Apoptosis-Related Gene Expression in Tumor Tissue Samples Obtained from Patients Diagnosed with Glioblastoma Multiforme
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Cloning and Sequence Analysis of Canine Apoptosis-Associated Molecules
Zurich Open Repository and Archive University of Zurich Main Library Strickhofstrasse 39 CH-8057 Zurich www.zora.uzh.ch Year: 2007 Cloning and sequence analysis of canine apoptosis-associated molecules Schade, Benjamin Abstract: The aim of the study was to clone and sequence the coding sequences of a representative set of proteins, primarily from the intrinsic apoptotic pathway in dogs and to assess their conservation with hu- man and murine orthologues. cDNA for these proteins, including Bcl-2 family members (Bcl-XL, Bcl-w, Mcl-1, Bax, Bak, Bad, Noxa), caspases (Caspase-3, Caspase-8, Caspase-9), Inhibitors of Apoptosis Pro- teins (XIAP, cIAP-1, cIAP-2, Survivin), their mitochondrial inhibitors (Smac/ DIABLO, Omi/HtrA2) and p53, were generated by RT-PCR with RNA extracted from two canine non-neoplastic cell lines. Eleven sequences are novel for the dog. Interspecies comparison revealed strongest similarity between the sequences of human and canine intrinsic apoptosis pathway members. Differences with potential func- tional impact, however, were observed in both dogs and mice. In dogs, these changes involve the putative Inhibitor of Apoptosis Protein binding motif of canine Omi/HtrA2, some caspase substrate recognition motifs and some functionally relevant residues of p53. Canine XIAP yields a caspase-cleavage site reported as unique to humans. In conclusion, the generally high degree of similarity of canine apoptosis-associated proteins as compared to human counterparts is supportive of the use of dogs as a model for human dis- eases. Single interspecies sequence variations with potential functional relevance under physiologic and neoplastic conditions do exist, however, and will require further analysis. -
Supplementary Materials For
Supplementary Materials for Elucidating cellular population dynamics by molecular density function perturbations 1 2,3, Thanneer Malai Perumal and Rudiyanto Gunawan * 1 Sage Bionetworks, Seattle, Washington, USA; [email protected] 2 Institute for Chemical and Bioengineering, ETH Zurich, Zurich, Switzerland; [email protected] 3 Swiss Institute of Bioinformatics, Lausanne, Switzerland * Correspondence: [email protected]; Tel.: +41-44-633-2134 Supplementary Material S1. Probability Distance Metrics Signed Engineering Metric: ∞ 2 ∆ (f A (t, x )||f B (t, x )) = sign(∆μ ) ∫ (x f A (t, x ) − x f B (t, x )) dx (S. 1) E Xi i Xi i Xi i Xi i i Xi i i −∞ Signed Jeffrey Divergence: ∞ f A (t,x ) A B A B Xi i ∆ (f (t, x )||f (t, x )) = sgn(∆μ ) ∫ (f (t, x ) − f (t, x ))ln ( B ) )dx (S. 2) JD Xi i Xi i Xi Xi i Xi i f (t,x ) i −∞ Xi i Signed Kullback-Leibler Distance: ∞ f B (t,x ) A B B Xi i ∆ (f (t, x )||f (t, x )) = sgn(∆μ ) ∫ f (t, x )ln ( A ) dx (S. 3) KLD Xi i Xi i Xi Xi i f (t,x ) i −∞ Xi i Signed Jensen-Shannon Divergence: f + (t,x )+f − (t,x ) Xi i Xi i ∆ f (t, x ) = sgn(∆μ ) (S. 4) JSD Xi i Xi 2 Signed Kolmogorov-Smirnov Metric: ∆ (f A (t, x )||f B (t, x )) = sgn(∆μ )sup|F A (t, x ) − F B (t, x )| (S. 5) KS Xi i Xi i Xi Xi i Xi i Supplementary Material S2. -
Supplemental Table S1
