A universal taxonomy of viruses is essential for a comprehensive view of the virus world and for communicating the complicated evolutionary relationships among viruses. However, there are major differences in the conceptualisation and approaches to virus classification and nomenclature among virologists, clinicians, agronomists, and other interested parties. Here, we provide recommendations to guide the construction of a coherent and comprehensive virus taxonomy, based on expert scientific consensus. Firstly, assignments of viruses should be congruent with the best attainable reconstruction of their evolutionary histories, i.e., taxa should be monophyletic. This fundamental principle for classification of viruses is currently included in the International Committee on Taxonomy of Viruses (ICTV) code only for the rank of species. Secondly, phenotypic and ecological properties of viruses may inform, but not override, evolutionary relatedness in the placement of ranks. Thirdly, alternative classifications that consider phenotypic attributes, such as being vector-borne , infecting a certain type of host  or displaying specific pathogenicity , may serve important clinical and regulatory purposes but often create polyphyletic categories that do not reflect evolutionary relationships. Nevertheless, such classifications ought to be maintained if they serve the needs of specific communities or play a practical clinical or regulatory role. However, they should not be considered or called taxonomies. Finally, while an evolution-based framework enables viruses discovered by metagenomics to be incorporated into the ICTV taxonomy, there are essential requirements for quality control of the sequence data used for these assignments. Combined, these four principles will enable future development and expansion of virus taxonomy as the true evolutionary diversity of viruses becomes apparent. Transforming an existing phenotypic classification of viruses into one based on evolutionary relationships that can accommodate the vast number of viruses characterized in metagenomics and environmental studies is an ongoing challenge. This Consensus View explains how such a taxonomy can be expanded to encapsulate viral diversity and to recognize independent biological origins of different virus groups. The International Committee on Taxonomy of Viruses (ICTV) is the official body mandated by the International Union of Microbiology Societies to develop and maintain a taxonomy of viruses and the naming of their taxa. Throughout its history, the rules and codes associated with taxonomy have been updated many times in response to new discoveries, changes in understanding of evolutionary relationships among viruses, and, importantly, the advent of new technologies, such as high-throughput sequencing (HTS) that have vastly increased our global knowledge of viral diversity.With roots in a pregenomic age, the criteria used for virus classification . In contrast, the naming of viruses is not regulated by the ICTV.Rank: A relative position in a hierarchy. The ICTV taxonomy provides up to 15 ranks, with the highest (top) termed realm, and the lowest  rank termed species.Taxon: A taxonomic category for a group of viruses that is evolutionarily related and whose members may share similar properties. In a hierarchical classification, the demarcation criteria that define higher-rank taxa are shared with all lower-level taxa within.Taxonomy: A biological classification based on evolutionary relationships in which viruses are assigned to a series of hierarchical taxa (classification) with regulated naming of component taxa (nomenclature).An expert group convened by the ICTV in 2016 debated and affirmed a policy to allow viruses known from their genome sequences alone to be incorporated into virus taxonomy. This policy enables taxonomic assignments without requiring prior knowledge of a virus phenotypic properties, such as host range or pathogenicity, nor isolation of viruses in cell culture/local lesion hosts, or visualization of virions . SubsequThe creation of a unified evolutionary taxonomy that incorporates viruses classified both by traditional and metagenomics-based analyses requires considerable knowledge and insight into how virus properties are genomically encoded, about their evolutionary histories, and the influence of past recombination or reassortment of genomic regions on phylogenetic congruence. Furthermore, viruses have multiple, independent, and likely ancient evolutionary origins . A group of 45 basic and clinical virologists, bioinformaticians, and evolutionary and structural biologists met in Oxford, United Kingdom, in April 2022, to develop a community-wide consensus on methodologies used for virus classification and to establish an integrated and internally consistent taxonomic framework. The discussions focused primarily on how an evolutionary taxonomy of all viruses infecting eukaryotes, archaea, and bacteria might be constructed, which tools and approaches could be used, and how this process could be guided by identification of the most evolutionarily informative attributes of virus genome sequences and their organization. The group also considered the broader issue of how to reconcile an expanding genetic and structural classification with a partly phenetic classification developed by virologists over many decades that takes into account, among other properties, clinical and regulatory utility, virus/host ecology, and epidemiology.The meeting achieved a substantial consensus on a range of approaches and challenges for taxonomy development, with all but two of the 45 participants endorsing a series of agreed recommendations in the form of four virus taxonomy principles . We beli1: Virus taxonomy should reflect the evolutionary history of viruses. Most viruses can be assigned to independent virus realms, each with an inferred separate evolutionary origin. Members of each realm possess sets of ancestral orthologous genes, termed hallmark genes, typically corresponding to replication or virion formation modules within their genomes. Their evolutionary relationships define monophyletic taxonomic assignments within each of these virus groups.2: Virus properties may guide assignment of ranks to maximize their utility. While evolutionary relationships determine the topology of virus taxonomies, the ranks assigned within it are human-made constructs, with up to 15 available from realm to species. Placement of viruses should follow patterns of evolutionary, genomic, and phenotypic properties; for example, species assignments may be based on host range, disease associations, or epidemiology, provided that such categories result in monophyletic groups.3: Taxonomy is but one of many possible means to classify viruses. The taxonomy produced by the ICTV provides an overarching framework for classifying viruses based on evolutionary relationships. However, alternative classifications based on, for example, clinical or epidemiological properties or regulatory requirements have their own utilities in specific circumstances. These may not follow evolutionary relationships  or may include polyphyletic categories, such as arboviruses or human immunodeficiency viruses, that have epidemiological or clinical value but cannot be represented within an evolutionary taxonomy.4: Taxonomic assignments of viruses inferred from metagenomic sequences require strict sequence quality control. Sequence-based assignment of a new taxon in the absence of other virus characterization requires it to be both accurate and complete. Published guidelines for minimum information about an uncultivated virus genome for taxonomic assignment have been produced [produced .Ranks used for virus taxonomy  must reflect degrees of evolutionary relatedness of the viruses assigned at each rank . This imWe recognize that the establishment of a coherent virus taxonomy requires a variety of tools and approaches to reconstruct the underlying evolutionary relationships of viruses across their spectrum of diversity. Reconstruction of the deeper evolutionary histories of viruses is particularly challenging due to the lack of conserved genes across all virus genomes. This reflects the growing certainty that viruses have emerged on multiple independent occasions –22. The Despite the lack of universal virus genes, considerable progress has been made recently in better defining virus groups that share common ancestry ,24. The Adnaviria, Duplodnaviria, and Varidnaviria. Viruses in these three realms encode major capsid proteins (MCPs) that are structurally radically different, as well as distinct virion assembly and genome packaging machineries [Virion morphogenesis modules were chosen as the defining characters for DNA viruses with larger genomes and govern assignments into the realms hineries ,19,26, shineries ,27.Riboviria [Monodnaviria , and Ribozyviria . The realm Riboviria unifies RNA viruses (kingdom Orthornavirae) and reverse-transcribing viruses (kingdom Pararnavirae), all of which encode homologous right-handed palm-domain RNA-directed RNA polymerase (RdRP) or reverse transcriptase (RT) genes, respectively. The phylogeny of these RdRPs and RTs was, therefore, used to guide the taxonomy within the Riboviria. In contrast, the capsid genes of RNA viruses fall into several unrelated groups, many likely to have been separately acquired from their hosts [Monodnaviria encode homologous histidine–hydrophobic residue–histidine (HUH) superfamily endonucleases [Kolmioviridae, currently the sole family in the realm Ribozyviria, have small circular negative-sense RNA genomes that do not encode an RNA polymerase but contain a particular ribozyme that serves to define the realm.On the other hand, the key features of the genome replication machinery are the most suitable for defining the realms iboviria , Monodnair hosts  or are cucleases ,29, but Tymovirales in the realm