Science topics: BiochemistryLabeling
Science topic
Labeling - Science topic
Explore the latest questions and answers in Labeling, and find Labeling experts.
Questions related to Labeling
We are trying to pick up an effect on lysozyme by measuring the absorbance of florescent labeled M. luteus cells at OD600. We are using this as a substrate because we are comparing the results we observed using this substrate in an enz chek kit. We are getting very wavy lines(see attached) in the reading. Anyone have any suggestions as to why?
I would like to run the FAM labelled oligo DNA on a agarose gel and detect it with Biorad Chemidoc MP, it has "Nucleic acid gels" option, "Protein Gels" and "Blots" Fluorescein channel. Which should I choose as my gel is not stained with anything but only the DNA is labelled with FAM, I wonder if I should still choose nucleic acid gels option.
Hi all!!!
I have been trying to quantify the DOTA on my labelled protein but did not get any success. What method is best to quantify the DOTA labelling? If anyone has prior experience with similar research, please reply so I can discuss and understand where I am making a mistake.
I`ve read the your article Comprehensive microRNA-sequencing of exosomes derived from head and neck carcinoma cells in vitro reveals common secretion profiles and potential utility as salivary biomarkers. Oncotarget 2017.I found it interesting and I’m now curious and willing to explore your GEO data (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84306), because I’m developing a study in the same area.However I can’t understand the labeling in the chart attached down bellow. In the GEO display, I can see the individual samples as follows:
GSM2231252H413_1
GSM2231253H413_2
GSM2231254H413_3
GSM2231255...
But I can’t relate them to the labels presented in the chart attached. For example, what does SL1.counts mean? Does it stand for H413_1_ GSM2231252? Are there replicates? Can you help me understand why the crude data values and adjusted values are the same?
Could someone helpe me with that? Athours did not have answer me...
I need to permanently label 38 metal cryo racks, and I'm interested in the solutions that you may have already arrived at.
Marker pen fades after about a year, stickers crack and fall off. The most durable thing I have found so far is metal cable and metal tag, but I'm concerned about these betting jammed in the carousel that holds the racks.
Any suggestions?
My extracted RNAs are biotin labelled. And I have used Biotin-Aniline to label RNAs. I want to store these RNAs at -80 degree Celsius for next day processing with streptavidin conjugation.
I'm working with Weka using KDD Cup 1999 dataset. So I've got a few questions I couldn't figure out via manuals:
- How do we know what parameters for Ranker to set? I mean, threshold and numToSelect. Is there any explaination to this?
- When I select attributes via explorer and save the modified dataset, it's always N+1 attribute (N selected attrbutes + class/label). Why? Isn't a label/class also an attribute?
- Why when I use PCA+Ranker with default settings for attribute selection I get more attributes than I had?
How we Detect it after labeling indirectly?
After being modified with DBCO-PEG4-NHS and subsequently labeled with a secondary antibody (targeting the Fc region), the antibody was found to be unable to bind to antigen-expressing cells. What could be the possible reasons for this
Hi everyone,
I’m currently working on flagella assembly and want to localize the FliN protein in my bacteria. We’ve already attempted to label the protein with eGFP at both the N-terminus and C-terminus, but the fluorescence appears to be cytoplasmic. We observed similar results when using NeonGreen at the N-terminus.
Do you have any recommendations?
Thank you very much!
Francois
I am intrested how to prepare 5' labeled primers (6-FAM, NED and HEX)? Specifically, do this primers that come in powder form need to activate for some time after I disolved them before I prepare working solutions out of them?
Thank you.
Q 1. Why does deuterium labeling experiment during CH activation?
Dear All,
Please let me know, that can be we use the dietary supplement ingredients for manufacturing and labeling of drug products.?
there is an uploaded image of correlated matrix. please help what types of this dataset will be treaded labeled or unlabeled.
What does ‘preventing carryover contamination’ mean?
If they are used, is pre-treatment with UDG necessary?
