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Identification of Proteins and Genes Associated with Hedgehog Signaling Pathway Involved in Neoplasm Formation Using Text-Mining Approach

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Big Data Mining and Analytics 2024年第1期7卷 107-130页

作者： Nadezhda Yu.Biziukova Sergey M.Ivanov Oga A.Tarasova Department of bioinformatics Institute of Biomedical ChemistryMoscow 119121Russia Department of bioinformatics Pirogov Russian National Research Medical UniversityMoscow 117997Russia

Analysis of molecular mechanisms that lead to the development of various types of tumors is essential for biology and medicine,because it may help to find new therapeutic opportunities for cancer treatment and cure including personalized treatment approaches.One of the pathways known to be important for the development of neoplastic diseases and pathological processes is the Hedgehog signaling pathway that normally controls human embryonic development.Systematic accumulation of various types of biological data,including interactions between proteins,regulation of genes transcription,proteomics,and metabolomics experiments results,allows the application of computational analysis of these big data for identification of key molecular mechanisms of certain diseases and pathologies and promising therapeutic targets.The aim of this study is to develop a computational approach for revealing associations between human proteins and genes interacting with the Hedgehog pathway components,as well as for identifying their roles in the development of various types of tumors.We automatically collect sets of abstract texts from the NCBI PubMed bibliographic database.For recognition of the Hedgehog pathway proteins and genes and neoplastic diseases we use a dictionary-based named entity recognition approach,while for all other proteins and genes machine learning method is used.For association extraction,we develop a set of semantic rules.We complete the results of the text analysis with the gene set enrichment analysis.The identified key pathways that may influence the Hedgehog pathway and their roles in tumor development are then verified using the information in the literature.

关键词： text-mining data mining Hedgehog pathway neoplastic processes enrichment analysis pathology molecularmechanisms

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Deciphering gastric inflammation-induced tumorigenesis through multi-omics data and AI methods

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Cancer Biology & Medicine 2024年第4期21卷 312-330页

作者： Qian Zhang Mingran Yang Peng Zhang Bowen Wu Xiaosen Wei Shao Li Institute for TCM-X MOE Key Laboratory of BioinformaticsBioinformatics DivisionBNRISTDepartment of AutomationTsinghua UniversityBeijing 100084China

Gastric cancer(GC), the fifth most common cancer globally, remains the leading cause of cancer deaths worldwide. Inflammation-induced tumorigenesis is the predominant process in GC development;therefore, systematic research in this area should improve understanding of the biological mechanisms that initiate GC development and promote cancer hallmarks. Here, we summarize biological knowledge regarding gastric inflammation-induced tumorigenesis, and characterize the multi-omics data and systems biology methods for investigating GC development. Of note, we highlight pioneering studies in multi-omics data and state-of-the-art network-based algorithms used for dissecting the features of gastric inflammation-induced tumorigenesis, and we propose translational applications in early GC warning biomarkers and precise treatment strategies. This review offers integrative insights for GC research, with the goal of paving the way to novel paradigms for GC precision oncology and prevention.

关键词： Gastric cancer inflammation-induced tumorigenesis multi-omics artificial intelligence network-based methods

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Interplant communication:an emerging battlefield in plant-aphid-virus interactions

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Science China(Life Sciences) 2024年第5期67卷 1069-1071页

作者： Yunjing Wang Qian Gong Yule Liu MOE Key Laboratory of bioinformatics and center for Plant Biology School of Life SciencesTsinghua UniversityBeijing 100084China Tsinghua-Peking center for Life Sciences Beijing 100084China

Plants constantly face threats from various organisms,including pathogens and herbivores.Among the pathogens,plant viruses are obligate intracellular parasites that infect plants and cause serious crop yield losses.

