Pregnancy intention, intimate partner violence, and the use of prenatal care in Jordan

Previous research has suggested an association between intimate partner violence and pregnancy intention status, and pregnancy intention status and the use of prenatal care services, however much of these studies have been conducted in high income countries (HIC) rather than low and middle income countries (LMIC). The objectives of this study were to examine the relationship between pregnancy intention status and intimate partner violence, and pregnancy intention status and the use of prenatal care among ever-married women in Jordan.^ Data were collected from a nationally representative sample of women interviewed in the 2007 Jordan Demographic and Health Survey. The sample was restricted to ever-married women, 15–49 years of age, who had a live birth within the five years preceding the survey. Multivariate logistic regression analyses was used to determine the relationship between intimate partner violence and pregnancy intention status, and pregnancy intention status and the use of prenatal care services.^ Women who reported a mistimed pregnancy (PORadj 1.96, 95% CI: 1.31–2.95), as well as an unwanted pregnancy (PORadj 1.32, 95% CI: 0.80–2.18) had a higher odds of experiencing lifetime physical and/or sexual abuse compared with women reporting a wanted pregnancy. Women not initiating prenatal care by the end of the first trimester had statistically significant higher odds of reporting both a mistimed (PORadj 2.07, 95% CI: 1.55–2.77) and unwanted pregnancy (PORadj 2.36, 95% CI: 1.68–3.31), compared with women initiating care in the first trimester. Additionally, women not receiving the adequate number of prenatal care visits for their last pregnancy had a higher odds of reporting an unwanted pregnancy (PORadj 2.11, 95% CI: 1.35–3.29) and mistimed pregnancy (POR adj 1.41, 95% CI: 0.96–2.07).^ Reducing intimate partner violence may decrease the prevalence of mistimed or unwanted pregnancies, and reducing both unwanted and mistimed pregnancies may decrease the prevalence of women not receiving timely and adequate prenatal care among women in this population. Further research, particularly in LMIC, is needed regarding the determinants of unintended pregnancy and its association with intimate partner violence as well as with the use of prenatal care services. ^

Exploring the Benefits of a Parent Partner Mentoring Program in Child Welfare

Parent partner mentoring programs are an innovative strategy for child welfare agencies to engage families in case planning and service delivery. These programs recruit and train parents who have been involved in the system and have successfully resolved identified child abuse or neglect issues to work with families with current open cases in the child welfare system. Parent partner mentors can provide social and emotional support, advocacy, and practical advice for navigating this challenging system. Insofar as parent partners share similar experiences, and cultural and socioeconomic characteristics of families, they may be more successful in engaging families and building trusting supportive relationships. The current study presents qualitative data from interviews and case studies of families who were matched with a parent partner in a large county in a Midwestern state. Interviews with families, parent partner mentors, child welfare agency staff, and community partners and providers suggest that parent partner programs may be just as beneficial for parent partner mentors as they are for families being mentored. These programs can build professional skills, help improve self-esteem, provide an avenue for social support, and may potentially prevent recidivism. Parent Partner programs also provide a mechanism for amplifying family voice at all levels of the agency.