Thanks :)
We have mice brains that were over-fixed due to old PFA used during perfusion. Thus, the synapses are no longer being labeled by the Synaptophysin (SY38) mAB. which works perfectly every other time.
I have already tried antigen retrieval, but that has not been helpful either.
It is really important for us to label the synapses and we have no option but to use the over-fixed mice brains we have right now.
I am planning to try other synaptic markers like PSD95 and Synapsin next.
But I am open to more suggestions or troubleshooting ideas.
Would love to hear if someone has faced similar issues.
Thanks a lot.
The above are manually labeled extrinsic matrices based on the first image
It can be seen that the projection error at the edge is large, while the error at the center is small.
What could be the reason? How can I solve it
Thanks.
I have a Polyjet that has passed its labeled expiration date for 1 year and I'm going to re-start transfection experiments. It is really needed to change it? Transfection efficiency may be lower?
Hello everyone!
I'm working on some problems in Natural Language Processing. Now I've been working on Stance Detection. I have an idea but I'm not sure either it's useful or not.
I want to use RTE data (labels: "entailment", "contradiction", "neutral") for training Stance model. I think "entailment" and "contradiction" labels in RTE and "support" and "deny" labels in Stance are equivalent respectively.
I wonder if you think so. if not please give me some reasons for it.
Thanks alot in advance.
While preparing fluorophore labeled probe via nick translation, would we obtain smear or should there be a single band of the same size as the template?
I am doing research on the effects of labeling and stigmatization of teen mothers as deviant and if it has negative or positive impact on their sense of self. Also, what variables contribute to the labeling of teenage pregnancy deviant? All input is appreciated and welcomed.
My goal is to see two kinds of particles mixed well in an aggregated form.
My experiment was as follows:
1. Prepared Microparticles 1 + EDC/NHS + RhoB, and Microparticles 2 + EDC/NHS + FITC.
2. Mixed them, centrifuged them, placed them on a glass slide, and then checked them with a fluorescence microscope using different filter sets.
3. Merged the image channels (green and red).
The outcome was not satisfying. There seems to be crosstalk between the particles. When the images were merged, the green and red colors overlapped, making it difficult to distinguish the particles. I troubleshooted by checking each type separately, and they both showed successful labeling (Particle 1 showed red with no green, and Particle 2 showed green with no red).
ChatGPT-4 recommended the following steps:
1. Wash each particle after labeling.
2. Use blocking agents (BSA, FBS, and Tween-20) to prevent non-specific binding.
3. Check the filter set range when measuring.
I did all these steps (including overnight blocking), but the crosstalk between particles 1 and 2 still occurs.
I would be appreciated if someone can recommend me the solution to solve this problem.
Thank you.
What are the conditions for labeling an Anthozoan species as an Invasive species?
Condition: "particular mode of being of a person or thing" / "a requisite or prerequisite, a stipulation," / "state; behavior; social status"
Symptom: "a departure from normal function or form as an expression or evidence of a disease," / "a happening, accident, disease," / "to befall, happen; coincide, fall together,"
It's becoming very apparent that mental health labels and loose terms of diagnosis are starting to cost countries a fortune.
I wanted to ask about depression because in the UK, some people get told they have depression as a condition. That diagnosis on its own can gain extra financial benefits and medical support.
When it is labelled alongside other things, it seems to convert into a symptom. Which I would imagine meant it is WORSE that depression. It's depression, plus some.
However, if it is "just" a symptom, it doesn't have any financial weight, or it is extremely hard to get the right support, because other symptoms start leading professionals into focusing on groups of symptoms which are faster than ever turning into conditions/ing.
Depression used to be called meloncholia. After a guy won a nobel prize in conditioning, the world had two massive wars within years. Then it was labelled "the Great Depression"
Depression is a transitional position. It feels like it is actually impossible to be depressed as a condition. If you are long term depressed, you must surely have other symptoms and conditions causing the depression to last? Or you must have not acknowledged something about yourself that needs processing properly?
I can think of no person who is just "depressed" without a story of why they feel that way, or where its cause is from." It feels like a bad therapist to just leave people with the label "depression". Is it not medically a term for "unfinished business"?
