dataesr/scientific-paragraphs-categorization huggingface dataset:
We did not do a regression for diabetes prevalence based on HbA 1c versus prevalence based on FPG-or-2hOGTT because very few surveys had data for both 2hOGTT and HbA 1c , leading to unstable regression coeffi cients. We probit-transformed diabetes prevalence because it provided better fi t to the data and it avoids predicting prevalences that are less than 0 or greater   High-income western countries Central Asia, Middle East, and north Africa Sub-Saharan Africa Latin America and the Caribbean Oceania East and southeast Asia South Asia • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •• • • • • • • • • • • • • • • • • • • • • • Coeffi cient (95% CI) p value Univariate R 2 * Semipartial R 2 † Intercept 0•135 (-0•020 to 0•290) 0•0872 NA NA Probit- -0•001 (-0•002 to 0•000) 0•1643 0•003 <0•001 Natural logarithm of per person gross domestic product -0•033 (-0•046 to -0•019) <0•0001 0•004 0•001 Mean BMI 0•000 (-0•004 to 0•004) 0•9057 0•092 <0•001 Study representativeness •• •• 0•021 0•001 National Reference •• •• •• Subnational -0•031 (-0•070 to 0•008) 0•1141 •• •• Community -0•070 (-0•101 to -0•039) <0•0001 •• •• FPG=fasting plasma glucose.
76 We examined the sources of heterogeneity in sensitivity and specifi city with metaregressions and a-priori selected study characteristics: mean age, proportion of male participants, midyear of study data collection period; sample size; prevalence of undiagnosed diabetes in the survey; whether the survey was representative of a national, subnational, or community population; geographical region; national income in the survey country and year; and mean haemoglobin concentration in the survey country and year. We did the analyses with Stata (version 12. 2) and R (version 3. 0. 3).
The reasons for additional regional eff ects-higher HbA 1c -based prevalence in south Asia and lower prevalence in high-income regions than in other regions after accounting for prevalence based on FPG-are unknown, but they might be a result of true physiological diff erences; for example, related to red blood cell turnover (itself related to anaemia and iron status), which aff ects HbA 1c , or related to glucose dysregulation during fasting and non-fasting which are captured by HbA 1c. 85 Establishing these reasons requires multicentre studies with consistent methods and protocols and data for phenotypical factors that might aff ect the relation between glucose and HbA 1c. For now, they are unexplained empirical results that should be taken into account when using surveys from diff erent regions.
Our analysis, which focused on questions that are relevant for population-based surveillance of diabetes and monitoring treatment coverage, has several strengths. We pooled data from a large number of population-based surveys from diff erent world regions, thereby increasing both the precision of our estimates and their generalisability compared with analyses of one or a small number of cohorts. We used consistent eligibility and inclusion criteria, and assessed whether the surveys met these criteria. In particular, we only used surveys that had rigorous protocols for fasting duration and for OGTT. Furthermore, most surveys measured glucose and HbA 1c in a laboratory. We also assessed the sources of heterogeneity in how diagnostic criteria compare across surveys, which could not be done in previous analyses because they included few surveys.
Our results should be interpreted with some limitations in mind. We had few studies from some regions including sub-Saharan Africa, south Asia, the Middle East and north Africa, and central and eastern Europe. We analysed the surveys with consistent methods but surveys might have diff ered in details such as the exact limit for fasting duration beyond the 6-h limit imposed by us. Because HbA 1c measurement has changed over time,  [91] [92] [93] [94] [95] [96] [97] [98] [99]  and to minimise the use of non-standard assays, we did not include any HbA 1c data from before the year 2000. 71 Despite this exclusion, and the fact that all of our surveys had measured HbA 1c in a laboratory, HbA 1c measurements can vary between laboratories and instruments, 100 about which we did not have complete data.
