Science method

Neoplasms - Science method

New abnormal growth of tissue. Malignant neoplasms show a greater degree of anaplasia and have the properties of invasion and metastasis, compared to benign neoplasms.
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Are you aware of any publication on mucinous cystic neoplasm of pancreas where the serum estrogen levels where measured? I am aware that many express ovarian tissue (struma ovarii). I keep getting hits on estrogen and progesterone receptor expression but I want to know the estrogen levels. Thanks in advance
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I didn't ask this question, that's why I like RG, so for new ideas!
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I'd like to determine microvessel dimensions in various tumor groups and am looking for an online database to draw pathology slides from.
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نعم ولكن تحتاج الى عملية بحث واسعة وكبيرة للحصول عليه
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I am trying to establish an ovarian cancer preclinical model through peritoneal injection into C57BL/6 mice.
The parental ID8 p53-/- cell line was modified through lentiviral infection in order to express OVA peptide and GFP-luciferase. We injected 5·10e^6 cells per mice.
In day 40 after injection we did not get any tumor in any of the mice.
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Couple things.... the ID8 cells you generated are expressing 3+ new proteins, each on their own can potentially slow tumor growth by increasing the immunogenicity of the tumor (especially for OVA). Knowing this, you should have included a set of mice with the parental ID8 p53 -/- along side as a positive control.
If you failed to see tumors in your positive control group, you either didn't inject as many cells as you thought (i.e. counting errors, substantial cell death) or you were working with a different cell line.
The original parental ID8 cell line grows very slowly (8-10 weeks), and the ID8-OVA cells are sooooo much slower (12-15).
Check these papers out.
The original ID8 p53-/- paper
Walton, J. et al. CRISPR/Cas9-Mediated Trp53 and Brca2 Knockout to Generate Improved Murine Models of Ovarian High-Grade Serous Carcinoma. Cancer Res 76, 6118–6129 (2016).
ID8-Luc2
Baert, T. et al. The dark side of ID8-Luc2: pitfalls for luciferase tagged murine models for ovarian cancer. J Immunother Cancer 3, 57 (2015).
ID8-GFP
Lee, W. et al. Neutrophils facilitate ovarian cancer premetastatic niche formation in the omentum. J Exp Med 216, 176–194 (2018).
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Hi, I need to have a dataset including the expression level of a particular miRNA and a particular mRNA in tumor (digestive cancer :Colorectal+gastric)+ its matched normal tissu across samples provided by TCGA database .What exactly should I do? thanks
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Ganesan Jothimani sure, you are welcome, this is my email "fatma.1990@hotmail.fr''.
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Hi. I am struggling with the mouse animal model. I found that the subcutaneous tumors are extremely uneven in my mode. I injected the same volume of tumor cells (human cell line) suspension s.c. in balb/c null mouse and the size of the tumor show uneven after 1-2weeks. This has a great impact on the following treatment. So, I wonder what is the best practice for subcutaneous tumor inoculation? Or, are there any ways to prevent uneven tumor growth?
Thanks a lot!
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1) I hope that by "the same volume" you also understand the same number of tumor cells.
2) Try to prepare suspension of cells just for a few mice (depending on your expertise) to minimize the time of cells waiting on the bench in PBS before being injected. Then prepare a second vial of cells for another couple of mice and so on.
3) Be careful not to go too deep with a needle- in case like this tumor may infiltrate the muscle and from the outside, by eye, it may look like the tumor is smaller than it actually is.
4) If for some reason the size of the tumor is essential for your therapy then don't focus on starting the treatment on the same day- just set a volume of the tumor on day 1 of the treatment and start the therapy when each of the tumors will reach a given volume.
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Hi has anyone had experiance of GL-261 not growing subcutaneously? I have inoculated 10e6 cells in C57BL/6J female mice and the tumors became palpable after a week cca but have subsequently disappeared except in few mice. The cell line is routinly used in the literature s.c in imunocompetent strains so I don't know what's the problem.
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Hi, no my research went in another direction and I used other cell lines such as E.G7-Ova and B16-Ova which worked perfectly.
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Hi, everyone, i am a fresher of tumor immunology.
Recently, i am preparing to study how pdl1 regulation in tumor cells will affect the function of t cells. and i have read a paper " miR-424(322) reverses chemoresistance via T-cell immune response activation by blocking the PD-L1 immune checkpoint. Nat Commun" . In this paper, author applied PBMC from healthy human with the anti-CD3, anti-CD28 and incubation of skov3 tumor lysates. Then, isolated CD8 T cells to co-culture with skov3 cells. i would like to apply this model, but i have a question, anti-CD3 and anti-CD28 has made CD8+ T cells activated, why do they need to add tumor lysates?
