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Figure 6 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 6 Simulating inflation, between 2024 and 2040 – Basic number: 2% inflation per year.
Figure 8 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 8 Simulation of inflation, Model B.
Figure 7 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 7 Simulation of inflation, Model A.
Figure 9 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 9 Simulation of inflation, Model C.
Figure 1 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 1 DiSSCo timeline.
Figure 11 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 11 DiSSCo national contribution models.
Figure 2 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 2 DiSSCo general membership fee calculation model.
Figure 4 from: Sidjimova D, Benisheva T, Topalova V, Petkova V (2024) Attitude of medical doctors to adverse drug reactions reporting in Bulgaria. Pharmacia 71: 1-7. https://doi.org/10.3897/pharmacia.71.e115559
Figure 4 Motivating factors for reporting of ADRs.
Figure 3 from: Sidjimova D, Benisheva T, Topalova V, Petkova V (2024) Attitude of medical doctors to adverse drug reactions reporting in Bulgaria. Pharmacia 71: 1-7. https://doi.org/10.3897/pharmacia.71.e115559
Figure 3 Reasons for not reporting an ADR.
Figure 2 from: Sidjimova D, Benisheva T, Topalova V, Petkova V (2024) Attitude of medical doctors to adverse drug reactions reporting in Bulgaria. Pharmacia 71: 1-7. https://doi.org/10.3897/pharmacia.71.e115559
Figure 2 Level of knowledge of ADRs reporting obligation.
Figure 1 from: Sidjimova D, Benisheva T, Topalova V, Petkova V (2024) Attitude of medical doctors to adverse drug reactions reporting in Bulgaria. Pharmacia 71: 1-7. https://doi.org/10.3897/pharmacia.71.e115559
Figure 1 Reported ADRs to a Marketing Authorization Holder or to Bulgarian Drug Agency.
MANAGEMENT OF CHRONIC GRANULAR HYPERTROPHIC PHARYNGITIS (VRUNDA) THROUGH AYURVEDA- A CASE REPORT
<p><strong><span>Background: </span></strong><span>Fungal, bacterial, or viral infections can result in pharyngitis</span><strong><span>. </span></strong><span>For adult and pediatric populations, respectively, sore throats account for over 2% and 5% of all outpatient primary care visits</span><strong><span>. </span></strong><span>The modified Centor or Fever PAIN scoring systems' primary clinical features are largely used to diagnose the cause of pharyngitis</span><strong><span>. Aim and objectives</span></strong><span>: The aim is to recognize the effectiveness and importance of Ayurvedic medicine in treating chronic catarrhal pharyngitis, or Vrunda. <strong>Material and</strong> <strong>Methods</strong>: This case study of a male child of 5 years old presented with Chronis Catarrhal Pharyngitis managed by Ayurveda treatment. Ayurveda therapy comprises oral medication, <em>Panchakarma</em> therapy, and <em>Pranayama. </em><strong>Observation and result</strong>: After treatment patient has shown improvement in all the symptoms. Patient follow-up and treatment were consistent on the 7th and 15th days, and oral intake was as advised. <strong>Discussion</strong>: In this case, patients showed improvement in chronic symptoms and Kawala therapy provided a new level of understanding through Ayurveda. </span></p>
Figure 1 from: Bouquillon L, Bindman D, Hendriksen J, Collin P, Hoskin J, Conn R, Geagan C, Quinlivan R (2024) Workshop report: Workshop on psychiatric prescribing and psychology testing and intervention in children and adults with Duchenne muscular dystrophy. Research Ideas and Outcomes 10: e119243. https://doi.org/10.3897/rio.10.e119243
Figure 1 The Big 10 model of non-motor problems in DMD (kindly provided by Dr Jos Hendriksen).
Temporal changes in treatment and late mortality and morbidity in adult survivors of childhood glioma: a report from the Childhood Cancer Survivor Study
<p><strong>Abstract:</strong></p> <p>Pediatric glioma therapy has evolved to delay or eliminate radiation for low-grade tumors. This study examined these temporal changes in therapy with long-term outcomes in adult survivors of childhood glioma. Among 2,501 5-year survivors of glioma in the Childhood Cancer Survivor Study diagnosed 1970–1999, exposure to radiation decreased over time. Survivors from more recent eras were at lower risk of late mortality (≥5 years from diagnosis), severe/disabling/life-threatening chronic health conditions (CHCs) and subsequent neoplasms (SNs). Adjusting for treatment exposure (surgery only, chemotherapy, or any cranial radiation) attenuated this risk (for example, CHCs (1990s versus 1970s), relative risk (95% confidence interval), 0.63 (0.49–0.80) without adjustment versus 0.93 (0.72–1.20) with adjustment). Compared to surgery alone, radiation was associated with greater than four times the risk of late mortality, CHCs and SNs. Evolving therapy, particularly avoidance of cranial radiation, has improved late outcomes for childhood glioma survivors without increased risk for late recurrence.</p>
Risk factors for neurocognitive impairment, emotional distress, and poor quality of life in survivors of pediatric rhabdomyosarcoma: A report from the Childhood Cancer Survivor Study
<p>Dataset contains all variables used in the manuscript. </p> <p>Variable name file describes the variable names in details.</p>
Figure 4 from: Islam S, Papale D, Vaira L, Rosati I, Peterseil J, Pichot C (2024) Navigating taxonomic complexity: A use-case report on FAIR scientific name-matching service usage in ENVRI Research Infrastructures. Research Ideas and Outcomes 10: e121871. https://doi.org/10.3897/rio.10.e121871
Figure 4 LifeWatch web service taxon match list. Screenshot captured 10 Jan 2024.