And strange that it can provide extra financial benefits, especially when people with more serious diagnosis struggle to get that same help and support.
What is so special about depression that it can be used as condition and symptom?
It feels like a loop hole created on purpose to trap poor people and or to make a bad therapist look good.
I am running a smart farm project, need to plant 20 sensors for 10 days and must bring them back for data labeling before inputting to the supervised ML model. Data will be collected every second so I am concerned about the amount of data which will affect the time for labeling.
We spent months doing data labeling from 9 sensors, 7 days each. We desperately need a better solution to deal with this problem.
Does any one has the experience using DiD, Dil to label cells for imaging? Do they work well? Is there any other choices? I will use them to label tumor cell line and T cells, and I would like to observe the cells for 2 days.
Thanks!
I am expressing a membrane protein (about 15 kDa) in BL21(DE3) cells. The expression is good, and the yield is decent, but each time I checked the mass with a TOF mass spec, the mass I get is nothing close to the expected value for an isotopically labeled protein, especially with 15N. When I introduced 13C glucose, I saw an increase in mass, which shows the incorporation of 13C. This is in contrast with the 15N labeling. I've tried increasing the concentration of 15NH4Cl and eliminating rich broth, but nothing has changed thus far. Does anyone have an idea how to go around this problem? Thank you
I treid to find the eigenvalues for a matrix with quaternion entires of oreder 4 or greater while using Matlab. I perforemd the following steps:
1. First I created quaternion arrays in the follwing way:
O=quaternion(0,0,0,0) % for 0
L=quaternion(1,0,0,0) % for 1
i = quaternion(0,1,0,0)
j = quaternion(0,0,1,0)
k = quaternion(0,0,0,1)
2. Next I defined a 4 by 4 matrix, corresponding to C_4 labelled by quaternion units.
A=[O i O L; -i O j O; O -j O -k; L O k O]
It gives me the following A matrix in Matlab.
A=
0 + 0i + 0j + 0k 0 + 1i + 0j + 0k 0 + 0i + 0j + 0k 1 + 0i + 0j + 0k
0 - 1i + 0j + 0k 0 + 0i + 0j + 0k 0 + 0i + 1j + 0k 0 + 0i + 0j + 0k
0 + 0i + 0j + 0k 0 + 0i - 1j + 0k 0 + 0i + 0j + 0k 0 + 0i + 0j - 1k
1 + 0i + 0j + 0k 0 + 0i + 0j + 0k 0 + 0i + 0j + 1k 0 + 0i + 0j + 0k
Now I am facing problems to find eigenvalues of A.
Can someone help me to find the eigenvalues of the matrix A while using Matlab?
Thanks
I'm having great success using Cell Tracker red with Lactobacillus. Cell Tracker Blue CMHC and Green CM-H2DCFDA aren't working. I'm doing some trouble-shooting but I'd appreciate any insights from people who have tried these dyes on bacteria.
I am working on Exosomes that is derived from cells that are engineered to express scFv of Anti-HER2 antibody. I want to see its expression in TEM. Can I directly label the exosomes with the Protein L-GNP or do I need to use Anti-Anti HER2 antibody and secondary antibody then stain with Protein L GNP?
Can anyone suggest literature on Protein L-GNP immuno gold staining in TEM?
I am looking at CD4 T cell populations in B6 mice at 42dpi with influenza B virus. I do perform CD45 IV labeling just before tissue harvest. Now I am running my samples on the 5L Cytek Aurora and I see this weird distribution of CD4 staining where it looks like there are two distinct populations of CD4 (see attached image). The CD4hi population (on the far right) is primarily IV protected and the CD4lo population is primarily IV labeled.
I also stain mLN, cLN, pLN and Spleen and they all look normal. This issue appears to be exclusive to the lung
Has anyone else seen this? I have been searching in the literature but haven't found anything helpful.
Thanks!
I used NHS-PEG4-Azide to label protein and temporarily store the labelled protein at 4 degrees. Is it suitable for long-term storage at this temperature?