And, right now, i don't make sure whether i should apply antigen-specific CD8+T cells to coculture with tumor cells? other papers indicated that firstly isolated monocyte-derived DC and then make them matured with some cytokine stimulation and tumor lysates incubation. Then matured DC cocultured with CD8+ T cells to get the tumor-antigen specific T cells. These obtained CD8 T cells then cocultured with tumor cell lines. could you kindly give me some advice based on my research purpose?
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why do they need to add tumor lysates?
We need to add tumor lysates to optimize the ability of the cells to generate tumor-specific T-cell responses. Thus, cells can be loaded either with whole tumor cells or tumor cell lysate, or tumor antigen-enriched fractions to achieve the desired anti-tumor T-cell response. Tumor cell lysate represents the whole protein content of lysed tumor cells. So, the advantage of using tumor lysate is that the multiple antigens heterogeneously expressed on growing tumors can sensitize
T-cells.
DCs are the most effective type of antigen-presenting cells and can stimulate naive T lymphocytes to initiate an immune response. DCs represent the interface between the universe of foreign and tissue-specific antigens and T lymphocytes. They also play a role in all aspects of T-cell responses. I would suggest you use monocyte-derived DCs in your study as it will help in a better response.
Best Wishes.
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Hello, i am searching for breast cancer elastography datasets, so that by using machine learning technique, sort out whether the given elastography of breast is benign or malignant.
However i cannot find the place to get enough number of elastography datas...
Would you let me know any?
I sincerely appreiciate it in advances!
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Hi! I'm looking for breast cancer strain elastography image dataset for research. If you find any source, please let me know as well.
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There are rat strains that are more likely than others to spontanuously develop tumors. Are there litteratures covering this questions?
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The Sprague-Dawley strain of laboratory rat has shown to develop tumors at greater rates regardless of diet or living conditions.
Suzuki H, Mohr U, Kimmerle G. Spontaneous endocrine tumors in Sprague-Dawley rats. J Cancer Res Clin Oncol. 1979 Oct;95(2):187-96. doi: 10.1007/BF00401012. PMID: 521452.
(CANCER RESEARCH 33, 2768-2773, November 1973] Spontaneous Tumors in Sprague-Dawley Rats and Swiss Mice1 J. D. Prejean, J. C. P
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EBV-B cells have been using our lab to investigate the role of B cells in tumor micro environment. Recently, I have realized that EBV-B cells start to turn into black cluster in 2nd passage after culturing from stock. You can see the pictures of healthy EBV-B cells and black cluster.
Thank you in advance,
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Flocculation effects
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I'm observing a small tumor with confocal. I imaged the expression of a fluorescent protein, which is supposed to express everywhere. However, I can see some vague DAPI signals, where I can't observe the fluorescent protein. Is this normal? If so, wouldn't the images that I obtained for a single layer be always interfered with vicinity layers?
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Hi Huijing, the goal of confocal is to reduce the intensity from out-of-focus planes, but the cutoff is never a sharp one, so strong signals from planes not too far from the focus can be observed in the image. Make sure that your pinhole is not too large. If larger than 1AU, you will have increased contribution from out of focus. Other factor to consider is that DAPI signals are often very strong, compared to your FP, so you may see some faint out-of-focus signal from DAPI but not from the FP.
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I want to know about the general mechanism of radiosensitizers.
how they locate tumor cells in the body?
how they differentiate between normal cells and tumor cells?
what basically happened when we take a radiosensitizer before the radiotherapy?
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in children, is liver transplantation for large HCC confined to the liver allowed or contraindicated?
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The transplantation team must select these patients very cautiously because the risk of neoplastic relapse into the new liver, is very high
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SLURP1 protein is known to be an anti-cancer protein. It can inhibit certain cancer cell lines at very low concentrations as observed in in vitro experiments. However, gene expression data on NCBI GEO database reveals SLURP1 expression is relatively high in tumors than normal tissues. Can anybody give an explanation for this phenomenon?
Thank You,
Amal.
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Dea Alexander,
I did some analysis using GEO data sets. If found an interesting feature, I will share it with you. I have one more question regarding SLURP1 protein. It's being a human protein, what sort of autoimmune conditions could be provoked if it used as an anti-cancer protein? Can it be a problem? and how to tackle?
Thank you,
Amal.
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If I report a breast imaging exam (MRI, US or Mx) which not shows any malignant findings in a biopsy-proven breast cancer, which BIRADS score do you use?
