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Primed In Situ Labeling

Primed In Situ Labeling is a powerful technique that allows for the sensitive and specific detection of target molecules within their native cellular context.
This approach involves the use of specially designed probe molecules that bind to and label the molecules of interest, enabling visualization and analysis.
The PubCompare.ai platform provides an innovative AI-driven solution to streamline the process of identifying the optimal research protocols for Primed In Situ Labeling, enhancinge reproducibility and accuracy.
By searchign the literature, pre-prints, and patents, the platform helps researchers find the best protocols and products to meet their specific research needs.
This streamlined workflow and AI-powered comparisons can improve scientific outcomes and advance the field of in situ labeling.

Most cited protocols related to «Primed In Situ Labeling»

1
Validation of PTSD Measures in Veterans
Cited 161 times
Sample 1 consisted of 167 veterans recruited at a VA Healthcare System for a study designed to validate both the PTSD Checklist for DSM–5 (PCL-5; Weathers, et al., 2013 ) and the CAPS-5 (Weathers, Blake, et al., 2013 ). A subset of these data was used previously to validate the PCL-5 (Bovin et al., 2016 (link)). This study followed the second version of the Quality Assessment of Diagnostic Accuracy Studies guidelines (QUADAS-2; Whiting et al., 2011 (link)), which minimizes the influence of various sources of bias that can affect diagnostic utility studies (see Bovin et al., 2016 (link)). This study was open to all veterans who were aged 18 or older who could read written materials in English. Potential participants were screened for trauma exposure and PTSD symptoms with the Brief Trauma Questionnaire (Schnurr et al., 2002 ) and Primary Care PTSD Screen (PC-PTSD; Prins et al., 2003 ), administered during an initial phone contact with a trained research assistant. Individuals who reported experiencing at least one PTSD Criterion A event and at least one PTSD symptom in the last 30 days were included in this study. The requirement of at least one PTSD symptom was applied to minimize restriction of range in scores on the CAPS-5 and other PTSD measures.
Participants for Sample 1 were recruited into one of three phases: Phase 1 (n = 31), Phase 2 (n = 61), and Phase 3 (n = 75). In Phase 1, CAPS-IV versus CAPS-5 comparisons were based on 30 participants with complete data (original interviewer’s ratings) for both interviews; one participant was excluded because he did not complete the CAPS-IV. Interrater reliability analyses were based on 27 participants for CAPS-IV and 28 for CAPS-5 for whom audio recorded interviews were available. For all Phase 1 participants, the index event for symptom inquiry met Criterion A for both DSM–IV and DSM–5 PTSD criteria. In Phase 2, test–retest analyses were based on 60 participants with complete data for both administrations of the CAPS-5; one participant was excluded because he did not complete the CAPS-5.
Participants from Phases 1 through 3 were combined for internal consistency and convergent and discriminant validity analyses. Two participants in Phase 3 did not complete the CAPS-5 and were excluded from all subsequent analyses. Thus, the combined sample for these analyses was 165, including 31 from Phase 1, 61 from Phase 2, and 73 from Phase 3 (see Table 1).
Sample 2 consisted of 207 male veterans who completed the baseline assessment of an ongoing clinical trial (Sloan, Unger, & Gayle Beck, 2016 (link)). Eligible veterans were invited to complete an initial assessment (see Sloan et al., 2016 (link) for a detailed overview of study procedures). The only inclusion criteria for the present study were being a male veteran with an index event that met DSM–5 Criterion A, and self-identifying as being appropriate for a PTSD treatment study. See Table 1 for characteristics of the sample.
Weathers F.W., Bovin M.J., Lee D.J., Sloan D.M., Schnurr P.P., Kaloupek D.G., Keane T.M, & Marx B.P. (2017). The Clinician-Administered PTSD Scale for DSM–5 (CAPS-5): Development and Initial Psychometric Evaluation in Military Veterans. Psychological assessment, 30(3), 383-395.
