dataesr/scientific-paragraphs-categorization huggingface dataset:
Third, in addition to HIV-related mortality, the model includes a monthly risk of "non-AIDS death," derived from UNAIDS age-and sex-adjusted, country-specific mortality rates that exclude the impact of HIV  [39]. For each simulated infant, the model tracks clinical events, changes in CD4%, and the amount of time spent in each health state. After an individual simulated patient has died, the next infant enters the model. Large cohorts (often 1 million-10 million patients) are simulated in order to generate stable model outcomes. Once the entire cohort has been simulated, summary statistics are tallied, including number and type of clinical events and the proportion alive each month. Additional information about CEPAC-Pediatric model structure, data sources, and procedures for initiating new collaborative projects are available at web2.
Discussion We developed a patient-level computer simulation model of disease progression among perinatally HIV-infected infants -the CEPAC-Pediatric model. This represents the first description of a Monte Carlo microsimulation model of untreated HIV disease in children, and the most detailed description to date of internal validation and calibration of a model of pediatric HIV disease according to recommended practices  [15] [16] [17]. In internal validation analyses, using a single set of input parameters to assess model structure, model outputs closely matched empiric data from the IeDEA East African regional pediatric cohort. Model-projected survival was closest to empiric survival data if the immunologic data parameters (not available from IeDEA) included an average CD4% at birth of 45%, a CD4% decline of 6%/month for infants < 3 months of age, and a CD4% decline of 0.
In contrast, children in IeDEA were likely to initiate ART when needed; although they were then censored from our analysis, this likely averted many of the risks of opportunistic infection and death that would have occurred had no ART been available. Second, the IeDEA dataset may reflect some degree of "survivor bias:" children who survive the first months and years of life may be longer-term survivors, with slower disease progression than those who become ill in infancy and are unavailable to enroll in many cohort studies. Infants in the UNAIDS analysis were followed from birth, permitting early infant mortality to be observed and avoiding this survivor bias, whereas infants in the IeDEA cohort enrolled at a median of 5 months of age. Our finding that IeDEA-observed mortality risks in the first 12 months of life required the largest increases to match UNAIDS data suggests that unobserved pre-enrollment CD4% values decline as per the best-fitting parameter set (6.
The WITS-derived CD4% inputs were varied extensively in sensitivity analyses, and found to have modest impact on goodness-of-fit between model-generated and observed survival risks. Second, there is no single accepted criterion by which to compare model-generated results to empiric data. Instead, expert guidance recommends that investigators choose and explicitly describe a criterion that fits their model structure and data sources  [5, [23] [24] [25] 30, 57]. We chose RMSE to assess goodness-of-fit between projected and observed survival. The complex microsimulation structure of the CEPAC model renders Bayesian analysis computationally infeasible  [58] , empiric datasets were too small to permit separate analyses in training and validation sets. We therefore selected a method that is transparent, well-described in policy models, and comparable to methods used to validate the adult CEPAC model  [19].
Although some possible parameter sets were necessarily excluded with this approach, we sampled the parameter space systematically, varying all model parameters in small increments through clinically plausible ranges and considering all 141 million resulting parameter combinations. In summary, we report the development, internal validation, and calibration of the CEPAC-Pediatric natural history model of HIV disease progression in young children. The model demonstrates excellent performance in internal validation analyses to evaluate model structure. The model also permits wide-ranging sensitivity analyses on all key input parameters, and variations in key clinical and immunologic parameters lead to model-generated survival curves that calibrate closely to UNAIDS survival data for untreated, perinatally HIV-infected children.
Differences in the mortality risk parameters required to match data from the IeDEA cohort (model internal validation) and the UNAIDS cohort (model calibration) highlight the importance of early infant mortality before enrollment in many cohort studies, as well as the ability of simulation models to estimate mortality risks among children ages two to five in the absence of such empiric data. This validated CEPAC-Pediatric model will be well-suited to address critical policy questions in pediatric HIV care for children from birth through five years of age. ), and CD4% values decline as per the best-fitting parameter set (6. 0%/month ages 0-3 months, 0. 3%/month ages ≥3 months). Simulated infants face competing risks of all three types of clinical events, as well as "acute" and "chronic" mortality.
