Identification and validation of a novel autoantibody biomarker panel for differential diagnosis of pancreatic ductal adenocarcinoma by Metoboroghene O. Mowoe, Metoboroghene O. Mowoe, Hisham Allam, Joshua Nqada, Marc Bernon, Karan Gandhi, Sean Burmeister, Urda Kotze, Miriam Kahn, Christo Kloppers, Suba Dharshanan, Zafirah Azween, Pamela Maimela, Paul Townsend, Eduard Jonas, Jonathan M. Blackburn, Jonathan M. Blackburn

“…Autoantibodies (AAbs) in principle make attractive biomarkers as they arise early in disease, report on disease-associated perturbations in cellular proteomes, and are static in response to other common stimuli, yet are measurable in the periphery, potentially well in advance of the onset of clinical symptoms.MethodsHere, we used high-throughput, custom cancer antigen microarrays to identify a clinically relevant autoantibody biomarker combination able to differentially detect PDAC. …”
Get full text

LIMA1-alpha staining predicts curative intent surgery response in HPV negative head and neck cancer by Xi Qiao, Johannes Routila, Mari Tienhaara, Heikki Irjala, Priyadharshini Parimelazhagan Santhi, Teemu Huusko, Linda Nissi, Ilkka Paatero, Noora Lehtinen, Juha Rantala, Toni Viljanen, Ilmo Leivo, Petri Koivunen, Anna Jouppila-Mättö, Rami Taulu, Leif Bäck, Tommy Wilkman, Eeva Haapio, Ilpo Kinnunen, Kari Kurppa, Jukka Westermarck, Sami Ventelä

Get full text

Transcriptional responses in different mouse models of septic liver injury differ from those in patients with septic liver injury by Qin Yan, Qin Yan, Qin Yan, Wei Fan, Wei Fan, Wei Fan, Xinsen He, Xinsen He, Xinsen He, Shi Zheng, Shi Zheng, Shi Zheng, Xiaolin Zhong, Xiaolin Zhong, Xiaolin Zhong

Get full text

Expression of long non-coding RNA in patients with non-IgA mesangial proliferative glomerulonephritis by CONG Shan, SUI Wei-guo, ZOU Gui-mian, XUE Wen, LI Huan, YAN Qiang, CHEN Jie-jing, LUO Ya-dan, CHEN Huai-zhou

“…Objective To study differential expression profile of mRNA and long non-coding RNA(IncRNA) through microarray analysis between non-IgA mesangial proliferative glomerulonephritis(MsPGN) patients and the controls,and then explore the potential role of IncRNA in the pathogenesis of non-IgA MsPGN.Methods Through simple random sampling,4 patients with non-IgA MsPGN and 2 controls were selected as disease group and control group,respectively.Renal cortical tissues from two groups were collected.Total RNA was extracted,quantified and prepared to ds-cDNA through reverse transcription ds-cDNA was labeled with NimbleGen one-color DNA labeling kit and used for array hybridization.All experimental data were processed through GO analysis,Pathway analysis and the gene loci correlation analysis of mRNA and IncRNA.Some IncRNAs that were closely related to non-IgA MsPGN were screened out.Finally,part of the array results was detected by PCR to verify the reliability of array test Results By fold change filtering,4317 differentially expressed mRNAs and 3502 differentially expressed IncRNAs were screened out.Five IncRNAs were found to play potential roles in the pathogenesis of non-IgA MsPGN:AF1180924(close to coding gene FGG),AK092233(close to coding gene COL18A1),AK130579(close to coding gene CREBBP),AK023598(close to coding gene LEPR),and AK055915(close to coding gene CDC42EP3).These results provided an important basis for revealing the pathogenesis of non-IgA MsPGN.Conclusions Some IncRNAs can potentially regulate related genes and plays an important role in the pathogenesis and development of non-IgA MsPGN.…”
Get full text

RETRACTED ARTICLE: Multi-stage biomedical feature selection extraction algorithm for cancer detection by Ismail Keshta, Pallavi Sagar Deshpande, Mohammad Shabaz, Mukesh Soni, Mohit kumar Bhadla, Yasser Muhammed

