dataesr/scientific-paragraphs-categorization huggingface dataset:
Probes were then hybridized for 2 h at 43 °C followed by RNAscope amplification. The following RNAscope probes were used in this study: RNAscope 2. 5 VS Probe-Hs-DapB (dihydrodipicolinate reductase; cat. #312039), RNAscope 2. 5 VS Probe-Hs-PPIB (cat. #313909), RNAscope 2. 5 VS Probe-Hs-CSF1R (cat. #310819) and RNAscope 2. 5 VS Probe-Hs-CSF1 (cat. # 313009). Final signal detection was carried out using mRNA HRP (ACD RNAscope VS Universal HRP Detection Reagents cat #323210) and counterstaining with hematoxylin II (Roche, cat# 05266726001) and bluing solution (Roche, cat# 05266769001). Finally, slides were removed from the Ventana, dehydrated, and coverslipped with Cytoseal XYL (Thermo Scientific, cat# 8312-4). Slides were dried and then imaged with Aperio Scanscope AT. Ki67 quantification was performed using the ImageJ Software.
CSF1R and CSF1 expression levels were calculated as the fold change compared to control samples and all samples were normalized to a housekeeping gene. Technical triplicates were averaged for each sample. Each data point represents the mean per subject and graphical bars represent the mean of each group with error bars depicting the standard error of the mean. A Kruskal-Wallis nonparametric one-way ANOVA with multiple comparisons was used to determine the statistical significance of differences between CTL, RRMS, and Prog MS samples. Statistical analysis was performed with Prism 6 (GraphPad Software) and the p values are 0. 0148 for CSF1R and 0. 0211 for CSF1.
The next day, membranes were washed 3 × 5 min in TBS with 0. 1% Tween 20 (0. 1% TBST) and incubated in secondary antibodies diluted in 0. 1% TBST for 1 h at room temperature. The secondary antibody were IRDye 800CW Donkey anti-Rabbit (1:5000; Li-Cor, Cat# 926-32213) and IRDye 680RD Donkey anti-Mouse (1:5000; Li-Cor, Cat# 926-68072). Membranes were then washed 3 × 5 min in 0. 1% TBST and once in TBS. The membranes were then imaged on the Licor Odyssey CLX. CSF1R protein expression was calculated on the Licor Odyssey CLX. Each data point represents a single subject and graphical bars represent the mean of each group with error bars depicting the standard error of the mean. A Kruskal-Wallis nonparametric one-way ANOVA with multiple comparisons was used to determine the statistical significance of differences between CTL, RRMS, and Prog MS samples.
Cerebrospinal fluid analysis Patient-derived cerebrospinal fluid was kindly provided by the Haghikia Lab at Ruhr-University Bochum Germany (CIS: n = 5; RRMS: n = 66; Prog MS: n = 64). Cerebrospinal fluid was assayed with the Human Quantikine CSF1 ELISA kit (R&D Systems, cat# DMC00B) or the Human Quantikine IL-34 ELISA kit (R&D Systems, cat# D3400) per the kit instructions. Each data point represents a single subject and graphical bars represent the mean of each group with error bars depicting the standard error of the mean. A Kruskal-Wallis nonparametric oneway ANOVA with multiple comparisons was used to determine the statistical significance of differences between CTL, RRMS, and Prog MS samples. Statistical analysis was performed with Prism 6 (GraphPad Software) and the p value is 0. 0005 for CSF1 and 0.
Following EAE induction, animals were scored for paralytic symptoms as described above for the NOD-EAE. For efficacy studies, animals were randomized into treatment groups as soon as they exhibited a score of 1 (n=13 per group). Treatment groups were blinded for the duration of the study and unblinded following final data analysis. For all EAE studies, the sample size was chosen based upon previous experience with the EAE models as well as previously published studies in the literature. A power analysis was conducted to confirm the sample size selection. For all EAE clinical disease score graphs, data points represent the mean clinical disease score for each day and error bars represent the standard error of the mean. Prism 6 (GraphPad Software) was used to calculate the area under the curve for each animal and a one-way ANOVA with multiple comparisons was used to determine the statistical significance of differences between treatment groups.