3  (blue line) and 5) the highest-mortality risk parameter set from Table  3  (red line). The 10 sample best-fitting parameter sets from calibration analyses are almost entirely obscured by the UNAIDS survival data (black line) due to their extremely close fit to the calibration target. The IeDEA survival curve from internal validation analyses, and both the highest-and lowest-mortality risk parameter sets are all projected to 60 months of age for comparison only, as they did not meet the threshold of UNAIDS risk ±1% at 6 months and therefore were not formally evaluated at subsequent time points in the calibration analyses. B: A zoom plot, enlarging the results for months 0-6, shows the nearly-overlapping curves in larger detail. doi: 10. 1371/journal. pone. 0083389. g004 Table  5. Root-mean-squared error for key parameters sets in the calibration of the CEPAC-Pediatric model to UNAIDS survival data.
Chronic HIV mortality multiplier c Mean CD4% at birthMonthly CD4% decline a Acute clinical event mortality multiplier b 0-6m7-12m13-24m25-36m37-48m49-60mRoot-mean-squared error (RMSE) a. CD4% decline is shown as monthly decline (in CD4 percentage points) for months 1-3 of life, followed by for months 4+ of life. b. Multipliers were applied to the monthly risks of "acute mortality" derived from the IeDEA cohort (defined as mortality <30 days following a WHO3, WHO4, or TB clinical event). c. Multipliers were applied to monthly risks of "chronic HIV mortality" derived from the IeDEA cohort (defined separately as mortality risks among infants with no history of clinical event, or >30 days after a clinical event for infants with a history of clinical event). d. Root-mean-squared error of CEPAC-Pediatric model projections compared to UNAIDS survival data at 6, 12, 24, 36, 48, and 60 months of age.
International Epidemiologic Databases for the Evaluation of AIDS; WHO: World Health Organization; TB: tuberculosis; WITS: Women and Infants Transmission Study. a. WHO Stage 4, Stage 4, and TB events defined according to WHO classifications for HIV disease staging in children [3]. b. The publicly available WITS dataset includes 193 perinatally HIV-infected children (positive HIV co-culture or PCR by 4-6 weeks of age), with a median of 5. 2 months of follow-up prior to initiation of 3-drug ART (Interquartile Range (IQR): 2. 1-12. 1 months; AZT monotherapy was permitted during the follow-up period) [33]. Of the 193 perinatally HIV-infected children included in the WITS dataset, 180 (93%) had at least one CD4% measurement before ART initiation, 152 (79%) had at least two values, and 121 (63%) had at least three; the first recorded CD4% was observed at a median age of 5.
International Epidemiologic Databases for the Evaluation of AIDS; WHO: World Health Organization; TB: tuberculosis; WITS: Women and Infants Transmission Study. a. WHO Stage 4, Stage 4, and TB events defined according to WHO classifications for HIV disease staging in children [3]. b. The publicly available WITS dataset includes 193 perinatally HIV-infected children (positive HIV co-culture or PCR by 4-6 weeks of age), with a median of 5. 2 months of follow-up prior to initiation of 3-drug ART (Interquartile Range (IQR):2. 1-12. 1 months; AZT monotherapy was permitted during the follow-up period) [33]. Of the 193 perinatally HIV-infected children included in the WITS dataset, 180 (93%) had at least one CD4% measurement before ART initiation, 152 (79%) had at least two values, and 121 (63%) had at least three; the first recorded CD4% was observed at a median age of 5.
5. 0 X IeDEA risks (increments of 0. 5) Chronic HIV mortality risk c 0-6 months 1. 0-20. 0 X IeDEA risks (increments of 1. 0) 7-12 months 1. 0-20. 0 X IeDEA risks (increments of 1. 0) 13-24 months 0. 5-5. 0 X IeDEA risks (increments of 0. 5IeDEA risks (increments of 0. 2) IeDEA: International Epidemiologic Database to Evaluate AIDS, East African region. m: month. a. Values for monthly CD4% decline reflect more rapid decline in the first three months of life than after age three months, based on published literature [43-45], and the results of internal validation analyses. b. Acute mortality risk: risk of death within 30 days of a clinical event (WHO Stage 3, WHO Stage 4, or tuberculosis; see Methods).
