bluuebunny/crossref_metadata_2025_split huggingface dataset:
The combined application of Hordeum vulgare and gut microbiota against non-alcoholic fatty liver disease via network pharmacology approach
Authors: Lee Su-Been , Gupta Haripriya , Min Byeong-Hyun , Ganesan Raja , Sharma Satya Priya , Won Sung-Min , Jeong Jin-Ju , Cha Min-Gi , Kwon Goo-Hyun , Jeong Min-Kyo , Hyun Ji-Ye , Eom Jung-A , Park Hee-Jin , Yoon Sang-Jun , Choi Mi-Ran , Kim Dong Joon , Oh Ki-Kwang , Suk Ki-Tae 
Published: October 2022

Abstract
Non-alcoholic fatty liver disease (NAFLD) is an initial etiology to be developed steatosis, liver fibrosis, cirrhosis, and even hepatocellular carcinoma. However, the noticeable therapeutics were not elucidated completely to dampen the progressive rate involved in NAFLD. In the incomplete project, we combined secondary metabolites (SMs) from gut microbiota (GM) and Hordeum vulgare (HV) as a representative grain with potent NAFLD to exert combinatorial effects via network pharmacology. Hence, we retrieved the SMs of HV from NPASS (Natural product Activity & Species Source Database) and SMs of GM from gutMGene database. Then, targets associated with SMs were identified from both SEA (Similarity Ensemble Approach) and STP (SwissTargetPrediction). The crucial overlapping targets were identified on NAFLD-related targets through Ven diagram plotter. We constructed the protein-protein interaction (PPI) network from the crucial targets and built a bubble plot to identify a key mechanism on NAFLD. Also, we analyzed microbiota or barley – signaling pathways – targets – metabolites (MBSTM) in aspects of combinatorial approach (HV, and GM). To be confirmed a significant SM against NAFLD, we performed Molecular Docking (MD) with Autodock 1.5.6 to verify the affinity between SMs and targets. Finally, drug-likeness and toxicity properties of key SMs were validated via SwissADME and ADMETlab platform. The number of 31 core targets was analyzed by PPI network, the result of which represented JUN as a key target on NAFLD. The key SM bound stably to JUN were Tryptanthrin from HV. On a bubble plot, we identified that Apelin signaling pathway might be an inhibitive mechanism to relieve NAFLD in the combinatorial approach. On the holistic viewpoints, we analyzed MBSTM to obtain components associated with Apelin signaling pathway. As a result, we found the primary GM to fight NAFLD: Microbiota (Eubacterium limosum; Eggerthella sp. SDG-2; Alistipes indistinctus YIT 12060; Odoribacter laneus YIT 12061; Paraprevotella clara YIT 11840; Paraprevotella xylaniphila YIT 11841). The MD provided what the key SM (Dihydroglycitein, 1,3-Diphenylpropan-2-ol, and Acetic) is on each target (HDAC5, NOS1, and NOS2) related directly to Apelin signaling pathway. Overall, these results suggest that combinatorial application could be an effective tactic for ameliorating NAFLD.
Kinetic study on oxidative bromination of 2,6-dichlorotoluene to 2,6-dichlorobenzyl bromide in a microchannel reactor under light irradiation
Authors: Xiao Minghui , Liu Lin , Wang Lei , Zhang Hong-Yu , Han Yaping , Zhang Yuecheng , Zhao Jiquan 
Published: October 2022

Abstract
2,6-dichlorobenzyl bromide (DCBB) is an important drug intermediate for the preparation of antibacterial and antitumor agents. DCBB was prepared by the photocatalytic benzylic bromination of 2,6-dichlorotoluene (DCT) with hydrogen peroxide and hydrobromic acid as bromine source in a microchannel reactor, which belongs to a green and safe, economical and environmentally friendly process. Herein, the work focused on the investigation of kinetics of oxidative bromination of DCT to DCBB, and a kinetic model for this process was proposed. A series of kinetic data were obtained under kinetically controlled conditions by eliminating the mass transfer effects of liquid-liquid phases, and the experimental data were fitted nonlinearly using Matlab software. The results showed that the calculated values based on the kinetic model were in good agreement with the empirical values, and the preexponential factor and activation energy were 635.3 and 24.0 KJ/mol, respectively, and high concentration of DCT inhibit the response.
Evaluation of Current Clinical Research Spectrum of Sickle Cell Anemia to Approach New Innovative Developmental Techniques for Enhancing Sudanese Health Systems
Authors: Salih Karimeldin Mohamed Ali , Saad Atif Ahmed , Eldouch Widad Mohamed , Mohamed Hiba Karimeldin , Alfaifi Jaber , Andarawi Mohamed O , Elshayeb Ayman A. 
Published: October 2022

