Frontiers in Molecular Biosciences最新文献

{"title":"Soft-sensor model development for CHO growth/production, intracellular metabolite, and glycan predictions.","authors":"George Liang, Sha Sha, Zhao Wang, Huolong Liu, Seongkyu Yoon","doi":"10.3389/fmolb.2024.1441885","DOIUrl":"10.3389/fmolb.2024.1441885","url":null,"abstract":"<p><p>Efficaciously assessing product quality remains time- and resource-intensive. Online Process Analytical Technologies (PATs), encompassing real-time monitoring tools and soft-sensor models, are indispensable for understanding process effects and real-time product quality. This research study evaluated three modeling approaches for predicting CHO cell growth and production, metabolites (extracellular, nucleotide sugar donors (NSD) and glycan profiles): Mechanistic based on first principle Michaelis-Menten kinetics (MMK), data-driven orthogonal partial least square (OPLS) and neural network machine learning (NN). Our experimental design involved galactose-fed batch cultures. MMK excelled in predicting growth and production, demonstrating its reliability in these aspects and reducing the data burden by requiring fewer inputs. However, it was less precise in simulating glycan profiles and intracellular metabolite trends. In contrast, NN and OPLS performed better for predicting precise glycan compositions but displayed shortcomings in accurately predicting growth and production. We utilized time in the training set to address NN and OPLS extrapolation challenges. OPLS and NN models demanded more extensive inputs with similar intracellular metabolite trend prediction. However, there was a significant reduction in time required to develop these two models. The guidance presented here can provide valuable insight into rapid development and application of soft-sensor models with PATs for ipurposes. Therefore, we examined three model typesmproving real-time product CHO therapeutic product quality. Coupled with emerging -omics technologies, NN and OPLS will benefit from massive data availability, and we foresee more robust prediction models that can be advantageous to kinetic or partial-kinetic (hybrid) models.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"11 ","pages":"1441885"},"PeriodicalIF":3.9,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11535473/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142582563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum: HPLC for at-line reaction monitoring and purification improves yield and purity of tRNA.","authors":"Polona Megušar, Ewen D D Calder, Tina Vodopivec Seravalli, Sergeja Lebar, Louise J Walport, Rok Sekirnik","doi":"10.3389/fmolb.2024.1507191","DOIUrl":"https://doi.org/10.3389/fmolb.2024.1507191","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.3389/fmolb.2024.1443917.].</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"11 ","pages":"1507191"},"PeriodicalIF":3.9,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11535852/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142582546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Functions of p120-catenin in physiology and diseases.","authors":"Xin Jin, Ting Lin, Yunjuan Wang, Xiaoqian Li, Yanhong Yang","doi":"10.3389/fmolb.2024.1486576","DOIUrl":"10.3389/fmolb.2024.1486576","url":null,"abstract":"<p><p>p120-catenin (p120) plays a vital role in regulating cell-cell adhesion at adherens junctions, interacting with the juxtamembrane domain (JMD) core region of E-cadherin and regulates the stability of cadherin at the cell surface. Previous studies have shown significant functions of p120 in cell-cell adhesion, tumor progression and inflammation. In this review, we will discuss recent progress of p120 in physiological processes and diseases, and focus on the functions of p120 in the regulation of cancer and inflammation.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"11 ","pages":"1486576"},"PeriodicalIF":3.9,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11532153/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142575601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of immune microenvironment subtypes and clinical risk biomarkers for osteoarthritis based on a machine learning model.","authors":"Bao Li, Yang Shen, Songbo Liu, Hong Yuan, Ming Liu, Haokun Li, Tonghe Zhang, Shuyuan Du, Xinwei Liu","doi":"10.3389/fmolb.2024.1376793","DOIUrl":"10.3389/fmolb.2024.1376793","url":null,"abstract":"<p><strong>Background: </strong>Osteoarthritis (OA) is a degenerative disease with a high incidence worldwide. Most affected patients do not exhibit obvious discomfort symptoms or imaging findings until OA progresses, leading to irreversible destruction of articular cartilage and bone. Therefore, developing new diagnostic biomarkers that can reflect articular cartilage injury is crucial for the early diagnosis of OA. This study aims to explore biomarkers related to the immune microenvironment of OA, providing a new research direction for the early diagnosis and identification of risk factors for OA.</p><p><strong>Methods: </strong>We screened and downloaded relevant data from the Gene Expression Omnibus (GEO) database, and the immune microenvironment-related genes (Imr-DEGs) were identified using the ImmPort data set by combining weighted coexpression analysis (WGCNA). Functional enrichment of GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted to explore the correlation of Imr-DEGs. A random forest machine learning model was constructed to analyze the characteristic genes of OA, and the diagnostic significance was determined by the Receiver Operating Characteristic Curve (ROC) curve, with external datasets used to verify the diagnostic ability. Different immune subtypes of OA were identified by unsupervised clustering, and the function of these subtypes was analyzed by gene set enrichment analysis (GSVA). The Drug-Gene Interaction Database was used to explore the relationship between characteristic genes and drugs.