Transposon Activation Mutagenesis As a Screening Tool for Identifying
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Bivariate Genome-Wide Association Analysis of the Growth and Intake Components of Feed Efficiency
Bivariate Genome-Wide Association Analysis of the Growth and Intake Components of Feed Efficiency Nick V. L. Sera˜o1., Dianelys Gonza´lez-Pen˜ a1., Jonathan E. Beever1, Germa´n A. Bollero2, Bruce R. Southey1, Daniel B. Faulkner1, Sandra L. Rodriguez-Zas1,3,4* 1 Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America, 2 Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America, 3 Department of Statistics, University of Illinois at Urbana-Champaign, Champaign, Illinois, United States of America, 4 Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America Abstract Single nucleotide polymorphisms (SNPs) associated with average daily gain (ADG) and dry matter intake (DMI), two major components of feed efficiency in cattle, were identified in a genome-wide association study (GWAS). Uni- and multi-SNP models were used to describe feed efficiency in a training data set and the results were confirmed in a validation data set. Results from the univariate and bivariate analyses of ADG and DMI, adjusted by the feedlot beef steer maintenance requirements, were compared. The bivariate uni-SNP analysis identified (P-value ,0.0001) 11 SNPs, meanwhile the univariate analyses of ADG and DMI identified 8 and 9 SNPs, respectively. Among the six SNPs confirmed in the validation data set, five SNPs were mapped to KDELC2, PHOX2A, and TMEM40. Findings from the uni-SNP models were used to develop highly accurate predictive multi-SNP models in the training data set. Despite the substantially smaller size of the validation data set, the training multi-SNP models had slightly lower predictive ability when applied to the validation data set. -
Genome-Wide Association Study of Body Weight
Genome-wide association study of body weight in Australian Merino sheep reveals an orthologous region on OAR6 to human and bovine genomic regions affecting height and weight Hawlader A. Al-Mamun, Paul Kwan, Samuel A. Clark, Mohammad H. Ferdosi, Ross Tellam, Cedric Gondro To cite this version: Hawlader A. Al-Mamun, Paul Kwan, Samuel A. Clark, Mohammad H. Ferdosi, Ross Tellam, et al.. Genome-wide association study of body weight in Australian Merino sheep reveals an orthologous region on OAR6 to human and bovine genomic regions affecting height and weight. Genetics Selection Evolution, 2015, 47 (1), pp.66. 10.1186/s12711-015-0142-4. hal-01341302 HAL Id: hal-01341302 https://hal.archives-ouvertes.fr/hal-01341302 Submitted on 4 Jul 2016 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. et al. Genetics Selection Evolution Al-Mamun (2015) 47:66 Genetics DOI 10.1186/s12711-015-0142-4 Selection Evolution RESEARCH ARTICLE Open Access Genome-wide association study of body weight in Australian Merino sheep reveals an orthologous region on OAR6 to human and bovine genomic regions affecting height and weight Hawlader A. Al-Mamun1,2, Paul Kwan2, Samuel A. -
A Genome-Wide Association Study Identifies Variants in KCNIP4