Riboviria. However, their capsid morphologies are diverse, including particles that are isometric (members of the Tymoviridae), filamentous/helical , or form no particles at all (members of the Deltaflexiviridae and fungus-infecting members of the Alphaflexiviridae). Even within a family, the phylogeny of capsid genes may be noncongruent with that of the replication genes, such as between genera of Alphaflexiviridae [Martellivirales share relatively closely related RdRPs and other genes involved in replication, such as helicases and capping enzymes, but produce flexible filamentous, rod-shaped, or icosahedral particles constructed from unrelated capsid proteins [Virus evolution is frequently punctuated by large-scale genome reorganizations and the exchange of gene modules analogous to horizontal gene transfer in prokaryotes. For example, alpha-, beta-, gamma-, and deltaflexiviruses and tymoviruses possess an evolutionarily conserved set of replication genes (Rep) that define their classification in the order iviridae . Similarproteins , or no cRiboviria and the ssDNA viruses to the realm Monodnaviria [Duplodnaviria infecting Mycolicibacterium species, are substantially influenced by horizontal gene transfer [Furthermore, capsid genes can be exchanged between viruses that are otherwise evolutionarily unrelated. For example, a range of plant and animal RNA viruses and small single-stranded (ss) DNA viruses encode homologous horizontal single a jelly-roll capsid proteins, despite the RNA viruses being assigned to the realm dnaviria –33. Sometransfer . These vtransfer . In suchAlthough gene-sharing networks are informative for tracking gene exchange across virus groups , the relWithin individual virus realms, currently, a range of genome sequence comparison methods are needed to describe and assign viruses to different taxonomic ranks. For viruses with similar genome sequences, i.e., within the same species and genus, genetic relationships may be inferred from alignments of nucleotide or amino acid sequences of (near) complete genomes or of specific genes. The relationship among viruses can be further explored by phylogenetic tree inference and analysis, and where this is not practical, clustering by sequence similarity and analysis of pairwise distance distributions using tools such as PASC , DEmARC At the intermediate levels of family, order, and class, relationships can be inferred by comparing sequences of evolutionarily conserved hallmark genes using sensitive methods for protein family profile comparison, such as HHPred , with suTaxonomic assignments at higher ranks, such as phyla, kingdoms, and realms, are based either on sequence comparison of the most highly conserved hallmark proteins and/or on protein structure comparisons. The latter can be informative for making evolutionary comparisons because homologous proteins typically retain similar structures, even when the corresponding amino acid sequences have diverged to the point that they are no longer sufficiently similar to infer homology based on sequence alone. Structure-based comparison methods include clustering based on estimates of distances between structures and structure-based phylogenetic analysis . Much ofRiboviria using sequence analysis alone has been questioned, as these are based on the purported arbitrariness of the alignment of highly divergent sequences [Riboviria [Hallmark gene-based assignments at the levels of kingdom and realm can be hampered by high levels of protein sequence divergence, with homology only detectable once high-resolution structures for the corresponding proteins become available. For this reason, the validity of the phylogenetic analyses used to designate kingdoms and phyla through evolutionary relationships among RdRP and RT genes of equences . Alignmeequences , but, uliboviria  matched iboviria ,59 at aliboviria ,60.Bamfordvirae, which falls within the realm Varidnaviria. Conversely, established structural relationships can now be used to inform sequence alignments and allow the incorporation of the ever-expanding wealth of virus sequence data into taxonomy [Varidnaviria and Duplodnaviria [Along similar lines, structure-based clustering and phylogeny of capsid proteins can provide a powerful approach when the reliable inference of evolutionary relationships by sequence comparisons (“traceability”) is lost –63. Thustaxonomy ,64. Detednaviria .Herelleviridae) [The ranges of sequence divergence  over which the various analytical methods used in virus taxonomy are defined overlap substantially . The recviridae)  is an ilviridae) . ConflicOrthornavirae [Our understanding of virus origins and the evolutionary relationships inferred from hallmark gene trees within realms may change over time as analytical methods improve and new data become available. These may necessitate revisions to virus taxonomy. The extent to which the currently assigned realms encapsulate the full range of virus diversity and their distinct evolutionary origins remains under intense scrutiny. On the one hand, the possibility exists that large-scale metagenomics-based analyses of viruses in the environment are already approaching saturation of higher taxonomic ranks, such that the overall structure of virus taxonomy is stabilizing, even if many taxa remain to be delineated at lower levels. For example, a recent analysis of RNA virus diversity in the marine virome has vastly expanded the number of distinct viruses and putative genera and families, but these mostly can be assigned to the five previously established phyla within the riboviriad kingdom rnavirae . On the rnavirae  and urgeVaridnaviria [Bamfordvirae and Helvetiavirae. Furthermore, many (relatively) narrow groups of viruses, particularly those with hyperthermophilic archaea as hosts [As an indication of future possible changes, structural analysis of virus capsid proteins within the realm dnaviria  indicateas hosts , cannot as hosts .While undoubtedly incomplete, the creation of the rank of realm and the recognition of a separate origin for each provides a substantive basis for a coherent and stable taxonomy of the viruses within them. The high value of hallmark gene relationships should be at the core of classification decisions at higher taxonomic ranks and will provide a blueprint for realm expansion, as needed in the future.The primary value of taxonomy lies in its ability to sort organisms into categories that reflect their evolutionary history, be it at the species, genus, or family level, or higher ranks. All evolutionarily based taxonomic codes, including that of the ICTV, follow the principle that each rank must be congruent with evolutionary relationships. The ICTV Code states that species should be monophyletic and, therefore, cannot group unrelated viruses sharing similarities in their physical properties, type of host/vector, disease associations, or other aspects of their phenotype, which might be polyphyletic in nature. This stipulation conflicts with many alternative (nontaxonomic) classifications of viruses used in medical, veterinary, agricultural, and regulatory fields described in Principle 3.A hierarchical taxonomy based on evolutionary relationships of hallmark genes is inviolate and cannot support polyphyletic categories. However, the taxonomic rank is ultimately a human-made construct that arbitrarily assigns diversity into discrete categories that can be more readily conceptualized and named. The ICTV provides up to 15 ranks to partition virus diversity, from realm to species , althougFlaviviridae Study Group to the species Hepacivirus C, in distinction from those infecting New World monkey species (Hepacivirus A and Hepacivirus B) and horses (Hepacivirus D) [Flaviviridae genera, such as Pestivirus A, Pestivirus B, Pestivirus C, and Pestivirus D, which, in this case, show substantially different host ranges and disease associations. This constitutes one of many cases in which ecological drivers  have shaped the evolutionary history of viruses and can be used to inform taxonomic outcomes.Such choices and the delineation of associated sequence divergence thresholds are typically made by expert groups of virologists, in most cases, ICTV Study Groups. As an example, the various genotypes of hepatitis C virus (HCV), all of which exclusively infect humans, were assigned by the ICTV virus D) . This isOrthobunyavirus (family Peribunyaviridae) [Bunyamwera orthobunyavirus, were considered to render these viruses so phenotypically distinctive as to warrant assignment to separate species [Similarly, virological knowledge informed a revision of species demarcation criteria among members of the genus viridae) . The dif species . The speThe “usefulness” of a taxonomy combining clustering by sequence similarity with phenotypic properties highlights the need for extensive interdisciplinary work bridging the fields of bioinformatics and virology, creating and maintaining taxonomy as the knowledge of viral diversity and their disease impact increases. At higher ranks, evolutionary and structural biologists may provide the more sophisticated approaches required to extract and evaluate genome sequence and structural features that depict the deepest evolutionary relationships of virus kingdoms and phyla.For viruses identified by genomes assembled in metagenomic sequence analyses, a phylogeny-based classification is required. Although information on the host range, effects on the host, and other phenotypic traits of these viruses is typically lacking, many of their attributes might be inferred from their genome organization and composition, evolutionary affinities of different genes, and base composition. In some cases, these characteristics may also suggest the likely host range –84. AddiThere is, therefore, an asymmetry between the classification and rank assignments of viruses with well-defined phenotypic properties and the entirely genome-based classification required