CD4(+) T cell count decreases by ethnicity among untreated patients with HIV infection in South Africa and Switzerland.

BACKGROUND: Estimates of the decrease in CD4(+) cell counts in untreated patients with human immunodeficiency virus (HIV) infection are important for patient care and public health. We analyzed CD4(+) cell count decreases in the Cape Town AIDS Cohort and the Swiss HIV Cohort Study. METHODS: We used mixed-effects models and joint models that allowed for the correlation between CD4(+) cell count decreases and survival and stratified analyses by the initial cell count (50-199, 200-349, 350-499, and 500-750 cells/microL). Results are presented as the mean decrease in CD4(+) cell count with 95% confidence intervals (CIs) during the first year after the initial CD4(+) cell count. RESULTS: A total of 784 South African (629 nonwhite) and 2030 Swiss (218 nonwhite) patients with HIV infection contributed 13,388 CD4(+) cell counts. Decreases in CD4(+) cell count were steeper in white patients, patients with higher initial CD4(+) cell counts, and older patients. Decreases ranged from a mean of 38 cells/microL (95% CI, 24-54 cells/microL) in nonwhite patients from the Swiss HIV Cohort Study 15-39 years of age with an initial CD4(+) cell count of 200-349 cells/microL to a mean of 210 cells/microL (95% CI, 143-268 cells/microL) in white patients in the Cape Town AIDS Cohort > or =40 years of age with an initial CD4(+) cell count of 500-750 cells/microL. CONCLUSIONS: Among both patients from Switzerland and patients from South Africa, CD4(+) cell count decreases were greater in white patients with HIV infection than they were in nonwhite patients with HIV infection.

Differential sensitivity of GLUT1- and GLUT2-expressing beta cells to streptozotocin.

Streptozotocin injection in animals destroys pancreatic beta cells, leading to insulinopenic diabetes. Here, we evaluated the toxic effect of streptozotocin (STZ) in GLUT2(-/-) mice reexpressing either GLUT1 or GLUT2 in their beta cells under the rat insulin promoter (RIPG1 x G2(-/-) and RIPG2 x G2(-/-) mice, respectively). We demonstrated that injection of STZ into RIPG2 x G2(-/-) mice induced hyperglycemia (>20 mM) and an approximately 80% reduction in pancreatic insulin content. In vitro, the viability of RIPG2 x G2(-/-) islets was also strongly reduced. In contrast, STZ did not induce hyperglycemia in RIPG1 x G2(-/-) mice and did not reduce pancreatic insulin content. The viability of in vitro cultured RIPG1 x G2(-/-) islets was also unaffected by STZ. As islets from each type of transgenic mice were functionally indistinguishable, these data strongly support the notion that STZ toxicity toward beta cells depends on the expression of GLUT2.

Imported Swine Count, July 2010

The imported swine court report monthly by the Department of Agricultural.

Imported Swine Count, August 2010

The imported swine court report monthly by the Department of Agricultural.

Differential reactivity of TCR Vbeta10 alleles to a mouse mammary tumor virus superantigen.

Mouse mammary tumor virus (MMTV) expresses a superantigen (SAg) which plays a critical role in the viral life cycle. We have recently described the new infectious MMTV (SIM) encoding a Vbeta4-specific SAg in mice with a TCR-Vbeta(b) haplotype. We have now compared the SAg activity of this virus in BALB/c mice harboring the TCR-Vbeta(a), TCR-Vbeta(b) or TCR-Vbeta(c) haplotypes which differ by a central deletion in the TCR-Vbeta(a) and TCR-Vbeta(c) locus and by mutations in some of the remaining Vbeta elements. Injection of MMTV (SIM) led to a strong stimulation of Vbeta4+ CD4+ T cells in TCR-Vbeta(b) mice, but only to a weak stimulation of these cells in TCR-Vbeta(a) or TCR-Vbeta(c) mice. A large increase in the percentage of Vbeta10+ cells was observed among CD4+ T cells in mice with the Vbeta(a) or Vbeta(c), but not the Vbeta(b) TCR-Vbeta haplotype. Vbeta10+ cells dominated the response when Vbeta10(a/c) and Vbeta4 subsets were present together. This is the first report of a viral SAg interacting with murine Vbeta10+ cells. Six amino acid differences between Vbeta10(a/c) and Vbeta10(b) could account for the gain of reactivity of Vbeta10(a/c) to the MMTV(SIM) SAg. No mutations were found in the hypervariable region 4 (HV4) of the TCR. Mutations at positions 22 and 28 introduce into Vbeta10(a/c) the same amino acids which are found at these positions in the MMTV(SIM)-reactive Vbeta4. Tridimensional models indicated that these amino acids lie close to HV4 and are likely to be important for the interaction of the SAg with the TCR.