Publication 2017
Diagnosis Interviewers Males Post-Traumatic Stress Disorder Primary Health Care Primed In Situ Labeling Tests, Diagnostic Veterans Wounds and Injuries
2
Comprehensive SNP Annotation Protocol
Cited 78 times
The user can create a list of SNP positions and this feature annotates the markers with evidence collected from various other databases and analyses. This list may be significant markers from gene expression or GWAS studies. The annotations can include gene models (RAP (17 (link)), MSUv7 (16 (link)) or FGenesh++ (18 (link))) or promoter regions (FGenesh++, PlantPromDB (24 (link))) if SNPs are located within these loci. The effects of SNP variants were also added using results from SNPEff (25 (link)). For SNPs within gene models, additional evidence about the gene are included using Gene Ontology terms, Plant and Trait Ontology terms and gene names collected from Oryzabase (20 (link)), trait genes from OGRO (21 (link)), and QTL from Q-TARO (26 ), interacting genes from RiceNet v2 (27 (link)) and rice proteins from PRIN (28 (link)). The list of annotations and references are in Supplementary Table S3.
Mansueto L., Fuentes R.R., Borja F.N., Detras J., Abriol-Santos J.M., Chebotarov D., Sanciangco M., Palis K., Copetti D., Poliakov A., Dubchak I., Solovyev V., Wing R.A., Hamilton R.S., Mauleon R., McNally K.L, & Alexandrov N. (2016). Rice SNP-seek database update: new SNPs, indels, and queries. Nucleic Acids Research, 45(Database issue), D1075-D1081.
Publication 2016
Genes Genetic Markers Genome-Wide Association Study Plants Primed In Situ Labeling Proteins Rice Single Nucleotide Polymorphism Taro
3
Large-Scale Electron Microscopy Imaging Protocols
Cited 15 times
All TEM data were collected on FEI Tecnai microscopes. The RCM images were collected on a Leica DMR microscope equipped with an RCM oil-immersion objective endowed with a quarter lambda plate and a reflection contrast module RC (Prins et al., 2005 ). The RCM images were recorded at room temperature with a Leica DFC420 C camera and the Leica application suite microscope software.
The virtual slide shown in Fig. 2 was recorded at 80 kV with a magnification at the detector plane of 9460. A total of 990 4k × 4k images were collected with an FEI Eagle CCD camera in a time interval of 240 min. Every 10th image, the FEI autofocus routine was used to maintain the sample at −1 µm defocus. The resulting slide of 172 × 158 µm2 consists of 108,544 × 99,840 pixels of 1.6 nm square each.
The virtual slide shown in Fig. 3 was recorded at 120 kV with a magnification at the detector plane of 18,080. A total of 441 4k×4k images were collected in 114 min at −1 µm defocus. The resulting slide of 59 × 59 µm2 consists of 71,168 × 70,656 pixels of 0.8 nm square each.
The cryo-TEM slide shown in Fig. 4 was recorded at 120 kV with a magnification at the detector plane of 32,000. A prespecimen shutter was used to avoid unnecessary exposure of the sample to the damaging electron beam. An incident flux of 5 e− Å−2 s−1 was used and the integration time per image was 1 s. The illuminated specimen area was adjusted such that the beam diameter within the detector plane was less than two times the detector width, thereby limiting the integrated flux for each spot of the specimen to a maximum of 15 e− Å−2 s−1. The data were recorded with −10 µm defocus as determined from a single spot nearby the imaged region. A total of 117 2k × 2k images were collected in 18 min. The resulting slide of 19 × 13 µm2 consists of 20,480 × 13,824 pixels of 0.9 nm square each.