for viruses characterized by metagenomic analyses alone. Nevertheless, there is a clear consensus that viruses identified in metagenomic studies should be incorporated by the ICTV into virus taxonomy as far as the evidence allows . Indeed,We recognize that classifications of viruses by clinicians, veterinarians, agronomists, and regulators may differ from a virus taxonomy that is grounded in evolutionary relationships. Numerous widely used clinical or veterinary virus designations cannot be supported by taxonomic assignments but often better serve clinical and regulatory purposes. The following cases, drawn from many possible examples, illustrate the various forms of mismatch that can occur.Lentivirus.The clinical and societal utility of the terms human immunodeficiency virus type 1 (HIV-1) and HIV type 2 (HIV-2) as the causative agents of AIDS requires no further explanation. However, the taxonomic assignment of these viruses has remained problematic because neither possesses a single common ancestor distinct from chimpanzee- (HIV-1) or sooty mangabey- (HIV-2) infecting viruses from which they derive  and SARS-CoV-2, the latter being the causative agent of COVID-19. As with HIV-1 and HIV-2, however, SARS-CoV and SARS-CoV-2 cannot logically be assigned to separate virus species despite their clinical distinctiveness. They are classified collectively as members of the species ast Asia . While sLouping ill virus and Tick-borne encephalitis virus, respectively, in the genus Flavivirus of the family Flaviviridae [Ixodes ricinus, while TBEV is found in central Europe, Scandinavia, and large parts of Asia, with deer as the primary host reservoir. However, the current taxonomic assignments of LIV and TEBV to two separate species are not supported by their genetic relationships; members of the species Louping ill virus are phylogenetically interspersed with members of the species Tick-borne encephalitis virus. Consistent with previous observations [Louping ill virus (LIV) and tick-borne encephalitis virus (TBEV) are currently members of two separate species, iviridae . The tworvations , while sEnterovirus C, in the family Picornaviridae, includes a clinically highly diverse range of member viruses, such as poliovirus types 1, 2, and 3, as well as several largely nonpathogenic enterovirus types. Their assignment to the same species was necessitated by their high degree of sequence similarity and their ability to recombine [The species ecombine . HoweverSome broader terms such as “respiratory viruses,” “viral meningitis,” and “arboviruses” (arthropod-borne viruses) have wide clinical utility, being the staples of textbooks on infectious diseases and of medical reviews. However, each of the listed groups contains large sets of otherwise unrelated viruses across many different virus families and orders .Adnaviria, Duplodnaviria, most members of Varidnaviria, and some of Monodnaviria belong to Baltimore class I (dsDNA genomes), but other viruses in the latter two realms possess ssDNA genomes and accordingly belong to class II. Members of Riboviria with RNA genomes are represented in all the remaining classes III to VII, whereas the one member of the Ribozyviria is in class V [The classic paper by David Baltimore  proposed class V .The broader point to be drawn from these examples is that an evolutionary taxonomy is not the only way to classify viruses, and its requirement to be congruent with evolutionary relationships can clash with classifications of viruses that are of greater value to clinicians, veterinarians, agronomists, regulators, and other stakeholders. It is similarly important to recognize that although species assignment thresholds can be selected so as to divide viruses into informative categories (see previous section), the requirement for congruency with evolutionary relationships means that this is not always possible.Bean common mosaic virus, whereas a second potyvirus causing mosaic in cowpea was classified as a member of Blackeye cowpea mosaic virus, and a third potyvirus causing dwarfing (growth reduction) in peanuts was classified as a member of Peanut stripe virus. Only when the genomes of these three viruses were sequenced did it become clear that they were closely related and therefore members of the same species, which currently retains the name Bean common mosaic virus [The assignment of virus species with members often possessing quite distinct clinical or epidemiological attributes contrasts strongly with assignments of bacterial species in the classification of prokaryotes, for which each clinically or otherwise phenotypically distinct bacterial strain has been assigned to separate species with descriptive definitions. The situation is not unlike the historical classification practices of plant virologists; viruses were named after their specific disease presentations and assigned as unique members of a species bearing the same name. For example, a potyvirus causing mosaic in common bean was classified as a member of the species ic virus .Homo sapiens). Virus names are simply what virologists want to call viruses, inasmuch as naming practices have also evolved to address concerns such as discrimination and stigmatization . Virus names are not within the remit of the ICTV. Viruses can be named with no restrictions on orthography , numbering or language—indeed, many viruses have different names in different languages. Taxon names, in contrast, are within the mandate of the ICTV. They are written with an initial capital letter, are italicized, and may only contain letters of the Latin alphabet, Arabic numerals, and a limited number of symbols. Furthermore, taxon names are constant irrespective of the language that refers to them.The ICTV has always maintained a typographic distinction between virus names and names of the taxa to which they are assigned , similarEnterovirus C. Far Eastern and Russian spring–summer strains of TBEV are handled at Biosafety Level (BSL) 4 in the United States, whereas the European strains are at BSL 3 and LIV at BSL 2, regulatory distinctions that do not map onto their current species assignments.The ICTV typographic conventions reinforce the typological distinction between viruses as real-world objects and taxa as human-made classes or categories. This practice enables virus isolates to be mapped onto species assignments in a much more flexible way than the simple one-to-one correspondence that applies in many other areas of biology. This flexibility provides the framework for an evolutionarily based taxonomy to run alongside a variety of functional virus classifications without conflict. For example, the codes of practice for laboratory handling of viral pathogens are more useful if based upon a categorization of viruses, not species. This is exemplified by specific biocontainment requirements for HIV-1 and HIV-2, and the now highly restrictive regulatory framework established for poliovirus laboratory handling, which contrasts markedly with containment requirements for other members of the species Taxonomic definitions can incorporate elements of virus descriptions in their formulations, as is often the case with plant viruses. Similarly, virus descriptions can be more informative if they refer to the corresponding taxa to which they are assigned. Alternative classification systems have their own rules and utilities in the real world, and their use removes conflicts that might otherwise arise if all virus classifications were irrevocably tied to an evolutionarily based taxonomy.As emphasized above, the assignment of viruses discovered by metagenomic analyses to new or established virus taxa must be based upon their genome sequences. Although the sample source is usually known, a genome sequence provides the key information about relatedness to other viruses, genome organization, inferred mechanisms of replication, and, increasingly, aspects of its virion structure, morphology, and even receptor use. As a unique source of information on the organism that is being classified, the genome sequence accordingly should be coding complete, i.e., contain the entire complement of protein-coding genes of the virus (as far as can be reasonably inferred), annotated and effectively free from sequencing or assembly errors. Thus, detailed bioinformatic information on the sequence acquisition methods used and their quality control is essential for taxonomic assignments of such viruses ,11,100.The ICTV does not require multiple, unique examples of sequences representing a new virus for taxonomic assignment, although characterization of additional members in such new taxa provides further information on genetic diversity and genome completeness. However, when a single sequence represents a species, it is particularly important to ensure that it depicts the virus genome as accurately and completely as possible . The ICTAcquisition of metagenomically derived sequence data in large environmental samples provides the best opportunity to fully explore and evaluate the true genetic diversity of viruses. However, the size and genetic complexity of such libraries and the widely used short read Illumina-based sequencing methods may hamper the assembly of complete genome sequences of viruses within samples. Consequently, much of the reported genetic diversity in such studies is based on phylogenetic comparisons of partial genome sequences, often restricted to reads spanning informative genes, such as the polymerases of riboviriad viruses. Such studies are vital for documenting the extent of virus diversity and, indeed, the completeness or otherwise of the current realm and kingdom structure of the virosphere. Partial sequences can also be used to improve the statistical support of large phylogenies that underlie the classification of viruses into taxonomic groups. However, our consensus view is that, without evidence of completeness, genome sequences obtained in such studies cannot be used as the sole basis for the creation of new taxa, meaning that the majority of viral sequences in current metagenomic datasets do not meet the standards for classification at this time. Further progress in long-read sequencing may help to speed up the acquisition of complete viral sequences with greater confidence in their proper assembly and completeness.Our description of the four principles of virus taxonomy—which represent the consensus view of the workshop attendees—and the associated review of the evidence we provide gives a roadmap to the ICTV and its constituent expert committees and Study Groups to further develop and expand virus taxonomy. Implementation of the guidelines will also provide consistency and clarity for virus classification to the wider virology community. We acknowledge the vital contribution that expertise in bioinformatics and phylogenetics applied to virus sequence and structure analysis makes to the ever-expanding virus taxonomy. We also recognize the importance of input from virology experts in developing a comprehensive view of the relationships among viruses at all taxonomic ranks.While there is an established consensus on the need to incorporate viruses characterized in metagenomic studies into virus taxonomy , the out