Differential regulation of RasGAPs in cancer

Ever since their discovery as cellular counterparts of viral oncogenes more than 25 years ago, much progress has been made in understanding the complex networks of signal transduction pathways activated by oncogenic Ras mutations in human cancers. The activity of Ras is regulated by nucleotide exchange factors (GEFs) and GTPase activating proteins (GAPs), and much emphasis has been put into the biochemical and structural analysis of the Ras/GAP complex. The mechanisms by which GAPs catalyze Ras-GTP hydrolysis have been clarified and revealed that oncogenic Ras mutations confer resistance to GAPs and remain constitutively active. However, it is yet unclear how cells coordinate the large and divergent GAP protein family to promote Ras inactivation and ensure a certain biological response. Different domain arrangements in GAPs to create differential protein-protein and protein-lipid interactions are probably key factors determining the inactivation of the 3 Ras isoforms H-, K-, and N-Ras and their effector pathways. In recent years, in vitro as well as cell- and animal-based studies examining GAP activity, localization, interaction partners, and expression profiles have provided further insights into Ras inactivation and revealed characteristics of several GAPs to exert specific and distinct functions. This review aims to summarize knowledge on the cell biology of RasGAP proteins that potentially contributes to differential regulation of spatiotemporal Ras signaling.

Imported Swine Count, September 2010

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Imported Swine Count, October 2010

The imported swine court report monthly by the Department of Agricultural.

Imported Swine Count, November 2010

The imported swine court report monthly by the Department of Agricultural.

Imported Swine Count, December 2010

The imported swine court report monthly by the Department of Agricultural.

A T42A Ran Mutation: Differential Interactions with Effectors and Regulators, and Defect in Nuclear Protein Import

Ran, the small, predominantly nuclear GTPase, has been implicated in the regulation of a variety of cellular processes including cell cycle progression, nuclear-cytoplasmic trafficking of RNA and protein, nuclear structure, and DNA synthesis. It is not known whether Ran functions directly in each process or whether many of its roles may be secondary to a direct role in only one, for example, nuclear protein import. To identify biochemical links between Ran and its functional target(s), we have generated and examined the properties of a putative Ran effector mutation, T42A-Ran. T42A-Ran binds guanine nucleotides as well as wild-type Ran and responds as well as wild-type Ran to GTP or GDP exchange stimulated by the Ran-specific guanine nucleotide exchange factor, RCC1. T42A-Ran·GDP also retains the ability to bind p10/NTF2, a component of the nuclear import pathway. In contrast to wild-type Ran, T42A-Ran·GTP binds very weakly or not detectably to three proposed Ran effectors, Ran-binding protein 1 (RanBP1), Ran-binding protein 2 (RanBP2, a nucleoporin), and karyopherin ß (a component of the nuclear protein import pathway), and is not stimulated to hydrolyze bound GTP by Ran GTPase-activating protein, RanGAP1. Also in contrast to wild-type Ran, T42A-Ran does not stimulate nuclear protein import in a digitonin permeabilized cell assay and also inhibits wild-type Ran function in this system. However, the T42A mutation does not block the docking of karyophilic substrates at the nuclear pore. These properties of T42A-Ran are consistent with its classification as an effector mutant and define the exposed region of Ran containing the mutation as a probable effector loop.

Imported Swine Count, January 2011

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