“…Abstract Cancer is a significant cause of death worldwide. Early cancer detection is greatly aided by machine learning and artificial intelligence (AI) to gene microarray data sets (microarray data). …”
Get full text

Improving machine learning detection of Alzheimer disease using enhanced manta ray gene selection of Alzheimer gene expression datasets by Zahraa Ahmed, Mesut Çevik

Get full text

CFS-MOES Ensemble Model on Metaheuristic Search-Based Feature Selection by Santosini Bhutia, Bichitrananda Patra, Mitrabinda Ray

“…Due to the availability of highly specialized cancer datasets, molecular classification of cancer by gene expression, machine learning, and deep learning, a part of artificial intelligence (AI) techniques is used in detecting the disease. The application of several classification and feature selection methods on microarray gene expression datasets helps learn models that are able to predict a given disease. …”
Get full text

Nanomaterials based biosensors applied for detection of aflatoxin B1 in cereals: a review by Loyce Namanya, Emma Panzi Mukhokosi, Ediriisa Mugampoza

“…However, more studies are needed to address the automatic simultaneous detection of various aflatoxins in real samples and a biosensing system that integrates with microarray technology.…”
Get full text

RETRACTED: Modern Subtype Classification and Outlier Detection Using the Attention Embedder to Transform Ovarian Cancer Diagnosis by S. M. Nuruzzaman Nobel, S M Masfequier Rahman Swapno, Md. Ashraful Hossain, Mejdl Safran, Sultan Alfarhood, Md. Mohsin Kabir, M. F. Mridha

“…This study primarily uses a unique dataset painstakingly selected from 20 esteemed medical institutes. The dataset includes a wide range of images, such as tissue microarray (TMA) images at 40× magnification and whole-slide images (WSI) at 20× magnification. …”
Get full text

EsoDetect: computational validation and algorithm development of a novel diagnostic and prognostic tool for dysplasia in Barrett’s esophagus by Migla Miskinyte, Benilde Pondeca, José B. Pereira-Leal, Joana Cardoso

Get full text

Tumour extracellular vesicle surface Protein-mRNA integration assay for early detection of epithelial ovarian cancerResearch in context by Ying-Tzu Yen, Chen Zhao, Tian Gao, Jacqueline Ziqian Yang, Ning Kang, Jiahui Pu, Lei Qiu, Qixin Hu, Hyoyong Kim, Anmin Wang, Junseok Lee, Ryan Y. Zhang, Na Liu, Yue Ma, You-Ren Ji, Yong Ju, Lynn L. Zheng, James Lee-South, Vivian X. Zuo, Audrey Qian, Aaron Kwan, Yating Zhang, Shenghua Zhang, Zhili Wang, Jing Ren, Huaichao Liu, Zihan Wang, Yang Yue, Jina Kim, Jennifer Sun, Gabriella A. DiBernardo, Laura B. James-Allan, Ying Chen, Weipei Zhu, Guoyun Wang, Renjun Pei, Sanaz Memarzadeh, Sungyong You, Bobbie J. Rimel, Kate Lawrenson, Beth Y. Karlan, Myung Shin Sim, Shaohua Lu, Jipeng Wan, Na Sun, Hsian-Rong Tseng, Yazhen Zhu

“…Three EOC EV surface protein markers (i.e., FRα, MSLN, and TROP2) were selected through a bioinformatic framework using multi-omics data and underwent rigorous validation using EOC cell lines and EOC tissue microarrays. …”
Get full text

A RNA-Seq Analysis of the Rat Supraoptic Nucleus Transcriptome: Effects of Salt Loading on Gene Expression. by Kory R Johnson, C C T Hindmarch, Yasmmyn D Salinas, YiJun Shi, Michael Greenwood, See Ziau Hoe, David Murphy, Harold Gainer

“…In addition, we compare the SON transcriptomes resolved by RNA-Seq methods with the SON transcriptomes determined by Affymetrix microarray methods in rats under the same osmotic conditions, and find that there are 6,466 genes present in the SON that are represented in both data sets, although 1,040 of the expressed genes were found only in the microarray data, and 2,762 of the expressed genes are selectively found in the RNA-Seq data and not the microarray data. …”
Get full text