Acknowledgements The authors would like to thank  Kathleen Kelly  for assistance with model-based analyses and  Jordan Francke  for assistance with manuscript preparation. We also gratefully acknowledge the contributions of the entire Cost-Effectiveness of  Preventing AIDS Complications-International (CEPAC-I ) research team. The authors also thank  Constantin Yiannoutsis  and  Beverly Musick  for detailed analyses of IeDEA East Africa data, as well as the  IeDEA East Africa Pediatric Working Group  for their valuable contributions:  Melanie Bacon ,  Winstone Nyandiko ,  Craig Cohen ,  Elizabeth Bukusi ,  Deo Wabwire ,  Pius Okong ,  Juliana Otieno ,  Geoffrey Somi ,  Rita Lyamuya ,  Batya Elul ,  Rachel Vreeman  and  Harriet Nuwagaba-Biribonwoha.
cIeDEA: International Epidemiologic Databases for the Evaluation of AIDS; WHO: World Health Organization; TB: tuberculosis; WITS: Women and Infants Transmission Study. a. WHO Stage 4, Stage 4, and TB events defined according to WHO classifications for HIV disease staging in children [3]. b. The publicly available WITS dataset includes 193 perinatally HIV-infected children (positive HIV co-culture or PCR by 4-6 weeks of age), with a median of 5. 2 months of follow-up prior to initiation of 3-drug ART (Interquartile Range (IQR): 2. 1-12. 1 months; AZT monotherapy was permitted during the follow-up period) [33]. Of the 193 perinatally HIV-infected children included in the WITS dataset, 180 (93%) had at least one CD4% measurement before ART initiation, 152 (79%) had at least two values, and 121 (63%) had at least three; the first recorded CD4% was observed at a median age of 5.
As the data were collected under 'non-wild' conditions, we stress that our data provide only an estimate of the defecation frequency needed for population counts. However, we will be able to compare our estimates when activity budget data become available from currently radiocollared free-living individuals (R. Kowalczyk, pers. comm. ) -if the captive and free-living bison spend similar amounts of time foraging and resting, it may be suggested that their diets may be similar enough to compare digestive parameters. Our estimate is, therefore, a step towards a more mechanistic understanding (sensu  Cousens et al. 2010 ) of endozoochorous seed dispersal by bison. Regarding the role of bison role as seed dispersers of forest plants, around 11 seedlings germinate from each dropping  (Jaroszewicz et al.
Acknowledgments We are very grateful to the staff of the  European Bison Show Reserve  for their generous assistance. This research received funding from the  European Union   7th Framework Programme  under the project  Research Potential in Conservation and Sustainable Management of Biodiversity-BIOCONSUS  (grant agreement no. 245737 ). We thank the editors and anonymous referees for assisting greatly in clarifying this manuscript. Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
General Melting points were determined with an electrothermal melting point apparatus and are uncorrected. NMR spectra ( 1 H, 13 C) were recorded on a Bruker AM 300 (operating at 300. 13 MHz for 1 H, at 75. 47 MHz for 13 C) spectrometer (Centre Universitaire Re´gional d'Interface, Fe`s). NMR data are listed in ppm and are reported relative to tetra-methylsilane ( 1 H, 13 C); residual solvent peaks being used as internal standard. All reactions were followed by TLC. TLC analyses were carried out on 0. 25 mm thick precoated silica gel plates (Merck Fertigplatten Kieselgel 60F254) and spots were visualized under UV light or by exposure to vaporized iodine. Mass spectra were recorded on a PolarisQ Ion Trap GC/MSn Mass Spectrometer (Centre Universitaire Re´gional d'Interface, Fe`s); except for the product 3 which was identified by electrospray on a micromass ESl Platform II (Universite´Montpellier II, France).
Acknowledgement These results were obtained with the support of CORUS-2 project, a programme from the  French Ministry of Foreign  and European Affairs implemented by the  Institut de Recherche pour le Développement (IRD-DSF ). The authors also thank the  Ministry of Higher Education and Research of Benin through the Institute of Applied Biomedical Sciences (ISBA)  which sanctioned the contingent grants for this work. We also express our sincere thanks to the  Islamic Development Bank (IDB)  and the Office of Scholarship Programme that granted a  Postdoctoral fellowship  to  A. Yessoufou  at the  Centre for Integrative Genomics (University of Lausanne, Switzerland ). We highly appreciate the contribution of  Professor Yohanna Mashalla (MD, PhD ,  Professor of Medical Physiology, Dean  of  Faculty of Health Sciences, University of Botswana ) for having carried out extensive proof reading of the manuscript and checked the English style and  Dr.
