Dang Baoquan , Guofeng Yu 
Published: May 2023

Abstract
Accurate P-phase first arrival time is a premise for improving accuracy of seismic source localizations and achieving hazard warning. Traditional algorithms failed to meet the requirements of high precision and accuracy for microseismic (MS) monitoring in deep geological engineering. In this study, a multi-step method: convolutional neural network combined with K-means and AIC (CNN-KA) for picking up arrival time of P-phases is proposed. Firstly, convolutional neural network (CNN) technique is used to recognize waveforms of rock fractures instead of manual. Secondly, maximum overlapping discrete wavelet transform and multi-resolution analysis are combined to denoise. Finally, a new picker was developed by introducing K-means clustering algorithm, which was used to extract the target time window where the P-phase was located. It compensates for inherent shortcomings of AIC when applied to field data itself. Experiments and engineering applications show that the average absolute error of the proposed method (CNN-KA) is 0.0915s at frequency of 200Hz, which is 86.65% lower than STA/LTA algorithm. Automatic location error of rock fracture MS events is reduced from 37.33m to 10.89m. CNN-KA was able to warn a potential geological hazard in a coal mine of Anhui Province, China. The in-situ mine pressure data validated the validity of CNN-KA. The proposed workflow greatly improves accuracy of P-phases and identification of rock fracturing events in geo-engineering. The computed results can be used further for calculating precise parameters of MS sources and early warning of engineering geohazards.
The geochemical compatibility and discrimination elements of magnetite in the western and eastern beaches of Taiwan
Authors: Mitwally Eslam , Yu Bing-Sheng 
Published: May 2023

Abstract
Our primary purposes are to determine the genesis and essential source rocks that supply the magnetite on beaches and the compatible and discriminate chemical elements of the rocks and beach sands magnetite using the multivariate diagram and Principle component analysis (PCA) technique. The magnetite formation environments in this study are magmatic and hydrothermal genesis. Regularly, the concentration of magnetite on the western side is decreasing from north to south, where the higher concentration at Crescent Beach, which is considered as the river mouth of the Touqian river which is passing across through some of the andesite rocks, that is regarded as the source of the magnetite at this region. On the eastern side, the higher concentration of magnetite at Dagangkou, Chenggong (Sanxiantai), Donghe beaches and Taitung Creek Estuary in Taitung city, and Nan-an and Heping beaches in Yilan city. A higher concentration of the magnetite at Dagangkou, Chenggong (Sanxiantai), Donghe beaches and Taitung Creek Estuary may be due to these sites considered the river mouths of the Beinan, Wamuku and Xiuguluan rivers, these rivers passing across through Lichi mélange, which leads to the higher concentration due to the presence of these igneous and hydrothermal facies. Generally, the surrounding rocks are considered the main supplies of magnetite on the western and eastern beaches. Iron, Mg, Al, Ti, V, Mn, Co, Sc, Ni, Ga, Zr, Nb, and Sn are not suitable variables to differentiate between the magmatic and hydrothermal magnetites of western and eastern sides, but Zn, P, Ca, Cr, Cu, Na and K are suitable differentiate variables. Iron, Al, Ca, Cu, Sn, Ga, Mn, Mg, Ti, Zn, Co, V, Ni, and Cr in the hydrothermal magnetite, and Fe, Al, Ca, Na, K, Sc, Nb, Cu, Sn, Zr, Ga, Mn, Ti, Zn, Co, V, Ni, and Cr in the magmatic magnetite are the compatible elements into the magnetite crystal structure. The high discriminate variables are Fe, Ti, Al, Mg, Mn, V, Zn, and P. Moderate discriminate variables are Co, Cr, Cu, Ga, Ni, K, and Na. Low discriminate variables are Zr, Sn, Sc, and Nb. PCA technique is useful tool to arrange the discriminate variables on the chemical composition of each studied samples separately. This arrangement can detect the provenance magnetite rock.
Adsorptive capture of Congo red and Erythromycin pollutants from water by Functionalized ecofriendly chitosan and nanobiochar with silica gel
Authors: Mahmoud Mohamed E. , El-Ghanam Abdel Moneim , Saad Shaimaa R. 
Published: May 2023