For the same reason, we could not standardise the HbA 1c data to account for diff erent assays and instruments used in measurement. Nutritional status-especially iron defi ciency-anaemia, malaria and other parasitic diseases, living at high altitudes, and high prevalence of haemoglobinopathies can aff ect HbA 1c , 101 but could not be assessed as a source of heterogeneity beyond their eff ects through mean haemoglobin concentration. Similarly, data for glucose can be aff ected by unrecorded factors such as inaccurate information about fasting, fl uctuations in diet and physical activity in days before measurement, and how samples were handled, including time between drawing blood and laboratory analysis and the type of tube used for collecting and storing blood. Although we assessed the role of geographical region, we did not have data for the ethnic composition of participants in each survey.
By their nature, health examination surveys used for population-based surveillance use a single measurement for each participant, whereas diagnosis in a clinical setting might repeat the measurements based on the fi rst test. The use of a single test is aff ected by within-individual and even within-laboratory variation, and could lead to misclassifi cation of some individuals. 99 Finally, we did not have longitudinal follow-up data to assess sensitivity and specifi city for diagnosis using one defi nition (or one cutoff value of HbA 1c ) compared to another or for development of diabetes complications and sequelae that contribute the bulk of the public health burden of diabetes. Such data are not available in population-based surveys because surveys are typically cross-sectional. There is no gold standard defi nition that captures the phenotypic complexity of diabetes and the risk of its microvascular and macrovascular complications, although 2hOGTT is often treated as the most reliable test.
Therefore, considerations about diabetes defi nition and diagnosis are diff erent from those of clinical practice, and the emphasis is on comparability of defi nitions over time and across populations. Our results provide much needed empirical evidence for planning global surveillance of diabetes and coverage of its interventions. Specifi cally, despite its relative ease of use, using HbA 1c alone in health surveys might miss some previously undiagnosed people who would be considered as having diabetes using a glucose-based test, and thus could benefi t from lifestyle and treatment interventions. Even so, 2hOGTT is diffi cult to measure even in a clinical setting, let alone in population-based surveys. Of 493 worldwide population-based diabetes data sources between 1975 and 2014 in the NCD-RisC databases, 448 had measured FPG but only 59 had measured 2hOGTT; 33% of surveys before 1990 had 2hOGTT and only 11% did after 1990.
Therefore, a strategy for consistent and comparable surveillance is to use FPG in populationbased surveys, be it national or multicountry survey programmes such as the WHO STEPS surveys, and defi ne diabetes based on FPG. Data such as those in fi gure 2 and table 1 can then be used to relate prevalences based on FPG to those based on FPG-or-2hOGTT. The use of HbA 1c in surveillance requires further consideration of how it predicts and helps prevent diabetes complications and sequelae. When HbA 1c is used, FPG should ideally also be measured in a subsample of participants to provide information about how the two tests relate.
Graphical and statistical analysis were performed using Graph Prism 5. 01 software. For statistical analysis, all experiments were performed at least 3 times as indicated in the Figure legends. The mean and SD of the results are shown in the graphs. The one-sided Mann-Whitney U-test, the student t-test and the one-way ANOVA with Bonferonni correction were used and p values ≤ 0. 05 were considered statistically significant.
, 2011). A project-specific subset of the Global Change Master Directory (GCMD; http://gcmd. nasa. gov/portals/ipy/) is what comes closest to an IPY data portal. Here, a set of 642 metadata descriptions are listed for IPY  (accessed 22 April 2015) , being comprised of documents, images, articles and contact links to scientists and institutes. Thus, GCMD only contains data set descriptions and links either directly to external sources (data sets) or to the data centres, where data are supposedly stored. For specific projects or countries, a multitude of smaller data centres can be found offering IPY-related data: data on local or traditional community knowledge and observations, for example, are distributed via the Exchange for Local Observations and Knowledge in the Arctic (http://eloka-arctic.