Example: Africa is a label for a continent. It has no overall leader or rulership, it is devided into countries. But now we are being told Africa is trying to sue Israel. But who is Africa? If "they" win, who gets the reward and how will it be fairly distributed around the continent of Africa? Or will only some people claim to have been successful in taking a country to court, and use it to show off against other African nations? I thought in order for a continent to take a country to courts, it would have to gather the signatures of every leader of each African country? If not, how does it work?
On the other side, there's Israel, the whole country's label. But within Israel are some people doing some things whilst others are not. Why should some people of Isreal get a reputation for genocide when it was just some other people using the Isreal label? How would others do trade and judge them in the future? It's not precise enough.
I don't think it is a legal move for a continent to sue a country and I'm struggling to see how this process is allowed, who personally will gain a reward from this, who will lose what etc?
It seems like an unfair trial with unfair uses of public legal systems both locally and globally. All because of labeling again. Like "them/they" issues.
Can anyone explain this process or direct me to further information I could read?
When a model is trained using a specific dataset with limited diversity in labels, it may accurately predict labels for objects within that dataset. However, when applied to real-time recognition tasks using a webcam, the model might incorrectly predict labels for objects not present in the training data. This poses a challenge as the model's predictions may not align with the variety of objects encountered in real-world scenarios.
- Example: I trained a real-time recognition model for a webcam, where I have classes lc = {a, b, c, ..., m}. The model consistently predicts class lc perfectly. However, when I input a class that doesn't belong to lc, it still predicts something from class lc.
Are there any solutions or opinions that experts can share to guide me further in improving the model?
Thank you for considering your opinion on my problems.
Cancer as of now is not an infectious disease. The Papillomavirus, virtually, causes all cervical cancers and yet cervical cancer is "not considered" as an infectious disease? Some lung cancers of the smokers could, justifiably, be caused by papilloma virus and or other microorganismes, then why at least these cancers are not labeled as infectious diseases?
I’m currently using a protein (36 kDa) which needs to be unfolded during a labelling reaction. unfortunately the protein precipitates completely upon denaturation with EDTA which chelates the zinc ions holding its structure together. I’ve tried the reaction at 37, 40, and 55 degrees Celsius all with the same issue.
The exact same protocol (37 degrees, same edta:zinc ratio, time course) works for smaller constructs of the protein. I typically unfold, reduce, and then add the labelling reagent sequentially for 50 minutes each (total 2.5 hours shaking at 37). My protein concentrations have been between 20 and 200 micromolar, and the pH is maintained at 7.8 in 100 mM ammonium bicarbonate buffer (no salt) for optimal labelling.
I need the protein to remain in solution for downstream experiments after the labelling reaction. How can I denature the protein while keeping it soluble?
The protein pI is 7.06, which may be too close to the reaction buffer, especially considering that the other constructs had pi’s at 5.3 and 6.6. I’m considering testing a higher pH, unfolding with EDTA and a detergent, and increasing the salt concentration. Ideally I’d have as low a salt concentration as possible for downstream mass spec, and maintain the pH between 7.5 and 8.5 for optimal labelling with the different reagents. I’d appreciate any feedback or advice!