Detection and pattern recognition applied to leaves and chromosomes

The Project you are about to see it is based on the technologies used on object detection and recognition, especially on leaves and chromosomes. To do so, this document contains the typical parts of a scientific paper, as it is what it is. It is composed by an Abstract, an Introduction, points that have to do with the investigation area, future work, conclusions and references used for the elaboration of the document. The Abstract talks about what are we going to find in this paper, which is technologies employed on pattern detection and recognition for leaves and chromosomes and the jobs that are already made for cataloguing these objects. In the introduction detection and recognition meanings are explained. This is necessary as many papers get confused with these terms, specially the ones talking about chromosomes. Detecting an object is gathering the parts of the image that are useful and eliminating the useless parts. Summarizing, detection would be recognizing the objects borders. When talking about recognition, we are talking about the computers or the machines process, which says what kind of object we are handling. Afterwards we face a compilation of the most used technologies in object detection in general. There are two main groups on this category: Based on derivatives of images and based on ASIFT points. The ones that are based on derivatives of images have in common that convolving them with a previously created matrix does the treatment of them. This is done for detecting borders on the images, which are changes on the intensity of the pixels. Within these technologies we face two groups: Gradian based, which search for maximums and minimums on the pixels intensity as they only use the first derivative. The Laplacian based methods search for zeros on the pixels intensity as they use the second derivative. Depending on the level of details that we want to use on the final result, we will choose one option or the other, because, as its logic, if we used Gradian based methods, the computer will consume less resources and less time as there are less operations, but the quality will be worse. On the other hand, if we use the Laplacian based methods we will need more time and resources as they require more operations, but we will have a much better quality result. After explaining all the derivative based methods, we take a look on the different algorithms that are available for both groups. The other big group of technologies for object recognition is the one based on ASIFT points, which are based on 6 image parameters and compare them with another image taking under consideration these parameters. These methods disadvantage, for our future purposes, is that it is only valid for one single object. So if we are going to recognize two different leaves, even though if they refer to the same specie, we are not going to be able to recognize them with this method. It is important to mention these types of technologies as we are talking about recognition methods in general. At the end of the chapter we can see a comparison with pros and cons of all technologies that are employed. Firstly comparing them separately and then comparing them all together, based on our purposes. Recognition techniques, which are the next chapter, are not really vast as, even though there are general steps for doing object recognition, every single object that has to be recognized has its own method as the are different. This is why there is not a general method that we can specify on this chapter. We now move on into leaf detection techniques on computers. Now we will use the technique explained above based on the image derivatives. Next step will be to turn the leaf into several parameters. Depending on the document that you are referring to, there will be more or less parameters. Some papers recommend to divide the leaf into 3 main features (shape, dent and vein] and doing mathematical operations with them we can get up to 16 secondary features. Next proposition is dividing the leaf into 5 main features (Diameter, physiological length, physiological width, area and perimeter] and from those, extract 12 secondary features. This second alternative is the most used so it is the one that is going to be the reference. Following in to leaf recognition, we are based on a paper that provides a source code that, clicking on both leaf ends, it automatically tells to which specie belongs the leaf that we are trying to recognize. To do so, it only requires having a database. On the tests that have been made by the document, they assure us a 90.312% of accuracy over 320 total tests (32 plants on the database and 10 tests per specie]. Next chapter talks about chromosome detection, where we shall pass the metaphasis plate, where the chromosomes are disorganized, into the karyotype plate, which is the usual view of the 23 chromosomes ordered by number. There are two types of techniques to do this step: the skeletonization process and swiping