The virtual slide shown in Fig. 5 was recorded at 120 kV with a magnification at the detector plane of 9460. A set of points was manually selected to outline the zebrafish and the convex hull of these points was used to define the data collection area. A total of 26,434 unbinned 4k × 4k images was collected with a FEI Eagle CCD camera (>8 s readout time full frame) in 4.5 d. The sample was maintained at −1 µm defocus throughout the whole data collection. The resulting slide of 1,461 × 604 µm2 consists of 921,600 × 380,928 pixels of 1.6 nm square each. The net data content of this slide is 281 Gpixel.
Faas F.G., Avramut M.C., M. van den Berg B., Mommaas A.M., Koster A.J, & Ravelli R.B. (2012). Virtual nanoscopy: Generation of ultra-large high resolution electron microscopy maps. The Journal of Cell Biology, 198(3), 457-469.
Publication 2012
Eagle Electrons Microscopy Primed In Situ Labeling Reading Frames Reflex Submersion Zebrafish
4
Kidney Ultrastructure Analysis in Mice
Cited 11 times
Vibrotome sections of the right kidney of 16-wk-old mice, chronically infused with either active or inactive hyaluronidase for 4 wk, were fixed overnight in 2% PFA, washed twice with phosphate-buffered saline (PBS), and blocked for 30 min on ice with 10% normal goat serum and 0.3% Triton X-100 in PBS. Next, samples were incubated overnight at 4°C with HRP-conjugated goat anti–mouse albumin antibody (Bethyl Laboratories, Inc.) in 1% normal goat serum in PBS, washed twice with PBS, stained for 30 min at 4°C with DAB and H2O2, washed with PBS and 0.1 M sodium cacodylate, incubated for 1 h with 1.5% GA and 1% PFA, rinsed in cacodylate, and postfixed for 1 h in 1% osmium tetroxide and 1.5% potassium ferrocyanide. Samples were dehydrated in a graded ethanol series up to 100% and embedded in Epon. Sequential 100-nm sections were mounted on a copper slot grid covered with formvar support film and a 3-nm carbon coating for TEM, and on a water drop on a clean glass slide for RCM (Prins et al., 2005 ). The RCM sample was mounted with immersion oil (Immersol 518F) on an RCM-adapted microscope (reflection contrast device RC; Leica). Images were recorded with a 1.25 NA 100× objective.
Faas F.G., Avramut M.C., M. van den Berg B., Mommaas A.M., Koster A.J, & Ravelli R.B. (2012). Virtual nanoscopy: Generation of ultra-large high resolution electron microscopy maps. The Journal of Cell Biology, 198(3), 457-469.
Publication 2012
Albumins Antibodies, Anti-Idiotypic Cacodylate Carbon Copper EPON Ethanol Formvar Goat Hyaluronidase Kidney Medical Devices Mice, House Microscopy Normal Saline Osmium Tetroxide Peroxide, Hydrogen Phosphates potassium ferrocyanide Primed In Situ Labeling Reflex Saline Solution Serum Sodium Submersion Triton X-100
5
Muscle Microtubule Directionality Analysis
Cited 9 times
Immunofluorescence images of muscle microtubules were collected as part of a published study [Prins et al. 2009 (link)] but the images used here were not published earlier. Single confocal images were captured on a Leica SP5 confocal system with a 63× NA1.4 oil immersion lens. The image size was 1024 × 512 or 1024 × 1024 square pixels. From the viewpoint of directionality, muscle microtubules form two domains: 1) a highly organized network of cortical microtubules encircling the fiber core, in the narrow space between myofibrils and plasma membrane; 2) sparse microtubules running mostly longitudinally, i.e. parallel to the axis of the fibers, in the myofibrillar core. The images analyzed here were single confocal planes of cortical microtubules. Maximum projections would be appropriate as long as the two domains are kept separate for analysis. As a first step, the program asks the user to select a region of interest (ROI). This steps allows us to exclude myonuclei, because they are surrounded by a cage of isotropic microtubules [Oddoux et al. 2013 (link)]. For best results, the ROI size should be at least 100 × 100 square pixels, because the program needs to calculate the texture correlation for pixel pairs that are separated by up to 60 pixels, as explained further.