Serine incorporator (SERINC) proteins 1–5 (SERINC1-5) are involved in the progression of several diseases. SERINC2-4 are carrier proteins that incorporate the polar amino acid serine into membranes to facilitate the synthesis of phosphatidylserine and sphingolipids. SERINC genes are also differentially expressed in tumors. Abnormal expression of SERINC proteins occurs in human cancers of the breast, lung, colon, liver, and various glands, as well as in mouse testes. SERINC proteins also affect cleft lip and palate and nerve-related diseases, such as seizure Parkinsonism and borderline personality. Moreover, SERINC proteins have garnered significant interest as retroviral restriction factors, spurring efforts to define their function and elucidate the mechanisms through which they operate when associated with viruses. Human SERINC proteins possess antiviral potential against human immunodeficiency virus (HIV), SARS-COV-2, murine leukemia virus (MLV), equine infectious anemia virus (EIAV), and hepatitis B virus (HBV). Furthermore, the crystal structure is known, and the critical residues of SERINC5 that act against HIV have been identified. In this review, we discuss the most prevalent mechanisms by which SERINC3 and SERINC5 antagonize viruses and focus on the potential therapeutic applications of SERINC5/3 against HIV. Drosophila melanogaster, which revealed a novel fold comprised of ten transmembrane helices organized into two subdomains and bisected by a long diagonal helix  family of proteins is a multiple-transmembrane-segment family composed of five members, SERINC1-5 . SERINC2al helix . Furtheral helix . All famal helix . Furtheral helix . Howeveral helix .SERINC family proteins participate in the development of many diseases, such as cancer, nerve-related disease, and other diseases. SERINC1 is associated with the development of lung cancer and hepatocarcinoma , while SAccording to the International Mouse Phenotyping Consortium (IMPC) database, SERINC2-knockout mice show impaired glucose tolerance (IGT). IGT is an indicator of pre-diabetes, which eventually turns into diabetes, and both conditions predispose patients to cardiovascular alterations. IGT is also associated with increased cardiovascular risk . Thus, SPrevious studies demonstrated that SERINC proteins are involved in several processes, such as defense against RNA and DNA viruses. It has been shown that SERINC3 and SERINC5 inhibit human immunodeficiency virus (HIV) infection at an early stage of the viral cycle, regulate viral fusion, and act as restriction factors . Bibert It has been demonstrated that complex interactions between virus and host are involved at each stage of the virus life cycle. Host restriction factors are an integral part of the host defense against a viral pathogen by limiting the virus at each stage of viral replication and sending out continuous pathogen-invasion signals. Host restriction factors and viral accessory proteins are involved in the interaction between viruses and host cells. Viruses seek to penetrate the resistance of host cells, while the host cells seek to prevent entry by the virus invader through complex mechanisms . SeveralViral accessory proteins are not necessary for replication . However+ T cells and monocytes isolated from chronic HIV-1-infected patients  . The canpatients . SERINC5patients . Interespatients  , gammaretrovirus (MLV), equine infectious anemia virus (EIAV), and hepatitis B virus (HBV) viral protein . SERINC5+ early, Rab7+ late, and Rab11+ recycling endosomes. However, SIV Nef promotes SERINC5 degradation via the proteasome pathway  in HIV-1, recognizes target cells, while gp41, the transmembrane subunit of Env, mediates the membrane fusion of HIV-host cells and the cytoplasmic release of the virus core . In the Drosophila melanogaster at subnanometer and near-atomic resolutions, respectively  and neuraminidase (NA) serotypes. Recently, it was reported that SERINC5 has inhibitory activity against H7/N1-pseudotyped HIV-1 particles , althougBetacoronavirus genus, and subgenus Sarbecovirus  is an accessory protein expressed by MLV, which reduces the expression of SERINC5 protein in mice through the endosomal/lysosomal pathway. Two key residues, P31 and R63, of MLV glycoGag are important for the regulation of SERINC5. The interaction between glycoGag and SERINC5 in living cells leads to the relocation of SERINC5 from the plasma membrane to the spotted compartment around the nucleus, and the Y36XXL39 motif of MLV glycoGag is essential in this process . EIAV S2Some non-retroviruses may be sensitive to SERINC5. It has been demonstrated that SERINC5 inhibits glycoprotein pseudoforms of several retroviruses, including HIV-1, A-MLV, RD114, M-MPV, orthomyxovirus , rhabdovirus (RABV), paramyxovirus , and sand virus . The retroviral core also affects the sensitivity of the virus to SERINC5 .HBV, an enveloped and hepatophilic DNA virus, antagonizes SERINC3 and SERINC5 through large (LHB), mid-sized (MHB), and small (SHB) surface proteins of HBV. By contrast, SERINC3 binds to LHBs, relocalizes these proteins to the Golgi apparatus, and reduces the glycosylation modification of envelope proteins, inhibiting HBV secretion. Transmembrane domains 4–6 of SERINC proteins are important for glycosylation modification and HBV inhibition .As mentioned above, the SERINC protein family is involved in the progression of viral infection. During the process of viral infection, SERINC-family proteins are a constitutive host resistance factor, which inhibits viral infection by integrating into virus particles. Currently, the viruses known to be inhibited by the SERINC family include HIV, SIV, MLV, EIAV, HBV, influenza virus, CSFV, and FV . Thus, tSERINC3 and five are correlated with virus resistance. The antiviral function of the SERINC family has been widely investigated. However, the details of the regulatory mechanism, including the identity of the transcription factor regulating SERINC family transcription and the molecules directly interacting with the SERINC family, should be investigated to reveal its antiviral network. Although cell therapy and gene therapy of some restriction factors against retroviruses have been assessed in clinical trials, the therapeutic potential of the SERINC family against viral diseases has not yet been properly investigated .+ T cells has proved to be effective and safe in HIV-positive patients , screening for activating drugs for SERINC3 and -5 may increase the number of potential targets. Although the crystal structure and critical residues of SERINC5 have been determined (C-C motif chemokine receptor 5 (CCR5) is the major cofactor required for HIV entry into the cell. Gene editing of CCR5 on autologous CD4patients . Kang etpatients . Thus, Stermined , residuetermined . High-thtermined . The tar


Geminiviridae and a negative-sense single-stranded RNA rhabdovirus, Lettuce necrotic yellows virus, the majority of the viruses that were detected in the xylem belong to the group of positive-sense RNA viruses. The diversity of the genome organization and virion morphology of those viruses indicates that xylem exploitation appears to be a widely adapted strategy for plant viruses. This review outlines the examples of the xylem-associated viruses and discusses factors that regulate virus inhabitation of the xylem as well as possible strategies of virus introduction into the xylem. In some cases, plant disease symptoms have been shown to be closely related to virus colonization of the xylem. Inhibiting viral xylem invasion could raise potential attractive approaches to manage virus diseases. Therefore, the identification of the host genes mediating virus interaction with the plant xylem tissue and understanding the underlying mechanisms call for more attention.Viruses are trailblazers in hijacking host systems for their own needs. Plant viruses have been shown to exploit alternative avenues of translocation within a host, including a challenging route through the xylem, to expand their niche and establish systemic spread, despite apparent host-imposed obstacles. Recent findings indicate that plant viruses from many families could successfully hack xylem cells in a broad range of plant hosts, including herbaceous and perennial woody plants. Similar to virus-related structures present in the phloem, virus particles and membrane-containing viral replication complexes are often observed in the xylem. Except for a few single-stranded DNA viruses in the family  Lettuce necrotic yellows virus (LNYV) were not observed in the thin sections of the phloem cells of tobacco (Nicotiana glutinosa L.). Instead, the