关键词： plant Plants communication

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Effect of heat-treatment on the surface properties of gallium phosphide nanosolids by Raman spectroscopy

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Rare Metals 2006年第3期25卷 253-259页

作者： ZHANG Zhaochun YUE Longyi GUO Jingkang School of Materials Science and Technology Shanghai University Shanghai 200072 China bioinformatics research center Shanghai University Shanghai 200072 China

Raman spectra of gallium phosphide （GAP） nanosolids （unheated and heat-treated at 598 and 723 K, respectively） were investigated. It was observed that both the longitudinal optical mode （LO） and the transverse optical mode （TO） displayed an asymmetry on the low-wavenumber side. The scattering bands were fitted to a sum of four Lorentzians which were assigned to the LO mode, surface phonon mode, TO mode, and a combination of Ga-O-P symmetric bending and sum band formed from the X-point TA ＋ LA phonons, respectively. Analysis of the characteristic of surface phonon mode revealed that the surface phonon peak of the GaP nanosolids could be confirmed. In the infrared spectrum of the GaP nanoparticles, we observed the bands on account of symmetric stretching and bending of PO2, as well as stretching of Ga-O The Raman scattering intensity arising from the Ga-O-P linkages increased as increasing the heat-treatment temperature.

关键词： semiconductor materials nanosolids Raman spectrum gallium phosphide

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scEpiTools: a database to comprehensively interrogate analytic tools for single-cell epigenomic data

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Journal of Genetics and Genomics 2024年第4期51卷 462-465页

作者： Zijing Gao Xiaoyang Chen Zhen Li Xuejian Cui Qun Jiang Keyi Li Shengquan Chen Rui Jiang Ministry of Education Key Laboratory of bioinformatics Bioinformatics Division at the Beijing National Research Center for Information Science and TechnologyCenter for Synthetic and Systems BiologyDepartment of AutomationTsinghua UniversityBeijing 100084China School of Mathematical Sciences and LPMC Nankai UniversityTianjin 300071China

Recent advances in single-cell sequencing technologies provide significant implications for understanding cellular heterogeneity,developmental biology,and disease mechanisms.To fully exploit the potential of these data,numerous tools have been proposed for upstream and downstream analyses.In the the single-cell RNA sequencing(scRNA-seq)community,scRNA-tools(Zappia et al.,2018)was proposed to help researchers navigate the plethora of tools by category.Since its inception,scRNA-tools has been widely used and its updated version further reveals trends in the field with over 1000 collected tools(Zappia and Theis,2021),providing a valuable guidance in selecting tools for analyses.

关键词： analytic selecting Tools

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The emerging role of mesenchymal stem cell-derived extracellular vesicles to ameliorate hippocampal NLRP3 inflammation induced by binge-like ethanol treatment in adolescence

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Neural Regeneration research 2025年第4期20卷 1153-1163页

作者： Susana Mellado María JoséMorillo-Bargues Carla Perpiñá-Clérigues Francisco García-García Victoria Moreno-Manzano Consuelo Guerri María Pascual Department of Physiology School of Medicine and DentistryUniversity of ValenciaValenciaSpain bioinformatics and Biostatistics Unit Príncipe Felipe Research CenterValenciaSpain Neuronal and Tissue Regeneration Laboratory Príncipe Felipe Research CenterValenciaSpain

Our previous studies have reported that activation of the NLRP3(NOD-,LRR-and pyrin domain-containing protein 3)-inflammasome complex in ethanol-treated astrocytes and chronic alcohol-fed mice could be associated with neuroinflammation and brain damage.Mesenchymal stem cell-derived extracellular vesicles(MSC-EVs)have been shown to restore the neuroinflammatory response,along with myelin and synaptic structural alterations in the prefrontal cortex,and alleviate cognitive and memory dysfunctions induced by binge-like ethanol treatment in adolescent mice.Considering the therapeutic role of the molecules contained in mesenchymal stem cell-derived extracellular vesicles,the present study analyzed whether the administration of mesenchymal stem cell-derived extracellular vesicles isolated from adipose tissue,which inhibited the activation of the NLRP3 inflammasome,was capable of reducing hippocampal neuroinflammation in adolescent mice treated with binge drinking.We demonstrated that the administration of mesenchymal stem cell-derived extracellular vesicles ameliorated the activation of the hippocampal NLRP3 inflammasome complex and other NLRs inflammasomes(e.g.,pyrin domain-containing 1,caspase recruitment domain-containing 4,and absent in melanoma 2,as well as the alterations in inflammatory genes(interleukin-1β,interleukin-18,inducible nitric oxide synthase,nuclear factor-kappa B,monocyte chemoattractant protein-1,and C–X3–C motif chemokine ligand 1)and miRNAs(miR-21a-5p,miR-146a-5p,and miR-141-5p)induced by binge-like ethanol treatment in adolescent mice.Bioinformatic analysis further revealed the involvement of miR-21a-5p and miR-146a-5p with inflammatory target genes and NOD-like receptor signaling pathways.Taken together,these findings provide novel evidence of the therapeutic potential of MSC-derived EVs to ameliorate the hippocampal neuroinflammatory response associated with NLRP3 inflammasome activation induced by binge drinking in adolescence.