Flow cytometry for NOD-EAE Cell suspensions were incubated with primary antibodies for 10 min at room temperature, protected from light. Cells were stained for the following: CD11b (Biolegend, cat# 108745, 1:100), CD45 (Biolegend, cat# 101243, 1:250). Samples were washed twice with staining buffer (0. 2% sodium azide, 1. 5% BSA, 5mM EDTA, 5% heat-inactivated Fetal Calf Serum in Dulbecco's Phosphate Buffered Saline) and then fixed with 0. 5% PFA. Data were acquired on a Biorad ZE5 flow cytometer and compensation was performed using UltraComp eBeads (Invitrogen, cat# 01-2222-42).
Slides were imaged by fluorescence microscopy using a Zeiss Imager. Z1 microscope equipped with a Zeiss AxioCam MRm digital camera and Zen Pro 2012 Imaging Software. Microglia were identified by Iba1 + immunoreactivity and Iba1+ area was quantified using the ImageJ Software. At least six images were quantified per animal. Data points represent the Iba1 + area for each animal, graphical bars represent the mean per group, and error bars represent the standard error of the mean. An unpaired t-test was used to determine the statistical significance of differences between naïve and NOD-EAE mice. Statistical analysis was performed with Prism 6 (GraphPad Software) and p values are 0. 0002 (cortex), 0. 0037 (cerebellum), and <0. 0001 (hippocampus and spinal cord).
Sequencing libraries were prepped and uniquely indexed using Illumina's Nextera XT kit without modification to the standard protocol. Average size of libraries ranged from 800-900bp using the Tapestation 4200. Each sample was quantified using Qubit then diluted to 4nM and pooled together. To prepare for sequencing, pooled libraries were first denatured with NaOH then diluted to 1. 8pM and finally run on an Illumina NextSeq500 using the High output kit and a 2x76bp paired end run. CSF1R and CSF1 expression were calculated as the fold change compared to naïve animals. Data point represents the expression level of each animal, graphical bars represent the mean of each group, and error bars depict the standard error of the mean. A one-way ANOVA with multiple comparisons was used to determine the statistical significance of differences between naïve and NOD-EAE samples.
Statistical analysis was performed with Prism 6 (GraphPad Software) and the p values are 0. 0001 (CSF1R: naïve versus NOD-EAE Day 6, 16, 22, 27, and 37), 0. 0023 (CSF1R: naïve versus NOD-EAE Day 65), 0. 0001 (CSF1: naïve versus NOD-EAE Day 6, 16, 27, 37, and 65), and 0. 0003 (CSF1: naïve versus NOD-EAE Day 22).
The plate was then placed on ice and a cell scraper was used to lift the cells off the plate. The lysate was collected into tubes, sonicated 5 × 1 s, and incubated for 15 min at 4 °C. After lysis, the protein concentration of each sample was determined in duplicate using a Pierce Rapid Gold BCA Protein Assay Kit (Thermo Fisher, cat# A53226). Briefly, 5 µl of sample was added to 200 µL BCA working reagent in a 96-well plate and 10 µL of Bovine Serum Albumin Standards were used to generate a standard curve. Sample absorbance was read at 490 nm using the Flex Station and SoftMax Pro 5. 4 software and the sample concentrations were calculated as µg/ml protein. Samples were then diluted in lysis buffer to prepare aliquots containing 16 µg protein in 20 µL total volume and run on western blot as described above.
Within each experiment, three separate wells were treated for each condition. Each stimulation paradigm was repeated three different times using BV2 cells from a distinct cell passage. Protein expression was calculated on the Licor Odyssey CLX. Each data point represents a single sample and graphical bars represent the mean of each group with error bars depicting the standard deviation. A one-way ANOVA with multiple comparisons was used to determine the statistical significance of differences between groups. Statistical analysis was performed with Prism 6 (GraphPad Software). For CSF1 stimulation, the p values are 0. 0001 (all comparisons in phospho-CSF1R and phospho-ERK1/2), 0. 0031 (CSF1R degradation: unstimulated versus CSF1 stimulation), and 0. 0021 (CSF1R degradation: CSF1 stimulation versus sCSF1R inh treatment).
The columns were then placed in a new collection tube and centrifuged at 1000 g for 2 min. The eluates were then analyzed in combination with the original input samples via Western Blot. Within each experiment, three separate wells were treated for each condition. Each stimulation paradigm was repeated three different times using BV2 cells from a distinct cell passage. Protein expression was calculated on the Licor Odyssey CLX. Each data point represents a single sample and graphical bars represent the mean of each group with error bars depicting the standard deviation. A one-way ANOVA with multiple comparisons was used to determine the statistical significance of differences between groups. Statistical analysis was performed with Prism 6 (GraphPad Software). For CSF1 stimulation, the p values are 0.