Western blot analysis of whole-cell extracts showed that SAMHD1 was equally expressed in PMA-treated and untreated U937eSAMHD1 cells (Figure  1A , lower panel). These results strongly suggest that the sole expression of SAMHD1 is not sufficient to confer resistance to HIV-1 infection. SAMHD1 restriction activity might require posttranslational modifications or the presence of partner expressed in PMA-treated cells. To test these hypotheses, we immunopurified SAMHD1 and its interacting partners from mock-or PMA-treated THP1 cells expressing Flag-and HA-tagged SAMHD1 (THP1eSAMHD1) (Figure  1B ). Proteins that specifically associate with SAMHD1 were identified by mass spectrometry. Interestingly, among the interacting partners identified, cyclin A2 and CDK1 were present only when SAMHD1 was purified from proliferating THP1 cells (data not shown).
Western blot analysis using anti-SAMHD1 antibody revealed equal amount of both wild-type and T592 SAMHD1 proteins (Figure  2D , lower panel). Next, in vivo detection of SAMHD1 phosphorylation at the T592 residue was tested using cell lysates of U937 cells expressing eSAMHD1 or eSAMHD1T592A mutant. The phospho-specific antibody recognized wild-type SAMHD1 but not the SAMHD1T592A mutant (data not shown). Both wild-type and SAMHD1T592A mutant show similar nuclear localization (data not shown). Endogenous SAMHD1 proteins were also recognized by the phosphospecific antibody, whereas phosphatase-treated proteins were not (Figure  2E , compare lanes 2 and 3 to lane 1). Furthermore, treatment of U937eSAMHD1 cells with selective CDK1 inhibitor (CGP-74514A hydrochloride, HC) reduced SAMHD1 phosphorylation at T592 residue as witnessed by western blot using anti-phosphoT592 antibody (Figure  2F ).
ACKNOWLEDGMENTS We wish to thank members of the  Molecular Virology lab  for critical reading of the manuscript. This work was supported by grants from the  ERC  (  250333 ),  Sidaction  ( Fonds de dotation PIERRE BERGE) ,  ANRS , European  FP7  '' HIT HIDDEN HIV '' contract  305762. A. C. was supported by  ANRS. B. D. was supported by  ERC. A. L. C. V. was supported by  CAPES Scholarship  (process number  867811-1 ). A. C. , N. L. , and M. B. conceived the study, designed experiments, and wrote the paper. A. C. , B. D. , A. L. C. V. , and N. L. performed the experiments. All the authors discussed the data.
Acknowledgements The meeting was supported by  Fondazione Melanoma Onlus and the Society of ImmunoTherapy of Cancer (SITC). A special thanks to  3P Solution of Napoli  for their support and cooperation in organizing the meeting and to  Michael Hoetzel  for providing us with the group picture from the meeting. Sacha Gnjatic would like to acknowledge the  Cancer Research Institute/Ludwig Institute for Cancer Research Cancer Vaccine Collaborative  for grant support. All Authors would like to dedicate this manuscript to the memory of  Natale Cascinelli  who devoted his life to the research and care of melanoma patients and was an example for all of us.
Toxicological data All substances present in the oxygen absorber formulation, iron, iron oxides, sodium chloride and calcium hydroxide, have been evaluated and authorised for use as additives in plastic food contact materials. Iron and sodium chloride have also been evaluated for use in oxygen scavenger mixtures incorporated in polyolefin layers. Therefore, no toxicity data are required. All these ingredients are expected to be stable under normal storage and handling conditions. Based on the above migration results, the specific migration limits of 48 mg/kg food for iron and of 60 mg/kg food (the overall migration limit) for sodium chloride and for calcium hydroxide are not expected to be exceeded when the oxygen absorber system is used under the intended conditions of use, notably behind a layer not containing the formulation of active substances.