Abstract

Background Sickle cell Anemia and/or Disease (SCA/SCD) is an autosomal recessive disease leading to abnormal hemoglobin with global prevalence in general and tribal burden in sub-Saharan Africa particularly. Methods Recent patients’ assessments were done using routine diagnostic protocols for SCA monitoring and manifestations. Insight of the physicians towards innovative techniques at the molecular level were done to enhance medical performance of the disease investigations. The online questionnaire showed the response and acceptance levels of the physicians to introduced innovative techniques in integration with current clinical and laboratory’s spectrums. Data interpretation and statistical analysis were done using IBM-SPSS ver 25 and MS. Excel 2019. Results Clinical manifestation showed painful crises, (Hand and food syndrome) and enuresis were observed in more than half of the patients, while stroke observed only in 5.5%. A strong association was observed in males regarding Hb vs RBC and MCV vs HbA2.However. females show an association between MCV vs HbA2 only. SCA current spectrum include CBC, BF and Solubility Sickling Test showed significant results in Hemoglobin P < 0.05 and Strong association was observed between Hb vs RBC, MCV vs HbA2 for males and MCV vs HbA2 for female only. Polymerase Chain Reaction (PCR) was introduced to detect inherited polymorphic traits in infants and parents beside the flow cytometry gave a detailed informatic image for the up normal blood cells shape and amounts comparing with normal ones. The high response of the online questionnaire (100%) showed the attitude of doctors and related staff accepting innovative techniques for enhancing current health system. Conclusions Although the current clinical and laboratory diagnostic protocols are effective for diagnosing SCA, the follow-up and treatment but the approach of innovative techniques is highly demanded for detecting un-seen symptoms and hidden polymorphic traits, beside monitoring all patients with including other family members.
Stigma Experienced by Patients Who Recovered from COVID-19 in the Post- Vaccination Period: Prevalence, Severity and Associated Factors
Authors: Techapoonpon Kamolvisa , Kerdchareon Nitchawan , Polruamngern Nongnuch , Chalermrungroj Teeraphan , Srikhamdokk Orranee , Matangkarat Premyuda 
Published: October 2022

Abstract
Purpose: This study aimed to estimate the prevalence and severity level of stigma experienced by patients who recovered from COVID-19 in the post-vaccination period and to explore associated factors.
Methods: This study consisted of two phases. The first phase involved the translation and validation of the COVID-19-related stigma questionnaire (15 items). The second phase was a questionnaire-based cross-sectional survey conducted between January and February 2022. Questionnaires regarding stigma, negative emotions (Depression Anxiety Stress Scale-21), and personal and admission information were given to patients who recovered from COVID-19 in Thailand (N = 354).
Results: The prevalence of stigma among patients who recovered from COVID-19 was 50.8%. Slight, moderate, and high stigma levels were reported by 40.7%, 9.3%, and 0.8% of the total participants, respectively. Our study found that admission duration and recovery duration were inversely related to stigma. Whereas depression, anxiety and stress were directly correlated with stigma. Other associated factors included age, income and education level.
Conclusion: Social stigma related to COVID-19 existed even after vaccination and still took a toll on mental health. Stigma might decrease through time in patients who recovered from COVID-19, but not completely disappear. Our findings suggested providing appropriate assessment and help to patients who recovered from COVID-19, especially during the initial stage of their return to the community.
Study on Pillar Design for Longwall Mining under Weak Immediate Roof and Floor Strata in Indonesia
Authors: Hashikawa Hiroto , Pisith Mao , Sasaoka Takashi , Hamanaka Akihiro , Shimada Hideki , Batsaikhan Ulaankhuu , Oya Jiro 
Published: October 2022