Entrez Gene Symbol Gene Name Affymetrix EST Glomchip SAGE Stanford Literature HPA confirmed Gene ID Profiling profiling Profiling Profiling array profiling confirmed 1 2 A2M alpha-2-macroglobulin 0 0 0 1 0 2 10347 ABCA7 ATP-binding cassette, sub-family A (ABC1), member 7 1 0 0 0 0 3 10350 ABCA9 ATP-binding cassette, sub-family A (ABC1), member 9 1 0 0 0 0 4 10057 ABCC5 ATP-binding cassette, sub-family C (CFTR/MRP), member 5 1 0 0 0 0 5 10060 ABCC9 ATP-binding cassette, sub-family C (CFTR/MRP), member 9 1 0 0 0 0 6 79575 ABHD8 abhydrolase domain containing 8 1 0 0 0 0 7 51225 ABI3 ABI gene family, member 3 1 0 1 0 0 8 29 ABR active BCR-related gene 1 0 0 0 0 9 25841 ABTB2 ankyrin repeat and BTB (POZ) domain containing 2 1 0 1 0 0 10 30 ACAA1 acetyl-Coenzyme A acyltransferase 1 (peroxisomal 3-oxoacyl-Coenzyme A thiol 0 1 0 0 0 11 43 ACHE acetylcholinesterase (Yt blood group) 1 0 0 0 0 12 58 ACTA1 actin, alpha 1, skeletal muscle 0 1 0 0 0 13 60 ACTB actin, beta 01000 1 14 71 ACTG1 actin, gamma 1 0 1 0 0 0 15 81 ACTN4 actinin, alpha 4 0 0 1 1 1 10700177 16 10096 ACTR3 ARP3 actin-related protein 3 homolog (yeast) 0 1 0 0 0 17 94 ACVRL1 activin A receptor type II-like 1 1 0 1 0 0 18 8038 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 1 0 0 0 0 19 8751 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 1 0 0 0 0 20 8728 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 1 0 0 0 0 21 81792 ADAMTS12 ADAM metallopeptidase with thrombospondin type 1 motif, 12 1 0 0 0 0 22 9507 ADAMTS4 ADAM metallopeptidase with thrombospondin type 1 -
Neurodevelopmental Signatures of Narcotic and Neuropsychiatric Risk Factors in 3D Human-Derived Forebrain Organoids
Molecular Psychiatry www.nature.com/mp ARTICLE OPEN Neurodevelopmental signatures of narcotic and neuropsychiatric risk factors in 3D human-derived forebrain organoids 1 1 1 1 2 2 3 Michael Notaras , Aiman Lodhi , Estibaliz✉ Barrio-Alonso , Careen Foord , Tori Rodrick , Drew Jones , Haoyun Fang , David Greening 3,4 and Dilek Colak 1,5 © The Author(s) 2021 It is widely accepted that narcotic use during pregnancy and specific environmental factors (e.g., maternal immune activation and chronic stress) may increase risk of neuropsychiatric illness in offspring. However, little progress has been made in defining human- specific in utero neurodevelopmental pathology due to ethical and technical challenges associated with accessing human prenatal brain tissue. Here we utilized human induced pluripotent stem cells (hiPSCs) to generate reproducible organoids that recapitulate dorsal forebrain development including early corticogenesis. We systemically exposed organoid samples to chemically defined “enviromimetic” compounds to examine the developmental effects of various narcotic and neuropsychiatric-related risk factors within tissue of human origin. In tandem experiments conducted in parallel, we modeled exposure to opiates (μ-opioid agonist endomorphin), cannabinoids (WIN 55,212-2), alcohol (ethanol), smoking (nicotine), chronic stress (human cortisol), and maternal immune activation (human Interleukin-17a; IL17a). Human-derived dorsal forebrain organoids were consequently analyzed via an array of unbiased and high-throughput analytical approaches, including state-of-the-art TMT-16plex liquid chromatography/mass- spectrometry (LC/MS) proteomics, hybrid MS metabolomics, and flow cytometry panels to determine cell-cycle dynamics and rates of cell death. This pipeline subsequently revealed both common and unique proteome, reactome, and metabolome alterations as a consequence of enviromimetic modeling of narcotic use and neuropsychiatric-related risk factors in tissue of human origin. -
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. -
A Multi-Omics Interpretable Machine Learning Model Reveals Modes of Action of Small Molecules Natasha L