2% PBT overnight at 4 °C. The next day, cells were washed 3 × 5 min in 0. 2% PBT and incubated in secondary antibody (donkey anti-rabbit Alexa Fluoro 488, 1:500; Life Technologies, cat# A21206) diluted in 1% donkey serum/0. 2% PBT for 1 h at room temperature. Cells were then washed 3 × 5 min in 0. 2% PBT, incubated in DAPI (1:10,000 in PBS) for 5 min at room temperature, and rinsed in PBS. Plates were then imaged on the IN Cell Analyzer 2200 with nine fields of view acquired per well. Quantification was performed with the INCell Developer Analysis software, calculating the sum of the area (in μm 2 ) of Iba1 staining or the number of Ki67 + cells for the nine fields. The average value per field in each well was calculated for each technical triplicate and normalized to the average of the DMSO control wells.
Each data point represents a single sample and graphical bars represent the mean of each group with error bars depicting the standard deviation. A one-way ANOVA with multiple comparisons was used to determine the statistical significance of differences between groups. Statistical analysis was performed with Prism 6 (GraphPad Software). For CSF1 stimulation, the p values are 0. 0019 (unstimulated versus CSF1 stimulation) and 0. 0037 (CSF1 stimulation versus sCSF1R inh treatment). Statistical analysis was performed with Prism 6 (GraphPad Software) and p values are 0. 0001 (Confluence: all comparisons, Iba1 area: DMSO + CSF1 versus unstimulated and DMSO, and Ki67: all comparisons) and 0. 0013 (Iba1 area: DMSO + CSF1 versus sCSF1R inh treated). Within each experiment, three separate wells were treated for each condition.
Once dry, 25 µL of Beta-Count scintillation fluid is added to each well, and the plate is counted on the Trilux counter using the 3 H protocol #10. The level of proliferation observed in CSF1-stimulated macrophages was set at 0% inhibition and the level proliferation observed in unstimulated macrophage proliferation was set at 100% inhibition. Subsequently, the % inhibition generated from each concentration of sCSF1R inh was calculated. Each data point represents the mean % inhibition of each concentration of sCSF1R inh with error bars depicting the standard deviation. The IC 50 value was calculated with Prism 6 (GraphPad Software). Within each experiment, three separate wells were treated for each condition. Each stimulation paradigm was repeated three different times using primary murine bone marrow macrophages obtained from three distinct animals.
Each data point represents a single well and graphical bars represent the mean of each group with error bars depicting the standard deviation. A one-way ANOVA with multiple comparisons was used to determine the statistical significance of differences between groups. Statistical analysis was performed with Prism 6 (GraphPad Software). For MCP1, the p value is 0. 0001 for all comparisons. For IL-12p40, the p values are 0. 0001 for all comparisons to DMSO + LPS and 0. 0022 for 100 nM versus 500 nM sCSF1R inh treatment. Within each experiment, six separate wells were treated for each condition. Each stimulation paradigm was repeated three different times using primary microglial cells obtained from three distinct litters. Cell survival assays in primary murine mixed glia and primary murine microglial cultures Mixed glia were seeded at 25,000 cells per well in a PDLcoated black 96-well plate and cultured for 12 days with media changes on DIV5 and DIV8.
On day 12, cells were treated with increasing dose of CSF1R inhibitors (sCSF1R inh and PLX3397) for three days. In addition, some plates were pretreated with a pan-caspase inhibitor, zVAD (Enzo, cat# ALX-260-020-M005), at 20 µM 2 h prior to CSF1R inhibitor treatment. After treatment, plates were fixed and stained for CSF1R and IBA1 (as described above). After staining, plates were imaged on the INCell Analyzer 2200 with nine fields of view acquired per well. The quantification was performed on the INCell Developer Analysis software, calculating the sum of the area (in µm 2 ) of CSF1R or Iba1 staining for the nine fields. The average area per field in each well was calculated and normalized to the average of the DMSO control wells. Each data point represents the mean % Iba1 area at each concentration of sCSF1R inh with error bars depicting the standard deviation.