Mutation Spectrum of the ABCA4 Gene in a Greek Cohort with Stargardt Disease: Identification of Novel Mutations and Evidence of Three Prevalent Mutated Alleles by Kamakari Smaragda, Kokkinou Vassiliki, Koutsodontis George, Stamatiou Polixeni, Giatzakis Christoforos, Anastasakis Anastasios, Aslanides Ioannis Minas, Koukoula Stavrenia, Panagiotoglou Theoni, Datseris Ioannis, Tsilimbaris K. Miltiadis

“…MLPA analysis as well as sequencing of two regions in introns 30 and 36 reported earlier to harbor deep intronic disease-associated variants was used in 4 selected cases. Results. An overall detection rate of at least one mutant allele was achieved in 52 of the 59 patients (88.1%). …”
Get full text

Genome-wide analysis of m6A-modified circRNAs in the mouse model of myocardial injury induced by obstructive sleep apnea by Jiuhuang Lan, Yuhui Wang, Chang Liu, Hongli Chen, Qingshi Chen

“…The results of MeRIP-qPCR were consistent with the microarray results. 73 pathways were detected in the up-regulated transcripts and no relevant pathways were detected in the down-regulated transcripts. …”
Get full text

The transcription factors Snail and Slug activate the transforming growth factor-beta signaling pathway in breast cancer. by Archana Dhasarathy, Dhiral Phadke, Deepak Mav, Ruchir R Shah, Paul A Wade

“…In order to obtain a global view of the impact of Snail and Slug expression, we performed a microarray experiment using the MCF-7 breast cancer cell line, which does not express detectable levels of Snail or Slug. …”
Get full text

Global gene expression profiling reveals SPINK1 as a potential hepatocellular carcinoma marker. by Aileen Marshall, Margus Lukk, Claudia Kutter, Susan Davies, Graeme Alexander, Duncan T Odom

“…Six genes identified by microarray as highly expressed in HH-HCC were confirmed by RT qPCR. …”
Get full text

Cysteine‐rich intestinal protein 1 enhances the progression of hepatocellular carcinoma via Ras signaling by Hong‐Yu He, Li Hu

“…Receiver operating characteristic analysis showed that compared with a single marker, the combined detection of alpha‐fetoprotein, carcinoembryonic antigen, and CRIP1 had the highest accuracy, sensitivity, and specificity. …”
Get full text

Investigating Single-Molecule Molecular Inversion Probes for Medium-Scale Targeted DNA Methylation Analysis by Roy B. Simons, Hieab H. H. Adams, Manfred Kayser, Athina Vidaki

“…Considering CpGs with at least 20X coverage, we yielded robust methylation detection with levels comparable to those obtained from the gold standard EPIC microarray analysis (Pearsons’s r: 0.96). …”
Get full text

Analysis of gene expression difference and biological process in chorionic villi of unexplained recurrent spontaneous abortion by Linling Shi, Lun Wei, Meiqiu Lu, Hongmei Ding, Le Bo

“…Abstract Objective To explore the biological relationship between the regulatory signal pathways involved in differentially expressed genes and recurrent spontaneous abortion (RSA) by analyzing the gene expression microarray data of unexplained RSA. Methods The gene expression profile data of chorionic villi from unexplained recurrent abortion with normal karyotype and selective induced abortion were compared. …”
Get full text

Integrating single-cell RNA sequencing, WGCNA, and machine learning to identify key biomarkers in hepatocellular carcinoma by Gang Wang, Jiaxing Zhang, Yirong Li, Yuyu Zhang, Weiwei Dong, Hengquan Wu, Jinglan Wang, Peiqing Liao, Ziqiang Yuan, Tao Liu, Wenting He

“…Abstract The microarray and single-cell RNA-sequencing (scRNA-seq) datasets of hepatocellular carcinoma (HCC) were downloaded from the Gene Expression Omnibus (GEO) database. …”
Get full text