www.nature.com/scientificreports OPEN A Multi-Omics Interpretable Machine Learning Model Reveals Modes of Action of Small Molecules Natasha L. Patel-Murray1, Miriam Adam2, Nhan Huynh2, Brook T. Wassie2, Pamela Milani2 & Ernest Fraenkel 2,3* High-throughput screening and gene signature analyses frequently identify lead therapeutic compounds with unknown modes of action (MoAs), and the resulting uncertainties can lead to the failure of clinical trials. We developed an approach for uncovering MoAs through an interpretable machine learning model of transcriptomics, epigenomics, metabolomics, and proteomics. Examining compounds with benefcial efects in models of Huntington’s Disease, we found common MoAs for compounds with unrelated structures, connectivity scores, and binding targets. The approach also predicted highly divergent MoAs for two FDA-approved antihistamines. We experimentally validated these efects, demonstrating that one antihistamine activates autophagy, while the other targets bioenergetics. The use of multiple omics was essential, as some MoAs were virtually undetectable in specifc assays. Our approach does not require reference compounds or large databases of experimental data in related systems and thus can be applied to the study of agents with uncharacterized MoAs and to rare or understudied diseases. Unknown modes of action of drug candidates can lead to unpredicted consequences on efectiveness and safety. Computational methods, such as the analysis of gene signatures, and high-throughput experimental methods have accelerated the discovery of lead compounds that afect a specifc target or phenotype1–3. However, these advances have not dramatically changed the rate of drug approvals. Between 2000 and 2015, 86% of drug can- didates failed to earn FDA approval, with toxicity or a lack of efcacy being common reasons for their clinical trial termination4,5. -
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Patterns of DNA methylation on the human X chromosome and use in analyzing X-chromosome inactivation by Allison Marie Cotton B.Sc., The University of Guelph, 2005 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in The Faculty of Graduate Studies (Medical Genetics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) January 2012 © Allison Marie Cotton, 2012 Abstract The process of X-chromosome inactivation achieves dosage compensation between mammalian males and females. In females one X chromosome is transcriptionally silenced through a variety of epigenetic modifications including DNA methylation. Most X-linked genes are subject to X-chromosome inactivation and only expressed from the active X chromosome. On the inactive X chromosome, the CpG island promoters of genes subject to X-chromosome inactivation are methylated in their promoter regions, while genes which escape from X- chromosome inactivation have unmethylated CpG island promoters on both the active and inactive X chromosomes. The first objective of this thesis was to determine if the DNA methylation of CpG island promoters could be used to accurately predict X chromosome inactivation status. The second objective was to use DNA methylation to predict X-chromosome inactivation status in a variety of tissues. A comparison of blood, muscle, kidney and neural tissues revealed tissue-specific X-chromosome inactivation, in which 12% of genes escaped from X-chromosome inactivation in some, but not all, tissues. X-linked DNA methylation analysis of placental tissues predicted four times higher escape from X-chromosome inactivation than in any other tissue. Despite the hypomethylation of repetitive elements on both the X chromosome and the autosomes, no changes were detected in the frequency or intensity of placental Cot-1 holes. -
XIAP's Profile in Human Cancer
