Robust Sampling of Defective Pathways in Alzheimer's Disease. Implications in Drug Repositioning
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Figure 2S 4 7 A - C 080125 CSCs 080418 CSCs - + IFN-a 48 h + IFN-a 48 h + IFN-a 72 h 6 + IFN-a 72 h 3 5 MRFI 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 7 B 13 080125 FBS - D 080418 FBS - + IFN-a 48 h 12 + IFN-a 48 h + IFN-a 72 h + IFN-a 72 h 6 080125 FBS 11 10 5 9 8 4 7 6 3 MRFI 5 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 Molecule Molecule FIGURE 4S FIGURE 5S Panel A Panel B FIGURE 6S A B C D Supplemental Results Table 1S. Modulation by IFN-α of APM in GBM CSC and FBS tumor cell lines. Molecule * Cell line IFN-α‡ HLA β2-m# HLA LMP TAP1 TAP2 class II A A HC§ 2 7 10 080125 CSCs - 1∞ (1) 3 (65) 2 (91) 1 (2) 6 (47) 2 (61) 1 (3) 1 (2) 1 (3) + 2 (81) 11 (80) 13 (99) 1 (3) 8 (88) 4 (91) 1 (2) 1 (3) 2 (68) 080125 FBS - 2 (81) 4 (63) 4 (83) 1 (3) 6 (80) 3 (67) 2 (86) 1 (3) 2 (75) + 2 (99) 14 (90) 7 (97) 5 (75) 7 (100) 6 (98) 2 (90) 1 (4) 3 (87) 080418 CSCs - 2 (51) 1 (1) 1 (3) 2 (47) 2 (83) 2 (54) 1 (4) 1 (2) 1 (3) + 2 (81) 3 (76) 5 (75) 2 (50) 2 (83) 3 (71) 1 (3) 2 (87) 1 (2) 080418 FBS - 1 (3) 3 (70) 2 (88) 1 (4) 3 (87) 2 (76) 1 (3) 1 (3) 1 (2) + 2 (78) 7 (98) 5 (99) 2 (94) 5 (100) 3 (100) 1 (4) 2 (100) 1 (2) 070104 CSCs - 1 (2) 1 (3) 1 (3) 2 (78) 1 (3) 1 (2) 1 (3) 1 (3) 1 (2) + 2 (98) 8 (100) 10 (88) 4 (89) 3 (98) 3 (94) 1 (4) 2 (86) 2 (79) * expression of APM molecules was evaluated by intracellular staining and cytofluorimetric analysis; ‡ cells were treatead or not (+/-) for 72 h with 1000 IU/ml of IFN-α; # β-2 microglobulin; § β-2 microglobulin-free HLA-A heavy chain; ∞ values are indicated as ratio between the mean of fluorescence intensity of cells stained with the selected mAb and that of the negative control; bold values indicate significant MRFI (≥ 2). -
Role of Cyclosporine in Gingival Hyperplasia: an in Vitro Study on Gingival Fibroblasts
International Journal of Molecular Sciences Article Role of Cyclosporine in Gingival Hyperplasia: An In Vitro Study on Gingival Fibroblasts 1, , 2, 3 3 Dorina Lauritano * y , Annalisa Palmieri y, Alberta Lucchese , Dario Di Stasio , Giulia Moreo 1 and Francesco Carinci 4 1 Department of Medicine and Surgery, Centre of Neuroscience of Milan, University of Milano-Bicocca, 20126 Milan, Italy; [email protected] 2 Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, via Belmoro 8, 40126 Bologna, Italy; [email protected] 3 Multidisciplinary Department of Medical and Dental Specialties, University of Campania-Luigi Vanvitelli, 80138 Naples, Italy; [email protected] (A.L.); [email protected] (D.D.S.) 4 Department of Morphology, Surgery and Experimental Medicine, University of Ferrara, 44121 Ferrara, Italy; [email protected] * Correspondence: [email protected]; Tel.: +39-335-679-0163 These authors contributed equally to this work. y Received: 25 November 2019; Accepted: 13 January 2020; Published: 16 January 2020 Abstract: Background: Gingival hyperplasia could occur after the administration of cyclosporine A. Up to 90% of the patients submitted to immunosuppressant drugs have been reported to suffer from this side effect. The role of fibroblasts in gingival hyperplasia has been widely discussed by literature, showing contrasting results. In order to demonstrate the effect of cyclosporine A on the extracellular matrix component of fibroblasts, we investigated the gene expression profile of human fibroblasts after cyclosporine A administration. Materials and methods: Primary gingival fibroblasts were stimulated with 1000 ng/mL cyclosporine A solution for 16 h. Gene expression levels of 57 genes belonging to the “Extracellular Matrix and Adhesion Molecules” pathway were analyzed using real-time PCR in treated cells, compared to untreated cells used as control. -