OPEN The Pharmacogenomics Journal (2016) 16, 231–237 © 2016 Macmillan Publishers Limited All rights reserved 1470-269X/16 www.nature.com/tpj ORIGINAL ARTICLE A genome-wide association study identifies variants in KCNIP4 associated with ACE inhibitor-induced cough JD Mosley1, CM Shaffer1, SL Van Driest1,2, PE Weeke1,3, QS Wells1, JH Karnes1, DR Velez Edwards4, W-Q Wei5, PL Teixeira5, L Bastarache5, DC Crawford6,RLi7, TA Manolio7, EP Bottinger8, CA McCarty9, JG Linneman10, MH Brilliant10, JA Pacheco11, W Thompson11, RL Chisholm11, GP Jarvik12, DR Crosslin12, DS Carrell13, E Baldwin13, J Ralston13, EB Larson13, J Grafton13, A Scrol13, H Jouni14, IJ Kullo14, G Tromp15, KM Borthwick15, H Kuivaniemi15, DJ Carey15, MD Ritchie16, Y Bradford16, SS Verma16, CG Chute17, A Veluchamy18, MK Siddiqui18, CNA Palmer18, A Doney18, SH MahmoudPour19, AH Maitland-van der Zee19, AD Morris20, JC Denny1,5,21 and DM Roden1,21 The most common side effect of angiotensin-converting enzyme inhibitor (ACEi) drugs is cough. We conducted a genome-wide association study (GWAS) of ACEi-induced cough among 7080 subjects of diverse ancestries in the Electronic Medical Records and Genomics (eMERGE) network. Cases were subjects diagnosed with ACEi-induced cough. Controls were subjects with at least 6 months of ACEi use and no cough. A GWAS (1595 cases and 5485 controls) identified associations on chromosome 4 in an intron of KCNIP4. The strongest association was at rs145489027 (minor allele frequency = 0.33, odds ratio (OR) = 1.3 (95% confidence interval (CI): 1.2–1.4), P = 1.0 × 10 − 8). Replication for six single-nucleotide polymorphisms (SNPs) in KCNIP4 was tested in a second eMERGE population (n = 926) and in the Genetics of Diabetes Audit and Research in Tayside, Scotland (GoDARTS) cohort (n = 4309). -
RSPH3 (NM 031924) Human Recombinant Protein – TP761392
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 TP761392 RSPH3 (NM_031924) Human Recombinant Protein Product data: Product Type: Recombinant Proteins Description: Purified recombinant protein of Human radial spoke 3 homolog (Chlamydomonas) (RSPH3), full length, with N-terminal GST and C-terminal HIS tag, expressed in E. coli, 50ug Species: Human Expression Host: E. coli Tag: N-GST and C-His Predicted MW: 91.5 kDa Concentration: >50 ug/mL as determined by microplate BCA method Purity: > 80% as determined by SDS-PAGE and Coomassie blue staining Buffer: 25mM Tris,pH8.0,150mM NaCl,10% glycerol,1% Sarkosyl. Storage: Store at -80°C. Stability: Stable for 12 months from the date of receipt of the product under proper storage and handling conditions. Avoid repeated freeze-thaw cycles. RefSeq: NP_114130 Locus ID: 83861 UniProt ID: Q86UC2 RefSeq Size: 2201 Cytogenetics: 6q25.3 RefSeq ORF: 1680 Synonyms: CILD32; dJ111C20.1; RSHL2; RSP3 Summary: The protein encoded by this gene acts as a protein kinase A anchoring protein. Mutations in this gene cause primary ciliary dyskinesia; a disorder characterized by defects of the axoneme in motile cilia and sperm flagella. The homolog of this gene was first identified in the blue- green algae Chlamydomonas as encoding a radial spoke protein that formed a structural component of motile cilia and flagella. Alternate splicing results in multiple transcript variants encoding distinct isoforms. [provided by RefSeq, Dec 2016] This product is to be used for laboratory only. -
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. -
Emerging Roles for Multifunctional Ion Channel Auxiliary Subunits in Cancer T ⁎ Alexander S
Cell Calcium 80 (2019) 125–140 Contents lists available at ScienceDirect Cell Calcium journal homepage: www.elsevier.com/locate/ceca Emerging roles for multifunctional ion channel auxiliary subunits in cancer T ⁎ Alexander S. Hawortha,b, William J. Brackenburya,b, a Department of Biology, University of York, Heslington, York, YO10 5DD, UK b York Biomedical Research Institute, University of York, Heslington, York, YO10 5DD, UK ARTICLE INFO ABSTRACT Keywords: Several superfamilies of plasma membrane channels which regulate transmembrane ion flux have also been Auxiliary subunit shown to regulate a multitude of cellular processes, including proliferation