WHOLE-BRAIN CT PERFUSION IMAGING ACQUISITION AND ANALYSIS Plain CT and CTp were acquired in succession using Siemens® Somatom Definition Flash Scanner. Perfusion images were acquired after a 4 s delay following an injection of 50 ml of Niopam-300 with a PSI injector at a rate of 5 ml/s and a saline chaser bolus, via a 16-18 gage intravenous cannula. Z -axis coverage was 70-100 mm, with acquisition parameters of 80 kV and 240-250 mA, rotation time of 0. 28-1 s, and reconstructed slice thickness of 10 mm with 4-6 mm overlap. Raw perfusion data were analyzed on a Siemens® workstation using Syngo® VPCT Neuro software. Brain parenchyma was isolated by skull bone contour findings; CSF and calcifications were removed by automatic thresholding. The arterial input function (AIF) and venous outflow function were semiautomatically selected from the anterior cerebral artery (ACA) and superior sagittal sinus respectively.
In two cases, the MCA was used to derive AIF. Major vessels were removed by applying relative thresholding to the maximal voxel enhancement. Adaptive spatial filtering was performed that did not smooth over edges and vessel borders. Subsequently, quantitative maps of relative CBF, CBV, and MTT were obtained using a deconvolution algorithm. Quantitative maps were transferred to a Windows® PC and segmented using voxel-based thresholds to define at-risk tissue or "penumbra"and irreversibly damaged tissue or"core"(3). This was performed using in-house software  (3, 17)  in Matlab® (R2007b, The MathWorks Inc. ) run using SPM8 (Wellcome Trust Centre for Imaging Neuroscience, London, UK).
BASELINE CLINICAL FEATURES Fifty-three patients were included in this study. Demographic and pertinent clinical data are described in Table  1. Imaging was performed at a mean (SD) time of 125. 2 (55. 3) minutes from stroke onset. Forty-six patients (86. 8%) received intravenous thrombolytic therapy with alteplase. Median (IQR) stroke severity score on the NIHSS (39) was 15  (6). Small vessel disease did not appear in the TOAST classification given that lacunar strokes were excluded. Majority of patients (50. 9%) had a cardioembolic etiology for their stroke. About 58. 5% of patients had hypertension as a comorbidity and 56. 6% had atrial fibrillation.
Each map was scored visually on each of the 10 regions of the ASPECTS template with a score of 0 if the affected side showed a comparative abnormality and a score of 1 if no relative abnormality was seen; thus a total ASPECTS score could vary from 0 to 10 for each of the perfusion maps, with 0 denoting an abnormality across all ten regions and 10 indicating no abnormality in the affected hemisphere. Each rater scored the scans individually and average of the two was subsequently used for the study analysis. In this example, average ASPECTS score was 7 for CBV, 3 for CBF and 2 for MTT. Our data show that collateral response does not change over time in the early window we studied. One explanation is that collateral response may be intrinsically variable in individuals with proximal occlusions and thus, either present or not  (48).
Larger studies with patients beyond this time window may help confirm the trends we demonstrate in our quantitative data and ASPECTS derived metrics. We studied patients in the time window for current thrombolysis license  (52)  due to the observational nature of our study. However, given the current clinical evidence-based guidelines or thrombolysis in stroke cover the first 4. 5 h post ictus, our study may also have utility in this very clinical setting. Another confound of our study, which may explain why we were unable to detect statistically significant relationships in our quantitative data, is the small sample size. Larger datasets of patients in longer time windows are needed to confirm the trends that we demonstrate, both, with respect to the quantitative findings and the visual assessment-based findings.
Material and Methods Participants Between 30 November 2009 and 20 December 2012, 91 older community-dwellers were followed in the Memory Clinic of Angers University Hospital, France, for a subjective memory complaint, and were recruited into the Gait and Alzheimer Interactions Tracking (GAIT) study (ClinicalTrials. gov number, NCT01315717). The GAIT study is an observational crosssectional study designed to examine gait in older community-dwellers reporting subjective memory complaint. The sampling and data collection procedures have been described elsewhere in detail  [20]. In summary, subjective memory complaint was documented using the Subjective Memory Complaints Questionnaire  [21] , and the main exclusion criteria were age below 60 years, Mini-Mental State Examination (MMSE) score <10  [22] , inability to walk independently, history of stroke, history of any acute medical illness within the past 3 months, current delirium, severe depression, and inability to understand or answer the study questionnaires.