angles. Skeletonization progress consists on suppressing the inside pixels of the chromosome to just stay with the silhouette. This method is really similar to the ones based on the derivatives of the image but the difference is that it doesnt detect the borders but the interior of the chromosome. Second technique consists of swiping angles from the beginning of the chromosome and, taking under consideration, that on a single chromosome we cannot have more than an X angle, it detects the various regions of the chromosomes. Once the karyotype plate is defined, we continue with chromosome recognition. To do so, there is a technique based on the banding that chromosomes have (grey scale bands] that make them unique. The program then detects the longitudinal axis of the chromosome and reconstructs the band profiles. Then the computer is able to recognize this chromosome. Concerning the future work, we generally have to independent techniques that dont reunite detection and recognition, so our main focus would be to prepare a program that gathers both techniques. On the leaf matter we have seen that, detection and recognition, have a link as both share the option of dividing the leaf into 5 main features. The work that would have to be done is to create an algorithm that linked both methods, as in the program, which recognizes leaves, it has to be clicked both leaf ends so it is not an automatic algorithm. On the chromosome side, we should create an algorithm that searches for the beginning of the chromosome and then start to swipe angles, to later give the parameters to the program that searches for the band profiles. Finally, on the summary, we explain why this type of investigation is needed, and that is because with global warming, lots of species (animals and plants] are beginning to extinguish. That is the reason why a big database, which gathers all the possible species, is needed. For recognizing animal species, we just only have to have the 23 chromosomes. While recognizing a plant, there are several ways of doing it, but the easiest way to input a computer is to scan the leaf of the plant. RESUMEN. El proyecto que se puede ver a continuación trata sobre las tecnologías empleadas en la detección y reconocimiento de objetos, especialmente de hojas y cromosomas. Para ello, este documento contiene las partes típicas de un paper de investigación, puesto que es de lo que se trata. Así, estará compuesto de Abstract, Introducción, diversos puntos que tengan que ver con el área a investigar, trabajo futuro, conclusiones y biografía utilizada para la realización del documento. Así, el Abstract nos cuenta qué vamos a poder encontrar en este paper, que no es ni más ni menos que las tecnologías empleadas en el reconocimiento y detección de patrones en hojas y cromosomas y qué trabajos hay existentes para catalogar a estos objetos. En la introducción se explican los conceptos de qué es la detección y qué es el reconocimiento. Esto es necesario ya que muchos papers científicos, especialmente los que hablan de cromosomas, confunden estos dos términos que no podían ser más sencillos. Por un lado tendríamos la detección del objeto, que sería simplemente coger las partes que nos interesasen de la imagen y eliminar aquellas partes que no nos fueran útiles para un futuro. Resumiendo, sería reconocer los bordes del objeto de estudio. Cuando hablamos de reconocimiento, estamos refiriéndonos al proceso que tiene el ordenador, o la máquina, para decir qué clase de objeto estamos tratando. Seguidamente nos encontramos con un recopilatorio de las tecnologías más utilizadas para la detección de objetos, en general. Aquí nos encontraríamos con dos grandes grupos de tecnologías: Las basadas en las derivadas de imágenes y las basadas en los puntos ASIFT. El grupo de tecnologías basadas en derivadas de imágenes tienen en común que hay que tratar a las imágenes mediante una convolución con una matriz creada previamente. Esto se hace para detectar bordes en las imágenes que son básicamente cambios en la intensidad de los píxeles. Dentro de estas tecnologías nos encontramos con dos grupos: Los basados en gradientes, los cuales buscan máximos y mínimos de intensidad en la imagen puesto que sólo utilizan la primera derivada; y los Laplacianos, los cuales buscan ceros en la intensidad de los píxeles puesto que estos utilizan la segunda derivada de la imagen. Dependiendo del nivel de detalles que queramos utilizar en el resultado final nos decantaremos por un método u otro puesto que, como es lógico, si utilizamos los basados en el gradiente habrá menos operaciones por lo que consumirá más tiempo y recursos pero por la contra tendremos menos calidad de imagen. Y al revés pasa con los Laplacianos, puesto que necesitan más operaciones y recursos pero tendrán un resultado final con mejor calidad. Después de explicar los tipos de operadores que hay, se hace un recorrido explicando los distintos tipos de algoritmos que hay en cada uno de los grupos. El otro gran grupo de tecnologías para el reconocimiento de objetos son