Hello,
I am a grad student working on a project on the photisomerization of 2'-hydroxychalcone. I was instructed to create a PES surface for the triplet state. My first attempt did not produce accurate results by using the method of:
%chk=r66a20.chk
# opt=modredundant ub3lyp/6-311g(d,p) nosymm empiricaldispersion=gd3
H atom moved by 0.66 ratio and 200 degrees torsional rotation
0 3
C 4.40955200 -1.07991300 -0.54555900
C 3.26596800 -1.74755000 -0.09909700
C 2.01417800 -1.42748400 -0.63366800
C 1.89642800 -0.41766900 -1.60620700
C 3.05378000 0.22560800 -2.07096300
C 4.30412000 -0.09762500 -1.53408500
C 0.59255400 -0.09649200 -2.22324900
C -0.55116400 0.12512000 -1.55522300
C -0.64735300 0.50053500 -0.12258300
O 0.34423300 1.01373800 0.46366800
C -1.90915400 0.31643500 0.63358200
C -3.15247100 0.58942200 0.03132200
C -4.33985300 0.42672200 0.74976200
C -4.30311100 -0.00451700 2.07603100
C -3.07829900 -0.27235000 2.68958800
C -1.87966600 -0.11514800 1.97776200
O -0.66382100 -0.40167900 2.59940300
H 5.37814800 -1.33016300 -0.13247600
H 3.35032800 -2.51880500 0.65556100
H 1.14048600 -1.97116500 -0.29583500
H 2.98682100 0.98376600 -2.84181500
H 5.19191700 0.41070500 -1.88749300
H 0.55957000 -0.05444000 -3.30552000
H -1.46703200 0.04969000 -2.12553300
H -3.21091500 0.95579300 -0.98478200
H -5.29020100 0.64320200 0.27899600
H -5.22451200 -0.12796000 2.63040400
H -3.06071800 -0.60621700 3.71928400
H -0.26302800 0.16107800 1.75025600
B 10 29 F
B 17 29 F
D 9 8 7 4 F
and then I used TD-DFT:
%chk=TD_r66a20.chk
#p td=50-50 b3lyp/6-311g(d,p) guess=read geom=modredundant
empiricaldispersion=gd3
0 1
C 4.57698700 -1.53187000 -1.36424900
C 3.75481000 -1.51008200 -0.23758000
C 2.55798100 -0.80468800 -0.24377800
C 2.14632500 -0.10708600 -1.39547000
C 2.99699900 -0.13134300 -2.51984500
C 4.19414400 -0.83516100 -2.50858000
C 0.89159700 0.62999000 -1.55114300
C -0.27435800 0.70469200 -0.86532400
C -0.59792900 0.35067600 0.52831800
O 0.30513800 0.24919700 1.38241800
C -2.01433100 0.18454400 0.90698200
C -3.03855200 0.09651400 -0.06205900
C -4.36552400 -0.05278100 0.28825300
C -4.71245400 -0.11193000 1.64622500
C -3.74051600 -0.04526600 2.62493200
C -2.38264300 0.08394500 2.28222800
O -1.50585900 0.10857200 3.28772500
H 5.51156300 -2.08122700 -1.34739000
H 4.05390600 -2.04016600 0.65965800
H 1.94681000 -0.76569400 0.64361800
H 2.70339300 0.40370600 -3.41709000
H 4.82662300 -0.83984000 -3.38890700
H 0.83873200 1.11664200 -2.52366400
H -1.06583700 1.23983900 -1.37662000
H -2.77550200 0.12198400 -1.11161000
H -5.12838300 -0.12504600 -0.47694700
H -5.75246200 -0.22022600 1.93411400
H -3.98663500 -0.10382500 3.67800000
H -0.51723700 0.14856600 2.81931600
B 10 29 F
B 17 29 F
D 4 7 8 9 F
Using TD-DFT I got results that made chemical sense for a T1 state. Any help would be much appreciated
The image labeled T1 is from TD-DFT
I have several cell in one picture, all of them contains vesicles. The cells labelled with red marker. the vesicles labelled with green marker. I would like to know each cell how many vesicles located inside. I would like to count all cells which are located in my image at once. How it is possible to do it?
I am using a fluorescence microscope with DAPI filter, here are the specifications:
Excitation wavelength: 360/40 nm
Emission wavelength: 460/50 nm
Dichroic mirror wavelength: 400 nm
I want to label my cells with cyan fluorescent protein. I just want to know if our DAPI filter can detect the CFP. Thanks.
Which fluorescence markers are best to use for staining macrophages. I want to prepare sample to get training with the microscope for my research.
I would like to know if you have any guide or research work to configure the parametric label. I have searched for information but I have not found almost nothing about it except the technical notes of the program.
Greetings
Is it possible to label plant probes with biotin for Oligo-FISH in the lab, or is it effective to use such labeled probes commercially?
