dataesr/scientific-paragraphs-categorization huggingface dataset:
sample size Given the paucity of available age-specific dengue incidence data in the study countries or nearby countries, it was difficult to obtain population-based incidence to make assumptions when calculating sample sizes. The required catchment population for the passive facility-based fever surveillance was roughly estimated based on the limited data available in the literature. Annual incidence estimates were calculated based on available prevalence estimates with the assumption that the outcome of interest has zero prevalence at age zero, and that force of infection is constant. It was assumed that prevalence estimates found for one particular age group would be adjusted as the annual incidence and used across all ages. Wichmann et al calculated an expansion factor for children by comparing data from three cohort studies to national surveillance data in Southeast Asia.
The cost-of-illness survey questionnaire was designed to estimate the direct medical, direct non-medical and indirect costs associated with dengue-positive patients identified at study facilities. This survey also estimates the cost of treating dengue at the facility level. Data were gathered by linking patients' medical records concerning outpatient visits, inpatient visits and service consumption (eg, diagnostic tests, medication and other services provided to patients). The cost-of-illness portion of the study will be described separately.
Four DENV serotype-specific real-time RT-PCR assays are used for laboratory confirmation of dengue and serotyping. 38 The DENV 1-4 RT-PCR assays are carried out in 25 µL reaction mixtures containing 5 µL template RNA, TagMan Fast Virus 1-step mastermix (Applied Biosystems), 0. 9 µM of each primer and 0. 2 µM probe. 38 Amplification and detection are performed in a StepOne Plus real-time PCR system, and the baseline and threshold are determined using the auto-baseline and threshold feature in StepOne Software V. 2. 2. 2 (Applied Biosystems). Thermocycling parameters are as follows: reverse transcription at 50°C for 5 min, inactivation at 95°C for 20 s, followed by 45 cycles of fluorescence detection at 95°C for 3 s and annealing at 60°C for 30 s. 38  A specimen is considered positive if target amplification is recorded within 40 cycles.
Open Access Mombasa. Without individual-level census information on all residents of Lambaréné and Mombasa, with help of community/village health workers, randomisation was done based on neighbourhoods (or defined areas for which the health workers/volunteers are responsible) as cluster units. As the community/village health workers are familiar with the villages and their residents, they are good entry points into the communities. With these health workers, the field team screened houses in the selected villages by knocking on doors of every 5-7 houses, depending on the household density per neighbourhood. Also, demographic information collected in previous research projects conducted in the same area was used as a guide, if available. In the case of the site in Ouagadougou, HDSS data were available and the EQUITE SANTE, a CIHR funded research programme of the University of Montreal, had set up a geographic information system database of houses in the study area.
Using the data collected in the Healthcare Utilisation Survey, the proportion of febrile cases missed by the passive surveillance system will be determined. Then using the proportion, the numerator will be further adjusted in recognition of those missed fever cases from the study area, which could have been dengue. Also, comparison will be made between those that agreed to participate and those that declined participation among the eligible potential enrolees. The enrolment log, which records basic information obtained during the screening process of potential enrolees, will be reviewed. In addition to checking that our sample of febrile cases is representative of febrile patients of the general population in the catchment area, refusal rates will be determined based on information in the log.
Then, the refusal rates will be used to adjust the numerator. SPSS software will be used for analysis of the fever surveillance data. Multivariable logistic regression will be used to compare confirmed patients with dengue versus patients with non-dengue febrile in terms of symptomatic presentation, based on signs and symptoms collected from all Open Access patients with laboratory-confirmed dengue by serology and RT-PCR, adjusting for possible confounders, such as age, days since onset of fever, primary versus secondary infection, inpatient versus outpatient and so on. Differences in symptomatic complex of dengue fever (DF) (and DHF, if data allows) by age and serotype will be also determined using multivariable logistic regression. As outpatient disease accounts for the greater part of dengue disease burden, clinical profile of individuals with DENV infection will be characterised by the type of treatment (hospitalised vs outpatients) as well as by severity of the disease (severe vs non-severe by the 2009 WHO criteria).