los basados en puntos ASIFT, los cuales se basan en 6 parámetros de la imagen y la comparan con otra imagen teniendo en cuenta dichos parámetros. La desventaja de este método, para nuestros propósitos futuros, es que sólo es valido para un objeto en concreto. Por lo que si vamos a reconocer dos hojas diferentes, aunque sean de la misma especie, no vamos a poder reconocerlas mediante este método. Aún así es importante explicar este tipo de tecnologías puesto que estamos hablando de técnicas de reconocimiento en general. Al final del capítulo podremos ver una comparación con los pros y las contras de todas las tecnologías empleadas. Primeramente comparándolas de forma separada y, finalmente, compararemos todos los métodos existentes en base a nuestros propósitos. Las técnicas de reconocimiento, el siguiente apartado, no es muy extenso puesto que, aunque haya pasos generales para el reconocimiento de objetos, cada objeto a reconocer es distinto por lo que no hay un método específico que se pueda generalizar. Pasamos ahora a las técnicas de detección de hojas mediante ordenador. Aquí usaremos la técnica explicada previamente explicada basada en las derivadas de las imágenes. La continuación de este paso sería diseccionar la hoja en diversos parámetros. Dependiendo de la fuente a la que se consulte pueden haber más o menos parámetros. Unos documentos aconsejan dividir la morfología de la hoja en 3 parámetros principales (Forma, Dentina y ramificación] y derivando de dichos parámetros convertirlos a 16 parámetros secundarios. La otra propuesta es dividir la morfología de la hoja en 5 parámetros principales (Diámetro, longitud fisiológica, anchura fisiológica, área y perímetro] y de ahí extraer 12 parámetros secundarios. Esta segunda propuesta es la más utilizada de todas por lo que es la que se utilizará. Pasamos al reconocimiento de hojas, en la cual nos hemos basado en un documento que provee un código fuente que cucando en los dos extremos de la hoja automáticamente nos dice a qué especie pertenece la hoja que estamos intentando reconocer. Para ello sólo hay que formar una base de datos. En los test realizados por el citado documento, nos aseguran que tiene un índice de acierto del 90.312% en 320 test en total (32 plantas insertadas en la base de datos por 10 test que se han realizado por cada una de las especies]. El siguiente apartado trata de la detección de cromosomas, en el cual se debe de pasar de la célula metafásica, donde los cromosomas están desorganizados, al cariotipo, que es como solemos ver los 23 cromosomas de forma ordenada. Hay dos tipos de técnicas para realizar este paso: Por el proceso de esquelotonización y barriendo ángulos. El proceso de esqueletonización consiste en eliminar los píxeles del interior del cromosoma para quedarse con su silueta; Este proceso es similar a los métodos de derivación de los píxeles pero se diferencia en que no detecta bordes si no que detecta el interior de los cromosomas. La segunda técnica consiste en ir barriendo ángulos desde el principio del cromosoma y teniendo en cuenta que un cromosoma no puede doblarse más de X grados detecta las diversas regiones de los cromosomas. Una vez tengamos el cariotipo, se continua con el reconocimiento de cromosomas. Para ello existe una técnica basada en las bandas de blancos y negros que tienen los cromosomas y que son las que los hacen únicos. Para ello el programa detecta los ejes longitudinales del cromosoma y reconstruye los perfiles de las bandas que posee el cromosoma y que lo identifican como único. En cuanto al trabajo que se podría desempeñar en el futuro, tenemos por lo general dos técnicas independientes que no unen la detección con el reconocimiento por lo que se habría de preparar un programa que uniese estas dos técnicas. Respecto a las hojas hemos visto que ambos métodos, detección y reconocimiento, están vinculados debido a que ambos comparten la opinión de dividir las hojas en 5 parámetros principales. El trabajo que habría que realizar sería el de crear un algoritmo que conectase a ambos ya que en el programa de reconocimiento se debe clicar a los dos extremos de la hoja por lo que no es una tarea automática. En cuanto a los cromosomas, se debería de crear un algoritmo que busque el inicio del cromosoma y entonces empiece a barrer ángulos para después poder dárselo al programa que busca los perfiles de bandas de los cromosomas. Finalmente, en el resumen se explica el por qué hace falta este tipo de investigación, esto es que con el calentamiento global, muchas de las especies (tanto animales como plantas] se están empezando a extinguir. Es por ello que se necesitará una base de datos que contemple todas las posibles especies tanto del reino animal como del reino vegetal. Para reconocer a una especie animal, simplemente bastará con tener sus 23 cromosomas; mientras que para reconocer a una especie vegetal, existen diversas formas. Aunque la más sencilla de todas es contar con la hoja de la especie puesto que es el elemento más fácil de escanear e introducir en el ordenador.