virus particles were successfully visualized in juvenile xylem cells [In plants, the xylem tissue functions to transport water and minerals unidirectionally, from roots towards the aboveground parts ,2. At them cells . With evTobacco mosaic virus (TMV) in the xylem guttation from tomato (Solanum lycopersicum L.) [Beet necrotic yellow vein virus (BNYVV) were frequently found in the undifferentiated and mature xylem vessel elements and xylem parenchyma of sugar beet (Beta vulgaris L.) [Tomato mosaic virus (ToMV) and Pepper mild mottle virus (PMMV) were recovered and visualized from the guttation fluid of tomato (Lycopersicon esculentum Mill.) and green pepper (Capsicum annuum L.), respectively [Blueberry shoestring virus (BSV) was shown to achieve the long-distance movement through the xylem, in addition to the phloem of a low woody shrub, highbush blueberry (Vaccinium corymbosum L.) [Citrus tristeza virus (CTV) reignited an interest in exploring virus–xylem interactions in perennial woody plants by demonstrating that CTV can invade and further develop a ‘clustered oasis’ of infected cells in the xylem tissue of Citrus macrophylla Wester [Research on the virus-xylem interplay can be traced back to the 1930s when Johnson revealed the presence of icum L.) . Since garis L.) . The infectively . With suectively . Compareosum L.) . Furthera Wester . It is pVerticillium dahliae Klebahn, a filamentous fungus, could secret a toxic protein named xylanase 4 to degrade the xylem’s cell walls and induce necrosis. The destruction of the xylem vessels results in wilt syndrome in the infected cotton plants [Brome mosaic virus (BMV) is able to invade xylem cells in oat (Arena sativa L.) and barley (Hordeum vulgare L.), leaf mosaic symptoms are attributed to the virus accumulation in the juvenile phloem and mesophyll cells [The healthy and functional xylem of a plant is important to its vigorous growth. The invasion of certain vascular pathogens was shown to damage the xylem function and trigger disease syndromes. For instance, a xylem-residing n plants . In contll cells . In contll cells ,17. SuchThere is no doubt that virus invasion in the xylem has critical outcomes for plant health and disease production in crops. Nonetheless, our understanding of the virus–xylem interactions is still in its infancy. Thus, it would be important to understand the connection of virus xylem invasion and disease manifestation.Alphaflexiviridae, Benyviridae, Bromoviridae, Closteroviridae, Potyviridae, Secoviridae, Sobemoviridae, Tombusviridae, and Virgaviridae  in cucumber (Cucumis surivus L.), and BMV in wheat (Triticum aestivum L.) and barley [Zucchini yellow mosaic virus (ZYMV) at a site beneath the treated area. The detection of the virus in the xylem of the upper leaves demonstrated that ZYMV could enter xylem vessels and move [Turnip mosaic virus (TuMV) in the Nicotiana benthamiana Domin [Southern bean mosaic virus (SBMV) in the pinto bean (Phaseolus vulgaris L.) [The fact that the xylem tissue is located deep inside a plant presents certain challenges for studying virus–xylem interactions. Thus, the limitation of available techniques has hindered the development of research in this area . Early ed barley ,12,13,20d barley . As an aand move . Stem stna Domin , and Souaris L.) ,28, resuaris L.)  could prIn situ observations based on fluorescence confocal microscopy and TEM could serve as straightforward methods to confirm the presence of a plant virus in xylem-associated cells. The thickened secondary cell walls in the mature xylem cells, which contain abundant cellulose and lignin, make them easily stained and recognizable. Confocal microscopy was used to examine the distribution of TuMV in the xylem of N. benthamiana by observing the localization of a green fluorescence protein (GFP)-tagged 6K2, a membrane-associated protein of TuMV [Artichoke mottle crinkle virus, Carnation yellow fleck virus (CYFV), and Cucumber green mottle mosaic virus (CGMMV), was detected in the xylem-associated cells mounted in the ultrathin sections of tobacco (N. glutinosa), artichoke (Cynara Cardunculus var. scolymus (L.) Benth.), carnation (Dianthus caryophyllus L.), and cucumber, respectively [in situ immunohistochemical microscopy is used as an option for general low magnification optical microscopy. Virus particles are typically labeled with antibodies raised against the virus coat protein (CP), which are further detected by a secondary antibody conjugated with a chromogenic substrate. Virus detection is usually coupled with tissue staining . This approach allowed the detection of tobacco (Nicotiana tabacum L. cv. Samsun) xylem cells harboring Prune dwarf virus and cucumber xylem cells harboring CGMMV as well as ZYMV or Cucumber mosaic virus (CMV) in co-infection with ZYMV [in situ three-dimensional analysis can overcome these limitations by integrating data collected from serial sections [ of TuMV . Similar of TuMV . Compareectively ,22,31. Oectively . In addiith ZYMV ,34. Nevesections . Yet, unin situ hybridization assay, and fluorescent antibody technique have been also used in some applications [In addition to the techniques mentioned above, the dot-blot immunoassay, ications ,37. UnfoWith high magnification microscopy, such as TEM, the virus-induced structures in the xylem tissue and sap can be documented in much detail. Although microscopy observations only capture information from a specific moment in virus infection, by assembling these snapshots into a bigger picture, we can put together a blueprint for virus biology in the host xylem.Squash mosaic virus, CMV, Cowpea chlorotic mottle virus (CCMV), and ZYMV, were detected in the guttation fluid of infected cucumbers [The most frequently detected forms of a plant virus in the xylem are intact virions and virion crystalline aggregates. In French and Elder’s study, the particles of many plant viruses, including ucumbers . It is aucumbers ,40,41,42ucumbers . RegardlRice yellow mottle virus (RYMV) accumulated in the xylem parenchyma cells and the phloem sieve elements of rice (Oryza sativa L.) were observed [Crystalline virion arrays are frequently observed in xylem-associated cells, including tracheary elements (vessels and tracheids) and xylem parenchyma. For instance, in addition to being present in the phloem, ground parenchyma, and epidermis, hexagonal crystalline bundles of CYFV virions were seen in the mature xylem tracheary elements of infected spray carnation plants . Likewisobserved . Such obN. benthamiana plants, TuMV replication complexes were observed in the mature xylem vessels, in addition to being present in the phloem sieve elements [Potato virus Y (PVY)-induced cytoplasmic inclusions were found in the epidermis, mesophyll, phloem parenchyma, phloem companion cells, and also in the xylem tracheary elements of Solanaceous plants [Soilborne wheat mosaic virus (SBWMV) into the mature xylem vessels of red winter wheat (T. aestivum L. cv. Vona) resulted in the formation of virus-induced inclusion bodies containing virion particles [Other virus-induced structures observed for a number of viruses in xylem-associated cells are membrane-associated viral replication complexes (VRCs) and viral inclusion bodies. In virus-infected elements . Potato s plants . The invarticles . In addition to the accumulation of virus particles and VRCs, other virus forms, such as viral genomic RNA molecules, possibly in association with viral or host proteins, could also exist in xylem tissues. However, they have not yet been reported. Thus, exploring the potential virus forms or structures and understanding how they mediate virus interaction with and multiplication and/or transport in the xylem is the next challenge.The findings of plant virus-induced VRCs and virion aggregations in xylem-associated cells, along with virus particles in the xylem sap, indicate that plant viruses can colonize xylem cells to complete their replication cycle and, subsequently, spread to distal plant tissues. From this point of view, the xylem and phloem play similar roles. Considering that the reported xylem-invading viruses belong to different families, each of which is involved in unique interactions with the host, a suite of different models of virus–xylem interplay may be appropriate. Tobacco ringspot virus (TRSV) might be transmitted into the xylem during nematode feeding [Cuscuta sp.) penetrates into the host xylem and phloem and, thus, could form a path for virus introduction into the xylem, such as in the case described with CMV [Potato mop-top virus transmitted by Spongospora subterranean  Lagerheim, BNYVV transmitted by Polymyxa betae Keskin, and CNV transmitted via Olpidium bornovanus (Sahtiyanci) Karling, it has been assumed that they are introduced through the fungus-penetrating hyphae generated during host colonization. Based on the anatomic examination of the P. betae-mediated BNYVV infection in sugar beet, Giunchedi and Pollini suggested that BNYVV reaches the xylem tissue of the taproot via a growing rootlet where the zoospores of the fungus have penetrated [The presence of virus complexes in the xylem raises the question of how these viruses arrive to this destination. Under natural conditions, most plant viruses are introduced into a plant by vectors such as insects, nematodes, parasitic weeds, or fungi, with some viruses transmitted vertically through seeds. In the plant–vector–virus interaction triangle, vector-mediated transmission may directly introduce some viruses into the xylem . Aphids  feeding . Furtherwith CMV . Regardinetrated . Such diUsually, the xylem is not the only tissue that the virus colonizes. Thus, it is generally accepted that the xylem colonization by a plant virus results from niche expansion. The virus cell-to-cell movement-based model suggests that the xylem-residing viruses move there from adjacent non-xylem cells. It is well known that plant viruses can pass through