Open Access With the age-stratified sera that reflect the age distribution of the general population of the country, the serological survey sampling strategy ensures sufficient subjects to obtain precise age-specific estimates of seropositivity and seroconversion of the catchment area population. The seroconversion rate and change in the immune status will be determined by age group during the study period. The age-stratified serosurvey data will also allow calculation of the force of infection of dengue in the study population. After enrolment, there are subjects who drop out in the follow-up bleeds about 6 months later. Basic demographic information will be compared between those that completed participation and those with incomplete participation to check whether study subjects represent the catchment area population.
Ethical considerations To minimise inconvenience of the study to patients, clinicians and nurses were sensitised and trained regarding the study requirements and procedures in order for data collection to be integrated into routine patient care. The clinicians and nurses selected for the study receive coordinated support from study field staff throughout the study process. Written informed consent and assent for participants 7 (13 for Kenya)-17 years of age were obtained from patients by study staff. Study staff go through consent and assent documents for short summary of the disease, detailed description of study procedures and information on reimbursement. Patient data are documented in the study designated office; only the study staff have access to the data that are de-identified. Data are exclusively handled in the study office and stored safely in a protected database in the study office as well as on the DVI main server.
ConClusIon The data collected from our studies will contribute to the assessment of the unknown dengue disease burden in Burkina Faso, Gabon and Kenya. These data can fill a gap in undocumented burden of dengue in the region and, collectively, may be used to infer dengue burden in other areas of Western, Central and Eastern Africa. Countries in Africa may not consider introduction of a dengue vaccine as a priority in the near future due to many other competing public health problems and limited resources. For cost-effective implementation of public health interventions, accurate data on dengue burden from epidemiological studies would be needed for policy makers to make evidence-based decisions on control and prevention of dengue. Our studies will provide some much needed information based on population-based research to assess dengue burden in Africa.
Acknowledgements We thank the doctors and laboratory staff of  CSPS of Ouagadougou, ASH, Ganjoni dispensary, Tudor subcounty Hospital and Coast Provincial General Hospital as well as at Centre Muraz, CERMEL  and  KEMRI. We thank collaborators at  AGIR ,  IRD France  and  University of Montreal , and  University of Tubingen. Last, we would like to thank the DVI team as well as statisticians, laboratory, and administrative staff at the  International Vaccine Institute  for their helpful comments during the preparation of this manuscript and support during the studies.
Surprisingly, the participation rate was lower in European-Americans than in African-Americans (57% vs 71%, respectively; P <. 0001). This difference was because willingness to participate was not seen as a major barrier; once reached, minorities were more likely to participate. Locating minority participants and establishing contact were the key barriers, suggesting that recruitment efforts should focus on areas with a high frequency of individuals of African ancestry. Another recent study  43  assessed willingness to participate in a biobank, hypothesizing that willingness would be higher under more restrictive scenarios. Participants (n = 13 000; African-Americans = 1483; white individuals = 6521) were randomized to receive a survey in one of three hypothetical biobank scenarios; all scenarios were the same except for consent type and data sharing approach.
using antipsychotic vs anti-anxiety treatment). This study suggests that culturally competent treatment regimens in populations with different sociocultural background may help address racial bias and aid in yielding more appropriate treatment recommendations. Consideration of sociocultural background may also be crucial regarding continuity of outpatient care. A 2005 Veterans Affairs (VA) National Patient Care Database study of veterans with bipolar disorder (n = 2316; African-Americans = 303) revealed that African-Americans were significantly less likely to have an outpatient follow-up visit within 90 days of their diagnosis compared to white individuals (13% African-Americans vs 87% white individuals; P =. 009).
| M ET HOD S We performed a retrospective cohort study based on analysis of electronic and paper-based medical records and hospital admission records. First, we identified pregnant women with SCD who had received prenatal care at the Department of Biotherapy at Necker Children's Hospital and had given birth at either of the two maternity units/reference centers that manage high-risk pregnancies in the Paris area (Necker Children's Hospital and Antoine B eclère Hospital) between January 2005 and December 2014. Some women had several pregnancies during the study period. Therefore, all the following results are reported with respect to the number of pregnancies, and each pregnancy constituted one case. The study database is available on request.