Abstract
More than 99% of coal mining in Indonesia is open-pit mining. Nowadays, the adoption of the underground coal mining method is discussed to extend coal production due to the increasing demand for coal. However, the geological conditions in Indonesia are very weak compared to the U.S., Europe, and Australia where the longwall mining method is often applied. Especially, the mechanical properties of immediate roof/floor in shallow depth are weaker than those of coal. Therefore, the control measures to maintain the stability around the developing area should be discussed for the safe longwall mining operation. This study discusses the design of safety pillar width in longwall mining under weak geological conditions by using FLAC3D. It is found that the conventional equations for the determination of the pillar width, Obert-Duvall, Holland-Gaddy, and Bieniawski equations, can be adopted to maintain the stability of the pillar itself, but are not suitable for the stability of the longwall face because of the influence on the neighboring panel extraction. Additionally, the increase of the pillar width can significantly reduce the fracture zone around the longwall face while increasing the setting load of the shield support can slightly improve the stability. The pillar design needs to be considered not only the pillar strength but also the stability of the longwall face under the weak geological conditions in Indonesia.
Uncertainty Driven Dynamics for Active Learning of Interatomic Potentials
Authors: Kulichenko Maksim , Barros Kipton , Lubbers Nicholas , Li Ying Wai , Messerly Richard , Tretiak Sergei , Smith Justin , Nebgen Benjamin 
Published: October 2022

Abstract
Machine learning (ML) models, if trained to datasets of high-fidelity quantum simulations, produce accurate and efficient interatomic potentials. Active learning (AL) is a powerful tool to iteratively generate diverse datasets. In this approach, the ML model provides an uncertainty estimate along with its prediction for each new atomic configuration. If the uncertainty estimate passes a certain threshold, then the configuration is included in the dataset. A key challenge in this process is locating structures for which the model lacks underlying training data. Here, we develop a strategy to more rapidly discover configurations that meaningfully augment the training dataset. The approach, uncertainty driven dynamics for active learning (UDD-AL), modifies the potential energy surface used in molecular dynamics simulations to favor regions of configuration space for which there is large model uncertainty. Performance of UDD-AL is demonstrated for two challenging AL tasks: sampling the conformational space of glycine and sampling the promotion of proton transfer in acetylacetone. The method is shown to efficiently explore chemically relevant configuration space, which may be inaccessible using regular dynamical sampling at target temperature conditions.
IL-6 up-regulates the expression of IL-6R through JAK2/STAT3 signaling pathway to promote HCC progression
Authors: Song Li , Xu Ruyue , Cai Wenpeng , Liang Jiaojiao , Cao Niandie , Gao Jiafeng , Tang Xiaolong 
Published: October 2022

Abstract
Background

The progression of hepatocellular carcinoma (HCC) involves multi-factor, multi-step interactions. It has been reported that the high expression of interleukin-6 receptor (IL-6R) plays an important role in the occurrence and development of tumors, but the regulation mechamismof IL-6R expression and its function in HCC have not been adequately reported.

Methods

Western Blot was used to evaluate the phosphorylation of key kinases in JAK2/STAT3 pathway and the protein expression levels of related proliferative molecules, migration molecules and apoptotic molecules. The anti-apoptosis, migration and proliferation abilities of cells of each group were analyzed using JC-1 measures cell apoptosis, EdU method to detect cell apoptosis, clone formation experiment and Transwell.

Result

In the study, we found that the high expression of IL-6R enhance the proliferation and migration of the cells and inhibited cell apoptosis. IL-6R expression was upregulated after the activation of the Janus kinase (JAK) signaling pathway by interleukin-6 (IL-6).

Conclusions

IL-6 regulates IL-6R expression through JAK2/STAT3 signaling pathway, thereby promoting the progression of HCC. The result are expected to provide experimental basis for IL-6R as a potential therapeutic target for HCC.
Blood RNA-Seq profiling reveals a set of circular RNAs differentially expressed in frail individuals
Authors: Iparraguirre Leire , Alberro Ainhoa , Iñiguez Saioa GS , Muñoz-Culla Maider , Vergara Itziar , Matheu Ander , Otaegui David 
Published: October 2022