and migration. Ion channels are Cancer typically multimeric complexes consisting of conducting subunits and auxiliary, non-conducting subunits. Calcium channel Auxiliary subunits modulate the function of conducting subunits and have putative non-conducting roles, further Chloride channel expanding the repertoire of cellular processes governed by ion channel complexes to processes such as trans- Potassium channel cellular adhesion and gene transcription. Given this expansive influence of ion channels on cellular behaviour it Sodium channel is perhaps no surprise that aberrant ion channel expression is a common occurrence in cancer. This review will − focus on the conducting and non-conducting roles of the auxiliary subunits of various Ca2+,K+,Na+ and Cl channels and the burgeoning evidence linking such auxiliary subunits to cancer. Several subunits are upregu- lated (e.g. Cavβ,Cavγ) and downregulated (e.g. Kvβ) in cancer, while other subunits have been functionally implicated as oncogenes (e.g. Navβ1,Cavα2δ1) and tumour suppressor genes (e.g. CLCA2, KCNE2, BKγ1) based on in vivo studies. The strengthening link between ion channel auxiliary subunits and cancer has exposed these subunits as potential biomarkers and therapeutic targets. -
Next Generation Massively Parallel Sequencing of Targeted
ARTICLE Next generation massively parallel sequencing of targeted exomes to identify genetic mutations in primary ciliary dyskinesia: Implications for application to clinical testing Jonathan S. Berg, MD, PhD1,2, James P. Evans, MD, PhD1,2, Margaret W. Leigh, MD3, Heymut Omran, MD4, Chris Bizon, PhD5, Ketan Mane, PhD5, Michael R. Knowles, MD2, Karen E. Weck, MD1,6, and Maimoona A. Zariwala, PhD6 Purpose: Advances in genetic sequencing technology have the potential rimary ciliary dyskinesia (PCD) is an autosomal recessive to enhance testing for genes associated with genetically heterogeneous Pdisorder involving abnormalities of motile cilia, resulting in clinical syndromes, such as primary ciliary dyskinesia. The objective of a range of manifestations including situs inversus, neonatal this study was to investigate the performance characteristics of exon- respiratory distress at full-term birth, recurrent otitis media, capture technology coupled with massively parallel sequencing for chronic sinusitis, chronic bronchitis that may result in bronchi- 1–3 clinical diagnostic evaluation. Methods: We performed a pilot study of ectasis, and male infertility. The disorder is genetically het- four individuals with a variety of previously identified primary ciliary erogeneous, rendering molecular diagnosis challenging given dyskinesia mutations. We designed a custom array (NimbleGen) to that mutations in nine different genes (DNAH5, DNAH11, capture 2089 exons from 79 genes associated with primary ciliary DNAI1, DNAI2, KTU, LRRC50, RSPH9, RSPH4A, and TX- dyskinesia or ciliary function and sequenced the enriched material using NDC3) account for only approximately 1/3 of PCD cases.4 the GS FLX Titanium (Roche 454) platform. Bioinformatics analysis DNAH5 and DNAI1 account for the majority of known muta- was performed in a blinded fashion in an attempt to detect the previ- tions, and the other genes each account for a small number of ously identified mutations and validate the process. -
Algorithms for Transcriptome Quantification and Reconstruction from RNA-Seq Data