The IC 50 value was calculated with Prism 6 (GraphPad Software). Within each experiment, three separate wells were treated for each condition. Each stimulation paradigm was repeated three different times using primary mixed glia obtained from three distinct litters. Similar experiments were conducted in primary murine microglia and the Cell Titer-Glo Luminescent Cell Viability Assay (Promega, cat# G7570) was used to assay cell survival. Each data point represents a single well and graphical bars represent the mean of each group with error bars depicting the standard deviation. A one-way ANOVA with multiple comparisons was used to determine the statistical significance of differences between groups. Within each experiment, six separate wells were treated for each condition. Each stimulation paradigm was repeated three different times using primary microglia obtained from three distinct litters.
In vivo microglial depletion study Adult C57BL/6 female mice (8 weeks old) were orally dosed with sCSF1R inh or PLX3397 for 7 days at 50 mg/kg, 100 mg/kg, and 200 mg/kg (n = 4-6 per group). One hour after their last dose, the mice were cardiac perfused with 25 mL of ice cold HBSS. A craniotomy was performed to excise the brain with dissecting tools and the meninges were carefully removed from the surface of the brain. The brain was placed in ice cold 4% PFA overnight at 4 °C and then continuously sectioned in the sagittal plane on a Leica vibratome. Slices were stored at 4 °C until processed for immunohistochemistry. Quantification was performed using the Analysis tools included in ImageJ Software. Microglia were identified by Iba1 + immunoreactivity and manually labeled within the Cell Counter Plugin.
At least six images were quantified per animal to determine the number of microglia. Data points represent the Iba1 quantification for each animal, graphical bars represent the mean per group, and error bars represent the standard error of the mean. A one-way ANOVA with multiple comparisons was used to determine the statistical significance of differences between groups. Statistical analysis was performed with Prism 6 (GraphPad Software) and p values are 0. 0005 (100 mg/kg versus 200 mg/kg), 0. 0007 (50 mg/kg versus 100 mg/kg) and 0. 0001 for all other significant comparisons.
A1 cocktail stimulation of primary human astrocytes Primary human astrocytes (Gibco cat# N7805-100) were at 20,000 cells per well in a 96 well matrigelcoated plate and maintained in culture for 6 days. On day 7, the media was changed to a serum-free formulation. The following day, cells were stimulated with increasing A1 cocktail concentrations (low = 0. 06ng/mL IL-1α + 0. 6ng/mL TNF-α + 8ng/mL C1q, med = 0. 12ng/mL IL-1α + 1. 2ng/mL TNF-α + 16ng/mL C1q, high = 0. 3ng/mL IL-1α + 3ng/mL TNF-α + 40ng/mL C1q) for 24 h. Supernatants were collected for quantification of CSF1 with the Human Quantikine CSF1 ELISA kit (R&D Systems, cat# DMC00B) per the kit instructions. Within each experiment, three separate wells were treated for each condition. Each data point represents a single well and graphical bars represent the mean of each group with error bars depicting the standard deviation.
The protein content of each sample was determined using the bicinchoninic acid (BCA) assay (Pierce cat # 23225, Rockford, IL), with bovine serum albumin (BSA) as a standard, according to the manufacturer's protocol. Sample absorbance was read at 560 nm using a spectrophotometer (Molecular Devices Versa Max, Sunnyvale, CA). Results were normalized to protein concentration and cytokine/chemokine levels were reported as picograms of cytokine/mg of tissue protein. Each data point represents a single spinal sample and graphical bars represent the mean of each group with error bars depicting the standard error of the mean. A one-way ANOVA with multiple comparisons was used to determine the statistical significance of differences between groups. Statistical analysis was performed with Prism 6 (GraphPad Software) and p values are 0.
Nanostring analysis Nanostring analysis was performed as previously described  20, 48. Briefly, the MG550 NanoString chip was designed using the quantitative NanoString nCounter platform. Selection of genes was based on analyses that identified genes and proteins which were specifically or highly expressed in adult mouse microglia 48 plus inflammation-related genes which were significantly affected in EAE, APP-PS1, and SOD1 mice. MG550 encompasses 400 unique and enriched microglial genes we have identified previously  48  and additional 150 inflammation-, inflammasome-and phagocytosis-related genes. NanoString data were normalized and analyzed using the nSolver software. RNA ncounts were normalized using the geometric mean of six housekeeping genes (HKGs): Cltc, Gapdh, Gusb, Hprt, Pgk1, and Tubb5.