Higd1a Is a Positive Regulator of Cytochrome C Oxidase
Higd1a is a positive regulator of cytochrome c oxidase Takaharu Hayashia,b, Yoshihiro Asanoa,b,1, Yasunori Shintania, Hiroshi Aoyamac, Hidetaka Kiokab, Osamu Tsukamotoa, Masahide Hikitad, Kyoko Shinzawa-Itohd, Kazuaki Takafujie, Shuichiro Higoa,b, Hisakazu Katoa, Satoru Yamazakif, Ken Matsuokab, Atsushi Nakanog, Hiroshi Asanumah, Masanori Asakurag, Tetsuo Minaminob, Yu-ichi Gotoi, Takashi Ogurad, Masafumi Kitakazeg, Issei Komuroj, Yasushi Sakatab, Tomitake Tsukiharad,k, Shinya Yoshikawad, and Seiji Takashimaa,k,1 Departments of aMedical Biochemistry and bCardiovascular Medicine, eCenter for Research Education, and cGraduate School of Pharmaceutical Science, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan; dDepartment of Life Science, University of Hyogo, 3-2-1 Kouto, Kamigohri, Akoh, Hyogo 678-1297, Japan; kCore Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency, Kawaguchi, Saitama 332-0012, Japan; Departments of fCell Biology and gClinical Research and Development, National Cerebral and Cardiovascular Center Research Institute, Suita, Osaka 565-8565, Japan; hDepartment of Cardiovascular Science and Technology, Kyoto Prefectural University School of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan; iDepartment of Child Neurology, National Center Hospital of Neurology and Psychiatry, National Center of Neurology and Psychiatry, Kodaira, Tokyo 187-8502, Japan; and jDepartment of Cardiovascular Medicine, Graduate School of Medicine, University of Tokyo, Tokyo 113-8656, Japan Edited by Gottfried Schatz, University of Basel, Reinach, Switzerland, and approved December 16, 2014 (received for review October 15, 2014) Cytochrome c oxidase (CcO) is the only enzyme that uses oxygen as we recently revealed (8). Because CcO is the only enzyme in to produce a proton gradient for ATP production during mitochon- the body that can use oxygen for energy transduction, it has been drial oxidative phosphorylation. -
Supplementary Materials: Evaluation of Cytotoxicity and Α-Glucosidase Inhibitory Activity of Amide and Polyamino-Derivatives of Lupane Triterpenoids
Supplementary Materials: Evaluation of cytotoxicity and α-glucosidase inhibitory activity of amide and polyamino-derivatives of lupane triterpenoids Oxana B. Kazakova1*, Gul'nara V. Giniyatullina1, Akhat G. Mustafin1, Denis A. Babkov2, Elena V. Sokolova2, Alexander A. Spasov2* 1Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences, 71, pr. Oktyabrya, 450054 Ufa, Russian Federation 2Scientific Center for Innovative Drugs, Volgograd State Medical University, Novorossiyskaya st. 39, Volgograd 400087, Russian Federation Correspondence Prof. Dr. Oxana B. Kazakova Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences 71 Prospeсt Oktyabrya Ufa, 450054 Russian Federation E-mail: [email protected] Prof. Dr. Alexander A. Spasov Scientific Center for Innovative Drugs of the Volgograd State Medical University 39 Novorossiyskaya st. Volgograd, 400087 Russian Federation E-mail: [email protected] Figure S1. 1H and 13C of compound 2. H NH N H O H O H 2 2 Figure S2. 1H and 13C of compound 4. NH2 O H O H CH3 O O H H3C O H 4 3 Figure S3. Anticancer screening data of compound 2 at single dose assay 4 Figure S4. Anticancer screening data of compound 7 at single dose assay 5 Figure S5. Anticancer screening data of compound 8 at single dose assay 6 Figure S6. Anticancer screening data of compound 9 at single dose assay 7 Figure S7. Anticancer screening data of compound 12 at single dose assay 8 Figure S8. Anticancer screening data of compound 13 at single dose assay 9 Figure S9. Anticancer screening data of compound 14 at single dose assay 10 Figure S10. -
The Title of the Article