While making forest plot Revman I label the plot as Left control and right experiment. I see that the data supports the control as the diamond is on the left. But when I change labels the diamond stays in the left and is now in favor of the experiment. How to fix that? The data should be in favor of control regardless of what side of the plot the labelling is right?
This is a first run in our lab and there are several variables that each add several days to the protocol. I will be using the DeepLabel Antibody Staining Kit from LogosBio to label c-Fos. Questions are:
Which primary antibody do you use? At what concentration? How long do you incubate?
What concentration of secondary antibody do you use? How long is this incubation?
If anyone would share experience/protocol that would be great! We have been clearing and imaging brain and other peripheral tissues as well so if we can be of any assistance, please feel free to contact me.
Hello all,
I have a question. I am trying to test my DNA probes (that are biotin labelled) that we have in our lab to perform FISH. Probes are around 80 to 200 bp. I am doing a dot blot, to test our probes. However, I can not see anything when I develop the blot with ECL.
Does anyone have a good protocol that can help me? I feel like, I am missing a fundamental point. It doesn't make sense there is absolutely nothing on the membrane, complete white.
Looking forward to hear ideas,
Dilan
I seeded 5e6 and 3e6 SW756 cells in two 15cm dishes with equal amounts of media on Thursday, anticipating one to be confluent Monday/Tuesday, and the other to be confluent sometime later, maybe Thursday. This is my first time testing with these, so it was just a rough guess.
However, on Monday, both were equal confluency - I could not have told a difference in plates if they weren't labelled. Is this normal? Should I give less media to the 3e6 plate to get the anticipated effect, or just plate less cells next time?
Just overall curious what factors play a role in cell growth, as the 3e6 plate grew at a much faster rate with the same conditions - aside from having a higher proportion of fresh media.
Hello,
I am using Pophelper in R to run the algorithm implemented in CLUMPP for label switching and to create the barplots for the different K (instead of DISTRUCT).
I am getting a warning message when I merge all the runs from the same K using the function mergeQ() from the package which is slightly bothering me. Can anyone help me with this?
The warning message is as follows...
In xtfrm.data.frame(x) : cannot xtfrm data frames
Thanks,
Giulia
Hi there, I used thermo's TMT 10plex kit to label peptides and pool them together for LCMS/MS analysis. I am analyzing my data in Proteome Discoverer 2.3 and wondering how to quantify the number of peptides that were labeled vs unlabeled to make sure my labeling strategy worked.
When I run the processing and consensus workflows recommended by thermo for this data, I get protein IDs and quantitation for most of the proteins- I have the TMT label set as a static modification for N-terminus for the peptides and on lysine residues. So, all of my identified peptides and proteins have the TMT label identified as a modification. Surely there are some peptides that the program can identify that weren't labeled, so how do I find those peptides and determine the ratio of labeled:unlabeled peptides in my sample?
Also, even though all of the identified peptides in this workflow are marked as having the TMT label, not all of them are quantified. Does anyone know why this happens?
Thank you!
Talia
I kindly notify that ResearchGate must consider the difference among the author's first names written only with one capital letter. It is obvious that published articles labeled only with surnames, are very confusing about differentiating their authors. Because of that the SCI is inevitable for scientific platform, a new approach is needed to label the articles also with the first names.
Technical scientist: SELÇUK SOYUPAK, Department of Civil Engineering, Faculty of Engineering, KTO Karatay University, Konya,Türkiye
Medical scientist: SÜREYYA SOYUPAK, Çukurova University, Medical School, Department of Pediatric Hematology-Oncology, Adana, Türkiye
Let S_2(n,k) denote the 2-associated Stirling number of the second kind for n objects and k blocks, with n being at least two. That is, we partition n labeled objects into k unlabeled blocks such that each block has at least two objects in it, and S_2(n,k) is the number of those partitions. I’d like to ask if the following is known: q(n,k) is strictly decreasing in k, where q(n,k):=S_2(n,k)/S(n,k), and S is the Stirling number of the second kind. Many thanks for the help!