Abstract
Both chitosan and biochar are known as biodegradable and ecofriendly materials with different functional groups that enable strong binding with various pollutants. Dyes and pharmaceuticals in wastewater are categorized as serious hazardous pollutants due to their nonbiodegradability and therefore, must be removed before discharge in water resources. In this work, a novel nanobiosorbent was designed and fabricated from three constituents based on the pyrolysis of banana peels to produce nanobiochar (BPNB) as a sustainable material. This was then modified with nanosilica gel via microwave heating to yield (BPNB-SiO2). Chitosan hydrogel (Chit Hgel) as a biodegradable polymer was further crosslinked with BPNB-SiO2 to produce the aimed BPNB-SiO2-Chit Hgel nanobiosorbent with particle size in the range of 22.48–26.23 nm. The effects of initial nanobiosorbent dosage (1–50 mg), initial adsorbate pH (pH 2–12), shaking time (1–45 min), initial pollutant concentration (5–100 mg L− 1), temperature (288–333 K), and interfering salts on the adsorption process of Erythromycin antibiotic (ERM) and Congo red dye (CRD) pollutants were investigated and optimized. The pseudo-second-order model revealed the perfect fit in kinetic investigations of ERM and CRD by BPNB-SiO2-Chit Hgel. The Langmuir model achieved (R2 = 0.997 for ERM and R2 = 0.992 for CRD) as the highest correlation coefficients. Moreover, the adsorption reactions of ERM and CRD onto BPNB-SiO2-Chit Hgel were classified as spontaneous and endothermic. The removal of ERM (92.80–96.50%) and CRD (92.80–95.0%) from tap, sea, and wastewater was successfully established to confirm the capability of the investigated BPNB-SiO2-Chit Hgel nanobiosorbent in removal of these two pollutants from polluted samples.
Molecular mechanisms and prognostic value of the selenoprotein gene family in lung adenocarcinoma and lung squamous cell carcinoma
Authors: Tian Tianjie , Qi Chuang , Luo Xianqing , Tu Qimin , Tong Guoyong , Zhang Zixiong 
Published: May 2023

Abstract

Lung cancer is the leading cause of cancer-related deaths worldwide, and has the highest morbidity among all cancers. Non-small cell lung cancer (NSCLC) accounts for 85% of all lung cancer cases and its most common subtypes are lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Although the selenium protein gene plays a key role in the initiation, development, and progression of many cancers, the panoramic picture of the involvement of selenoprotein gene family in LUAD and LUSC is unclear. Therefore, the expression and prognostic value of the selenoprotein family genes, as well as their potential mechanisms in LUAD and LUSC, were systematically examined in this study. First, differential expression and survival analyses revealed that a high expression of glutathione peroxidase 2 (GPX2) and low expression of both GPX3 and selenoprotein P (SELENOP) in tumors correlated with poor overall survival in patients with LUAD, while a high expression of iodothyronine deiodinase 2 (DIO2) in tumors correlated with better overall survival, and a low expression of GPX3 correlated with poor overall survival in patients with LUSC. Next, we developed a nomogram based on the Cox regression model to visualize survival and confirmed its predictive capability. Methylation, gene mutation, and immune infiltration analyses of selenoprotein genes indicated that they all participated in the progression of LUAD and LUSC. Enrichment analysis and protein–protein interaction networks showed that the common differentially expressed genes mainly participated in selenocompound metabolism, glutathione metabolism, arachidonic acid metabolism, and thyroid hormone synthesis. In addition, we constructed transcription factor (TF)-mRNA, mRNA-RNA-binding protein (RBP), and mRNA-drug regulatory networks. Our research shows that selenoprotein family members have potential as novel biomarkers for prognostic assessment and as therapeutic targets for LUAD and LUSC.
Do Crohn's disease patients benefit from an optimized adalimumab therapy?
Authors: Peng Xiang , Xu Zhao-yuan , Yao Jia-Yin , Zhang Min , Zhi Min 
Published: May 2023