关键词： adolescence binge-like ethanol treatment extracellular vesicles hippocampus mesenchymal stem cells neuroinflammation NOD-,LRR-and pyrin domain-containing protein 3(NLRP3)

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Cognitive impairment in cerebral small vessel disease induced by hypertension

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Neural Regeneration research 2024年第7期19卷 1454-1462页

作者： Weipeng Wei Denglei Ma Lin Li Lan Zhang Department of Pharmacy Xuanwu Hospital of Capital Medical UniversityBeijingChina Beijing Geriatric Medical research center Beijing Engineering Research Center for Nervous System DrugsNational Center for Neurological DisordersNational Clinical Research Center for Geriatric DiseasesBeijingChina

Hypertension is a primary risk factor for the progression of cognitive impairment caused by cerebral small vessel disease,the most common cerebrovascular disease.Howeve r,the causal relationship between hypertension and cerebral small vessel disease remains unclear.Hypertension has substantial negative impacts on brain health and is recognized as a risk factor for cerebrovascular disease.Chronic hypertension and lifestyle factors are associated with risks for stro ke and dementia,and cerebral small vessel disease can cause dementia and stroke.Hypertension is the main driver of cerebral small vessel disease,which changes the structure and function of cerebral vessels via various mechanisms and leads to lacunar infarction,leukoaraiosis,white matter lesions,and intracerebral hemorrhage,ultimately res ulting in cognitive decline and demonstrating that the brain is the to rget organ of hypertension.This review updates our understanding of the pathogenesis of hypertensioninduced cerebral small vessel disease and the res ulting changes in brain structure and function and declines in cognitive ability.We also discuss drugs to treat cerebral small vessel disease and cognitive impairment.

关键词： blood-brain barrier cerebral small vessel disease cognitive impairment dementia endothelial dysfunction enlarged perivascular space hypertension lacunar infarction neuroinflammation treatment white matter high signal intensity

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Curation,nomenclature,and topological classification of receptor-like kinases from 528 plant species for novel domain discovery and functional inference

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Molecular Plant 2024年第4期17卷 658-671页

作者： Qian Liu Qiong Fu Yujie Yan Qian Jiang Longfei Mao Long Wang Feng Yu Heping Zheng State Key Laboratory of Chemo/Biosensing and Chemometrics Hunan University College of BiologyChangshaHunan 410082China bioinformatics center Hunan University College of BiologyChangshaHunan 410082China

Receptor-like kinases(RLKs)are the most numerous signal transduction components in plants and play important roles in determining how different plants adapt to their ecological environments.research on RLKs has focused mainly on a small number of typical RLK members in a few model plants.There is an urgent need to study the composition,distribution,and evolution of RLKs at the holistic level to increase our understanding of how RLKs assist in the ecological adaptations of different plant species.In this study,we collected the genome assemblies of 528 plant species and constructed an RLK dataset.Using this dataset,we identified and characterized 524948 RLK family members.Each member underwent systematic topological classification and was assigned a gene ID based on a unified nomenclature system.Furthermore,we identified two novel extracellular domains in some RLKs,designated Xiao and Xiang.Evolutionary analysis of the RLK family revealed that the RLCK-XVII and RLCK-XII-2 classes were present exclusively in dicots,suggesting that diversification of RLKs between monocots and dicots may have led to differences in downstream cytoplasmic responses.We also used an interaction proteome to help empower data mining for inference of new RLK functions from a global perspective,with the ultimate goal of understanding how RLKs shape the adaptation of different plants to the environments/ecosystems.The assembled RLK dataset,together with annotations and analytical tools,forms an integrated foundation of multiomics data that is publicly accessible via the metaRLK web portal(http://metaRLK.biocloud.top).