biomolecules Review XIAP’s Profile in Human Cancer Huailu Tu and Max Costa * Department of Environmental Medicine, Grossman School of Medicine, New York University, New York, NY 10010, USA; [email protected] * Correspondence: [email protected] Received: 16 September 2020; Accepted: 25 October 2020; Published: 29 October 2020 Abstract: XIAP, the X-linked inhibitor of apoptosis protein, regulates cell death signaling pathways through binding and inhibiting caspases. Mounting experimental research associated with XIAP has shown it to be a master regulator of cell death not only in apoptosis, but also in autophagy and necroptosis. As a vital decider on cell survival, XIAP is involved in the regulation of cancer initiation, promotion and progression. XIAP up-regulation occurs in many human diseases, resulting in a series of undesired effects such as raising the cellular tolerance to genetic lesions, inflammation and cytotoxicity. Hence, anti-tumor drugs targeting XIAP have become an important focus for cancer therapy research. RNA–XIAP interaction is a focus, which has enriched the general profile of XIAP regulation in human cancer. In this review, the basic functions of XIAP, its regulatory role in cancer, anti-XIAP drugs and recent findings about RNA–XIAP interactions are discussed. Keywords: XIAP; apoptosis; cancer; therapeutics; non-coding RNA 1. Introduction X-linked inhibitor of apoptosis protein (XIAP), also known as inhibitor of apoptosis protein 3 (IAP3), baculoviral IAP repeat-containing protein 4 (BIRC4), and human IAPs like protein (hILP), belongs to IAP family which was discovered in insect baculovirus [1]. Eight different IAPs have been isolated from human tissues: NAIP (BIRC1), BIRC2 (cIAP1), BIRC3 (cIAP2), XIAP (BIRC4), BIRC5 (survivin), BIRC6 (apollon), BIRC7 (livin) and BIRC8 [2]. -
Anti-Smac / Diablo Antibody (ARG54653)
Product datasheet [email protected] ARG54653 Package: 50 μg anti-Smac / Diablo antibody Store at: -20°C Summary Product Description Rabbit Polyclonal antibody recognizes Smac / Diablo Tested Reactivity Hu, Ms, Rat Tested Application ELISA, ICC/IF, IHC, IP, WB Host Rabbit Clonality Polyclonal Isotype IgG Target Name Smac / Diablo Immunogen Synthetic peptide (16 aa) within the last 50 aa of Mouse Smac. Conjugation Un-conjugated Alternate Names Smac; Second mitochondria-derived activator of caspase; Diablo homolog, mitochondrial; SMAC; Direct IAP-binding protein with low pI; DFNA64 Application Instructions Application table Application Dilution ELISA Assay-Dependent ICC/IF 10 μg/mL IHC 2 μg/mL IP Assay-Dependent WB 1 μg/mL Application Note * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Positive Control Mouse Heart Tissue Lysate Calculated Mw 27 kDa Properties Form Liquid Purification Affinity purification with immunogen. Buffer PBS and 0.02% Sodium azide Preservative 0.02% Sodium azide Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. For long-term storage, aliquot and store at -20°C or below. Storage in frost free freezers is not recommended. Avoid repeated freeze/thaw cycles. Suggest spin the vial prior to opening. The antibody solution should be gently mixed before use. www.arigobio.com 1/3 Note For laboratory research only, not for drug, diagnostic or other use. Bioinformation Database links GeneID: 56616 Human GeneID: 66593 Mouse Swiss-port # Q9JIQ3 Mouse Swiss-port # Q9NR28 Human Gene Symbol Diablo Gene Full Name diablo homolog (Drosophila) Background Smac Antibody: The inhibitor of apoptosis proteins (IAPs) regulate programmed cell death by inhibiting members of the caspase family of enzymes. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Hepatic Transcriptome Profiling Indicates