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BIRADS 3 ( Suspicious lesion)
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Can a 3D mammary epithelial cell culture model be established using Matrigel since it is a tumor matrix? Or should we use collagen matrix to create a true model of the epithelium?
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Thankyou
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I'm conducting a retrospective study on diagnostic accuracy in detecting thyroid malignancy for 2 different ultrasound scoring systems. The same cohort will be scored based on both scoring systems and their pathological report reviewed to determine the malignancy pick up rates. When do I do the calculation for power of study - Is it before or after? And what test should I be using?
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This seems like the comparative evaluation of two different ultrasound diagnostic methods against a gold standard of pathologic malignancy.. You should just compare the sensitivity, specificity, positive /negative predictive power of the two tests, bearing in mind that these are dependent on prevalence of the condition.
Power calculations are not necessary.
Alternatively,if you are interested in incidence of path malignancy in those scored positive by ultrasound 1 vs ultrasound 2. This is a comparison of two rates. For a given sample size you can calculate the power of detecting a given rate difference
or ratio at a given alpha significance level . Alternatively you can choose a sample size for required power. These calculations should be done before the study.
referenced stats program suite covers all of this.
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Hello,
I have developped 4 markers to detect microsatellite instability in a cancer type using digital PCR.
I would like to determine the discriminatory power of each marker, meaning the cut-off (mutant allelic frequency) to classify a tumor as microsatellite instable (MSI) or microsatellite stable (MSS). For each marker, I performed ROC analysis using 7 MSI tumors and 20 MSS tumors but I was wondering if ROC is the right analysis for this purpose. Could you help please ?
Best,
Khadidja
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Go and check the guidelines for interpretations of forensic samples typed by microsatellites. They have done huge anount og experimental work to be able to separate artifacts like stutter and pull up from true alleles in samples with more than one contributor and where the amount of DNA is different from the contributors. This is analog situation to your samples with normal tissue and cancer tissue.
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I have a question about T-cell recall assays. We vaccinated mice and wanted to see if there was a T-cell response against our tumor cells. There was no tumor challenge. We pulsed DCs from naive cells and then cocultured these DCs with the T-cells. But we also seeded the tumor cells and cocultured the T-cells with them. Could anyone shed light on why we would do both of these?
My guess is that the pulsed DCs activate naive T cells and can show that you have tumor specific T cells but they were not activated by the vaccination. But if you do it with the whole tumor cells and there is a response, it means the T cells were already activated by the vaccination. Is this correct?
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Malcolm Nobre Thank you very much for your insight Malcolm! If we culture the DCs like this, and we see a response only with those cultured with the pulsed DCs, and not with the whole tumor, could we say that the cells are naive and haven't been activated? So there is vaccination did not work?
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Hi,
I want to stain brain sections of mice which have been xenografts with tumor and treated with a new anti cancer agent. Can some please share the protocol with me including tips and does and dont's for the staining. I would also appreciate cat# for antibodies and any other critical reagent.
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Thank you Suckert.
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Hi everyone!
I analyzed 20 tissue samples of oral leukoplakia (OL - an oral potentially malignant disease) through untargeted metabolomics to compare the metabolic profile of those OL who had malignant transformation (5) and those who did not (15). I know that the small sample size is one important limitation of the study, but OL is a rare disease and I have to deal with it.
Well, when I use my complete dataset (around 4k compounds) to perform multivariate analysis such as PLS-DA, my model is overfitted, exhibiting a negative q2. However, when I use the 72 compounds considered statistically significant by the univariate methods (hypothesis tests) as the input data, my q2 rises to 0.6. The improvement also occurs when I use this small dataset to build the heatmap that clearly distinguishes the malignant transformed from the non-transformed OL. Interestingly most of the compounds classified on the PLS-DA VIP list are the same, both using my whole data and using the 72 discriminant features as the input.
I recently presented my thesis to a metabolomics specialist and she told me that my analysis is curious and that she cannot tell me whether it is right or wrong.
Would anyone here help me with this question?
Thanks!
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HI, you are actually asking two different questions here, as PCA is only a data reduction method while PLS and clusterization aim to interpret the data.
You have 2 groups and only 20 samples all in all, so of course way too many compounds and potential confusions. And I would not rely exclusively on "significantly different" between the 2 groups to select data as, with 4k variables, it is more likely than not that you may have false positive (depending on how stringent you ran the statistical test).
My approach would be to do the PCA and look, is there some spontaneous separation of the 2 groups on one of the early principal compoments? Do your data "cluster" i.e. do you have groups of very correlated data? In which case you can probably simplify these groups to a single variable.