关键词： RLK RLCK domain signaling pathway receptor-protein interactions

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Synthesis of boron nitride nanorod and its performance as a metalfree catalyst for oxidative desulfurization of diesel fuel

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Chinese Journal of Chemical Engineering 2024年第4期68卷 120-132页

作者： Tanaz Ghanadi Gholamreza Moradi Alimorad Rashidi Catalyst research center Faculty of Chemical and Petroleum EngineeringRazi UniversityKermanshahIran Nanotechnology research center Research Institute of Petroleum Industry(RIPI)TehranIran

In order to reduce the sulfur compounds in diesel fuel,boron nitride(BN)has been used as a novel metal-free catalyst in the present research.This nanocatalyst was synthesized via template-free approach followed by heating treatment at 900℃ in nitrogen atmosphere that the characteristics of the sample were identified by the X-ray diffraction,Fourier-transform infrared spectroscopy,Raman spectroscopy,field emission scanning electron microscopy,transmission electron microscopy,atomic force microscopy,and N2 adsorption-desorption isotherms.The results of structural and morphological analysis represented that BN has been successfully synthesized.The efficacy of the main operating parameters on the process was studied by using response surface methodology based on the Box-Behnken design method.The prepared catalyst showed high efficiency in oxidative desulfurization of diesel fuel with initial sulfur content of 8040 mg·kg^(-1)S.From statistical analysis,a significant quadratic model was obtained to predict the sulfur removal as a function of efficient parameters.The maximum efficiency of 72.4%was achieved under optimized conditions at oxidant/sulfur molar ratio of 10.2,temperature of 71℃,reaction time of 113 min,and catalyst dosage of 0.36 g.Also,the reusability of the BN was studied,and the result showed little reduction in activity of the catalyst after 10 times regeneration.Moreover,a plausible mechanism was proposed for oxidation of sulfur compounds on the surface of the catalyst.The present study shows that BN materials can be selected as promising metal-free catalysts for desulfurization process.

关键词： Desulfurization Boron nitride(BN)nanostructure Experimental design BoxeBehnken

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Integrated analysis of public datasets for the discovery and validation of survival-associated genes in solid tumors

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The Innovation 2024年第3期5卷 129-137页

作者： Balázs Gyorffy Department of Biophysics Medical SchoolUniversity of Pecs7624 PecsHungary Department of bioinformatics Semmelweis University1094 BudapestHungary Cancer Biomarker research Group Institute of Molecular Life SciencesHUN-REN Research Centre for Natural Sciences1117 BudapestHungary

Identifying genes with prognostic significance that can act as biomarkers in solid tumors can help stratify patients and uncover novel therapy targets.Here,our goal was to expand our previous ranking analysis of survival-associated genes in various solid tumors to include colon cancer specimens with available transcriptomic and clinical data.A Gene Expression Omnibus search was performed to identify available datasets with clinical data and raw gene expression measurements.A combined database was set up and integrated into our Kaplan-Meier plotter,making it possible to identify genes with expression changes linked to altered survival.As a demonstration of the utility of the platform,the most powerful genes linked to overall survival in colon cancer were identified using uni-and multivariate Cox regression analysis.The combined colon cancer database includes 2,137 tumor samples from 17 independent cohorts.The most significant genes associated with relapse-free survival with a false discovery rate below 1%in colon cancer carcinoma were RBPMS(hazard rate[HR]=2.52),TIMP1(HR=2.44),and COL4A2(HR=2.36).The three strongest genes associated with shorter survival in stage II colon cancer include CSF1R(HR=2.86),FLNA(HR=2.88),and TPBG(HR=2.65).In summary,a new integrated database for colon cancer is presented.A colon cancer analysis subsystem was integrated into our Kaplan-Meier plotter that can be used to mine the entire database(https://***).The portal has the potential to be employed for the identification and prioritization of promising biomarkers and therapeutic target candidates in multiple solid tumors including,among others,breast,lung,ovarian,gastric,pancreatic,and colon cancers.

关键词： colon tumors analysis

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