Mechanism-Anchored Profiling Derived from Epigenetic Networks Predicts Outcome in Acute Lymphoblastic Leukemia Xinan Yang, PhD1, Yong Huang, MD1, James L Chen, MD1, Jianming Xie, MSc2, Xiao Sun, PhD2, Yves A Lussier, MD1,3,4§ 1Center for Biomedical Informatics and Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL 60637 USA 2State Key Laboratory of Bioelectronics, Southeast University, 210096 Nanjing, P.R.China 3The University of Chicago Cancer Research Center, and The Ludwig Center for Metastasis Research, The University of Chicago, Chicago, IL 60637 USA 4The Institute for Genomics and Systems Biology, and the Computational Institute, The University of Chicago, Chicago, IL 60637 USA §Corresponding author Email addresses: XY: [email protected] YH: [email protected] JC: [email protected] JX: [email protected] XS: [email protected] YL: [email protected] - 1 - Abstract Background Current outcome predictors based on “molecular profiling” rely on gene lists selected without consideration for their molecular mechanisms. This study was designed to demonstrate that we could learn about genes related to a specific mechanism and further use this knowledge to predict outcome in patients – a paradigm shift towards accurate “mechanism-anchored profiling”. We propose a novel algorithm, PGnet, which predicts a tripartite mechanism-anchored network associated to epigenetic regulation consisting of phenotypes, genes and mechanisms. Genes termed as GEMs in this network meet all of the following criteria: (i) they are co-expressed with genes known to be involved in the biological mechanism of interest, (ii) they are also differentially expressed between distinct phenotypes relevant to the study, and (iii) as a biomodule, genes correlate with both the mechanism and the phenotype. -
Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
Supplementary Information Integrative Analyses of Splicing in the Aging Brain: Role in Susceptibility to Alzheimer’S Disease
Supplementary Information Integrative analyses of splicing in the aging brain: role in susceptibility to Alzheimer’s Disease Contents 1. Supplementary Notes 1.1. Religious Orders Study and Memory and Aging Project 1.2. Mount Sinai Brain Bank Alzheimer’s Disease 1.3. CommonMind Consortium 1.4. Data Availability 2. Supplementary Tables 3. Supplementary Figures Note: Supplementary Tables are provided as separate Excel files. 1. Supplementary Notes 1.1. Religious Orders Study and Memory and Aging Project Gene expression data1. Gene expression data were generated using RNA- sequencing from Dorsolateral Prefrontal Cortex (DLPFC) of 540 individuals, at an average sequence depth of 90M reads. Detailed description of data generation and processing was previously described2 (Mostafavi, Gaiteri et al., under review). Samples were submitted to the Broad Institute’s Genomics Platform for transcriptome analysis following the dUTP protocol with Poly(A) selection developed by Levin and colleagues3. All samples were chosen to pass two initial quality filters: RNA integrity (RIN) score >5 and quantity threshold of 5 ug (and were selected from a larger set of 724 samples). Sequencing was performed on the Illumina HiSeq with 101bp paired-end reads and achieved coverage of 150M reads of the first 12 samples. These 12 samples will serve as a deep coverage reference and included 2 males and 2 females of nonimpaired, mild cognitive impaired, and Alzheimer's cases. The remaining samples were sequenced with target coverage of 50M reads; the mean coverage for the samples passing QC is 95 million reads (median 90 million reads). The libraries were constructed and pooled according to the RIN scores such that similar RIN scores would be pooled together. -
The Genetic Architecture of Hearing Impairment in Mice: Evidence for Frequency Specific 2 Genetic Determinants