Georgia State University ScholarWorks @ Georgia State University Computer Science Dissertations Department of Computer Science Fall 11-16-2012 Algorithms for Transcriptome Quantification and Reconstruction from RNA-Seq Data Serghei Mangul Follow this and additional works at: https://scholarworks.gsu.edu/cs_diss Recommended Citation Mangul, Serghei, "Algorithms for Transcriptome Quantification and Reconstruction from RNA-Seq Data." Dissertation, Georgia State University, 2012. https://scholarworks.gsu.edu/cs_diss/71 This Dissertation is brought to you for free and open access by the Department of Computer Science at ScholarWorks @ Georgia State University. It has been accepted for inclusion in Computer Science Dissertations by an authorized administrator of ScholarWorks @ Georgia State University. For more information, please contact [email protected]. ALGORITHMS FOR TRANSCRIPTOME QUANTIFICATION AND RECONSTRUCTION FROM RNA-SEQ DATA by SERGHEI MANGUL Under the Direction of Dr. Alexander Zelikovsky ABSTRACT Massively parallel whole transcriptome sequencing and its ability to generate full tran- scriptome data at the single transcript level provides a powerful tool with multiple inter- related applications, including transcriptome reconstruction, gene/isoform expression esti- mation, also known as transcriptome quantification. As a result, whole transcriptome se- quencing has become the technology of choice for performing transcriptome analysis, rapidly replacing array-based technologies. The most commonly used transcriptome sequencing pro- tocol, referred to as RNA-Seq, generates short (single or paired) sequencing tags from the ends of randomly generated cDNA fragments. RNA-Seq protocol reduces the sequencing cost and significantly increases data throughput, but is computationally challenging to re- construct full-length transcripts and accurately estimate their abundances across all cell types. We focus on two main problems in transcriptome data analysis, namely, transcriptome reconstruction and quantification. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Cldn19 Clic2 Clmp Cln3
NewbornDx™ Advanced Sequencing Evaluation When time to diagnosis matters, the NewbornDx™ Advanced Sequencing Evaluation from Athena Diagnostics delivers rapid, 5- to 7-day results on a targeted 1,722-genes. A2ML1 ALAD ATM CAV1 CLDN19 CTNS DOCK7 ETFB FOXC2 GLUL HOXC13 JAK3 AAAS ALAS2 ATP1A2 CBL CLIC2 CTRC DOCK8 ETFDH FOXE1 GLYCTK HOXD13 JUP AARS2 ALDH18A1 ATP1A3 CBS CLMP CTSA DOK7 ETHE1 FOXE3 GM2A HPD KANK1 AASS ALDH1A2 ATP2B3 CC2D2A CLN3 CTSD DOLK EVC FOXF1 GMPPA HPGD K ANSL1 ABAT ALDH3A2 ATP5A1 CCDC103 CLN5 CTSK DPAGT1 EVC2 FOXG1 GMPPB HPRT1 KAT6B ABCA12 ALDH4A1 ATP5E CCDC114 CLN6 CUBN DPM1 EXOC4 FOXH1 GNA11 HPSE2 KCNA2 ABCA3 ALDH5A1 ATP6AP2 CCDC151 CLN8 CUL4B DPM2 EXOSC3 FOXI1 GNAI3 HRAS KCNB1 ABCA4 ALDH7A1 ATP6V0A2 CCDC22 CLP1 CUL7 DPM3 EXPH5 FOXL2 GNAO1 HSD17B10 KCND2 ABCB11 ALDOA ATP6V1B1 CCDC39 CLPB CXCR4 DPP6 EYA1 FOXP1 GNAS HSD17B4 KCNE1 ABCB4 ALDOB ATP7A CCDC40 CLPP CYB5R3 DPYD EZH2 FOXP2 GNE HSD3B2 KCNE2 ABCB6 ALG1 ATP8A2 CCDC65 CNNM2 CYC1 DPYS F10 FOXP3 GNMT HSD3B7 KCNH2 ABCB7 ALG11 ATP8B1 CCDC78 CNTN1 CYP11B1 DRC1 F11 FOXRED1 GNPAT HSPD1 KCNH5 ABCC2 ALG12 ATPAF2 CCDC8 CNTNAP1 CYP11B2 DSC2 F13A1 FRAS1 GNPTAB HSPG2 KCNJ10 ABCC8 ALG13 ATR CCDC88C CNTNAP2 CYP17A1 DSG1 F13B FREM1 GNPTG HUWE1 KCNJ11 ABCC9 ALG14 ATRX CCND2 COA5 CYP1B1 DSP F2 FREM2 GNS HYDIN KCNJ13 ABCD3 ALG2 AUH CCNO COG1 CYP24A1 DST F5 FRMD7 GORAB HYLS1 KCNJ2 ABCD4 ALG3 B3GALNT2 CCS COG4 CYP26C1 DSTYK F7 FTCD GP1BA IBA57 KCNJ5 ABHD5 ALG6 B3GAT3 CCT5 COG5 CYP27A1 DTNA F8 FTO GP1BB ICK KCNJ8 ACAD8 ALG8 B3GLCT CD151 COG6 CYP27B1 DUOX2 F9 FUCA1 GP6 ICOS KCNK3 ACAD9 ALG9 -
Muscle Enriched Lamin Interacting Protein (Mlip) Binds Chromatin and Is Required for Myoblast Differentiation
