Regulation of T Cell Homeostasis and Responses by Pten

The generation of lipid products catalyzed by PI3K is critical for normal T cell homeostasis and a productive immune response. PI3K can be activated in response to antigen receptor, co-stimulatory, cytokine, and chemokine signals. Moreover, dysregulation of this pathway frequently occurs in T cell lymphomas and is implicated in lymphoproliferative autoimmune disease. Akt acts as a central mediator of PI3K signals, downstream of which is the mTOR pathway, controlling cell growth and metabolism. Members of the Foxo family of transcription factors are also regulated by Akt, thus linking control over homing and migration of T cells, as well cell cycle entry, apoptosis, and DNA damage and oxidative stress responses, to PI3K signaling. PTEN, first identified as a tumor suppressor gene, encodes a lipid phosphatase that, by catalyzing the reverse of the PI3K “reaction,” directly opposes PI3K signaling. However, PTEN may have other functions as well, and recent reports have suggested roles for PTEN as a tumor suppressor independent of its effects on PI3K signaling. Through the use of models in which Pten is deleted specifically in T cells, it is becoming increasingly clear that control over autoimmunity and lymphomagenesis by PTEN involves multi-faceted functions of this molecule at multiple stages within the T cell compartment

Dilute Bose gases interacting via power-law potentials

Neutral atoms interact through a van der Waals potential which asymptotically falls off as r^{-6}. In ultracold gases, this interaction can be described to a good approximation by the atom-atom scattering length. However, corrections arise that depend on the characteristic length of the van der Waals potential. We parameterize these corrections by analyzing the energies of two- and few-atom systems under external harmonic confinement, obtained by numerically and analytically solving the Schrodinger equation. We generalize our results to particles interacting through a longer-ranged potential which asymptotically falls off as r^{-4}.Comment: 7 pages, 4 figure

Detection of Multi-drug Resistant \u3cem\u3eEscherichia coli\u3c/em\u3e in the Urban Waterways of Milwaukee, WI

Urban waterways represent a natural reservoir of antibiotic resistance which may provide a source of transferable genetic elements to human commensal bacteria and pathogens. The objective of this study was to evaluate antibiotic resistance of Escherichia coli isolated from the urban waterways of Milwaukee, WI compared to those from Milwaukee sewage and a clinical setting in Milwaukee. Antibiotics covering 10 different families were utilized to determine the phenotypic antibiotic resistance for all 259 E. coli isolates. All obtained isolates were determined to be multi-drug resistant. The E. coli isolates were also screened for the presence of the genetic determinants of resistance including ermB (macrolide resistance), tet(M) (tetracycline resistance), and β-lactamases (blaOXA, blaSHV, and blaPSE). E. coli from urban waterways showed a greater incidence of antibiotic resistance to 8 of 17 antibiotics tested compared to human derived sources. These E. coli isolates also demonstrated a greater incidence of resistance to higher numbers of antibiotics compared to the human derived isolates. The urban waterways demonstrated a greater abundance of isolates with co-occurrence of antibiotic resistance than human derived sources. When screened for five different antibiotic resistance genes conferring macrolide, tetracycline, and β-lactam resistance, clinical E. coli isolates were more likely to harbor ermB and blaOXA than isolates from urban waterway. These results indicate that Milwaukee’s urban waterways may select or allow for a greater incidence of multiple antibiotic resistance organisms and likely harbor a different antibiotic resistance gene pool than clinical sources. The implications of this study are significant to understanding the presence of resistance in urban freshwater environments by supporting the idea that sediment from urban waterways serves as a reservoir of antibiotic resistance

Precision Doppler Shift Measurements with a Frequency Comb Calibrated Laser Heterodyne Radiometer

We report precision atmospheric spectroscopy of $CO_2$ using a laser heterodyne radiometer (LHR) calibrated with an optical frequency comb. Using the comb-calibrated LHR, we record spectra of atmospheric $CO_2$ near 1572.33 nm with a spectral resolution of 200 MHz using sunlight as a light source. The measured $CO_2$ spectra exhibit frequency shifts by approximately 11 MHz over the course of the five-hour measurement, and we show that these shifts are caused by Doppler effects due to wind along the spectrometer line of sight. The measured frequency shifts are in excellent agreement with an atmospheric model, and we show that our measurements track the wind-induced Doppler shifts with a relative frequency precision of 100 kHz (15 cm/s), equivalent to a fractional precision of a few parts in $10^{10}$. These results demonstrate that frequency-comb-calibrated LHR enables precision velocimetry that can be of use in applications ranging from climate science to astronomy.Comment: 4 pages, 3 figure

An approximate Bayesian marginal likelihood approach for estimating finite mixtures

Estimation of finite mixture models when the mixing distribution support is unknown is an important problem. This paper gives a new approach based on a marginal likelihood for the unknown support. Motivated by a Bayesian Dirichlet prior model, a computationally efficient stochastic approximation version of the marginal likelihood is proposed and large-sample theory is presented. By restricting the support to a finite grid, a simulated annealing method is employed to maximize the marginal likelihood and estimate the support. Real and simulated data examples show that this novel stochastic approximation--simulated annealing procedure compares favorably to existing methods.Comment: 16 pages, 1 figure, 3 table