Aquatic Toxicology 130–131 (2013) 58–67 Contents lists available at SciVerse ScienceDirect Aquatic Toxicology jou rnal homepage: www.elsevier.com/locate/aquatox Hepatic transcriptome profiling indicates differential mRNA expression of apoptosis and immune related genes in eelpout (Zoarces viviparus) caught at Göteborg harbor, Sweden a,∗ b a c a Noomi Asker , Erik Kristiansson , Eva Albertsson , D.G. Joakim Larsson , Lars Förlin a Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden b Department of Mathematical Statistics, Chalmers University of Technology, Gothenburg, Sweden c Department of Infectious Diseases, Institute of Biomedicine, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden a r t i c l e i n f o a b s t r a c t Article history: The physiology and reproductive performance of eelpout (Zoarces viviparus) have been monitored along Received 5 June 2012 the Swedish coast for more than three decades. In this study, transcriptomic profiling was applied for Received in revised form the first time as an exploratory tool to search for new potential candidate biomarkers and to investigate 12 December 2012 possible stress responses in fish collected from a chronically polluted area. An oligonucleotide microar- Accepted 18 December 2012 ray with more than 15,000 sequences was used to assess differentially expressed hepatic mRNA levels in female eelpout collected from the contaminated area at Göteborg harbor compared to fish from a national Keywords: reference site, Fjällbacka. Genes involved in apoptosis and DNA damage (e.g., SMAC/diablo homolog and Transcriptomics DDIT4/DNA-damage-inducible protein transcript 4) had higher mRNA expression levels in eelpout from Chronic exposure Pollution the harbor compared to the reference site, whereas mRNA expression of genes involved in the innate Eelpout immune system (e.g., complement components and hepcidin) and protein transport/folding (e.g., sig- Microarray nal recognition particle and protein disulfide-isomerase) were expressed at lower levels. -
BAP31 (BCAP31) (NM 001139457) Human Mass Spec Standard Product Data
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for PH327334 BAP31 (BCAP31) (NM_001139457) Human Mass Spec Standard Product data: Product Type: Mass Spec Standards Description: BCAP31 MS Standard C13 and N15-labeled recombinant protein (NP_001132929) Species: Human Expression Host: HEK293 Expression cDNA Clone RC227334 or AA Sequence: Predicted MW: 34.6 kDa Protein Sequence: >RC227334 representing NM_001139457 Red=Cloning site Green=Tags(s) MGAEASSSWCPGTALPEERLSVKRASEISGFLGQGSSGEAALDVLTHVLEGAGNKLTSSCGKPSSNRMSL QWTAVATFLYAEVFVVLLLCIPFISPKRWQKIFKSRLVELLVSYGNTFFVVLIVILVLLVIDAVREIRKY DDVTEKVNLQNNPGAMEHFHMKLFRAQRNLYIAGFSLLLSFLLRRLVTLISQQATLLASNEAFKKQAESA SEAAKKYMEENDQLKKGAAVDGGKLDVGNAEVKLEEENRSLKADLQKLKDELASTKQKLEKAENQVLAMR KQSEGLTKEYDRLLEEHAKLQAAVDGPMDKKEE TRTRPLEQKLISEEDLAANDILDYKDDDDKV Tag: C-Myc/DDK Purity: > 80% as determined by SDS-PAGE and Coomassie blue staining Concentration: 50 ug/ml as determined by BCA Labeling Method: Labeled with [U- 13C6, 15N4]-L-Arginine and [U- 13C6, 15N2]-L-Lysine Buffer: 100 mM glycine, 25 mM Tris-HCl, pH 7.3. Store at -80°C. Avoid repeated freeze-thaw cycles. Stable for 3 months from receipt of products under proper storage and handling conditions. RefSeq: NP_001132929 RefSeq ORF: 939 Synonyms: 6C6-AG; BAP31; CDM; DDCH; DXS1357E Locus ID: 10134 UniProt ID: P51572 Cytogenetics: Xq28 This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 2 BAP31 (BCAP31) (NM_001139457) Human Mass Spec Standard – PH327334 Summary: This gene encodes a member of the B-cell receptor associated protein 31 superfamily. The encoded protein is a multi-pass transmembrane protein of the endoplasmic reticulum that is involved in the anterograde transport of membrane proteins from the endoplasmic reticulum to the Golgi and in caspase 8-mediated apoptosis.