The following data were recorded on the e-CRF for each patient: age, parity, ethnic group, personal medical history (the presence or absence of painful VOCs, acute chest syndrome (ACS), stroke, pulmonary arterial hypertension (PAH, defined as a mean pulmonary arterial pressure of at least 25 mm Hg), or other types of SCD-related chronic organ damage), transfusion history, and obstetric history. Any SCDrelated complications during pregnancy were also recorded, along with the number of prenatal visits, any antepartum hospitalizations, and treatments. VOCs necessitating hospitalization, ACS, PAH, acute anemia, splenic sequestration, and other complications of SCD were also recorded, as well as any episodes of pneumonia and urinary tract infections. The following obstetric parameters were recorded on the e-CRF: preterm delivery, premature rupture of membranes, antepartum hemorrhage, placenta previa, gestational diabetes, oligohydramnios, IUGR, pregnancy-induced hypertension, pre-eclampsia, eclampsia, hemolysis elevated liver enzyme and low platelet count (HELLP) syndrome, intrauterine fetal death (IUFD), stillbirth, uterine rupture, postpartum hemorrhage, chorioamnionitis, breast feeding, and maternal mortality.
42  Considering this limitation, we have set up a prospective, multicenter, randomized clinical trial (RCT) of prophylactic oxygen therapy during SCD pregnancies (NCT02813850). In fact, we hypothesize that prophylactic oxygen therapy relieves the symptoms of SCD (particularly during pregnancy). Accordingly, we intend to determine whether an independent effect on treatment outcomes exists in this high-risk medical setting. The study will investigate whether prophylactic oxygen therapy will decrease (i) the transfusion requirement and (ii) the incidence of severe post-transfusion complications without increasing the incidence of VOCs or obstetric complications. If this endpoint is met, prophylactic oxygen therapy may be of major value, especially in regions with sub-optimal transfusion safety.
After the study protocol had been approved by the local investigational review boards and data protection bodies (Comit e d'Ethique de l'Hôpital Necker-Enfants Malade (Paris); approved on September 10, 2012; Comit e Consultatif sur le Traitement de l'Information en matière de Recherche dans le domaine de la Sant e; approved on November 15, 2012; Commission Nationale de l'Informatique et des Libert es; approved on August 13, 2013), an electronic case report form (e-CRF, available on request) was established for the collection of pre-and postnatal data from prenatal records, hospital admission records, and a database of deliveries at more than 20 WA (estimated from the crown-rump length on the first trimester scan, when available, or the date of the last period). Therefore, elective abortions and unreported, spontaneous abortions were not included in the present survey.
ACKNOWLEDGMENTS This work was funded by the  International Sickle Cell Disease Observatory. We also thank the partner organizations  Monacord Eurocord  from the  Centre Scientifique de Monaco  and the  Association Cordon de Vie charity  for financial support. We thank the  Clinical Investigation Center at Necker Children's Hospital  for funding the study database and providing advice on the development of registers. Lastly, we wish to thank all the medical staff in the  Necker Children's Hospital's Biotherapy Department , the  Apheresis Day Hospital Unit, and the company VitalAire. DISCLOSURES Dr. Ribeil reports personal fees from  Bluebird Bio ,  Novartis  and from  Addmedica , and nonfinancial support from Vitalaire, outside the present work. The other authors declare no competing financial interests.
SPECT data were reconstructed using the iterative ordered subset expectation maximization (OSEM) method, with six iterations and ten subsets, attenuation, scatter, recovery resolution corrections, and a Gaussian post-filter of 0. 11 cm. The liver, spleen, kidneys, and red marrow dose per administered activity (AD/A admin) values were calculated with the Medical Internal Radiation Dose (MIRD) formalism and the residence times (Dosimetry toolkit® application) using standard and CT imaging-based organ masses (OLINDA/EXM® V1. 0 software). Results: Sensitivity factors of 6. 11 ± 0. 01 and 5. 67 ± 0. 08 counts/s/MBq were obtained with planar and SPECT/CT acquisitions, respectively. A recovery coefficient of 0. 78 was obtained for the modeled L2-L4 red marrow. The mean AD/A admin values were 0. 43 ± 0.