Liu W, & Ralston E. (2014). A new directionality tool for assessing microtubule pattern alterations. Cytoskeleton (Hoboken, N.J.), 71(4), 230-240.
Publication 2014
Cortex, Cerebral Epistropheus Fibrosis Immunofluorescence Lens, Crystalline Microtubules Muscle Tissue Myofibrils Plasma Membrane Primed In Situ Labeling Submersion

Most recents protocols related to «Primed In Situ Labeling»

1
Barley Metaphase Chromosome Flow Sorting
Barley metaphase chromosomes (Hordeum vulgare L. cv. Morex) were sorted according to Lysák et al. (1999 (link)). Briefly, a chromosome suspension was prepared from synchronized primary roots meristems. Chromosomes were DAPI-stained, immediately analyzed, and flow-sorted using a FACSAria II SORP flow cytometer and sorter (BD Bioscience, San Jose, CA, USA). Five thousand chromosomes were sorted into 15 μl of PRINS buffer supplemented with 2.5% sucrose (10 mM TRIS, 50 mM KCl, 2 mM MgCl2.6H2O, 2.5% sucrose; pH 8) onto high precision coverslips (Paul Marienfeld GmbH & Co. KG, Lauda-Königshofen, Germany). Before immunolabeling, the coverslips were stored at −20 °C.
Kubalová I., Weisshart K., Houben A, & Schubert V. (2023). Super-resolution microscopy reveals the number and distribution of topoisomerase IIα and CENH3 molecules within barley metaphase chromosomes. Chromosoma, 132(1), 19-29.
Full text: Click here
Publication 2023
Buffers Chromosomes DAPI Hordeum Hordeum vulgare Magnesium Chloride Meristem Metaphase Plant Roots Primed In Situ Labeling Sucrose Tromethamine
2
Evaluating Vibrotactile Feedback for Object Stiffness Perception in Prosthetic Limbs
The subjects were seated comfortably in front of a table (refer to Figure 4) with EMG sensors positioned on the forearm or stump using an elastic band. The electrodes measured the activity of the forearm muscles involved in the opening and closing of the hand (Flexor Carpi Ulnaris and Extensor Carpi Ulnaris, respectively), which were selected by manual inspection. The Hannes system was detached from the users' bodies (except for the two EMGs) and fixed on the table, lying between the subjects' arms with the palm up, to allow the experimenter place the objects to be grasped within the prosthetic hand. Hence, subjects were only asked to close and open their hand, not to approach or grasp the objects. The prosthesis was commanded in proportional-speed-control mode through the EMG signals. To convey the vibratory feedback, the vibromotor was positioned on the pisiform bone for able-bodied subjects and on the lateral epicondyle for the amputees by means of a second elastic band.
First, the minimum and maximum amplitude for the vibromotor was determined using the method of limits (Prins, 2016 ), to find the minimum level of perception and avoid discomfort. To this aim, the vibration intensity was increased in small steps (4–5% in the normalized scale of PWM). When the subject warned, as soon as it was perceptible, the sensing of a small and then of a strong sensation, the respective PWM was saved. Subsequently, 30% of the PWM range was adopted for soft objects and 100% was adopted for rigid objects. The vibration intensity was then modulated between these two values to generate clearly perceivable and localized vibrations that were not intrusive to the subject but intuitive for the encoding of the object stiffness.
Six objects (Figure 1) were randomly presented three times to the user by the experimenter and three void closures were also inserted along the test, to have a total number of 21 trials. Before the test phase, a training phase was performed to let the user become familiar with the feedback. A total of six closures were performed, alternating between rigid and soft objects without headphones and with open eyes, so the user could learn to associate the proper feedback with the right stiffness. Furthermore, the involved upper limb side was covered with a black blanket to strengthen a possible embodiment effect.