G3: Genes|Genomes|Genetics Early Online, published on September 4, 2015 as doi:10.1534/g3.115.021592 1 The genetic architecture of hearing impairment in mice: evidence for frequency specific 2 genetic determinants. 3 4 Amanda L. Crow1, Jeffrey Ohmen2, Juemei Wang3, Joel Lavinsky3, Jaana Hartiala1, Qingzhong 5 Li4, Xin Li5, Pezhman Salehide 3, Eleazar Eskin6, Calvin Pan7, Aldons J. Lusis7, Hooman 6 Allayee1, Rick A. Friedman3 7 8 1Department of Preventive Medicine and Institute for Genetic Medicine, Keck School of 9 Medicine, University of Southern California, Los Angeles, CA 90033 10 2House Ear Institute, Los Angeles, CA 90057 11 3Department of Otolaryngology and Zilkha Neurogenetic Institute, Keck School of Medicine, 12 University of Southern California, Los Angeles, CA, 90033 13 4Department of Otolaryngology - Head and Neck Surgery, Eye & ENT Hospital of Fudan 14 University, Shanghai 200031, China 15 5Clinical Laboratory Department, First Affiliated Hospital of Nanchang University, Nanchang, 16 Jiangxi Province 330006, China 17 6Department of Computer Science and Inter-Departmental Program in Bioinformatics, 18 University of California, Los Angeles, Los Angeles, CA 90095 19 7Departments of Human Genetics, Medicine, and Microbiology, Immunology, and Molecular 20 Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095 21 © The Author(s) 2013. Published by the Genetics Society of America. 1 Short Title 2 Genetics of Hearing in Mice 3 4 Keywords 5 Genome-wide association study (GWAS), Hybrid Mouse Diversity Panel (HMDP), genetics, 6 genomics, ABR, hearing, cochlear function 7 8 9 Corresponding Author: 10 Rick A. Friedman 11 USC Keck School of Medicine 12 Zilkha Neurogenetic Institute 13 1501 San Pablo Street (ZNI 231) 14 Los Angeles, CA 90033 15 Tel: (323) 442-4843 16 Fax: (323) 442-2059 17 Email: [email protected] 18 19 1 Abstract 2 Genome-wide association studies (GWAS) have been successfully applied in humans for 3 the study of many complex phenotypes. -
2335 Roles of Molecules Involved in Epithelial/Mesenchymal Transition
[Frontiers in Bioscience 13, 2335-2355, January 1, 2008] Roles of molecules involved in epithelial/mesenchymal transition during angiogenesis Giulio Ghersi Dipartimento di Biologia Cellulare e dello Sviluppo, Universita di Palermo, Italy TABLE OF CONTENTS 1. Abstract 2. Introduction 3. Extracellular matrix 3.1. ECM and integrins 3.2. Basal lamina components 4. Cadherins. 4.1. Cadherins in angiogenesis 5. Integrins. 5.1. Integrins in angiogenesis 6. Focal adhesion molecules 7. Proteolytic enzymes 7.1. Proteolytic enzymes inhibitors 7.2. Proteolytic enzymes in angiogenesis 8. Perspective 9. Acknowledgements 10. References 1.ABSTRACT 2. INTRODUCTION Formation of vessels requires “epithelial- Growth of new blood vessels (angiogenesis) mesenchymal” transition of endothelial cells, with several plays a key role in several physiological processes, such modifications at the level of endothelial cell plasma as vascular remodeling during embryogenesis and membranes. These processes are associated with wound healing tissue repair in the adult; as well as redistribution of cell-cell and cell-substrate adhesion pathological processes, including rheumatoid arthritis, molecules, cross talk between external ECM and internal diabetic retinopathy, psoriasis, hemangiomas, and cytoskeleton through focal adhesion molecules and the cancer (1). Vessel formation entails the “epithelial- expression of several proteolytic enzymes, including matrix mesenchymal” transition of endothelial cells (ECs) “in metalloproteases and serine proteases. These enzymes with vivo”; a similar phenotypic exchange can be induced “in their degradative action on ECM components, generate vitro” by growing ECs to low cell density, or in “wound molecules acting as activators and/or inhibitors of healing” experiments or perturbing cell adhesion and angiogenesis. The purpose of this review is to provide an associated molecule functions. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