Segregation of viral plasmids depends on tethering to chromosomes and is regulated by phosphorylation

Eukaryotic viruses can maintain latency in dividing cells as extrachromosomal nuclear plasmids. Segregation and nuclear retention of DNA is, therefore, a key issue in retaining copy number. The E2 enhancer protein of the papillomaviruses is required for viral DNA replication and transcription. Viral mutants that prevent phosphorylation of the bovine papillomavirus type 1 (BPV) E2 protein are transformation-defective, despite normal viral gene expression and replication function. Cell colonies harboring such mutants show sectoring of viral DNA and are unable to maintain the episome. We find that transforming viral DNA attaches to mitotic chromosomes, in contrast to the mutant genome encoding the E2 phosphorylation mutant. Second-site suppressor mutations were uncovered in both E1 and E2 genes that allow for transformation, maintenance, and chromosomal attachment. E2 protein was also found to colocalize to mitotic chromosomes, whereas the mutant did not, suggesting a direct role for E2 in viral attachment to chromosomes. Such viral hitch-hiking onto cellular chromosomes is likely to provide a general mechanism for maintaining nuclear plasmids.

The location of Z- and W-linked marker genes and sequence on the homomorphic sex chromosomes of the ostrich and the emu

Perhaps the most striking fact about early Cenozoic avian history some 70 million years ago was the rapid radiation of large, flightless, ground-living birds. It has been suggested that, for a time, there was active competition between these large terrestrial birds and the early mammals. Probably reflecting the above noted early start of Ratitae of the infraclass Eoaves, the presumptive sex chromosomes of their present day survivors, such as the emu and the ostrich, largely remained homomorphic. The signs of genetic differentiation between their still-homomorphic Z and W chromosomes were tested by using two marker genes (Z-linked ZOV3 and the gene for the iron-responsive element-binding protein) and one marker sequence of a part of a presumptive pseudogene (W-linked EE0.6 of the chicken). Their homologues, maintaining 71–92% identities to the chicken counterparts, were found in both the emu (Dromaius novaehollandiae) and the ostrich (Struthio camelus). Their locations were visualized on chromosome preparations by fluorescence in situ hybridization. In the case of the emu, these three marker sequences were localized on both members of the fifth pair of a female, thus revealing no sign yet of genetic differentiation between the Z and the W. The finding was the same with regard to both members of the fourth pair of male ostriches. In the female ostrich, however, the sequence of the gene for the iron-responsive element-binding protein was missing from one of the pairs, thus revealing the differentiation by a small deletion of the W from the Z.

Identification of novel susceptibility loci for inflammatory bowel disease on chromosomes 1p, 3q, and 4q: Evidence for epistasis between 1p and IBD1

The idiopathic inflammatory bowel diseases, Crohn’s disease (CD) and ulcerative colitis (UC), are chronic, frequently disabling diseases of the intestines. Segregation analyses, twin concordance, and ethnic differences in familial risks have established that CD and UC are complex, non-Mendelian, related genetic disorders. We performed a genome-wide screen using 377 autosomal markers, on 297 CD, UC, or mixed relative pairs from 174 families, 37% Ashkenazim. We observed evidence for linkage at 3q for all families (multipoint logarithm of the odds score (MLod) = 2.29, P = 5.7 × 10−4), with greatest significance for non-Ashkenazim Caucasians (MLod = 3.39, P = 3.92 × 10−5), and at chromosome 1p (MLod = 2.65, P = 2.4 × 10−4) for all families. In a limited subset of mixed families (containing one member with CD and another with UC), evidence for linkage was observed on chromosome 4q (MLod = 2.76, P = 1.9 × 10−4), especially among Ashkenazim. There was confirmatory evidence for a CD locus, overlapping IBD1, in the pericentromeric region of chromosome 16 (MLod = 1.69, P = 2.6 × 10−3), particularly among Ashkenazim (MLod = 1.51, P = 7.8 × 10−3); however, positive MLod scores were observed over a very broad region of chromosome 16. Furthermore, evidence for epistasis between IBD1 and chromosome 1p was observed. Thirteen additional loci demonstrated nominal (MLod > 1.0, P < 0.016) evidence for linkage. This screen provides strong evidence that there are several major susceptibility loci contributing to the genetic risk for CD and UC.

Su(UR)ES: A gene suppressing DNA underreplication in intercalary and pericentric heterochromatin of Drosophila melanogaster polytene chromosomes

A genetic locus suppressing DNA underreplication in intercalary heterochromatin (IH) and pericentric heterochromatin (PH) of the polytene chromosomes of Drosophila melanogaster salivary glands, has been described. Found in the In(1)scV2 strain, the mutation, designated as Su(UR)ES, was located on chromosome 3L at position 34.8 and cytologically mapped to region 68A3-B4. A cytological phenotype was observed in the salivary gland chromosomes of larvae homozygous and hemizygous for Su(UR)ES: (i) in the IH regions, that normally are incompletely polytenized and so they often break to form “weak points,” underreplication is suppressed, breaks and ectopic contacts disappear; (ii) the degree of polytenization in PH grows higher. That is why the regions in chromosome arm basements, normally β-heterochromatic, acquire a distinct banding pattern, i.e., become euchromatic by morphological criteria; (iii) an additional bulk of polytenized material arises between the arms of chromosome 3 to form a fragment with a typical banding pattern. Chromosome 2 PH reveals additional α-heterochromatin. Su(UR)ES does not affect the viability, fertility, or morphological characters of the imago, and has semidominant expression in the heterozygote and distinct maternal effect. The results obtained provide evidence that the processes leading to DNA underreplication in IH and PH are affected by the same genetic mechanism.

