Effectiveness of a Federal Healthy Start Program in Reducing Infant Mortality

Objective: Infant mortality is an important indicator of the health status of a community. In this analysis, we aimed to evaluate temporal changes in infant mortality rates (IMR) in the Central Hillsborough Healthy Start (CHHS) program service area in Tampa, Florida compared to rates in the rest of Hillsborough County and the state. Method: We conducted a five-year (2010-2014) trends analysis using birth and infant death data extracted from the Florida Community Health Assessment Resource Tool Set (CHARTS). The number of infant deaths and live births were used to calculate and compare IMRs in the CHHS catchment area to those in the rest of Hillsborough County, and the state of Florida. Three-year centered moving averages were directly adjusted to account for differences in the racial/ethnic distribution of mothers across geographic areas. Results: Between 2010 and 2014, the IMR decreased 42.8% in the CHHS service area (from 14.5 to 8.3 per 1,000 live births) compared to decreases of 10.1% and 7.7% in the rest of Hillsborough County and the state of Florida, respectively. Additionally, the infant mortality gap in the CHHS catchment area narrowed from 72% in 2010 to 14% in 2014 compared to the rest of the state, and was eliminated when compared to the rest of Hillsborough County. Discussion: The absolute and relative decreases in IMR in the CHHS catchment area reflect the program’s effectiveness in decreasing disparity in infant mortality. The quality services provided by the CHHS program have had a significant positive impact on the families served

Gender-specific changes in energy metabolism and protein degradation as major pathways affected in livers of mice treated with ibuprofen.

Ibuprofen, an inhibitor of prostanoid biosynthesis, is a common pharmacological agent used for the management of pain, inflammation and fever. However, the chronic use of ibuprofen at high doses is associated with increased risk for cardiovascular, renal, gastrointestinal and liver injuries. The underlying mechanisms of ibuprofen-mediated effects on liver remain unclear. To determine the mechanisms and signaling pathways affected by ibuprofen (100 mg/kg/day for seven days), we performed proteomic profiling of male mice liver with quantitative liquid chromatography tandem mass spectrometry (LC-MS/MS) using ten-plex tandem mass tag (TMT) labeling. More than 300 proteins were significantly altered between the control and ibuprofen-treated groups. The data suggests that several major pathways including (1) energy metabolism, (2) protein degradation, (3) fatty acid metabolism and (4) antioxidant system are altered in livers from ibuprofen treated mice. Independent validation of protein changes in energy metabolism and the antioxidant system was carried out by Western blotting and showed sex-related differences. Proteasome and immunoproteasome activity/expression assays showed ibuprofen induced gender-specific proteasome and immunoproteasome dysfunction in liver. The study observed multifactorial gender-specific ibuprofen-mediated effects on mice liver and suggests that males and females are affected differently by ibuprofen

Proteomes of Lactobacillus delbrueckii subsp. bulgaricus LBB.B5 Incubated in Milk at Optimal and Low Temperatures.

We identified the proteins synthesized by Lactobacillus delbrueckii subsp. bulgaricus strain LBB.B5 in laboratory culture medium (MRS) at 37°C and milk at 37 and 4°C. Cell-associated proteins were measured by gel-free, shotgun proteomics using high-performance liquid chromatography coupled with tandem mass spectrophotometry. A total of 635 proteins were recovered from all cultures, among which 72 proteins were milk associated (unique or significantly more abundant in milk). LBB.B5 responded to milk by increasing the production of proteins required for purine biosynthesis, carbohydrate metabolism (LacZ and ManM), energy metabolism (TpiA, PgK, Eno, SdhA, and GapN), amino acid synthesis (MetE, CysK, LBU0412, and AspC) and transport (GlnM and GlnP), and stress response (Trx, MsrA, MecA, and SmpB). The requirement for purines was confirmed by the significantly improved cell yields of L. delbrueckii subsp. bulgaricus when incubated in milk supplemented with adenine and guanine. The L. delbrueckii subsp. bulgaricus-expressed proteome in milk changed upon incubation at 4°C for 5 days and included increased levels of 17 proteins, several of which confer functions in stress tolerance (AddB, UvrC, RecA, and DnaJ). However, even with the activation of stress responses in either milk or MRS, L. delbrueckii subsp. bulgaricus did not survive passage through the murine digestive tract. These findings inform efforts to understand how L. delbrueckii subsp. bulgaricus is adapted to the dairy environment and its implications for its health-benefiting properties in the human digestive tract. IMPORTANCELactobacillus delbrueckii subsp. bulgaricus has a long history of use in yogurt production. Although commonly cocultured with Streptococcus salivarius subsp. thermophilus in milk, fundamental knowledge of the adaptive responses of L. delbrueckii subsp. bulgaricus to the dairy environment and the consequences of those responses on the use of L. delbrueckii subsp. bulgaricus as a probiotic remain to be elucidated. In this study, we identified proteins of L. delbrueckii subsp. bulgaricus LBB.B5 that are synthesized in higher quantities in milk at growth-conducive and non-growth-conductive (refrigeration) temperatures compared to laboratory culture medium and further examined whether those L. delbrueckii subsp. bulgaricus cultures were affected differently in their capacity to survive transit through the murine digestive tract. This work provides novel insight into how a major, food-adapted microbe responds to its primary habitat. Such knowledge can be applied to improve starter culture and yogurt production and to elucidate matrix effects on probiotic performance

HIV-1 Evolutionary Patterns Associated with Metastatic Kaposi's Sarcoma during AIDS.