You have only 20 samples so when there are significant differences (72 variables) it might be worthwhile to actually plot and look, is the difference pulled by a few samples or is nicely repeatable in one group.
Anyway you look at it, you are in trouble... too many variables for few samples, this is going to require a lot of brain exercise. This is where statistical tools, however good they are, must leave way to knowledge and human intelligence. Do you have hypotheses as to the related biological mechanisms to help you sift through the data , and the predictive value, as said by Guillermo Quintas, will stay poor. Tentative I'd say, it might be a tool to help the practician but not totally relaible as a diagnostic.
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Magnetic nanoparticles are present in the center of the tumor and are the source of heat. Which is heated using an external magnetic field. Assuming that the tumor is spherical in shape.
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Dear Prof. Khan,
Thank you very much for your interest.
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Recently, I am exploring the potential function of one gene in cancer. Since the TCGA datasets as well as some other clinical data show that this gene is up-regulated in cancer and especially in basal-like subtype. I tried to knockdown it by shRNA and the result show the depletion of this gene accelerate the proliferation, migration and invasion rate of cancer cells. I also tested the over-expression in cancer cells and the result show the over-expression impaired the proliferation rate. This observations is also consistent with some previous report which reported it as tumor suppressor. Although I found that expression of this gene maintain the basal-like feature of breast cancer. The results is still confused me.
My question is whether you know some similar works or papers.
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not unfortunately
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  1. We are working on a tumor microenvironment project in a mouse model of a cancer. We have generated tumors that develop at multiple anatomic sites and we want to identify the differences in tumor stromal cell changes at scRNA depth. We are obviously running scRNA seq on tumors, but would you recommend using databased control tissue (there is databased scRNA seq for each of the anatomic sites), or would you independently do your own control tissue and eliminate all batch effects?
  2. Also, would you do an admixture of cells from multiple mice (as a way to even out individual difference in cell composition) or just use a single mouse (we want to be somewhat cost effective, while still doing good science, especially when we are talking about scRNA seq)?
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  1. In general, it's always better to include controls from your own animals to eliminate any changes that might arise from differences in genetic background. Plus you'll be able to ensure that the controls are collected from the same area as the tumors. You can always add the published scRNAseq data later too, but I would not be surprised if the databased scRNAseq cells segregated themselves away from your tumors and normals after cell-type clustering.
  2. Combining cells from multiple mice before capturing is not advisable since you will not be able to identify differences between animals. It's also not ideal to use only a single animal as you won't be able to distinguish between consistent and idiosyncratic gene expression changes (this is essentially a n=1 study despite the fact you are looking at thousands of individual cells).
I think this is quite an ambitious study, but it is going to be quite expensive no matter how you go about it.
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We have been orthotopic study to analyze the in vivo anti-cancer efficacy (brain, liver).
As you know, its study should do H&E staining to distinguish tumor from sectioned sample.
although we manually annotate the area and extract its intensity, I think, there seems like a automatic program to calculate a ratio of area (tumor / entire section).
Or Do you know some efficient and rapid way to calculate a ratio.
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Hi there,
If you share an image maybe we can help. Even if there is not a specific software, this kind of calculations, I think this could be easily performed in ImageJ.
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Hepatocellular carcinoma is one of the deadly malignancies. It usually occurs in cirrhotic patients.
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With pleasure.
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 TCIA - REMBRANDT consist of 130 cases with 3 categories of tumor such as glioblastoma, astrocytomas, and oligodendrogliomas. How to identify the images are belong to the 3 different categories?? how can I keep a separate folder to have these 3 tumor classes to use it on CNN.
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Estou com a mesma dúvida amigo! O dataset não informa quais imagens possuem ou não tumor.
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I work on gastric cancer. I want to separate the top layer of tumor cells from the lower layers.
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Although much research into the molecular basis of cancer utilizes cells growing in culture, we need first to consider tumors as they occur in experimental animals and humans. In this way, we can see the disease's gross properties — the properties that ultimately must be explained by analysis of genes and cells.
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Hello everyone,
I am interested in expression of miRNA in different AML cell lines (such as HL-60, OCI-AML2, ... and also the myeloproliferative neoplasm cell line SET-2) which I will investigate with RT-qPCR. It is highly recommended to use endogenous controls for the experiments but I could not find literature for all of the cell lines. I thought about using Broad Institute Cancer Cell Line Encyclopedia (CCLE) to look for stably expressed miRNA.