modified plasmodesmata in a form of ribonucleoprotein complexes (RNP) or virions ,48,49. TWe cannot exclude the possibility that the virions or RNPs of some viruses could move directly into mature xylem cells by some mechanisms because the movement of the virus through the thickened xylem cell walls is theoretically possible . Pits inMany host and viral factors, including proteins and even RNA motifs involved in virus phloem entry and transportation, have been identified . Yet, thCitrus macrophylla. In contrast, a virus mutant with the deletion of the p33 protein gene is able to invade the immature xylem cells, which consequently results in the enhancement of disease [Bean common mosaic virus (BCMV), named “Bean black root virus NL3”, into the xylem of bean (Phaseolus vulgaris L. ‘Bataaf’) stems was delayed upon co-infection with another BCMV strain NY15. The NL3 migration from the primary leaves to the stem was hampered in the dual infection possibly due to lower virus loading or a shifted virus distribution as compared to those upon the single-virus inoculations [2+ ions from pit membranes by the capsid shells of sobemoviruses results in the disruption of the pit membranes and facilitates virion transport between vessels [The ability of plant viruses to enter the xylem tissue does not appear to correlate with the morphology of virus particles or their size, as the shapes of the virions as well as their dimensions are quite diverse. On the other hand, similar to the viral factors that mediate virus movement in the phloem, one can expect that virus-encoded proteins, especially the movement proteins and CPs, play key roles in the virus translocation into and within the xylem. However, our knowledge of those is essentially lacking. Yet, we know that certain alterations on the virus side can affect its ability to enter the xylem. Thus, the wild-type CTV variant of the T36 strain remains primarily limited to the phloem-associated cells in  disease ,52. Furtulations ,24. Addi vessels . Arabidopsis thaliana (L.) Heynhold and N. benthamiana, the phloem appears to have stronger transcriptional and translational alterations than the surrounding tissues, including xylem [Plant host factors also play important roles in virus xylem invasion. This would be expected since viruses rely on the host machinery to complete the infection cycle, including replication, virion assembly, and movement in the xylem. Undoubtedly, host immunity could affect the ability of plant viruses to build a niche in the xylem. It is well known that the xylem acts as a field of battle between the plant hosts and vascular wilt pathogens . The recng xylem . V. dahliae [Brassica juncea (L.) Czernohorsky) plants. The invasion of TuMV into the vasculature not only triggered phloem necrosis, but also induced xylem gel occlusions [The formation of gel xylem occlusions is a common defense phenomenon observed in the xylem vessels against vascular wilt pathogens. For instance, the timely deposition of occluding gums and gels secreted by xylem parenchyma cells and tyloses could effectively trap the spread of the filamentous fungus  dahliae . Similarclusions . Thus, tSolanaceous plants corelated with the intensity of the host hypersensitive response [From the perspective of defense signaling, host PCD and reactive oxygen species (ROS) signaling are of importance. The accumulation of PVY cytopathological inclusion bodies in the xylem of response . In the response . These dresponse . From thPhaseolus vulgaris L.) or monarch cowpea (Vigna unguiculata L.) stem sections below the steam-treated nodes. Interestingly, only the beetle-transmissible viruses, SBMV, Bean pod mottle virus, and Cowpea severe mosaic virus, but not Sunn-hemp mosaic virus or TRSV, could successfully establish infection in the non-wounded tissue above the steam-killed area. This showed that the virus xylem translocation is associated with transmissibility by leaf-feeding beetles [Acquisition and transmission by vectors are central to the infection cycle of most plant pathogenic viruses. It has been suggested that xylem invasion by viruses is aligned with vector transmissibility. Gergerich and Scott injected several purified viruses into the Black Valentine bean ( beetles . From thEn masse, hijacking the xylem cells seems to be a widely adapted strategy for plant viruses to promote infection in a broad range of plant hosts.As more viruses are found to be associated with the xylem, our understanding of the importance of these largely overlooked interactions increases. The colonization of host xylem tissue provides plant viruses with a new niche to establish a successful infection. In particular, xylem invasion provides the virus with alternative routes for systemic spread, but also promotes virus acquisition by corresponding vectors. To date, the majority of the plant viruses found in the xylem is from the group of viruses with +ssRNA genomes, with a few that possess a −ssRNA or a ssDNA genome. The viruses can be classified into many different virus families and exhibit a range of diverse characteristics such as various shapes and unique genome organizations. Similarly, the diversity of plant hosts extends from herbaceous to perennial woody plants. Apple stem pitting virus, grapevine infected with Grapevine rupestris stem pitting-associated virus, and stone fruit infected with Tomato ringspot virus [Despite a number of discoveries, most of which are discussed in this review, our understanding of virus–xylem interactions at the molecular level is still in its infancy. This is primarily caused by the difficulties tracing the virus buried in the xylem or isolating xylem-specific cells. However, thanks to the pioneering investigations of the interactions between viruses and the xylem tissue, a suite of virus–xylem interplay models that could explain virus entry and transport in the xylem conduit has been developed. In addition, some virus- and host-derived processes and factors that influence the xylem invasion by viruses have been identified. Next, we have yet to understand whether viruses spread via the xylem tissue unidirectionally or bidirectionally and how the virus entities traverse the plant cell walls. From the perspective of agronomy and horticulture, the investigation of virus–xylem interactions could provide potential solutions to manage severe virus-induced disease syndromes. Take CTV as an example, the invasion of CTV into the xylem tissue of citrus has been associated with the induction of stem pitting, a disease that is also commonly found in many tree crops, such as the apple crop infected with ot virus ,58,59,60


The authors would like to make the following corrections to the published paper : Section 5.3. W Protein Binds Host STAT to Create High Molecular Weight Complexes that Inhibit Type I IFN Signalling, page 10, which should now read:There are some mistakes in the order of references and their citations in the original article due to bibliography software errors . In the The W protein has been found to be the dominant STAT-1 inhibitor compared to V/P/C counterparts . Unlike V, C, and P proteins that are mostly cytoplasmic, the W protein of NiV co-localizes to the nucleus with STAT-1 in its unphosphorylated form [39]. This indicates that W either binds STAT-1 in the nucleus, preventing its nuclear export and recycling in the JAK-STAT pathway, or transports latent (and unphosphorylated) STAT-1 directly to the nucleus where W then sequesters it as a high molecular weight non-functional complex  [39].There was an error in the original publication. 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Elements of perceived control are associated with recidivism in offender populations. We investigated the application of locus of control to the frequency of personal involvement with the law and to beliefs surrounding the likelihood of future contact with the legal system. We hypothesized that, as the number of sentencings or legal experiences increased, locus of control would externalize. We also predicted that increased legal involvement would lead to greater belief in the likelihood of future involvement. A statistically significant path model suggests that locus of control appears to be a predictor of increased criminality, as opposed to the other way around. Further, data suggests that an offender will view future legal involvement as more likely if they have experienced greater lifetime contact with the legal system. We speculate on the possible application of these data to intervention strategies identifying offenders with high priority intervention needs. Consistent stress, loss of control, and hopelessness have been linked to recidivism and external locus of control in both adult and juvenile populations . Locus oUnfortunately, many offenders enter the legal system with more externalized locus of control, the belief that they have little or no control over what happens to them. Understanding more about where this externalization comes from may help correctional systems to better rehabilitate offenders toward more internalized control thinking.Many express hopeless resignations when faced with the prospect of incarceration for current or continued criminal activity. Often, offenders attribute criminality to survival necessities and to a sense of resignation directed at their surrounding environments . This apThese feelings can be perpetuated by consistent exposure to stressful external factors . These cConsistent and seemingly inescapable stress, such as relationship stress, factors of poverty, violence exposure, and drug use are strongly associated with criminality. These stressors may influence the development of external locus of control . This isThis hopelessness may lead individuals back toward criminality if their surrounding environmental factors do not change. Up to 83% of offenders in the United States are re-arrested or re-incarcerated within