cells Article Muscle Enriched Lamin Interacting Protein (Mlip) Binds Chromatin and Is Required for Myoblast Differentiation Elmira Ahmady 1,2, Alexandre Blais 1,3,4 and Patrick G. Burgon 5,* 1 Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, Ottawa, ON K1H 8M5, Canada; [email protected] (E.A.); [email protected] (A.B.) 2 Molecular Signaling Laboratory, University of Ottawa Heart Institute, Ottawa, ON K1Y 4W7, Canada 3 Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, ON K1H 8M5, Canada 4 University of Ottawa Centre for Infection, Immunity and Inflammation (CI3), Ottawa, ON K1H 8M5, Canada 5 Department of Chemistry and Earth Sciences, College of Arts and Sciences, Qatar University, Doha 999043, Qatar * Correspondence: [email protected] Abstract: Muscle-enriched A-type lamin-interacting protein (Mlip) is a recently discovered Amniota gene that encodes proteins of unknown biological function. Here we report Mlip’s direct interaction with chromatin, and it may function as a transcriptional co-factor. Chromatin immunoprecipitations with microarray analysis demonstrated a propensity for Mlip to associate with genomic regions in close proximity to genes that control tissue-specific differentiation. Gel mobility shift assays confirmed that Mlip protein complexes with genomic DNA. Blocking Mlip expression in C2C12 myoblasts down- regulates myogenic regulatory factors (MyoD and MyoG) and subsequently significantly inhibits myogenic differentiation and the formation of myotubes. Collectively our data demonstrate that Mlip is required for C2C12 myoblast differentiation into myotubes. Mlip may exert this role as a transcriptional regulator of a myogenic program that is unique to amniotes. Citation: Ahmady, E.; Blais, A.; Burgon, P.G. -
Ciliary Dyneins and Dynein Related Ciliopathies
cells Review Ciliary Dyneins and Dynein Related Ciliopathies Dinu Antony 1,2,3, Han G. Brunner 2,3 and Miriam Schmidts 1,2,3,* 1 Center for Pediatrics and Adolescent Medicine, University Hospital Freiburg, Freiburg University Faculty of Medicine, Mathildenstrasse 1, 79106 Freiburg, Germany; [email protected] 2 Genome Research Division, Human Genetics Department, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 KL Nijmegen, The Netherlands; [email protected] 3 Radboud Institute for Molecular Life Sciences (RIMLS), Geert Grooteplein Zuid 10, 6525 KL Nijmegen, The Netherlands * Correspondence: [email protected]; Tel.: +49-761-44391; Fax: +49-761-44710 Abstract: Although ubiquitously present, the relevance of cilia for vertebrate development and health has long been underrated. However, the aberration or dysfunction of ciliary structures or components results in a large heterogeneous group of disorders in mammals, termed ciliopathies. The majority of human ciliopathy cases are caused by malfunction of the ciliary dynein motor activity, powering retrograde intraflagellar transport (enabled by the cytoplasmic dynein-2 complex) or axonemal movement (axonemal dynein complexes). Despite a partially shared evolutionary developmental path and shared ciliary localization, the cytoplasmic dynein-2 and axonemal dynein functions are markedly different: while cytoplasmic dynein-2 complex dysfunction results in an ultra-rare syndromal skeleto-renal phenotype with a high lethality, axonemal dynein dysfunction is associated with a motile cilia dysfunction disorder, primary ciliary dyskinesia (PCD) or Kartagener syndrome, causing recurrent airway infection, degenerative lung disease, laterality defects, and infertility. In this review, we provide an overview of ciliary dynein complex compositions, their functions, clinical disease hallmarks of ciliary dynein disorders, presumed underlying pathomechanisms, and novel Citation: Antony, D.; Brunner, H.G.; developments in the field.