Abstract
Background Adalimumab induction and maintenance therapy have been applied to patients with Crohn's disease (CD). This study aimed to analyze the efficacy and safety of an optimized dose versus a standard dose of adalimumab in the treatment of CD.Methods It was a retrospective study involving 192 CD patients treated with adalimumab. According to the maintenance therapy following an induction therapy, CD patients were assigned to receive a standard dose (subcutaneously injected with 40mg of adalimumab every other week) and an optimized dose (subcutaneously injected with 80mg of adalimumab every other week). The clinical remission rate, inflammatory and nutritional indicators, mucosal healing rate, endoscopic response rate at 12th week, risk of treatment failure and safety were compared between groups.Results There were 139 patients in the standard dose group and 53 in the optimized dose group. At 12 weeks, no significant difference was detected in the clinical remission rate (79.1% vs. 81.1%; RR, 0.97; 95% CI, 0.81–1.24; P = 0.842). In infliximab-exposed CD patients, the optimized dose of adalimumab provided a significantly higher clinical remission rate (76.9% vs. 44.4%; RR, 0.58; 95% CI, 0.37–0.88; P = 0.018) and lower risk of treatment failure (HR, 0.36; 95% CI, 0.14–0.97; P = 0.042), but not in infliximab-naïve CD patients. The incidence of adverse events was comparable between groups (32.1% vs. 30.9%, P = 0.864).Conclusions An optimized adalimumab dose does not provide additionally clinical benefits to infliximab-naïve CD patients, compared with a standard dose, but can increase the clinical remission rate and lower the risk of treatment failure in infliximab-exposed CD patients at 12 weeks, without increasing the incidence of adverse events.
CNBA: Coregulatory Network Builder and Analyzer
Authors: Banerjee Ayushman Kumar , Mal Chittabrata 
Published: May 2023

Abstract
Knowledge gained from coregulatory relationship studies can be used to develop drugs, modify treatment strategies, discover biomarkers, and so on. Proteins, RNAs, DNAs, transcription factors, and small molecules are commonly used to reveal the mechanisms of cellular systems in various contexts. Building and analyzing biomolecular networks helps in understanding complex biological systems. Although there are numerous tools for studying biological networks, tools for studying synergistic or coregulatory networks are limited. Therefore, we developed Coregulatory Network Builder and Analyzer (CNBA), a novel tool that uses network transformation (degree-preserving randomization) procedures based on prior bipartite relationship data among biomolecules to identify any correspondence between pairs of molecules under study. The tool identifies coregulatory or synergistic pairs and assigns each pair a coregulatory coefficient score. It performs an overrepresentation analysis on the pairs that have been identified as associated in order to add more biological context to the associated pairs identified. We have demonstrated the activities of the tool by a case study and described the advantages and limitations of it. CNBA's utility extends beyond computational biology, as it can be used in a variety of network analysis-based fields ranging from ecological research to social network analysis.
World Cafés as a participatory approach to understanding research agendas in primary care with underserved communities: reflections, challenges and lessons learned
Authors: McGrath Carmel , Kennedy Mari-Rose , Gibson Andy , Musse Samira , Kosar Zahra , Dawson Shoba 
Published: May 2023