Do you have any suggestions how I should proceed? Investigating endogenous controls can take a lot of effort like shown for T-Cell ALL (10.3390/ijms19102858) but I am looking for controls to use in just a few cell lines (less than 10).
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Small nucleolar RNA, C/D box 43 gene (RNU43) gave a good normalisation for miR-181b in our experiment in CLL.
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I did Immunofluorescence staining of DAPI using the lung tumor tissue frozen section which contains part of the normal site, but I find it hard to figure out why the DAPI staining (or other antibodies) intensity was weaker compared to the normal sites under the same condition. I repeated it more than once, I don't know what's wrong with it.
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I am a little bit confused that after the sectioning, the antigens are all exposed on the surface, is there still a problem of antibody penetration? Oscar L. Sierra Philip Patrick Yost
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We are in concern of CSF flowcytometry to detect lymphoid malignancies, Please could you give some of experience toward standardization
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Dear Fatma,
Please find attached link for CSF flowcytometry.
Feel free to contact for further help.
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We injected different densities of GL 261 cells (1, 2, 5 or 10x106 cells) in 100 µL PBS or 100 µl 50%PBS/50%matrigel in the flank of 8-week female C57BL/6J. A few days after the injections we observed, on some mice, non measurable tumors. But in the end, we did not manage to obtain any tumor. Do you have some advice to obtain subcutaneous GL261 tumors.
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I have the same problem, injected 1x105 and 1x106 cells in 100 ul PBS in the flank of 8 wks old female c57bl/6J. After injection of 1x106 I observed tumor in just one mouse (out of 35), that after some days disappeared.
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I am interested in cancer treatment. Especially in Boron-neutron capture therapy(BNCT).
And my questions are as follow:
1) When the boron-10 compound will reach the malignant cell? Does it depend on the carrier?
2) How much time should be left from the injection of the boron-10 compound until the irradiation?
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Dear Vahagn Ivanyan
Thanks for such a nice question. Currently we are also working on the same ideas as discussed in you question. During our research, we have come across a very informative and knowledgable review article with the title “Boron delivery agents for neutron capture therapy of cancer”. In This article and its cited literature you can find all the necessary information ....
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Out of T98G, U87MG, U118MG, A172, U251MG cell lines, which line is more preferred or considerable in GBM tumors? Can anyone provide subcultured cells with an excellent passage number?
Thank you
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The answers you seek can be obtained by careful experimentation. Laboratory conditions as well as funding problems are a major encumbrance to research reproducibility. At least, perform the experiments under the condition that prevail in your area, with the amount of funds available to you. Let research guide the selection and not some conjecture. The world awaits a report from you soon.
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We used WB to analysis tumor sample from Hepa1-6 transplanted to C57BL6J mouse flank. In drug treatment group, we observed reduced p62 level and accumulation of LC3B-I.
We assumed that reduced p62 level indicates that autophagy is stimulated. However, accumulation of LC3B-I is the marker of autophagy inhibition. We feel confused to draw a conclusion.
How to explain these results? Can we do some more experiments to analyze autophagic flux?
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the reduced level of P62 triggered the expression of LC3B1. have you analyzed the mRNA level of LC3B1?
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Recently, we have injected s.c. B16F10 tumor cells in BL/6 mice. At around 12-15th day some animals showed ulcerations in tumors , with a big hole in the middle (it looks like a volcano). We have also observed this problem in MC38 and EG7 tumors. This did not happen to us so often until now. Any suggestion or personal experience that helps us to resolve this issue will be really appreciated. Thanks in advance.
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Try decreasing the number injected vital cells
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I am looking for tools/methods for somatic variant calling for unpaired samples. The somatic variant calling through GATK best practices is specifically for tumor/normal paired samples. My study entails somatic variant analysis studying complex disorders, thus I have unpaired samples. I found following options:
Samtools, ISOWN, Mutect (only tumor mode) and SomVarIUS .
I would like to compile as many options as i could and choose the best suitable for my study.
Kindly suggest further options and any opinions and suggestions are welcome.
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The pipeline explianed in gdc portal also deals with tumor only mode variant calling
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There are various points of view some of them reported the ratio of early/late apoptosis as killed tumor cells by CTLs. Others reported the sum of early and late. However, we know CTLs kill tumor cells through lysing so it seems PI positive should be considered as the killed cells. What is your idea?