Janos
Supervised Learning
In supervised learning, the dataset is labeled, meaning each input has an associated output or target variable. For instance, if you're working on a classification problem to predict whether an email is spam or not, each email in the dataset would be labeled as either spam or not spam. Algorithms in supervised learning are trained using this labeled data. They learn the relationship between the input variables and the output by being guided or supervised by this known information. The ultimate goal is to develop a model that can accurately map inputs to outputs by learning from the labeled dataset. Common tasks include classification, regression, and ranking.
Unsupervised Learning
Unsupervised learning deals with unlabeled data, where the information does not have corresponding output labels. There's no specific target variable for the algorithm to predict. Algorithms in unsupervised learning aim to find patterns, structures, or relationships within the data without explicit guidance. For instance, clustering algorithms group similar data points together based on some similarity or distance measure. The primary goal is to explore and extract insights from the data, uncover hidden structures, detect anomalies, or reduce the dimensionality of the dataset without any predefined outcomes. Supervised learning uses labeled data with known outcomes to train models for prediction or classification tasks, while unsupervised learning works with unlabeled data to explore and discover inherent patterns or structures within the dataset without explicit guidance on the expected output. Both have distinct applications and are used in different scenarios based on the nature of the dataset and the desired outcomes.
Can I use flow to compare flourescently labelled intracellular structures between different cells? Can I use it to compare the same cells before and after treatment? Is the mean intensity of a fluorescent signal a reasonable measure for relative quantification?
Can i cluster documents to label them as a first step. Then in the second step, can I use the labelled documents to apply a classification method such as svm, knn, etc.?
I want to digest sumo/His label when the protein in still hang on the Ni column. I wash the undesired proteins as usual, then balance the column with 3ml enzyme digestion buffer, then add sumo enzyme for digesting the fusion protein at 4℃ for 12h in 4ml sumo digesting buffer. Then catch the flow through liquid, take some sample from flow through liquid and beads after elution for SDS-PAGE, the brand explains the label did not have been cut, it is still on the beads entirely.
We have to add specific molar concentration to the media (10^-6M). it is labelled as 1000X how can we convert it.
Im looking into brand marketing for underground record labels and also marketing for releases such as singles and EPs. I would like to find studies on the most effective methods of marketing within the music industry.
Might be a stupid question but I can’t find papers about it: can fluorophores (rdTomato, EGFP etc) be taken up by EVs and transported, or do they only get attached to the surface? All I could find was when researchers are attaching it on purpose to the surface to label EVs. However, I want to know whether a fluorescent cell would produce EVs with that fluorophore inside?
I am planning to perform C13 MFA, and I was wondering how I can weigh the labeled glucose and add it to the media while maintaining sterility. I didn't find any protocol specifically explain this part.
How do I get a superscript in my axis labelling in Minitab? I need my axis to read mg g-1 but not mg/g. Any suggestions?
Dear all,
I'm trying to perform expansion microscopy, which work quite nicely, but we have this recurring problem of cells cracking.
Here is the protocol I'm using:
After labelling, incubation in acryloyl-x SE 0.1mg/mL O/N at 4°C
Polymerization in a monomeric solution containing 0.4% TEMED and 0.2% APS for 1h at 37°C
Denaturation in a buffer of 50mM Tris, 200mM NaCl and 200mM SDS for 1h30 at 95°C
Gels back in PBS for 30min then labelling with DAPI for 15min.
Finally expansion in water (changed twice) O/N.
We have an expansion factor of ~3-4, which is fine for us, but most of the cells are fragmented/torn in their cytosol (the cell itself, not the labelling which is very nice)- never the nucleus.
My hypotheses are either the denaturation is not good enough or the expansion is too quick.
Does anyone had the same problem and could give me a lead?
Thank you very much in advance!
Good evening,
Can you please advice on a protocol for labeling of OMVs for cellular uptake assay. OMVs are derived from gram-negative strain. I was thinking of applying R-18 but other dyes are also possible. The readout is spectrophotometer. Do I need to wash and/or lysed cells before measuring fluorescence? Thank you for you help.