Acknowledgments The authors have listed everyone who contributed significantly to the work in the Acknowledgments section. Permission has been obtained from all persons named in the Acknowledgments section. Melinda Beaudenon, MS ,  Jennifer Gautier , BS,  Romain Simon, MS,  and  Samuel Thiery , BS, from  Angers University Memory Clinic, France , for daily assistance. There was no compensation for this contribution. Claire Rabaute  and  Marielle Chatreaux  (orthoptists),  Stephanie Leruez, MD ,  Solene Coisy, MD ,  Angelique Caignard, MD , and  Marion Verschorre, MD , from the  Department of Ophthalmology of Angers University Hospital, France , for daily assistance. There was no compensation for this contribution.
DISCUSSION We investigated the effect of the BH3 mimetic ABT-263 used in combination with the MEK1/2 inhibitor AS703026, also known as pimasertib, on AML cells. Both molecules are currently being tested in clinical trials as single drug, in phase II for ABT-263 (NCT00445198)  [31]  and in phase II for AS703026 (Study NCT00957580). In vitro, we observed in combination a synergistic effect in apoptosis induction in HL-60 and THP-1 cell lines but not in U-937 cells. This heterogeneity in response rates could be partly explained by the differential expression of the BCL-2 family members or by the inability of the MEKI to block the cell cycle in G1 phase in U-937 cells. We need to take into account that AML is a heterogeneous disease depending on many factors such as blast cells number, lineage, genetic events and stromal environment.
Bone marrow samples Bone marrow samples were obtained from patients with AML and from non-hematological patients ('normal') under informed consent obtained in accordance with the Declaration of Helsinki from all participants and data were analyzed anonymously. The study was approved by the local Ethics at the University of Bordeaux. Mononuclear cells (MNC) were separated by Ficoll sedimentation (PAN Biotech GmbH, Germany), washed and suspended in culture medium in the presence of the different drugs.
Mice were treated five days a week during three weeks. Tumour size was measured twice a week. At the end of the experiments, mice were sacrified by cervical dislocation and tumour was excised and weighted. The tumour growth was calculated in mm3/days as the slope of the regression line of the size of the tumour as a function of the duration of treatment for each mice. Both series of experiments were pooled in the statistical analysis and the significance between the treated and control groups were analyzed using the Mann-Whitney test using the Medcalc software.
Statistical analysis All experiments on cell lines were performed in triplicate and results expressed as the mean ± standard deviation (SD). The paired Student's t-test was used to analyze the data. Considering the elevated spontaneous apoptosis occurring during culture of patients' cells, drug-induced apoptosis was calculated as the percentage of drug specific apoptosis: (apoptosis in treated sample -apoptosis in control) x 100 divided by (100 -apoptosis in control). Experiments performed on patients' cells were analyzed for significance using either the Mann-Whitney or Wilcoxon test for paired samples. The combination index (CI) was determined by the method of Chou-Talalay  [26]  using the Calcusyn software (Biosoft, Cambridge, UK). Results were expressed as the CI value at the effective dose inducing 50, 75 or 90% apoptosis (ED50, ED75 and ED90) for AML cell lines.
Results SPM analysis revealed positive correlation between neuropsychological scores (mostly exploring executive functions) and brain perfusion in the posterior associative cortex, including cuneus/precuneus/occipital lingual areas, the periventricular white matter/corpus callosum, and the cerebellum, while negative correlation was found with amygdalo-hippocampal/entorhinal complexes. A positive correlation was also observed between brain perfusion and the Data Availability Statement: All relevant data are within the paper and its Supporting Information files. Funding: N. Ranganuthan-Thangarajah was recipient of a fellowship from French research program "Partenariats Institutions-Citoyens pour la Recherche et l'Innovation" (PICRI) 2010. M. Aoun Sebaiti was recipient of a grant from the French patients' association "Entraide des Malades de la Myofasciite à Macrophages" (E3M).