</p><p><strong>Results: </strong>Single sample gene set enrichment analysis (ssGSEA) revealed that 16 of 28 immune cell subsets in the dataset significantly differed between OA and normal groups. There were 26 Imr-DEGs identified by WGCNA, showing that functional enrichment was related to immune response. Using the random forest machine learning model algorithm, nine characteristic genes were obtained: <i>BLNK</i> (AUC = 0.809), <i>CCL18</i> (AUC = 0.692), <i>CD74</i> (AUC = 0.794), <i>CSF1R</i> (AUC = 0.835), <i>RAC2</i> (AUC = 0.792), <i>INSR</i> (AUC = 0.765), <i>IL11</i> (AUC = 0.662), <i>IL18</i> (AUC = 0.699), and <i>TLR7</i> (AUC = 0.807). A nomogram was constructed to predict the occurrence and development of OA, and the calibration curve confirmed the accuracy of these 9 genes in OA diagnosis.</p><p><strong>Conclusion: </strong>This study identified characteristic genes related to the immune microenvironment in OA, providing new insight into the risk factors of OA.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"11 ","pages":"1376793"},"PeriodicalIF":3.9,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11524973/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142557518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mutant ATRX: pathogenesis of ATRX syndrome and cancer.","authors":"Kejia Yuan, Yan Tang, Zexian Ding, Lei Peng, Jinghua Zeng, Huaying Wu, Qi Yi","doi":"10.3389/fmolb.2024.1434398","DOIUrl":"10.3389/fmolb.2024.1434398","url":null,"abstract":"<p><p>The transcriptional regulator ATRX, a genetic factor, is associated with a range of disabilities, including intellectual, hematopoietic, skeletal, facial, and urogenital disabilities. ATRX mutations substantially contribute to the pathogenesis of ATRX syndrome and are frequently detected in gliomas and many other cancers. These mutations disrupt the organization, subcellular localization, and transcriptional activity of ATRX, leading to chromosomal instability and affecting interactions with key regulatory proteins such as DAXX, EZH2, and TERRA. ATRX also functions as a transcriptional regulator involved in the pathogenesis of neuronal disorders and various diseases. In conclusion, ATRX is a central protein whose abnormalities lead to multiple diseases.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"11 ","pages":"1434398"},"PeriodicalIF":3.9,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11521912/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142544653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating molecular, biochemical, and immunohistochemical features as predictors of hepatocellular carcinoma drug response using machine-learning algorithms.","authors":"Marwa Matboli, Hiba S Al-Amodi, Abdelrahman Khaled, Radwa Khaled, Marwa Ali, Hala F M Kamel, Manal S Abd El Hamid, Hind A ELsawi, Eman K Habib, Ibrahim Youssef","doi":"10.3389/fmolb.2024.1430794","DOIUrl":"10.3389/fmolb.2024.1430794","url":null,"abstract":"<p><strong>Introduction: </strong>Liver cancer, particularly Hepatocellular carcinoma (HCC), remains a significant global health concern due to its high prevalence and heterogeneous nature. Despite the existence of approved drugs for HCC treatment, the scarcity of predictive biomarkers limits their effective utilization. Integrating diverse data types to revolutionize drug response prediction, ultimately enabling personalized HCC management.</p><p><strong>Method: </strong>In this study, we developed multiple supervised machine learning models to predict treatment response. These models utilized classifiers such as logistic regression (LR), k-nearest neighbors (kNN), neural networks (NN), support vector machines (SVM), and random forests (RF) using a comprehensive set of molecular, biochemical, and immunohistochemical features as targets of three drugs: Pantoprazole, Cyanidin 3-glycoside (Cyan), and Hesperidin. A set of performance metrics for the complete and reduced models were reported including accuracy, precision, recall (sensitivity), specificity, and the Matthews Correlation Coefficient (MCC).</p><p><strong>Results and discussion: </strong>Notably, (NN) achieved the best prediction accuracy where the combined model using molecular and biochemical features exhibited exceptional predictive power, achieving solid accuracy of 0.9693 ∓ 0.0105 and average area under the ROC curve (AUC) of 0.94 ∓ 0.06 coming from three cross-validation iterations. Also, found seven molecular features, seven biochemical features, and one immunohistochemistry feature as promising biomarkers of treatment response. This comprehensive method has the potential to significantly advance personalized HCC therapy by allowing for more precise drug response estimation and assisting in the identification of effective treatment strategies.