three years of their release from detention . This caIt may thus be possible to use locus of control measurements to identify those individuals at greater need for intervention early on in their involvement with the legal system. In order to do this, however, the predictive relationship between the two must first be demonstrated empirically. This is the goal of the present study.Factors such as poverty, dangerous living conditions, and social influences are often linked to criminal behavior . These fLocus of control does not appear to be a static construct. Rather, the literature points to a more dynamic and malleable nature where locus of control may change and shift from internal to external and back again based on varying environmental factors . This isThis principle of flexibility is an important one for the investigation of externalizing locus of control and its potential use as an early indicator of intervention need. If locus of control can be changed based on environmental factors and treatment, then it may be possible to use the construct as a viable testing platform for intervention programs.Concerning the potential applications to rehabilitative practice, internal locus of control has been linked to adaptive behaviors and high levels of resilience . ExternaThe increased stress exposure, autonomy restriction, social restriction, and danger exposure often coupled with incarceration may, then, influence the development of the more maladaptive external locus of control .This has significant implications for treatment efficacy in offender populations as well. Any intervention focused on controlling the individual, deterrence, building extrinsic motivation, or basic discipline does little to curb recidivism. This is true for interventions based inside a correctional facility or out in the community. However, programs focused on building intrinsic motivation and those based upon restorative intent are far more effective in reducing recidivism .This is particularly impactful here because of the analytic distinction between extrinsic ineffectiveness and intrinsic effectiveness. Extrinsic interventions, or those designed to emphasize external reasoning, appear to be ineffective in dealing with recidivism while those focused on building internal motivation for change and behavioral decisions, appear to be effective in curbing recidivism . TherefoIncarceration itself results in behavioral disturbances and significant mental health consequences that may lead to repeat incarceration, particularly in juvenile offenders . Indeed,More internal orientations predict greater levels of help-seeking behavior, treatment participation, and positive treatment outcomes. Individuals with more external orientation displayed more resistance to behavioral changes and treatment strategies. These are significant locus of control-based influencers on treatment amenability .Helplessness is a related concept when discussing treatment and intervention efficacy. It is a depression-like behavior observed consistently in animals and humans when perceived control over the environment is lacking . This feThis construct has a neurobiological foundation, granting important biological validity to this investigation. Repeated exposure to inescapable tail shocks in rats results in decreased observable desire to leave the aversive environment, decreases social exploration, and activates the serotonergic dorsal raphe nucleus, an area of the brain implicated in depression . This tyFor offenders, failed attempts to break a criminal cycle or feelings of hopelessness relating to uncontrollable environmental factors create stressors that influence criminal continuity . FeelingGiven established relationships between locus of control, environmental factors, treatment amenability, and lifetime recidivism risk, we examined whether repeated contact with the legal system is related to externalizing locus of control in adult criminal offenders. From the available literature, we developed and tested the following hypothesis: as the number of sentencings or legal experiences increases, locus of control will predictively externalize. Meaning that the more times an individual has been in contact with the legal system, the more they will view the causes of their legal involvement as external. We further hypothesized that increased legal involvement would lead to greater belief in the likelihood of future legal involvement.This research utilized a correlational design. All participants were given the same surveys in similar conditions. Informed consent was obtained from each participant, and all participants were educated on the definitions of the variables before completing the survey to ensure self-reporting could be as accurate as possible.Surveys were administered on a volunteer, one-on-one basis in designated jail visitation areas or in the inmate’s personal living area. Participants retained the option to fill out the survey on their own or have the administrator read the survey to them and transcribe their responses to compensate for any limited literacy, educational disadvantage, or other written language barriers.N = 112.We surveyed 117 county jail inmates in Washington, a state in the northwest of the United States. In order to participate in the study, volunteers needed to be currently incarcerated in a county jail and at least 18 years of age. Additionally, they needed to understand written or spoken English at an appropriate level to receive informed consent, as we did not have the ability to provide translators for non-English speaking participants. Five surveys were removed from analysis for lack of completion or as extreme outliers. The final sample for analysis was In order to ensure the protection of inmate identity, minimal demographic data were collected, at the insistence of both the participating jail facilities and the Institutional Review Board (IRB). This was due to the potentially undecided nature of some legal cases, as county jail inmates may be awaiting trial, sentencing, or some part of their record may be sealed. This was an unfortunate omission, as we lost any potential ability to evaluate relationships within these demographic areas. Nonetheless, compliance with this requirement was necessary for the completion of the research.Participants were asked to answer limited demographic questions regarding their age, race/ethnicity, education level, household type (to determine homelessness status), and household income. It is important to note that demographic factors were recorded only to give a descriptive representation of the population. Excluding age, which we did analyze in line with established age-crime relationships, they were otherwise not intended to be used in the analysis and were not expressly relevant to the hypothesis. Additionally, many participants did not know their household income, and thus we lacked significant information to use this variable in the analysis.Of course, we understand that there may be significant relationships between these factors and locus of control and are aware that these factors play important parts as antecedents to criminality. However, our hypothesis sought to explore only the relationships between locus of control, legal involvement, and predictive thoughts on future incarceration. A detailed analysis on the relationship between these variables and our demographic identifiers is both interesting and valuable, but beyond the intended scope of this research.We developed a questionnaire designed to record self-reported data concerning the legal history of study participants. This questionnaire asked participants to estimate their lifetime “legal involvement”, defined as the number of times they had experienced arrest, jail time awaiting trial or court date, jail sentences, prison sentences, electronic home monitoring (house arrest), community service or community restitution, group homes or work release programs, probation, and “other” involvement with the law, which they were asked to explain. We computed “legal involvement” as the sum-total of all self-reported involvement in these categories. To develop the list of categories, we consulted with participating jail facilities and a corrections expert present on the IRB in order to determine possible sentencing types.Participants then used a Likert-type scale to indicate how likely, if at all, they believed they were to be involved with the law post-release, which we termed “future likelihood”. Finally, they were presented with an open-ended question which prompted them to reflect on the causes for their current and past legal involvement. For the Involvement with the Law Questionnaire, Cronbach’s alpha was .78.The Revised Causal Dimension Scale was selected because it is designed to examine locus of control with respect to prompting scenarios, allowing locus of control to be examined with specific respect to legal involvement . This alWe coded data based on participant responses to numeric or scale-based questions. Some responses were converted to bivariate data to reflect affirmative/negative answer types. We recorded self-reported frequencies of juvenile legal involvement and lifetime legal involvement. We calculated a third variable, adult legal involvement, as the difference between lifetime and juvenile legal involvement. We were not able to access personal files to verify these numbers, as county jail inmates typically have protected files, and thus rely only on the assumed accuracy of the self-reported frequencies.We coded two different variables concerning future likelihood. The first was a dichotomous response variable concerning whether participants thought future legal involvement was likely. Those that selected “yes” were asked to rate how likely future legal involvement was to occur on a Likert-type scale. A score of one denoted “extremely unlikely,” and a score of eight denoted “extremely likely.” A score