The Inactive X Chromosome Is Epigenetically Unstable and Transcriptionally Labile in Breast Cancer
Supplemental Information The inactive X chromosome is epigenetically unstable and transcriptionally labile in breast cancer Ronan Chaligné1,2,3,8, Tatiana Popova1,4, Marco-Antonio Mendoza-Parra5, Mohamed-Ashick M. Saleem5 , David Gentien1,6, Kristen Ban1,2,3,8, Tristan Piolot1,7, Olivier Leroy1,7, Odette Mariani6, Hinrich Gronemeyer*5, Anne Vincent-Salomon*1,4,6,8, Marc-Henri Stern*1,4,6 and Edith Heard*1,2,3,8 Extended Experimental Procedures Cell Culture Human Mammary Epithelial Cells (HMEC, Invitrogen) were grown in serum-free medium (HuMEC, Invitrogen). WI- 38, ZR-75-1, SK-BR-3 and MDA-MB-436 cells were grown in Dulbecco’s modified Eagle’s medium (DMEM; Invitrogen) containing 10% fetal bovine serum (FBS). DNA Methylation analysis. We bisulfite-treated 2 µg of genomic DNA using Epitect bisulfite kit (Qiagen). Bisulfite converted DNA was amplified with bisulfite primers listed in Table S3. All primers incorporated a T7 promoter tag, and PCR conditions are available upon request. We analyzed PCR products by MALDI-TOF mass spectrometry after in vitro transcription and specific cleavage (EpiTYPER by Sequenom®). For each amplicon, we analyzed two independent DNA samples and several CG sites in the CpG Island. Design of primers and selection of best promoter region to assess (approx. 500 bp) were done by a combination of UCSC Genome Browser (http://genome.ucsc.edu) and MethPrimer (http://www.urogene.org). All the primers used are listed (Table S3). NB: MAGEC2 CpG analysis have been done with a combination of two CpG island identified in the gene core. Analysis of RNA allelic expression profiles (based on Human SNP Array 6.0) DNA and RNA hybridizations were normalized by Genotyping console. -
Primate Specific Retrotransposons, Svas, in the Evolution of Networks That Alter Brain Function
Title: Primate specific retrotransposons, SVAs, in the evolution of networks that alter brain function. Olga Vasieva1*, Sultan Cetiner1, Abigail Savage2, Gerald G. Schumann3, Vivien J Bubb2, John P Quinn2*, 1 Institute of Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, U.K 2 Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, The University of Liverpool, Liverpool L69 3BX, UK 3 Division of Medical Biotechnology, Paul-Ehrlich-Institut, Langen, D-63225 Germany *. Corresponding author Olga Vasieva: Institute of Integrative Biology, Department of Comparative genomics, University of Liverpool, Liverpool, L69 7ZB, [email protected] ; Tel: (+44) 151 795 4456; FAX:(+44) 151 795 4406 John Quinn: Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, The University of Liverpool, Liverpool L69 3BX, UK, [email protected]; Tel: (+44) 151 794 5498. Key words: SVA, trans-mobilisation, behaviour, brain, evolution, psychiatric disorders 1 Abstract The hominid-specific non-LTR retrotransposon termed SINE–VNTR–Alu (SVA) is the youngest of the transposable elements in the human genome. The propagation of the most ancient SVA type A took place about 13.5 Myrs ago, and the youngest SVA types appeared in the human genome after the chimpanzee divergence. Functional enrichment analysis of genes associated with SVA insertions demonstrated their strong link to multiple ontological categories attributed to brain function and the disorders. SVA types that expanded their presence in the human genome at different stages of hominoid life history were also associated with progressively evolving behavioural features that indicated a potential impact of SVA propagation on a cognitive ability of a modern human.