Software The Dosimetry Toolkit®, an application of the Xeleris® software provided with the SPECT/CT Discovery NM/CT 670 system (GE Healthcare)  [19] , was used to determine the radiopharmaceutical residence time in segmented organs with the multi-SPECT/CT scenario, as described by Kupitz et al. [20]. First, the application "Preparation for dosimetry toolkit" was used for SPECT/CT raw data reconstruction and CT data registration. Then, the "Dosimetry Toolkit" application was used to segment the different organs, to create the time activity curves fitted by a mono-exponential function, and to calculate the residence time. The OLINDA/EXM® V1. 0 software  [21]  was used to calculate the organ absorbed and effective doses. It contains a large pre-established database of radionuclides and S factors to calculate the absorbed dose per unit of administered activity.
Optimization of the reconstruction parameters The reconstruction parameters were optimized using the SPECT/CT images acquired with the previously used NEMA IEC phantom. Using the "Preparation for Dosimetry toolkit" application, SPECT data were reconstructed with different numbers of iterations and subsets, with or without the manufacturer's corrections (scatter, CT-based attenuation correction, resolution recovery), and different Gaussian post-filters. With the "Dosimetry toolkit" application, regions of interest were segmented in the CT slices. Information about the radionuclide and the previously computed planar sensitivity factor were entered in the appropriate interface. The segmented volume and internal activity were obtained for each evaluated reconstruction, and compared with those expected for the phantom.
Dosimetry imaging protocol Dosimetry calculations were based on the imaging data collected after the first two cycles. Images were acquired with the SPECT/CT Discovery NM/CT 670, at 4 h, 24 h, 72 h, and 192 h after the first and second injection. In total, 60 projections (45 s per projection) were acquired with a 128 × 128 pixel matrix (pixel size: 4. 416 mm). For medical consideration, a whole body (WB) scan was performed at 72 h with a scan speed of 15 cm/min. At 4 h post-injection, CT images were acquired with a better image quality (120 kV, automatic mA regulation with max = 200 mA, noise index of 6. 43, slice thickness of 5 mm, rotation time of 0. 8 s, pitch 1. 375, 512 × 512 pixel matrix, and standard reconstruction filter). For this first CT scan, patient set-up and immobilization devices were recorded to reproducibly position the patients for the next SPECT/CT image acquisitions.
Dosimetry calculations Following the last SPECT/CT acquisition, at 192 h after cycle 2, all SPECT/CT data were loaded on the "Preparation for dosimetry toolkit" application. Transversal slices were reconstructed using the OSEM algorithm with the reconstruction settings defined in the optimization study associated with correction of the patient's movements. Each SPECT acquisition was registered with the corresponding CT acquisition. A rigid registration between CT scans was performed. The reconstruction results were loaded on the "Dosimetry toolkit" application. The OARs (red marrow, kidneys, liver, and spleen) were segmented using the CT and SPECT images collected at 4 h post-injection. They were then replicated for the 24 h, 72 h, and 192 h images. The red marrow absorbed dose was determined by delineating the trabecular section on the L2-L4 lumbar vertebrae, considering that this section represents 6.
7% of the total red marrow  [22]. For kidneys, the delineation encompassed the cortex and the medulla regions of the left and right kidney, as described by Sundlöv et al. [11]. For the kidney volume, the partial volume effect correction was considered negligible. For the trabecular section on the L2-L4 lumbar vertebrae, the obtained recovery coefficient was applied. The residence times were calculated with the SPECT sensitivity factor, and then exported to OLINDA/EXM® V1. 0 to calculate the AD/A admin values using the standard organ masses included in the software and the personalized organ masses. These were determined using the volume of each organ of interest defined on the CT images and the biological tissue density proposed by the Monte Carlo Gate database and by Vieira et al. [23]. The relative difference (in %) between the personalized and standard mass for organ i and patient j (Δ mass i, j ) was defined as follows: Δ mass i; j ¼ 100 Â Personalized organ mass ij -Standard organ mass ij Standard organ mass ij where the personalized organ mass ij is the mass of organ i for patient j calculated from the CT images and the biological tissue density, and the standard organ mass ij is the mass of organ i for patient j included in the OLINDA/EXM®V1.