of zero was coded for all participants who indicated “no” on the bivariate question, to indicate they did not believe there was any likelihood of future involvement.Finally, we recorded total scores for each of the four Revised Causal Dimension Scale elements, termed “locus of causality,” “stability,” “personal control,” and “external control” after their original operational designations . The scaWe first performed a preliminary data check to examine our data for normality. Some data were highly kurtotic, and thus we performed appropriate logarithmic transformations to achieve the required normality for further parametric testing. We then performed descriptive analysis, correlational analysis and linear regression analysis to extrapolate meaning from the data using a combination of R, a programming language used for statistical analysis, IBM’s SPSS statistics software, and G*Power analysis software.SD = 8.886), 75.9% reported graduating from high school or a General Education Diploma (G.E.D.) program, and 33.9% reported being homeless before becoming incarcerated. Ethnically, the participants identified as White , Hispanic or Latin American , Black or African American , Native American or Alaska Native , Asian , Multiracial , or some “other” ethnicity .The mean age of participants was 33.73 years  reported a juvenile criminal record (n = 63). Concerning future legal involvement, 68.8% indicated that they believed future legal involvement was likely (n = 77). The mean future likelihood score across participants was 3.67 (SD = 3.08).Concerning past legal involvement, 56.3% of participants (SD = 25.57). For adult and lifetime legal involvement, the mean frequencies were 51.19 (SD = 66.02) and 62.65 (SD = 77.18), respectively.We divided legal involvement into juvenile, adult, and lifetime frequencies. The mean juvenile legal involvement was 11.47 individual instances of involvement (n = 32), while the moderate and high categories represented 38.4% (n = 43) and 33.0% (n = 37), respectively.We divided lifetime legal involvement into low, moderate, and high levels of involvement. These are defined as total involvement greater than 0.5 standard deviations below the mean for low, within +/- 0.5 standard deviation from the mean for moderate, and greater than 0.5 standard deviation for high involvement. These parameters were selected in order to achieve the most even distribution possible between the categories. Maintaining a standard deviation difference of less than 1 likewise ensured that the low and high categories would represent more than just the extreme ends of the overall distribution, giving a more realistic picture of the differences between participants. The low legal involvement category represented only 28.6% of participants (SD = 6.00). External control had a mean score of 13.71 (SD = 6.69), while the mean stability score was 12.28 (SD = 5.82). Finally, personal control exhibited a mean score of 17.41 (SD = 6.20).For the Revised Causal Dimensions Scale, the range of response scores was between 3 and 27. For locus of causality, the mean score was 17.11  = .24, p = .01, r(110) = .33, p = .000, and r(110) = .35, p = .000, respectively. All correlations were positive, suggesting a positive relationship between these variables.Future likelihood was statistically significantly correlated with juvenile, adult, and lifetime legal involvement, r(110) = .25, p = .007. This reflects a relationship between the belief in future legal involvement and the perception of surrounding environmental stability. In our case, it is likely that “stability” reflects a continuity of the conditions that surrounded incarceration, thus influencing future likelihood predictions in a positive correlational relationship.Future likelihood was significantly and positively correlated with the stability element in r(110) = .24, p = .01; r(110) = .20, p = .04, but not with juvenile legal involvement, r(110) = .14, p = .15. Stability was significantly correlated with juvenile legal involvement, r(110) = .20, p = .03, and future likelihood, r(110) = .25, p = .01.Locus of causality was significantly correlated with adult and lifetime legal involvement, r(110) = -.22, p = .02, and external control was not statistically significantly correlated with any of the causal dimensions variables.Personal control and external control were minimally correlated with legal involvement. Personal control was only statistically significantly correlated with future likelihood, r(110) = -.32, p = .001; r(110) = -.29, p = .002. There is a significant positive correlation between personal control and locus of causality, r(110) = .34, p = .000. These relationships reflect the statistically significant correlations between the same variables identified by the original authors at the p < .05 level.Some correlations are present between the various Revised Causal Dimension Scale elements, all of which reflect correlations measured by the original scale authors. Our data showed a significant negative correlation between personal control and both external control and stability, t(110) = 2.95, p = .004, accounting for an acceptable proportion of variance therein, 2R = .07, F = 8.67, p = .004. This offers some evidence that our results are in line with known relationships.Linear regression and multiple linear regression analyses were used to build predictive models between our variables of interest . To estat(110) = -3.49, p = .001, and accounts for a modest proportion of the variance, 2R = .10, F = 12.18, p = .001. Additionally, external control is significantly predictive of locus of causality, β = -.31, t(110) = -3.46, p = .001, and predicted a modest amount of variance, 2R = .10, F = 11.99, p = .001. Personal control is individually predictive of stability, β = -.29, t(110) = -3.13, p = .002, but accounts for less of the variance compared to external control, 2R = .08, F = 9.97, p = .002.External control significantly predicts personal control, β = -.32, t(110) = 2.21, p = .03, but accounts for a small proportion of the variance, 2R = .04, F = 4.64, p = .03. Juvenile involvement is significantly predictive of future likelihood, β = .24, t(110) = 2.54, p = .01, and accounts for a proportion of the variance in likelihood scores, 2R = .06, F = 6.47, p = .01, suggesting more juvenile involvement leads to viewing future legal involvement as more likely.Stability significantly predicts juvenile legal involvement, β = .20, p = .004) and accounts for a significant proportion of the variance there, 2R = .12, F = 4.66, p = .004. Stability and personal control were both significant predictors in this model individually, β = .21, t(110) = 2.19, p = .03; β = -.22, t(110) = -2.18, p = .03, with locus of causality approaching significance as an individual predictor, β = .18, t(110) = 1.86, p = .07. Thus, higher stability and lower personal control scores significantly predict higher future likelihood scores.A combined model of stability, personal control, and locus of causality is overall a statistically significant predictor of future likelihood (p = .000) and accounted for a sizable proportion of variance in adult involvement, 2R = .20, F = 9.24, p = .000. Locus of causality, β = .20, t(110) = 2.32, p = .02, future likelihood, β = .26, t(110) = 2.98, p = .004, and juvenile legal involvement, β = .23, t(110) = 2.57, p = .01, all provided significant contributions to the model.Adult legal involvement is significantly predicted by locus of causality, future likelihood, and juvenile legal involvement. A multiple linear regression containing all three predictors was statistically significant . It is important to remember that the prompting scenario for the Revised Causal Dimension Scale scores asked participants to describe the overall cause for their legal involvement. This means that stability scores are reflective of how stable  they believe that cause to be. Thus, results suggest that the less changeable one perceives the causes of legal involvement to be, the more likely they will be to believe future involvement will occur.The correlation between adult legal involvement and locus of causality was positive, indicating that more legal involvement reflected viewing the involvement as an aspect of personal quality  identifying measurable scores on locus of control would allow for a prediction of how likely an individual believes future legal involvement is and (b) may allow for predictive identification of those at high risk for recidivism, which we defined as increased adult legal involvement.The significance of our data rests in the suggestion that high-recidivism individuals may already have elements of external locus of control when they enter the system. This may fuel a continuation in criminality. Further, our correlations suggest that offenders view criminality as a personal attribute, yet still view the related life circumstances as unchangeable. Linear regression analysis also provides evidence to support this latter portion, illustrating that such control-based orientations may be predictive of increased legal involvement in adulthood. Together, these results suggest that addressing control orientations centered on life circumstances may be an effective strategy for offender rehabilitation. Further research is necessary to properly evaluate this in a treatment-oriented setting.It is also possible that identifying those individuals with high stability and low personal control orientations related to these legal causes may serve as the first indicator to high recidivism risk. If these patterns could be identified while the offender still has relatively low legal involvement, they may be more likely to break the criminal cycle following control orientation-based treatment. Further research is needed to properly evaluate the efficacy of these speculations. Nonetheless, our results provide an important foundation to these future rehabilitative directions.