After adding the tree block to my NEXUS file, I get the "Error parsing sequence data; Tree labels do not match alignment labels" error message. I've checked the labels multiple times, they're all correct, no additional tabs or spaces. The tree itself also looks correct. Could there be something else leading to this error? The NEXUS file wihtout the tree block works well.
Hello everyone! I am studying Graph Neural Networks to apply to my field.
My problem: I have a dataset with multiple graphs. Each node in a graph have Y label. I want to predict Y label of nodes in new graph.
I want to ask: I can make predictions by Graph Neural Network? If can, Could you give me some hints?
Below is a illustration about my question.
Thank you!
Dear colleagues:
I have used the Vybrant™ Alexa Fluor™ 555 Lipid Raft Labeling Kit on the HT22 cell line. I followed the indicated protocol, followed by 4% PFA fixation (20 min), phalloidine staining and mounting with Vectashield. Then, I acquired some pictures by using confocal microscopy (40X oil objective, 2X digital zoom) and found that not every cell got the stain. I have seen some publications that used this kit in other cells, and they show that every cell get the stainning (at least they show that). Does anibody experienced something similar using this kit??? what could be the pissible reasons to explain this results????
Best,
Felipe
Computer vision tasks, such as object detection, have traditionally relied on labeled image datasets for training. However, this approach is limited to detecting only the set of classes present in the training data. Zero-shot object detection (ZSD) is a breakthrough in computer vision that allows models to detect objects in images based on free-text queries, without the need for fine-tuning on labeled datasets
This capability has significant implications for businesses, as it enables more flexible and adaptable computer vision systems. In this blog post, we will explore how zero-shot object detection is changing computer vision tasks in business and discuss some of the key benefits and challenges associated with this technology.
Hellow Everyone .
I have a query that i have build a monomer of both phospholipids and glycolipids for Md Simulation but the problem which i face is that once i go to tool/software and put the molecules click on label atom than their numbering come on randomly can't come on proper manner than how to solve this issue thanks in advance
For the English version of the Pure Procrastination Scale (Steel, 2010) the scale is listed as having a 5 point scale ranging from 1 very seldom or not true of me to 5 very true of me. However, what are the middle anchor point labels for the scale? Thanks
I and a second coder coded data coming from open-ended questions from a survey, and now I want to calculate the intercoder reliability.
I want to use the KALPHA MACRO to calculate Krippendorff’s α, but I am not sure how to do it with data like mine, where each data unit could be coded for more than one categorical/nominal code.
All the examples I find work with binary nominal coding.
Does anyone can help me with this?
Thank you in advance
Hello, I'm trying to find pre labelled 90mm petri dishes to be included in an automation workflow for a new biotech lab. Does anyone know a brand? I can't find one! THX
Nidia
I extracted the genomic DNA from Salmonella Typhi culture for its molecular identification. Then designed the primers for the 16S rRNA gene, perfomred the PCR and then run the amplified product on GE along with DNA ladder. After the run, I got this picture from GEL Doc system.
But unfortunatetly I lost the DNA ladder specifications, and now unable to label the amplified gene bp size as well as the DNA ladder size and labelling.
You are professionally request to sort this out?
Thanks in advance.
Hi,
I am trying to stain different cellular compartments in bone marrow sections from adult mice. When I use direct labelled antibodies, for example CD3-FITC, CD9-PE etc, the staining result is always very bad. I can not see any specific signal. But when I try with primary and secondary antibody, I usually get good result. Curretly there is an experiment that requires to use direct label antibodies. Therefore, I am wondering if there is any good way for me to stain bone marrow sections using direct labelled abtibodies. Thanks.
I'm trying to predict a disease based on both facial features and questionnaires.But I have two different datasets such that one is on the question and answers with labelling and the other is with images and labels as well. I mean both the datasets are different but they predict the same thing. How can I merge and use these datasets together to predict using deep learning?