Abstract
Background:
Frailty is an intermediate and reversible geriatric syndrome that often precedes dependence. Therefore, its identification is essential to prevent dependence. Several molecules have been proposed as biomarkers of frailty, but none of them have reached clinical practice. Recently, circular RNAs have emerged as new non-coding RNAs. Their regulatory role together with their high stability in biofluids makes them good candidates as biomarkers for various processes, but, to date, no study has characterized the expression of circRNA in frailty.
Results:
We studied RNA from leukocytes of 35 frails and 35 robust individuals. After RNA-Sequencing, circRNA detection was performed by CIRI2 and Circexplorer2 and differential expression analysis by DESeq2. Validation was performed by Quantitative-PCR. Linear Discriminant Analysis was performed to determine the best circRNA combination to discriminate frail from robust. In addition, CircRNA candidates were studied in 13 additional elder donors before and after a 3-month physical intervention. We found 89 differentially expressed circRNAs (p-value<0.05, FC>|1.5|) with frailty. Upregulation of hsa_circ_0007817, hsa_circ_0101802 and hsa_circ_0060527 in frail individuals was validated. The combination of hsa_circ_0079284, hsa_circ_0007817 and hsa_circ_0075737 levels showed a great biomarker value with a 95.9% probability of correctly classifying frail and robust individuals. Moreover, hsa_circ_0079284 levels decreased after physical intervention in concordance with an improvement in frailty scores.
Conclusions:
This work describes for the first time a different expression pattern of circular RNA (circRNAs) between frail and robust individuals. Moreover, the level of some circRNAs is modulated after a physical intervention. These results suggest that they could be used as minimally invasive biomarkers of frailty.
LncTUG1 contributes to the progression of hepatocellular carcinoma via the miR-144-3p/RRAGD axis and mTOR/S6K pathway
Authors: Chen Weixi , Bai Zekun , Bai Wen , Wang Wei , Guo Jiapei , Guo Mengnan , Sai Yingying , Shi Jun , Wu Jinghua 
Published: October 2022

Abstract
Background

Hepatocellular carcinoma (HCC) is a symptomatic disease involed multi-stage program. Here, we elucidated the molecular mechanism of LncTUG1 in the regulation of HCC evolvement. And that may in all likelyhood supply a innovative latent target for HCC’s diagnoses and prognosis.

Methods

LncRNA TUG1, miR-144-3p, RRAGD and mTOR signaling pathway were screened as target genes in the database, and their expression levels at the cytological level were verified utilized qRT-PCR, Western Blot and immunohistochemistry. Then, we adopted CCK-8, Transwell and flow cytometry assays to estimate cell proliferation, invasion and apoptosis. By use of luciferase reporter assay, the relationships of LncRNA TUG1, miR-144-3p and RRAGD was confirmed. In addition, the LncRNA TUG1-miR-144-3p-RRAGD-mTOR signaling pathway in HCC cells was verified adopted rescue experiment and confirmed by xenotransplantation animal experiment

Results

LncTUG1 in HCC tissues from three databases were identified and further verified through qRT-PCR in HCC cells (Huh7, Hep3B). Knockdown the LncTUG1 could increase apoptosis and inhibite invasion and proliferation in HCC cells. Using inhibitors and activators of the mTOR/S6K pathway, LncTUG1 was confirmed to regulate HCC progression by the mTOR/S6K pathway. Luciferase reporter assay demonstrated that TUG1 negatively regulates miR-144-3p. Furthermore, miR-144-3p negativly regulates RRAGD by way of interacting with the 3’UTR of the RRAGD mRNA in HCC utilized luciferase reporter assay. In vivo, we also discovered that neoplasm weight and tumor volume reduced significantly in subcutaneous xenograft nude mouse models derived from sh-LncTUG1-expressing Huh7 cells. And the expressions of p-mTOR, p-S6K and RRAGD were decreased obviously while the miR144-3p increased in subcutaneous xenograft nude mouse models.

Conclusions

In a word, the research suggests that LncTUG1 targets miR-144-3p while miR-144-3p binds to RRAGD mRNA, which induces mTOR/S6K pathway activation and promotes the progression of HCC.
Development of a necroptosis-related gene signature and the immune landscape in ovarian cancer
Authors: Nie Sipei , Ni Na , Chen Ningxin , Gong Min , Feng Ercui , Liu Jinhui , Liu Qiaoling 
Published: October 2022