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Dear Lora, thanks for precise answer I have co-cultured colon cancer cell line with splenocytes of mice for 24h. So the rate of death cells were considerable relative to the control. I've read your answer in some articles. Ok I will evaluate the %Anx and %double positive. So what should I do. I mean next I should report the ratio of %Anx/%death cells? This is an article which is associated in this case but at the end I got confused how the results were reported I attached it for you@ Lora Benoit
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Greetings, everyone! I am a student and have question about radiotherapy planning. Where can I find recommendations and/or instructions for beam arrangements of different tumor localisations? For example "box" for rectum and prostate, and tangencial fields for mammal.
Thank you so much and have a good day!
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I think there in no such recommendation in documents. But you have to take care about beam entry in OAR region.
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I want to make single cell suspension from mice ovarian tumor for FACS sorting. For that I will be using 10x triple enzyme stock solution (collagenase 10mg/ml, hyaluronidase 1mg/ml, DNase 200mg/ml or 20U/ml) prepared in DPBS . I am little confused regarding the concentration of DNase? Can anyone suggest if I am using the right conc. of DNase ? Should I use calcium free DPBS or HBSS-Ca2+ solution for incubating tumor pieces?
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Please see the link to a very comprehensive protocol in this field of study. I hope you find answers to your questions.
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I tried to do a study about calculate the sensitivity and specificity of fine needle aspiration cytology (FNAC) in a type of cancer.
After I have collected all the data, I noticed that some results are indefinite (means the results are there but from the results, we couldn't identify whether it's malignant or benign tumor. )
I'm thinking whether should I exclude the inconclusive results from all the calculations (means consider the inconclusive result as false positive for sensitivity and false negative for specificity).
This is my first study so I am kinda' lost. Anyway, thank you in advance for your help.
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Hello Qi Xuang Ang,
If the sensitivity is with respect to correctly identifying instances of malignant tumors, then any indeterminate outcome would be classed as a negative (e.g., not a malignant tumor) case. If you discard those cases, you'll overestimate sensitivity.
If your research protocol had explicitly incorporated the option for FNAC with follow-up (as suggested by Aedrian Abrilla ), then you would use the final (follow-up) result instead for cases that were initially indeterminate.
Good luck with your work.
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I am looking for some pointers on what medical imaging techniques that are capable of estimating total cell number in a tumor. Being able to estimate the difference between a tumor of a defined size presuming tumor 1. has half the mount of cells and tumor 2. of the same size with double the amount of cells would be a great start.
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Do you have the data? Why not train a model like Mask R-CNN on it and deploy in the wild.
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I don't understand it. Sellar tumors in the 2016 version of the WHO-classification of primary brain tumors contain craniopharyngeoma and several tumors originating from the posterior pituitary (pituicytoma, granular cell tumor...) but the pituitary adenoma is nowhere to be found. How come? What's the reason?
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I'm fairly new to cancer research and there's a host of articles on Sunitinib being administered via oral gavage in mice models but I'm unable to find any information on studies that have explored directly injecting tumors with Sunitinib. Just curious.
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Hi Paul
The name of the article is as follows:
Injecting activator of a powerful tumor suppressor directly into the cancer increases tumor destruction, decreases toxicity. Science Daily May 23, 2017.
Regards.
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Chemotherapy for breast cancer costs the UK economy more than £248 million annually, including ‘out-of-pocket’ personal costs of more than £1,000 per patient – according to new research from the University of East Anglia.
Key findings: - The total cost of breast cancer chemotherapy in the UK economy is over £248 million.
- Societal productivity losses of £141.4 million - including £3.2 million lost to premature mortality, and £133.7 million lost to short-term (£28.7 m) and long-term (105m) work absence. Further costs include £3.4m associated with mortality losses from secondary malignancies due to adjuvant chemotherapy and £1.1m in lost productivity arises from informal care provision.
- £1.1 million in lost productivity arises from informal care provision.
- Out-of-pocket patient costs for chemotherapy total £4.2million, or an annual average of £1,100 per patient. In addition, costs for the emotional wellbeing of carers could be as much as £82 million. Emotional wellbeing reflects how much additional income would be required to offset a wellbeing loss.
‘Societal costs of chemotherapy in the UK: an incidence-based cost-of-illness model for early breast cancer’ is published in the journal BMJ Open on January 5, 2021.
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Yes, we added as many cost as we could given the data available.
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Which any type of tumors most commonly found in broiler chickens carcasses in processing plant ?
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I following the best answer.
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The tumor cells are from a variety of cell lines from ATCC .
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I agree with Adhiraj
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I stored tumors in RNAlater. However, I want to use these tumors for making protein lysates for cytokine expression analysis.