Kaposi's sarcoma (KS) in HIV-infected individuals can have a wide range of clinical outcomes, from indolent skin tumors to a life-threatening visceral cancer. KS tumors contain endothelial-related cells and inflammatory cells that may be HIV-infected. In this study we tested if HIV evolutionary patterns distinguish KS tumor relatedness and progression. Multisite autopsies from participants who died from HIV-AIDS with KS prior to the availability of antiretroviral therapy were identified at the AIDS and Cancer Specimen Resource (ACSR). Two patients (KS1 and KS2) died predominantly from non-KS-associated disease and KS3 died due to aggressive and metastatic KS within one month of diagnosis. Skin and visceral tumor and nontumor autopsy tissues were obtained (n = 12). Single genome sequencing was used to amplify HIV RNA and DNA, which was present in all tumors. Independent HIV tumor clades in phylogenies differentiated KS1 and KS2 from KS3, whose sequences were interrelated by both phylogeny and selection. HIV compartmentalization was confirmed in KS1 and KS2 tumors; however, in KS3, no compartmentalization was observed among sampled tissues. While the sample size is small, the HIV evolutionary patterns observed in all patients suggest an interplay between tumor cells and HIV-infected cells which provides a selective advantage and could promote KS progression

Gaussian Markov random fields for discrete optimization via simulation:framework and algorithms

We consider optimizing the expected value of some performance measure of a dynamic stochastic simulation with a statistical guarantee for optimality when the decision variables are discrete, in particular, integer-ordered; the number of feasible solutions is large; and the model execution is too slow to simulate even a substantial fraction of them. Our goal is to create algorithms that stop searching when they can provide inference about the remaining optimality gap similar to the correct-selection guarantee of ranking and selection when it simulates all solutions. Further, our algorithm remains competitive with fixed-budget algorithms that search efficiently but do not provide such inference. To accomplish this we learn and exploit spatial relationships among the decision variables and objective function values using a Gaussian Markov random field (GMRF). Gaussian random fields on continuous domains are already used in deterministic and stochastic optimization because they facilitate the computation of measures, such as expected improvement, that balance exploration and exploitation. We show that GMRFs are particularly well suited to the discrete decision–variable problem, from both a modeling and a computational perspective. Specifically, GMRFs permit the definition of a sensible neighborhood structure, and they are defined by their precision matrices, which can be constructed to be sparse. Using this framework, we create both single and multiresolution algorithms, prove the asymptotic convergence of both, and evaluate their finite-time performance empirically

Nutrition, physical activity, and other lifestyle factors in the prevention of cognitive decline and dementia

Multiple factors combined are currently recognized as contributors to cognitive decline. The main independent risk factor for cognitive impairment and dementia is advanced age followed by other determinants such as genetic, socioeconomic, and environmental factors, including nutrition and physical activity. In the next decades, a rise in dementia cases is expected due largely to the aging of the world population. There are no hitherto effective pharmaceutical therapies to treat age-associated cognitive impairment and dementia, which underscores the crucial role of prevention. A relationship among diet, physical activity, and other lifestyle factors with cognitive function has been intensively studied with mounting evidence supporting the role of these determinants in the development of cognitive decline and dementia, which is a chief cause of disability globally. Several dietary patterns, foods, and nutrients have been investigated in this regard, with some encouraging and other disappointing results. This review presents the current evidence for the effects of dietary patterns, dietary components, some supplements, physical activity, sleep patterns, and social engagement on the prevention or delay of the onset of age-related cognitive decline and dementia. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

Feedback cooling of the normal modes of a massive electromechanical system to submillikelvin temperature

We apply a feedback cooling technique to simultaneously cool the three electromechanical normal modes of the ton-scale resonant-bar gravitational wave detector AURIGA. The measuring system is based on a dc Superconducting Quantum Interference Device (SQUID) amplifier, and the feedback cooling is applied electronically to the input circuit of the SQUID. Starting from a bath temperature of 4.2 K, we achieve a minimum temperature of 0.17 mK for the coolest normal mode. The same technique, implemented in a dedicated experiment at subkelvin bath temperature and with a quantum limited SQUID, could allow to approach the quantum ground state of a kilogram-scale mechanical resonator.Comment: 4 pages, 4 figure

Robust Chauvenet Outlier Rejection

Sigma clipping is commonly used in astronomy for outlier rejection, but the number of standard deviations beyond which one should clip data from a sample ultimately depends on the size of the sample. Chauvenet rejection is one of the oldest, and simplest, ways to account for this, but, like sigma clipping, depends on the sample's mean and standard deviation, neither of which are robust quantities: Both are easily contaminated by the very outliers they are being used to reject. Many, more robust measures of central tendency, and of sample deviation, exist, but each has a tradeoff with precision. Here, we demonstrate that outlier rejection can be both very robust and very precise if decreasingly robust but increasingly precise techniques are applied in sequence. To this end, we present a variation on Chauvenet rejection that we call "robust" Chauvenet rejection (RCR), which uses three decreasingly robust/increasingly precise measures of central tendency, and four decreasingly robust/increasingly precise measures of sample deviation. We show this sequential approach to be very effective for a wide variety of contaminant types, even when a significant -- even dominant -- fraction of the sample is contaminated, and especially when the contaminants are strong. Furthermore, we have developed a bulk-rejection variant, to significantly decrease computing times, and RCR can be applied both to weighted data, and when fitting parameterized models to data. We present aperture photometry in a contaminated, crowded field as an example. RCR may be used by anyone at https://skynet.unc.edu/rcr, and source code is available there as well.Comment: 62 pages, 48 figures, 7 tables, accepted for publication in ApJ