In the first phase to evaluate the classifier performance and the feedback effectiveness, the able-bodied subjects underwent a single test with a single condition. They performed the test with the 2FB condition. The participant was asked to wear headphones with white noise and to close the eyes (avoiding the sight of the prosthesis and the grasped object). The subject was not required to reach out to the object. Instead, the experimenter proceeded to insert it directly into the prosthesis, asking the subject to perform a full closure, and then to identify the stiffness of the squeezed object. The answer was provided by the subject's left hand pressing the keyboard arrows, left for rigid objects and right for soft objects. No button needed to be pressed when the prosthesis performed a void closure. Finally, the subject could reopen the eyes to check if the answer was correct.
In the second phase, a comparison between the four different feedback conditions, discussed in the “Feedback conditions” section, was carried out by five transradial amputees. The order of these four sessions was randomly presented to the amputees. Each condition had the same test protocol already described in the first phase with able-bodied subjects, in which the experimenter places the object inside the prosthetic hand and the amputee performs a grasp with closed eyes and gives the answer using the keyboard. At the end of each session, the proprioceptive drift was detected with respect to the initial arm position (refer to the “Amputees” section) and an ad-hoc questionnaire was administered (refer to Supplementary material).
Bruni G., Marinelli A., Bucchieri A., Boccardo N., Caserta G., Di Domenico D., Barresi G., Florio A., Canepa M., Tessari F., Laffranchi M, & De Michieli L. (2023). Object stiffness recognition and vibratory feedback without ad-hoc sensing on the Hannes prosthesis: A machine learning approach. Frontiers in Neuroscience, 17, 1078846.
Full text: Click here
Publication 2023
Amputation Stumps Amputees Arecaceae Eye Forearm Grasp Muscle Rigidity Muscle Tissue Pisiform Bones Primed In Situ Labeling Proprioception Prosthesis Upper Extremity Urination Vibration Vision Wrist
3
Auditory Localization and Bisection in Blind and Sighted Individuals
For the auditory localization task, localization error was calculated for each
individual as their mean absolute error, a common descriptor of error in
pointing tasks (Biguer et
al., 1984; de
Rugy et al., 2000; Schoemaker et al., 2001 (link)). In our case,
the mean absolute error corresponds to the average of the absolute difference
(in centimeters) between the correct position and the position the participant
indicated. We considered the correct position as the midpoint of each
loudspeaker. The minimum error was 5 cm, which is the distance between the
midpoints of two adjacent loudspeakers. The mean absolute error was then
converted from centimeters to degrees for each group of individuals. The
analyses were then conducted on the mean absolute error in degrees.
Regarding the bisection task, the proportion of trials where the second sound was
perceived as closer to the third sound was calculated; then, psychometric
curves, in the shape of cumulative Gaussian functions, were fitted on those
proportions following a standard psychophysical procedure (Kingdom & Prins, 2010 ), which
consists of fitting the psychometric function to each individual's responses
set, extracting individual PSEs and threshold estimates (Figure 2). PSE and threshold estimates
were obtained from the mean and SD of the fitted psychometric
function. Standard errors for the bisection PSE and threshold estimates were
calculated by bootstrapping, a technique that takes into account the error
associated with each individual threshold as well as the between-subject
variance (Efron &
Tibshirani, 1994). The obtained PSE and threshold samples were then
compared at the group level.
All values are presented as a mean and standard error of the mean (SEM). The
Kolmogorov–Smirnoff (KS) test was used to evaluate the normality of the data.
Data from each task were then analyzed using a mixed ANOVA between factor
group (blind, sighted) and within factor
hearing (mono, binaural). Student t-test
with Bonferroni corrections were used for post hoc comparisons. The alpha level
for effect significance was set to .05.
Finocchietti S., Esposito D, & Gori M. (2023). Monaural auditory spatial abilities in early blind individuals. i-Perception, 14(1), 20416695221149638.