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Hello dear, Tanvi Visal. First thing If u stored your sample in proper way i.e sample stored in deep freeze or using liquid nitrogen and second thing if u use proper protocol for extraction of protein I think your protein quality and quantity will be good ......good luck
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Hello,
I am curious as to if anyone has any expertise or information about setting up a subcutaneous human xenograft model for a CD19 bearing tumor and human CAR experimental system. I looked up many different references using either the NALM6 or Raji cell lines at varying log differences in cells injected with and without matrigel. We piloted a tumor growth study using the range of cells published (10^4-10^6) without Matrigel and did not get any tumor growth in the time frame (21 days) of the published reports. Any tricks or hints on sublcones for the NALM6 and/or Raji cells would be helpful. The pilot was performed with the NALM6 CRL-3273 from ATCC. Thanks.
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I would prefer to develop a xenograft with 10^6 cells with an equal amount of PBS and matrigel (100:100 ul).
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Dear all,
I'd like to introduce a tumor in such geometry, how I can do that?
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Dear Yjjou
You must define a material and after that use it?
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Dear colleagues,
I would appreciate your advice on the following issue.
Let's say, first I had investigated expression of Prot1 and Prot2 in tumor tissue, it's association with relevant clinical data (stage, histotype, prognosis, outcome, etc).
Then, I studied expression of Prot3 and Prot4 again in tumor tissue.
However the patients are not the same, although the all have same cancer type, but overall study groups barely slightly overlap.
My question is what might be a good approach to summarise previous work and analyze those proteins altogether (I mean without performing additional experiments). I thought of using some ML classification/regression but haven't gone too far.
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You can find more information in the following paper. In summary, federated learning is an innovative mechanism to train a united model on data from multiple parties without compromising privacy and security of those data. There are different types of federated learning including horizontal, vertical and transfer learning that you can use based on your dataset. For example, if you have same features but different samples (different patients have same disease, symptoms ...) you can use horizontal federated learning.
"... Medical data such as disease symptoms, gene sequences, medical reports are very sensitive and private, yet medical data are difficult to collect and they exist in
isolated medical centers and hospitals. The insufficiency of data sources and the lack of labels have led to an unsatisfactory performance of machine learning models, which becomes the bottleneck of current smart healthcare. We envisage that if all medical institutions are united and share their data to form a large medical dataset, then the performance of machine learning models trained on
that large medical dataset would be significantly improved. Federated learning combining with transfer learning is the main way to achieve this vision. Transfer learning could be applied to fill the missing labels thereby expanding the scale of the available data and further improving the performance of a trained model. Therefore, federated transfer learning would play a pivotal role in the development of smart healthcare and it may be able to take human health care to a whole new
level."
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Hi all,
I used tumor dissociation kit(Miltenyi Biotec) to first isolate cells from tumors. Then I washed cells twice with PBS, and cultured the cells in complete RPMI (5%FBS, and pen strep). However, 2 days later, I found my cell culture is totally contaminated by bacteria. Frustrated.
How to make primary cell line from tumors without contamination? Thanks!!
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You used media with pen/strep and still there was a bacterial contamination - that's surprising and worrying. Hopefully, it's not a bacterial strain that is resistant to antibiotics.
What concentration did you use - like this?
100 U/ml penicillin + 100 µg/ml streptomycin
or
50 µg/ml gentamicin + 50 ng/ml amphotericin B
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Our lab is trying to establish a BT-474 xenograft model. We have not been able to get the tumors to grow past 50-100mm3. We inject 1x107 cells in a 50:50 matrigel suspension. We used nude mice (5 weeks old) that have been implanted with estradiol tablets (90-day; 0.36mg). After 5 weeks the tumors have stopped growing and some are shrinking. Does anyone have experience with this model and can offer any advice? Should we go up on the estradiol dose? We used 0.36mg to avoid toxicity. Thank you!
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Thank you all for your suggestions! To answer some of the questions, we inject in the mammary fat pad with 50uL cells (1x107) and 50uL Corning Matrigel Matrix. We have been monitoring the mice for 6 weeks now, and will continue to monitor them - hopefully they are just slow growing as others have stated. However, some of the tumors have completely disappeared at this point. Thank you again for your suggestions and protocols!
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I am looking for CT images of different Cancer cell like ( Brain- Head&Neck - Liver- Lung and Prostate ) with contoured area that shows me where is the tumor exactly.
I need to Download Dicom files which I know Where to find them but the important thing to be with previously known and determined exact place of the Tumor which I could not find them so I could use it later in the simulation in the master thesis.