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"11 ","pages":"1430794"},"PeriodicalIF":3.9,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11521808/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142544652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Cryogenic electron microscopy of infectious diseases.","authors":"Jiho Yoo","doi":"10.3389/fmolb.2024.1506197","DOIUrl":"10.3389/fmolb.2024.1506197","url":null,"abstract":"","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"11 ","pages":"1506197"},"PeriodicalIF":3.9,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11521902/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142544649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Bio-nanomaterials and systems for enhanced bioimaging in biomedical applications.","authors":"Sumin Park, Sudip Mondal","doi":"10.3389/fmolb.2024.1491376","DOIUrl":"https://doi.org/10.3389/fmolb.2024.1491376","url":null,"abstract":"","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"11 ","pages":"1491376"},"PeriodicalIF":3.9,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11518781/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142544648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Profiling of the serum MiRNAome in pediatric egyptian patients with wilms tumor.","authors":"Fatma S Mohamed, Deena Jalal, Youssef M Fadel, Samir F El-Mashtoly, Wael Z Khaled, Ahmed A Sayed, Mohamed A Ghazy","doi":"10.3389/fmolb.2024.1453562","DOIUrl":"https://doi.org/10.3389/fmolb.2024.1453562","url":null,"abstract":"<p><p>Wilms tumor (WT) is a pediatric kidney cancer associated with poor outcomes in patients with unfavorable histological features such as anaplasia. Small non-coding RNAs, such as miRNAs, are known to be involved in WT pathogenesis. However, research on the clinical potential of blood-based miRNAs is limited. This study aimed to profile aberrantly expressed miRNAs in WT serum samples, evaluate their potential to differentiate standard-risk patients with favorable histology from those with anaplastic WTs, and assess their clinical value as minimally invasive biomarkers for WT detection. The study used next-generation sequencing (NGS) to analyze miRNA expressions in serum samples from 37 Egyptian children, including 10 healthy individuals, 14 with non-anaplastic WTs (favorable histology FH-WTs), and 13 with anaplastic WTs (unfavorable histology UnFH-WTs). Functional enrichment analysis was conducted to identify critical pathways and biological processes affected by dysregulated miRNAs, and a network was created for the most promising miRNA-target interactions linked to WT. The study identified a distinct miRNA expression signature of 45 miRNAs (3 upregulated and 42 downregulated) in WT serum samples compared to healthy controls, with 29 miRNAs exclusively dysregulated in FH-WTs and 6 miRNAs dysregulated solely in UnFH-WTs. These dysregulated miRNAs displayed significant enrichment in cancer-related pathways, such as PI3K/AKT, FOXO, and MAPK signaling. In relation to WT clinicopathological features, decreased levels of hsa-miR-2355-3p showed a significant positive correlation with clinical stage (<i>r</i> = 0.6597, <i>p</i> = 0.0006) and WT metastasis (<i>r</i> = 0.439, <i>p</i> = 0.021). The ROC curve analysis revealed that multiple dysregulated miRNAs in WT, specifically hsa-miR-7-5p, hsa-miR-146a-5p, hsa-miR-378a-3p, and hsa-miR-483-5p, exhibited high diagnostic potential for WT, with AUC values exceeding 0.86. Among WT histopathology types, the hsa-miR-1180-3p showed a 2.3 log2fold difference in expression between UnFH-WTs and FH-WTs, indicating its potential as a biomarker with 92% sensitivity and 85% specificity for identifying UnFH-WTs. Its target genes were enriched in pathways related to cell division and cell cycle regulation. In conclusion, hsa-miR-1180-3p could be a reliable blood-based biomarker for distinguishing WT histopathological types, and further research is needed to validate its clinical value.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"11 ","pages":"1453562"},"PeriodicalIF":3.9,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11519528/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142544654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of potential bioactive phytochemicals for the inhibition of platelet-derived growth factor receptor β: a structure-based approach for cancer therapy.","authors":"Insan Habib, Md Nayab Sulaimani, Deeba Shamim Jairajpuri, Afzal Hussain, Taj Mohammad, Mohamed F Alajmi, Anas Shamsi, Md Imtaiyaz Hassan","doi":"10.3389/fmolb.2024.1492847","DOIUrl":"https://doi.org/10.3389/fmolb.2024.1492847","url":null,"abstract":"<p><p>Platelet-derived growth factor receptor beta (PDGFRβ) belongs to the receptor tyrosine kinase (RTK) protein family and is implicated in several disorders such as hematopoietic, glial, and soft-tissue cancer, non-cancerous disorders, including skeletal defects, brain calcification, and vascular anomalies. The research on small molecule inhibitors targeting PDGFRβ in cancer treatment has seen promising developments, but significant gaps remain. PDGFRβ, receptor tyrosine kinase, is overexpressed in various cancers and plays an important role in tumor progression, making it a potential therapeutic target. However, despite advances in identifying and characterizing PDGFRβ inhibitors, few have progressed to clinical trials, and the mechanistic details of PDGFRβ's interactions with small molecule inhibitors are still not fully understood. Moreover, the specificity and selectivity of these inhibitors remain challenging, as off-target effects can lead to unwanted toxicity. In this investigation, two compounds, Genostrychnine and Chelidonine, were discovered that help inhibit the kinase activity of PDGFRβ. These small molecules were identified by employing various parameters involved in the drug discovery process, such as Lipinski's rule of five (RO5), 2D similarity search and 3D pharmacophore-based virtual screening followed by MD simulation studies. The identified molecules were found to be effective and significantly bound with the PDGFRβ kinase domain. Overall, our findings demonstrate that these small drug-like compounds can be beneficial tools in studying the properties of PDGFRβ and can play a crucial role in the therapeutic development of cancers and other associated diseases.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"11 ","pages":"1492847"},"PeriodicalIF":3.9,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11518818/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142544650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}