Patient dosimetry Patients Dosimetry was performed after the first two treatment cycles, but for patients 1 and 2. Patient 1 did not have evaluable SPECT/CT data after cycle 1, and patient 2 died before the second cycle of 177 Lu-[DOTA0, Tyr3]-octreotate. Patients received between two and four cycles of 177 Lu-[DOTA0, Tyr3]-octreotate (Table  1 ). For six patients, SPECT/CT image acquisitions were not performed at all four time points after the first and second cycle (Table  1 ), mainly due to health reasons, technical issues, or logistic reasons.
[27], Gupta et al. [35] , and Heikkonen et al. [26]. The mean liver AD/A admin value was slightly higher than what previously published, possibly due to the presence of liver metastases in patient 7. Indeed, the mean and the range of liver AD/A admin values were in accordance with the literature after exclusion of this patient  [35]. The mean red marrow AD/A admin was similar to published data. However, in our study, the dosimetry Fig. 4  Absorbed dose per administered activity (in mGy/MBq) calculated with personalized (CT scan-based) organ masses and standard organ masses (given by OLINDA/EXM® V1. 0 software) after cycle 1 (C1 personalized and C1 standard) and cycle 2 (C2 personalized and C2 standard). As our dosimetry methodology was based on L2-L3-L4 red marrow delineation, it could not be used for patients 3 and 11 who had tumors in contact with L2, L3, L4 and L2, L3, or L4 vertebral metastases methodology was not based on blood sampling, but on L2-L4 red marrow delineation, and could not be applied to patient 3 and 11 who had tumors in contact with L2-L4 vertebrae and L2, L3, or L4 vertebral metastases.
Particularly, variations of blood pressure and body hydration, and thus renal perfusion, could affect the residence time and the absorbed dose in kidneys. Previous studies  [35, 39]  have shown that also in healthy tissues, the time-activity curve shape can differ considerably among patients and in the same patient between treatment cycles. The impact of kinetics and image timing on the absorbed dose to organs is crucial  [40]. Consequently, our dosimetric results are clearly restricted to the use of the Dosimetry Toolkit® software because the time activity curves for each segmented organ were fitted automatically by a mono-exponential function to calculate the residence times. Although other analytic fit functions, such as bi-or tri-exponential functions, are known to better fit the time-activity curves  [40, 41] , these options were not implemented in the software.
Moreover, the Dosimetry Toolkit® software has a limited set of segmentation tools, is not user-friendly, and not optimal. Another major drawback is that this software cannot save the images and volumes of interest in Dicom format from the beginning to the end of the process. For example, it is not possible to change organ delineation after the process. In addition, the Dosimetry Toolkit® software is associated with a specific gamma camera by a license system. The software only accepts images obtained with a gamma camera with a known license number. Consequently, imaging data obtained with other gamma cameras cannot be used. However, new solutions are commercially available with user-friendly tools for segmentation, including those commonly used for EBRT (such as Boolean operators, easy manual, semi-automatic, automatic segmentation options…) and for nuclear medicine.
, 2017). Snow-related observations are provided both at daily and hourly resolution. Weekly manual snow pits enable to collect internal snowpack information (e. g. snow temperature, density profiles, liquid water content). Furthermore, hourly records of temperature and height of vertically-free settling disks are available. Along with weekly manual SWE measurements, since the season 2001-2002 SWE is automatically measured on a daily basis by a ground-based cosmic rays counter. Hourly snow albedo data are estimated through the radiation sensors, as the ratio between incoming and reflected shortwave radiation  (Morin et al. , 2012). Moreover, measurements of snow surface and soil temperatures are hourly available. Snowmelt runoff is hourly estimated through two lysimeters, as well.