A cutoff was introduced at the value of the highest negative control present on the chip. Fold changes were calculated using the average of each group. For each experiment, the fold changes were calculated comparing the experimental group to their appropriate controls. Each data point represents microglia from a single spinal cord sample and graphical bars represent the mean of each group with error bars depicting the standard error of the mean. A one-way ANOVA with multiple comparisons was used to determine the statistical significance of differences between groups. Statistical analysis was performed with Prism 6 (GraphPad Software) and p values are 0. 0053 (TMEM119), 0. 0203 (P2RY12), 0. 0134 (CX3CR1), 0. 0407 (SPP1), 0. 0474 (Lilrb4), and 0. 0011 (Fabp5).
Acknowledgements The authors thank  Mark Czekaj ,  Barret Giese ,  Liang Ma ,  Patrick Shum , and  Jin Zhao  for help preparing the sCSF1R inh compound for our studies and  Yan He  for compound formulations. We also thank  Tim Hammond ,  Carlos Pedraza , and  Lamya Shihabuddin  for their critical feedback during manuscript preparation. Human tissue was obtained from  Human Brain  and  Spinal Fluid Resource Center (HBSFRC) at University of California Los Angeles.
Background: There is a growing body of evidence highlighting the potential of mobile health (mHealth) in reducing health care costs, enhancing access, and improving the quality of patient care. However, user acceptance and adoption are key prerequisites to harness this potential; hence, a deeper understanding of the factors impacting this adoption is crucial for its success. Objective: The aim of this review was to systematically explore relevant published literature to synthesize the current understanding of the factors impacting clinicians' adoption of mHealth tools, not only from a technological perspective but also from social and organizational perspectives. Methods: A structured search was carried out of MEDLINE, PubMed, the Cochrane Library, and the SAGE database for studies published between January 2008 and July 2018 in the English language, yielding 4993 results, of which 171 met the inclusion criteria.
Search Strategy A search of MEDLINE, PubMed, the Cochrane Library, and the SAGE database in August and September 2018 identified the relevant studies. The scope was narrowed to studies published in the English language between January 2008 and August 2018. Only original, peer-reviewed, and published papers were included. Other forms, such as editorials, unsystematic reviews, interviews, comments, unstructured observations, and position papers, were excluded. It was decided not to include articles on the basis of on hand searches of reference lists for causes summarized in the Cochrane Handbook: "positive studies are more likely to be cited" and "retrieving literature by scanning reference lists may thus produce a biased sample of studies"  [27]. The search string shown in Figure  1  was developed according to the participants, intervention, comparators, and outcome (PICO) framework  [29].
After completing the screening, and resolving any conflicting views between the researchers, the selected full texts were assessed for eligibility by CJ and AV, independently. Any disagreements were resolved by discussing with CI. Subsequently, the risk of bias was assessed using the Critical Appraisal Skills Program tool  [32]. The checklist is included in Multimedia Appendix 2, and an Excel sheet with the appraisal of the included studies can be accessed in Multimedia Appendix 3. On the basis of the appraisal, 38 out of the 171 studies did not report a clear participant recruitment strategy, 40 papers did not give enough details on their data collection techniques, 76 did not clarify how they addressed potential ethical considerations, and 25 were not clear enough about their data analysis strategy and whether it was sufficiently rigorous.
Data Collection and Synthesis The variety of measures and outcomes that were identified in the included articles were not homogenous enough to enable a quantitative synthesis of the data. Therefore, a narrative synthesis was used and structured around the organizational and technological factors impacting clinicians' adoption of mHealth solutions. QSR NVivo, a computer-assisted qualitative data analysis software, was used to assist in this task. Data coding began with an initial data extraction grid that included themes based on previous research and technology acceptance frameworks; more themes were added as they emerged during the review process. Braun and Clarke's thematic analysis  [33]  was used to identify and extract themes that addressed the review's research question. The phases of the thematic analysis are explained in detail in Multimedia Appendix 4.
Data Collection We extracted the following: 1) rate of aneurysm occlusion, 2) rate of complications, and 3) clinical outcomes. Adequate aneurysm occlusion (complete/near-complete occlusion) was defined on the basis of the O'Kelly-Marotta grades C-D,  7  the Raymond-Roy scale (class I-II),  8  or when the terms "complete occlusion" or "neck remnant" were used in the study. Treatment-related complications were classified as following: 1) periprocedural (within 30 days after treatment) and delayed events (after 30 days); 2) transient complications (asymptomatic events or complete neurologic recovery) and permanent events (symptomatic complications with permanent deficits); and 3) hemorrhagic and ischemic complications. Aneurysms were classified as small and large lesions (,10 and $10 mm, respectively).