Figure 3 from: Islam S, Papale D, Vaira L, Rosati I, Peterseil J, Pichot C (2024) Navigating taxonomic complexity: A use-case report on FAIR scientific name-matching service usage in ENVRI Research Infrastructures. Research Ideas and Outcomes 10: e121871. https://doi.org/10.3897/rio.10.e121871
Figure 3 LifeWatch web service data upload screen. Screenshot captured 10 Jan 2024.
Figure 1 from: Islam S, Papale D, Vaira L, Rosati I, Peterseil J, Pichot C (2024) Navigating taxonomic complexity: A use-case report on FAIR scientific name-matching service usage in ENVRI Research Infrastructures. Research Ideas and Outcomes 10: e121871. https://doi.org/10.3897/rio.10.e121871
Figure 1 COL Checklistbank cross dataset search. Screenshot captured 10 Jan 2024.
Figure 2 from: Islam S, Papale D, Vaira L, Rosati I, Peterseil J, Pichot C (2024) Navigating taxonomic complexity: A use-case report on FAIR scientific name-matching service usage in ENVRI Research Infrastructures. Research Ideas and Outcomes 10: e121871. https://doi.org/10.3897/rio.10.e121871
Figure 2 COL name match tool for bulk input. Screenshot captured 10 Jan 2024.
Oil extraction report from Chlamydomonas reinhardtii engineered to produce ketocarotenoids
<p>Report of oil extraction efficiency on <em>Chlamydomonas reinhardtii</em> strain engineered to produce ketocarotenoids and astaxanthin.</p> <p> </p> <p><strong>Oil report on lab scale:</strong></p> <p>Oil extraction was performed as described in Perozeni et al. Plant Biotechnology Journal 2020, starting from different volumes of saturated culture (300, 600, 900, and 1800 ml). The cells were pelleted and dissolved in 25 ml of sunflower oil. The extraction was thus performed on wet biomass. After centrifugation, the oil extract was diluted in oil and the absorption spectrum was used to determine the ketocarotenoid concentration as described in Perozeni et al. Plant Biotechnology Journal 2020.</p> <p> </p> <p>The spectra recorded are in the sheet “Raw”. In the sheets “Quantification” there are the results of the ketocarotenoids quantification and the extraction efficiency. In the sheet "summary" the overall results in terms of starting material, final oil volume, ketocarotenoid concentration and extraction efficiency are presented.</p> <p>Samples:</p> <p>1x: extraction starting from 300ml of C. reinhardtii EN1 strain saturated culture, oil extract diluted 1:10 before measuring the absorption spectrum.</p> <p>2x: extraction starting from 600ml of C. reinhardtii EN1 strain saturated culture, oil extract diluted 1:100 before measuring the absorption spectrum.</p> <p>3x: extraction starting from 900ml of C. reinhardtii EN1 strain saturated culture, oil extract diluted 1:100 before measuring the absorption spectrum.</p> <p>6x: extraction starting from 1800ml of C. reinhardtii EN1 strain saturated culture, oil extract diluted 1:1000 before measuring the absorption spectrum.</p> <p>6x 3<sup>rd</sup> cycle: extraction starting from 5400ml of C. reinhardtii EN1 strain saturated culture in three extraction steps recycling in each step the oil used for extraction to increase ketocarotenoid concentration, oil extract diluted 1:1000 before measuring the absorption spectrum.</p> <p>6x 4<sup>th</sup> cycle: extraction starting from 7200ml of C. reinhardtii EN1 strain saturated culture in three extraction steps recycling in each step the oil used for extraction to increase ketocarotenoid concentration, oil extract diluted 1:1000 before measuring the absorption spectrum.</p> <p>6x 5<sup>th</sup> cycle: extraction starting from 9000ml of C. reinhardtii EN1 strain saturated culture in three extraction steps recycling in each step the oil used for extraction to increase ketocarotenoid concentration, oil extract diluted 1:1000 before measuring the absorption spectrum.</p> <p>6x 6<sup>th</sup> cycle: extraction starting from 10800ml of C. reinhardtii EN1 strain saturated culture in three extraction steps recycling in each step the oil used for extraction to increase ketocarotenoid concentration, oil extract diluted 1:1000 before measuring the absorption spectrum.</p> <p> </p> <p> </p> <p><strong>Oil extraction report on large scale:</strong></p> <p>Oil extraction was performed according to the procedure developed for lab scale starting from 200 gr of total dry biomass (corresponding to a volume of 250L of a saturated cell culture). The overall biomass was extracted in three independent extractions (Extraction 1, 2, and 3), recycling the oil extract for up to 4th cycle, keeping the same ratio of oil/biomass adopted in the lab scale experiment. In the case of Extraction 1 the extraction was performed on wet biomass, while Extraction 2 and 3 were performed on dry biomass. After Extractions 1 and 2, the final pellet obtained was further extracted in oil (samples “ 2nd extraction 1” and “2nd extraction 2”). The spectra recorded are in the sheet “Raw”. In the sheet “Quantification” there are the results of the ketocarotenoids quantification considering the dilution (in oil) applied to the oil extracts. </p> <p>In the sheet “extraction eff." the finalresults in terms of starting material, final oil volume, ketocarotenoid concentration and extraction efficiency are presented. The overall extraction efficiency obtained considering all the extraction performed and the total oil extracts obtained is also reported </p> <p> </p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.