(2009a). In this work, potential radiative systematic biases existing between simulations used to train the networks and observations are computed for each channel by averaging, over the first three years of operation (July 2007-June 2010), the differences between simulations and collocated (in time and space) satellite observations. The simulations are performed using the 4A/OP-2009 forward model  (Scott and Chédin, 1981 ; http://www. noveltis. net/4AOP/), which is based on the updated 2009 version of the GEISA spectroscopic database (available at http://ether. ipsl. jussieu. fr/) (Jacquinet-Husson et al. , 2011) , and radiosonde measurements from the Analyzed RadioSoundings Archive database (available at http: //ara. abct. lmd. polytechnique. fr/) as inputs. Because of the lesser variability of the atmospheric temperature profiles in the tropics compared to higher latitudes, the decorrelation between temperature and methane signals in the observations is easier to do in the tropical belt, yielding a better precision there.
Aircraft data Very few measurements of CH 4 are available in the midtroposphere, rendering the validation of satellite retrievals as well as model simulations in the mid-troposphere quite delicate. The Total Carbon Column Observing Network (TCCON) is a network of ground-based Fourier transform spectrometers recording direct solar spectra in the nearinfrared spectral region from which accurate and precise column-averaged abundances of CH 4 can be derived. It thus provides an essential validation resource for the retrievals of total column of CH 4 performed from shortwave-infrared observations. However, IASI gives access to a mid-tropospheric column, and direct comparison to TCCON total CH 4 abun-dance is thus not straightforward. In the following, we will use measurements made by commercial aircraft in the framework of two programs that provide valuable information about CH 4 variations in the middle troposphere: CONTRAIL (Comprehensive Observation Network for Trace gases by AIrLiner) and CARIBIC (Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrument Container).
We will also use measurements performed during 5 HIPPO (HIAPER Pole-to-Pole Observations) campaigns. The CONTRAIL project originates from regular in situ measurements of CO 2 made by commercial airliners of Japan Airlines (JAL) between Japan and Australia since the mid-1980s  (Nakazawa et al. , 1991; Matsueda et al. , 2002 ; data available at http://gaw. kishou. go. jp/wdcgg. html). In November 2005, the National Institute for Environmental Studies (NIES), the Meteorological Research Institute (MRI), Tohoku University and Japan Airlines started a new phase of the JAL project called CONTRAIL, expanding the commercial aircraft measurement program to include regular JAL flights from Japan to Europe, North America and Asia and providing measurements of CO 2 , CH 4 and CO  (Machida et al. , 2007 (Machida et al.
, 2007). Its first operational phase was from 1999-2001. Since May 2005 the new, extended CARIBIC instrumentation package is employed once per month during regular passenger flights out of Germany to Asia, Africa, and North and South America. Both real-time measurements and air sample collection are performed. The air samples are analyzed for a large number of trace gases in several laboratories, including GC-FID analysis of CH 4  (Schuck et al. , 2009). CH 4 data are reported on the NOAA/GMD scale, with a precision of 2. 2 ppbv. The HIPPO project is investigating the carbon cycle and greenhouse gases throughout various altitudes of the Western Hemisphere through the annual cycle. HIPPO is supported by the National Science Foundation (NSF) and its operations are managed by the Earth Observing Laboratory (EOL) of the National Center for Atmospheric Research (NCAR).
Five missions took place from January 2009 to September 2011. They measured atmospheric constituents along transects from approximately pole-to-pole over the  Pacific Ocean and flew hundreds of vertical profiles from the ocean/ice surface to as high as the tropopause, at five times during different seasons over the 3 yr period. In the following, use is made of the 10 second merge product  (Wofsy et al. , 2012). HIPPO methane data are reported on the NOAA04 calibration scale. While comparing IASI and aircraft observations, it must be kept in mind that CONTRAIL and CARIBIC CH 4 is representative of methane at aircraft altitude (∼11 km), whereas IASI gives access to a mid-tropospheric integrated content. 3 General features of mid-tropospheric CH 4.
IASI and CONTRAIL cycles agree quite well for the period July 2007-March 2009 when both data are available. This is particularly true in the Northern Hemisphere, where the seasonal cycle is well defined. The amplitudes of CONTRAIL and IASI cycles are in good agreement with each other: about 25 ppbv in the northern tropics and 15 ppbv in the southern tropics. In the southern tropics, there seems to be an overestimation of IASI CH 4 compared to CONTRAIL in August-October 2008. However, such high values of methane are not seen for the other years and seem to be specific to 2008. CONTRAIL data lie in the monthly standard deviation of IASI data computed along the flight tracks (red shaded area in Fig. 2 ).