Direct isolation of human transcribed sequences from yeast artificial chromosomes through the application of RNA fingerprinting

The identification of cDNA clones from genomic regions known to contain human genes is usually the rate-limiting factor in positional cloning strategies. We demonstrate here that human genes present on yeast artificial chromosomes (YACs) are transcribed in yeast host cells. We have used the arbitrarily primed RNA (RAP) fingerprinting method to identify human-specific, transcribed sequences from YACs located in the 13q12 chromosome region. By comparing the RAP fingerprints generated using defined, arbitrary primers from various fragmented YACs, megaYACs, and host yeast, we were able to identify and map 20 products transcribed from the human YAC inserts. This method, therefore, permits the simultaneous isolation and mapping of novel expressed sequences directly from whole YACs.

Localization of a putative transcriptional regulator (ATRX) at pericentromeric heterochromatin and the short arms of acrocentric chromosomes

ATRX is a member of the SNF2 family of helicase/ATPases that is thought to regulate gene expression via an effect on chromatin structure and/or function. Mutations in the hATRX gene cause severe syndromal mental retardation associated with α-thalassemia. Using indirect immunofluorescence and confocal microscopy we have shown that ATRX protein is associated with pericentromeric heterochromatin during interphase and mitosis. By coimmunofluorescence, ATRX localizes with a mouse homologue of the Drosophila heterochromatic protein HP1 in vivo, consistent with a previous two-hybrid screen identifying this interaction. From the analysis of a trap assay for nuclear proteins, we have shown that the localization of ATRX to heterochromatin is encoded by its N-terminal region, which contains a conserved plant homeodomain-like finger and a coiled-coil domain. In addition to its association with heterochromatin, at metaphase ATRX clearly binds to the short arms of human acrocentric chromosomes, where the arrays of ribosomal DNA are located. The unexpected association of a putative transcriptional regulator with highly repetitive DNA provides a potential explanation for the variability in phenotype of patients with identical mutations in the ATRX gene.

The Vibrio cholerae genome contains two unique circular chromosomes

Vibrio cholerae, the etiologic agent of the diarrheal disease cholera, is a Gram-negative bacterium that belongs to the γ subdivision of the family Proteobacteriaceae. The physical map of the genome has been reported, and the genome has been described as a single 3.2-Mb chromosome [Majumder, R., et al. (1996) J. Bacteriol. 178, 1105–1112]. By using pulsed-field gel electrophoresis of genomic DNA immobilized in agarose plugs and digested with the restriction enzymes I-CeuI, SfiI, and NotI, we have also constructed the physical map of V. cholerae. Our analysis estimates the size of the genome at 4.0 Mb, 25% larger than the physical map reported by others. Our most notable finding is, however, that the V. cholerae chromosome appears to be not the single chromosome reported but two unique and separate circular megareplicons.

Telomeres of polytene chromosomes in a ciliated protozoan terminate in duplex DNA loops

The end of a telomeric DNA sequence isolated from a polytene chromosome of a hypotrichous ciliate folds back and hybridizes with downstream telomeric sequence to form a t loop that is stable in the absence of protein and DNA cross-linking. The single-stranded, telomeric DNA sequence at the end of a macronuclear molecule does not form a t loop but, instead, is complexed with a heterodimeric, telomere-binding protein. Thus, two mechanisms for capping the ends of DNA molecules are used in the same cell.

Pontin52, an interaction partner of β-catenin, binds to the TATA box binding protein

β-catenin, the vertebrate homolog of the Drosophila Armadillo protein, has been shown to have dual cellular functions, as a component of both the cadherin-catenin cell adhesion complex and the Wnt signaling pathway. At Wnt signaling, β-catenin becomes stabilized in the cytoplasm and subsequently available for interaction with transcription factors of the lymphocyte enhancer factor-1/T-cell factor family, resulting in a nuclear localization of β-catenin. Although β-catenin does not bind DNA directly, its carboxyl- and amino-terminal regions exhibit a transactivating activity still not well understood molecularly. Here we report the identification of an interaction partner of β-catenin, a nuclear protein designated Pontin52. Pontin52 binds β-catenin in the region of Armadillo repeats 2–5 and, more importantly, also binds the TATA box binding protein. We provide evidence for an in vivo multiprotein complex composed of Pontin52, β-catenin, and lymphocyte enhancer factor-1/T-cell factor. Our results suggest involvement of Pontin52 in the nuclear function of β-catenin.