Abstract
Background
Certain communities are underserved by research, resulting in lower inclusion rates, under researched health issues and a lack of attention to how different communities respond to health interventions. Racial and ethnic minority groups are often underserved by research and services. They experience health inequalities and face significant barriers to accessing health services. It is recognised that new approaches are needed to reach underserved communities and make and make research more relevant. The purpose of this work was to utilise World Cafés, a participatory method, to explore research agendas with diverse communities.
Methods
Two World Cafés were conducted as research agenda setting activities with individuals from minoritised ethnic communities in Bristol, UK. World Café 1 explored Black and Asian women’s perspectives about supporting mental health, World Café 2 with men from the Somali community, focussed on prostate cancer. Community members co-developed the focus and questions of each World Café and were also instrumental in recruiting individuals to the sessions and facilitating discussions, including translation. Audio and written records were made of the discussions and from these key issues about each topic were identified, and a visual representation of the discussion was also generated. These were shared with participants to check for accuracy.
Results
Community members identified a range of issues that are important to them in relation to mental health and prostate cancer, including barriers to help seeking and accessing primary and secondary care, ideas for service improvements and a need for health information that is accessible and culturally relevant.
Conclusions
World Cafés are a flexible method that can be successfully adapted for research agenda setting with individuals from racial and minoritised ethnic communities. The role of community members in co-developing the focus of sessions, recruiting community members and co-facilitating sessions is crucial to this success. The discussions at both World Cafés provided a rich insight into the experiences of participants in relation to the topics mental health and prostate cancer and identified issues that are important to these communities that will be followed-up with communities, researchers and clinicians to co-develop research and service improvement strategies.
Computational prediction of phytochemical inhibitors against the cap-binding domain of Rift Valley fever virus
Authors: Muralitharan Ishwarya , Sahoo Ajaya Kumar , Augusthian Priya Dharshini , Samal Areejit 
Published: May 2023

Abstract
Rift Valley fever is a zoonotic disease that can spread through livestock and mosquitoes, and its symptoms include retinitis, photophobia, hemorrhagic fever and neurological effects. The World Health Organization has identified Rift Valley fever as one of the viral infections that has potential to cause a future epidemic. Hence, efforts are urgently needed toward development of therapeutics and vaccine against this infectious disease. Notably, the causative virus namely, the Rift Valley fever virus (RVFV), utilizes the cap-snatching mechanism for viral transcription, rendering its cap-binding domain (CBD) as an effective antiviral target. To date, there are no published studies towards identification of potential small molecule inhibitors for the CBD of RVFV. Here, we employ a virtual screening workflow comprising of molecular docking and molecular dynamics (MD) simulation, to identify 5 potential phytochemical inhibitors of the CBD of RVFV. These 5 phytochemical inhibitors can be sourced from Indian medicinal plants, Ferula assa-foetida, Glycyrrhiza glabra and Leucas cephalotes, used in traditional medicine. In sum, the 5 phytochemical inhibitors of the CBD of RVFV identified by this purely computational study are promising drug lead molecules which can be considered for detailed experimental validation against RVFV infection.
Pharmacophore, atom-based 3D-QSAR modeling and binding mode analysis of QcrB inhibitors as potential tuberculosis agents
Authors: Sindhu Thangaraj , Rajamanikandan Sundarraj , Jeyakanthan Jeyaraman , Pal Debnath 
Published: May 2023

Abstract
QcrB is an essential subunit of cytochrome-bc1 complex and is anticipated as a therapeutic target for tuberculosis. In recent years, significant attempts have been made to develop different chemical classes of QcrB inhibitors. Among them, a series of 31 phenoxyalkylimidazoles (PABs) showed anti-tuberculosis activity with MIC90 values ranging from 0.10µM to 20µM were used to develop a pharmacophore and 3D-QSAR model. Five featured pharmacophore model, HHRRR, which consists of two hydrophobic regions (H) and three aromatic ring features (R), was chosen as the best-fitted model based on the highest survival score and molecular occupancy. The statistically significant 3D-QSAR model constructed using the HHRRR hypothesis possessed good predictive power with an excellent correlation coefficient (R2 = 0.9859) and cross-validation coefficient (Q2 = 0.8593). The contour map analysis provided crucial structural insights into the activity of active compounds. Furthermore, comparative binding mode analysis of a known clinical candidate, Q203, and the most active compound through induced fit docking approach revealed that these two compounds share a similar binding mode with the QP site of QcrB and form hydrogen bonds with the critical residue T313. Substitution of different chemical scaffolds at the R position of PABs would lead to developing potential QcrB inhibitors.