Patients The study population included 76 consecutive patients with histopathological features of MMF at muscle biopsy and a cognitive complain, followed in the Garches-Necker-Mondor-Hendaye reference center for rare neuromuscular diseases. Mean age was 49 ± 10 y, sex ratio 21 men/55 women, and mean socio-cultural level (years of education after highschool) 4. 9 ± 1. 3 y. All but 4 patients were right handed. Patients presented with MACD of varying severity and underwent both brain perfusion SPECT and neuropsychological testing within 1. 3 ± 5. 5 mo from each other, as standard care and in accordance with current national regulations (verbal informed consent was obtained and reported in patient medical records). Collection and analysis of data was retrospective and performed after de-identification.
Analysis of Statistical Parametric Maps (SPM) All SPECT image volumes were spatially normalized onto the Montreal Neurological Institute (MNI) template (McGill University, Montreal, Canada) using a 12-parameter affine transformation, followed by non-linear transformations. Dimensions of the resulting voxels were 2 x 2 x 2 mm3. Images were smoothed using a Gaussian filter (FWHM 10 mm) to blur individual variations in anatomy and to increase the signal-to-noise ratio. Spatial preprocessing and statistical analysis were performed using the SPM12 software implemented in Matlab version R2014a (Mathworks Inc. , Sherborn, MA). Global normalization was performed using proportional scaling to control for individual variation. Analyses were restricted to white matter when callosal disconnection was investigated and to gray matter for all other parameters using mask from WFU PickAtlas v.
Optical testing configurations Two opto-electronic arrangements for the line sensor were built to test for timing uniformity (Fig. 7(a) ) and spectral lifetime (Fig. 7(b) ). Fluorescent dye solution was placed in a cuvette and illuminated by a pulsed laser diode. Throughout this study we use three pulsed laser diodes: Picoquant 485 nm laser diode head, Hamamatsu 443 nm laser and Hamamatsu 654 nm laser. Illumination at 443 nm and 654 nm was used to estimate the IRF variability with illumination wavelength. This is important as broadband spectral decay data sets will need to take into account any "colour effects" (see section 4. 6. 5 in  [1] ). The pulsed laser has an electrical synchronization trigger BNC cable connected to the line sensor PCB (not shown). Laser repetition rates used were 10 MHz and 20 MHz.
To perform this comparison, the multimode fibre shown in Fig. 7 (b) can alternatively be connected to a separate spectrometer. The efficiency of the spectrometer over the wavelength range is ~70% as measured by optical power meter. Spectral resolution was ~1. 2 nm due to the slit size (105 µm). The line sensor is controlled via custom FPGA firmware and PC software written in Labview 2011 (National Instruments, Texas, USA) for flexible operation in a variety of modes (TCSPC, time-gated and CMM). In this manuscript we focus on TCSPC and CMM aspects of the sensor.
TCSPC and CMM The main aim of work presented is to demonstrate prompt spectral lifetime data acquisition using novel CMOS SPAD arrays. Two methods have been used to provide fluorescence lifetime, namely CMM and TCPSC. Prior work on CMM incorporates FIRST and LAST settings  [37, 39]  which provide the boundaries for the histogram window. This is useful since the center of mass for the decay curve is required and not necessarily the whole of the histogram. On-chip implementation of the CMM, however, does not include FIRST and LAST settings due to circuit complexity involved for the current spectrometer chip revision. Therefore, the CMM was estimated by first acquiring CMM of the IRF and then acquiring the CMM of the decay. The difference between the two values is indicative of changes in lifetime and this we call CMM diff in the present article  [47, 48].
Decays were fitted using a customized version of DecayFit software  [49, 50]. Solutions of fluorescein and 1,8 -anilinonaphthalenesulphonate (ANS) were used to verify measurements of TCSPC and CMM diff uniformity. Multi-color constellation microspheres (Life Technologies, part number C-14837) were used to demonstrate different spectral lifetimes. TRES was derived by scaling wavelength-dependent decay curves so that the sum along the time axes were equal to steady state spectra of the same sample (see section 7. 2. 2 in  [1]  and  [51]  for details). Steady state spectra for TRES scaling were acquired using a USB2000 spectrometer (Ocean Optics, USA). The main reason for doing this was to compensate for photon response non uniformity (PRNU) which was measured to be 20%. PRNU measurements were done using an established standard  [52].