Abstract
Background: Necroptosis is a novel type of programmed cell death distinct from apoptosis. However, the role of necroptosis in ovarian cancer (OC) remains unclear. The present study tried to investigate the prognostic value of necroptosis‐related genes (NRGs) and the immune landscape in OC.
Methods: The gene expression profiling and clinical information were downloaded from the TCGA and GTEx databases. Differentially expressed NRGs (DE-NRGs)were identified. The regression analyses were conducted to screen the prognostic NRGs and construct the predictive risk model. Patients were then divided into high- and low-risk groups, and the GO and KEGG analyses were performed to explore bioinformatics functions between the two groups. Subsequently, the risk level and immune status correlations were assessed through the ESTIMATE and CIBERSORT algorithms. The tumor mutation burden (TMB)and the drug sensitivity were also analyzed based on the two-NRG signature in OC.
Results: Totally 42 DE-NRGs were identified in OC. The regression analyses screened out two NRGs (MAPK10 and STAT4) with prognostic values for overall survival. The ROC curve showed a better predictive ability in five-year OS using the risk score. Immune-related functions were significantly enriched in the high- and low-risk group. Macrophages M1, T cells CD4 memory activated, T cells CD8 and T cells regulatory infiltration immune cells were associated with the low-risk score. The lower tumor microenvironment score was demonstrated in the high-risk group. Patients with lower TMB in the low-risk group showed a better prognosis, and a lower TIDE score suggested a better immune checkpoint inhibitor response in the high-risk group. Besides, cisplatin and paclitaxel were found more sensitive in the low-risk group.
Conclusions: MAPK10 and STAT4 can be important prognosis factors in OC, and the two-gene signature performs well in predicting survival outcomes. Our study provided novel ways of OC prognosis estimation and potential treatment strategy.
Isolation, identification, and growth-promotion function of Streptomyces sp. in wetland rhizosphere
Authors: Zhang Hong , Bai Xue , Han Yujie , Han Lizhen 
Published: October 2022

Abstract
Wetlands are the most biologically diverse ecosystems on Earth. The isolation of Streptomyces strains from wetlands is helpful to study their diversity and functions in such habitats. In this study, six strains of Streptomyces were isolated from the rhizosphere soil of three plant species in Huaxi Wetland of Guiyang and were identified as Streptomyces galilaeus, S. avidinii, S. albogriseolus, S. hydrogenans, S. spororaveus, and S. cellulosae, respectively. The six strains all solubilized phosphate, fixed nitrogen, and produced ACC deaminase and siderophores, and four strains also secreted indole-3-acetic acid. The six strains grew well in the ranges of 0%–3% NaCl, 0%–25% PEG, and pH 5.0–10.0, which showed that the screened strains were tolerant to certain degrees of salinity, drought, and acidic/alkaline pH stress. In addition, the S. avidinii WL3 and S. cellulosae WL9 strains (especially the former) significantly promoted seed germination of mung bean, pepper, and cucumber. A pot experiment further showed that WL3 significantly promoted the growth of cucumber seedlings compared with that of the control, with plant height, root length, lateral root number, and fresh weight increased by 104.99%, 49.99%, 94.12%, and 82.86%, respectively. Thus, strains of six species of Streptomyces with multiple plant growth-promoting characteristics were isolated from the wetland. These results lay a foundation for their potential use as microbial agents and seed-coating treatments.
Status of Deforestation of Madagascar
Authors: Suzzi-Simmons Amanda 
Published: October 2022

Abstract
Several studies have reported tree cover loss at an unprecedented rate in Madagascar because of human population expansion which affects biodiversity, ecosystems, and weather patterns. Here we examine deforestation in Madagascar over the past 20 years. Results from time-series analysis of Landsat images empirically show that Madagascar lost 4.36 million hectares of tree cover, equivalent to a 25% decrease in tree cover since 2000, and 2.14 gigatonnes of CO2e – carbon dioxide equivalent greenhouse gas emissions. Deforestation will continue to impact Madagascar's flora and fauna, increasing rates of extinction.
Power Analysis for Causal Discovery
Authors: Kummerfeld Erich , Williams Leland , Ma Sisi 
Published: October 2022

Abstract
Causal discovery algorithms have the potential to impact many fields of science. However, substantial foundational work on the statistical properties of causal discovery algorithms is still needed. This paper presents what is to our knowledge the first method for conducting power analysis for causal discovery algorithms. The power sample characteristics of causal discovery algorithms typically cannot be described by a closed formula, but we resolve this problem by developing a new power sample analysis method based on standardized in silico simulation experiments. Our procedure generates data with carefully controlled statistical effect sizes in order to enable an accurate numerical power sample analysis. We present that method, apply it to generate an initial power analysis table, provide a web interface for searching this table, and show how the table or web interface can be used to solve several types of real world power analysis problems, such as sample size planning, interpretation of results, and sensitivity analysis.