Full text: Click here
Publication 2023
neuro-oncological ventral antigen 2, human Primed In Situ Labeling Psychometrics Sound Sound Localization Student Visually Impaired Persons
4
Adaptive Psychometric Procedure for Perceptual Judgments
Each participant’s probability of responding that the test foot was more forward at each stimulus position (s) was represented as a normal cumulative distribution function (cdf) with two parameters:
ψ(s)=normcdf⁡(s;α,β)
The α parameter, the mean or inflection point of the cdf, represents the PSE, corresponding to the position that the participant perceives the feet were in the same location along the laboratory’s y -axis (i.e., where the probability of judging “left” is exactly 0.5 ). The β parameter, the standard deviation of the cdf, represents the uncertainty, which reflects the noise within the sensory system itself. Both are measured in terms of foot position difference. The α and β parameters were estimated adaptively on each trial using the Psi algorithm. Of note, in our pilot testing the probability of responding left at −100 and +100 was consistently 0 or 1, respectively. Thus, we did not include the lapse and guess rate parameters that are sometimes estimated in other adaptive algorithms (Prins, 2013 (link)).
Wood J.M., Morton S.M, & Kim H.E. (2023). A reliable and efficient adaptive Bayesian method to assess static lower limb position sense. bioRxiv.
Full text: Click here
Publication Preprint 2023
Acclimatization Epistropheus Foot Primed In Situ Labeling Sensory System
5
PC-PTSD-5: Assessing Post-Traumatic Stress
The PC‐PTSD‐5 (Prins et al., 2015 , 2016 (link)) was used to determine the presence of posttraumatic stress symptoms over the last month. Each of five items were rated on a binary scale (0 = No, 1 = Yes). Higher scores indicate increased posttraumatic stress symptoms. Internal consistency of PC-PTSD-5 items was high in this study (α = 0.80).
Lathan E.C., Petri J.M., Haynes T., Sonu S.C., Mekawi Y., Michopoulos V, & Powers A. (2023). Evaluating the Performance of the Primary Care Posttraumatic Stress Disorder Screen for DSM-5 (PC-PTSD-5) in a Trauma-Exposed, Socioeconomically Vulnerable Patient Population. Journal of Clinical Psychology in Medical Settings.
Publication 2023
Post-Traumatic Stress Disorder Primed In Situ Labeling

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More about "Primed In Situ Labeling"

Primed In Situ Labeling (PRISL) is a powerful technique that enables the sensitive and specific detection of target molecules within their native cellular context.
This approach involves the use of specially designed probe molecules that bind to and label the molecules of interest, allowing for visualization and analysis.
The PubCompare.ai platform provides an innovative AI-driven solution to streamline the process of identifying the optimal research protocols for PRISL, enhancing reproducibility and accuracy.
By searching the literature, pre-prints, and patents, the PubCompare.ai platform helps researchers find the best protocols and products to meet their specific research needs.
This includes identifying the most appropriate techniques and tools, such as MATLAB for data analysis, Stat Profile Prime for sample preparation, Stellaris RNA FISH System for RNA detection, BHB Stat Site BHB test strips and meter for metabolite measurement, TaqMan Gene Expression Assays for gene expression analysis, Colorless GoTaq Reaction Buffer for PCR, CBA/CaJ mice for model systems, and the Rotor-Gene Q real-time PCR detection system with Rotor-Disc 100 for high-throughput qPCR.
The streamlined workflow and AI-powered comparisons offered by PubCompare.ai can help improve scientific outcomes and advance the field of in situ labeling.
By utilizing this innovative platform, researchers can enhance the reproducibility and accuracy of their PRISL experiments, leading to more reliable and impactful findings.
The High-Capacity cDNA Reverse Transcription Kit can also be used in conjunction with PRISL to enable comprehensive gene expression analysis.