DNA double-strand break repair proteins are required to cap the ends of mammalian chromosomes

Recent findings intriguingly place DNA double-strand break repair proteins at chromosome ends in yeast, where they help maintain normal telomere length and structure. In the present study, an essential telomere function, the ability to cap and thereby protect chromosomes from end-to-end fusions, was assessed in repair-deficient mouse cell lines. By using fluorescence in situ hybridization with a probe to telomeric DNA, spontaneously occurring chromosome aberrations were examined for telomere signal at the points of fusion, a clear indication of impaired end-capping. Telomeric fusions were not observed in any of the repair-proficient controls and occurred only rarely in a p53 null mutant. In striking contrast, chromosomal end fusions that retained telomeric sequence were observed in nontransformed DNA-PKcs-deficient cells, where they were a major source of chromosomal instability. Metacentric chromosomes created by telomeric fusion became even more abundant in these cells after spontaneous immortalization. Restoration of repair proficiency through transfection with a functional cDNA copy of the human DNA-PKcs gene reduced the number of fusions compared with a negative transfection control. Virally transformed cells derived from Ku70 and Ku80 knockout mice also displayed end-to-end fusions. These studies demonstrate that DNA double-strand break repair genes play a dual role in maintaining chromosomal stability in mammalian cells, the known role in repairing incidental DNA damage, as well as a new protective role in telomeric end-capping.

A method that allows the assembly of kinetochore components onto chromosomes condensed in clarified Xenopus egg extracts

Kinetochores are complex macromolecular structures that link mitotic chromosomes to spindle microtubules. Although a small number of kinetochore components have been identified, including the kinesins CENP-E and XKCM1 as well as cytoplasmic dynein, neither how these and other proteins are organized to produce a kinetochore nor their exact functions within this structure are understood. For this reason, we have developed an assay that allows kinetochore components to assemble onto discrete foci on in vitro-condensed chromosomes. The source of the kinetochore components is a clarified cell extract from Xenopus eggs that can be fractionated or immunodepleted of individual proteins. Kinetochore assembly in these clarified extracts requires preincubating the substrate sperm nuclei in an extract under low ATP conditions. Immunodepletion of XKCM1 from the extracts prevents the localization of kinetochore-associated XKCM1 without affecting the targeting of CENP-E and cytoplasmic dynein or the binding of monomeric tubulin to the kinetochore. Extension of this assay for the analysis of other components should help to dissect the protein–protein interactions involved in kinetochore assembly and function.

Cleavage Furrows Formed between Centrosomes Lacking an Intervening Spindle and Chromosomes Contain Microtubule Bundles, INCENP, and CHO1 but Not CENP-E

PtK1 cells containing two independent mitotic spindles can cleave between neighboring centrosomes, in the absence of an intervening spindle, as well as at the spindle equators. We used same-cell video, immunofluorescence, and electron microscopy to compare the structure and composition of normal equatorial furrows with that of ectopic furrows formed between spindles. As in controls, ectopic furrows contained midbodies composed of microtubule bundles and an electron-opaque matrix. Despite the absence of an intervening spindle and chromosomes, the midbodies associated with ectopic furrows also contained the microtubule-bundling protein CHO1 and the chromosomal passenger protein INCENP. However, CENP-E, another passenger protein, was not found in ectopic furrows but was always present in controls. We also examined cells in which the ectopic furrow initiated but relaxed. Although relaxing furrows contained overlapping microtubules from opposing centrosomes, they lacked microtubule bundles as well as INCENP and CHO1. Together these data suggest that the mechanism defining the site of furrow formation during mitosis in vertebrates does not depend on the presence of underlying microtubule bundles and chromosomes or on the stable association of INCENP or CHO1. The data also suggest that the completion of cytokinesis requires the presence of microtubule bundles and specific proteins (e.g., INCENP, CHO1, etc.) that do not include CENP-E.