Sewage reflects the microbiomes of human populations

© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in mBio 6 (2015): e02574-14, doi:10.1128/mBio.02574-14.Molecular characterizations of the gut microbiome from individual human stool samples have identified community patterns that correlate with age, disease, diet, and other human characteristics, but resources for marker gene studies that consider microbiome trends among human populations scale with the number of individuals sampled from each population. As an alternative strategy for sampling populations, we examined whether sewage accurately reflects the microbial community of a mixture of stool samples. We used oligotyping of high-throughput 16S rRNA gene sequence data to compare the bacterial distribution in a stool data set to a sewage influent data set from 71 U.S. cities. On average, only 15% of sewage sample sequence reads were attributed to human fecal origin, but sewage recaptured most (97%) human fecal oligotypes. The most common oligotypes in stool matched the most common and abundant in sewage. After informatically separating sequences of human fecal origin, sewage samples exhibited ~3× greater diversity than stool samples. Comparisons among municipal sewage communities revealed the ubiquitous and abundant occurrence of 27 human fecal oligotypes, representing an apparent core set of organisms in U.S. populations. The fecal community variability among U.S. populations was significantly lower than among individuals. It clustered into three primary community structures distinguished by oligotypes from either: Bacteroidaceae, Prevotellaceae, or Lachnospiraceae/Ruminococcaceae. These distribution patterns reflected human population variation and predicted whether samples represented lean or obese populations with 81 to 89% accuracy. Our findings demonstrate that sewage represents the fecal microbial community of human populations and captures population-level traits of the human microbiome.Funding for this work was provided by the NIH grant R01AI091829-01A1 to S.L.M. and M.L.S

A single genus in the gut microbiome reflects host preference and specificity

© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in ISME Journal 9 (2015): 90–100, doi:10.1038/ismej.2014.97.Delineating differences in gut microbiomes of human and animal hosts contributes towards understanding human health and enables new strategies for detecting reservoirs of waterborne human pathogens. We focused upon Blautia, a single microbial genus that is important for nutrient assimilation as preliminary work suggested host-related patterns within members of this genus. In our dataset of 57 M sequence reads of the V6 region of the 16S ribosomal RNA gene in samples collected from seven host species, we identified 200 high-resolution taxonomic units within Blautia using oligotyping. Our analysis revealed 13 host-specific oligotypes that occurred exclusively in fecal samples of humans (three oligotypes), swine (six oligotypes), cows (one oligotype), deer (one oligotype), or chickens (two oligotypes). We identified an additional 171 oligotypes that exhibited differential abundance patterns among all the host species. Blautia oligotypes in the human population obtained from sewage and fecal samples displayed remarkable continuity. Oligotypes from only 10 Brazilian human fecal samples collected from individuals in a rural village encompassed 97% of all Blautia oligotypes found in a Brazilian sewage sample from a city of three million people. Further, 75% of the oligotypes in Brazilian human fecal samples matched those in US sewage samples, implying that a universal set of Blautia strains may be shared among culturally and geographically distinct human populations. Such strains can serve as universal markers to assess human fecal contamination in environmental samples. Our results indicate that host-specificity and host-preference patterns of organisms within this genus are driven by host physiology more than dietary habits.This study was funded by the NIH grant R01AI091829-01A1 to SLM

Financial Well-Being and Postdeployment Adjustment Among Iraq and Afghanistan War Veterans

Research has yet to examine the relationship between financial well-being and community reintegration of veterans. To address this, we analyzed data from n=1,388 Iraq and Afghanistan War Era Veterans who completed a national survey on post-deployment adjustment. The results indicated that probable major depressive disorder, posttraumatic stress disorder, and traumatic brain injury were associated with financial difficulties. However, regardless of diagnosis, veterans who reported having money to cover basic needs were significantly less likely to have post-deployment adjustment problems such as criminal arrest, homelessness, substance abuse, suicidal behavior, and aggression. Statistical analyses also indicated that poor money management (e.g. incurring significant debt or writing bad checks) was related to maladjustment, even among veterans at higher income levels. Given these findings, efforts aimed at enhancing financial literacy and promoting meaningful employment may have promise to enhance outcomes and improve quality of life among returning veterans

Self-report and Longitudinal Predictors of Violence in Iraq and Afghanistan War Era Veterans

This study, using a longitudinal design, attempted to identify whether self-reported problems with violence were empirically associated with future violent behavior among Iraq and Afghanistan war veterans and whether and how collateral informant interviews enhanced the risk assessment process. Data were gathered from N = 300 participants (n = 150 dyads of Iraq and Afghanistan war veterans and family/friends). The veterans completed baseline and follow-up interviews 3 years later on average, and family/friends provided collateral data on dependent measures at follow-up. Analyses showed that aggression toward others at follow-up was associated with younger age, posttraumatic stress disorder, combat exposure, and a history of having witnessed parental violence growing up. Self-reported problems controlling violence at baseline had robust statistical power in predicting aggression toward others at follow-up. Collateral report enhanced detection of dependent variables: 20% of cases positive for violence toward others would have been missed relying only on self-report. The results identify a subset of Iraq and Afghanistan war veterans at higher risk for problematic postdeployment adjustment and indicate that the veterans' self-report of violence was useful in predicting future aggression. Underreporting of violence was not evidenced by most veterans but could be improved upon by obtaining collateral information