I use many websites but the problem that I could not find where is the tumor in the CT images
I use the following websites but they do not have contouring around the tumor:
The only website I have found with contoured area with CTV and PTV is:
3- https://econtour.org but the problem that I could not download them as a DICOM files.
Any help is appreciated and Thanks in Advance
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I have a protocol from Himes J Neuro-Onc 2020 using GBM EVs on peripheral blood monocytes. The endpoint is converting monocytes (CD14+ HDA-DR high) to MDSC (CD14+ HLA-DR low) with tumor derived EVs, and using these cells for functional studies. These cells are cultured w/o FBS, I am new in this field and wonder if not using FBS is routine in the field.
Thanks
Dominique
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It is common to decrease or null the FBS in culture leading to any differentiation experiment.
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Hi, is there any dataset about occupational skin diseases (especially skin cancers) that contains skin lesions images (simple or dermoscopic or histologic) ,integrated with clinical data and occupational history (e.g. to see if they have had occupations with carcinogenic exposures particularly UV)
I want to use it to make a research on the contributions of these exposures in the development of skin cancers and the possibility of early detection of the malignancy of these lesions by data mining and image processing considering occupational exposure as an important parameter
any suggestion is appreciated
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I actually found a few dataset samples on https://www.kaggle.com/search?q=skin+diseases.
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I am working on tumor induction in experimental rats and needed 1,2-Dimethylhydrazine to induced tumor in the lab. animals. Please I need help from anyone who can render help.
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Chen Jingwen ,Thank you so much
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I am interested in identifying all relevant case reports or case series related to a very rare complication of neoplasms. I am currently searching PubMed and CINAHL for this purpose, but I am interested in expanding my search to other databases which are either specific to or which have a large number of indexed case reports or case series. Do you have any suggestions? Many thanks in advance!
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BMJ case report but it a journal
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I'm looking at doing a transwell migration assay with tumor conditioned media for RAW264.7 cells, but the literature has a pretty wide variety of pore sizes used for this specific cell line. Does anyone have recommendations on what's worked for them? Thanks!
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Hi Hayden,
Did you find the answer? Recently I plan to do a transwell migration assay for RAW cell line too. I found some paper used 8um and some for 5um.
Bests
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I am trying to extract intact nuclei from OCT-frozen tumor tissue samples. Does anybody have a protocol for doing so? I need as many intact nuclei as possible for performing ATAC-seq on them.
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What is the best way to quantify tumor cell death (cell lines) after incubating with CAR-T cells?
Thanks.
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The Pierce LDH assay is pretty robust, and no hazardous chemicals. You need a plate reader. Beyond that, if you use MTT or Annexin-V, these need finer calibration of spontaneous death rates. You CAR-T cells will die, too.
Bruce
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Hyperspectral medical imaging, hyperspectral image for cancer/tumor detection
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Contact Prof. Ines Gockel at Leipzig University Department of Surgery
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with my matlab code as following
classNames = ["background","tumor"];
pixelLabelID = [0 1];
pxds = pixelLabelDatastore(im ,classNames,pixelLabelID, ...
'FileExtensions','.nii','ReadFcn',volReader);
Error using pixelLabelDatastore>parseInputs (line 202)
'FileExtensions' is not a recognized parameter. For a list of valid name-value pair arguments,
see the documentation for this function.
Error in pixelLabelDatastore (line 151)
[location, classes, values,params] = parseInputs(varargin{:});
Error in SEp1 (line 27)
pxds = pixelLabelDatastore(im,classNames,pixelLabelID, ...
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I'm trying to evaluate for mRNA expression level of ONE gene in hundreds of tumor samples. What is the method to do this?
Edit: Also, does the type of tissue I have affect which method to use? For example, frozen tissue vs FFPE tissue.
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Hi Lingjuan Wang-Li,
If you are able to obtain good yield of RNA after isolating from formalin-fixed, paraffin-embedded tissue sections OR cryo preserved tissues both in terms of quantity and quality, you may opt for RT-PCR based assay. Although it might be labor-intensive for performing this assay in hundreds of samples but this method is certainly more economic, reproducible, robust and free from inter-individual and intra-individual assay variations.
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Different types of neuronal tumors occur in children such as neurocytoma and neuroblastoma. I look for any evidence and details about the mechanism by which a neuron can develop a tumor.
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When it comes to neuroblastomas, they develop from neuroblasts, primitive nerve cells differentiated from radial glial cells. Under normal conditions, it is these cells that would, after their migration phase, develop into neurons. But, sometimes neuroblasts are unable to differentiate into mature nerve cells or adrenal medulla cells, due to certain gene changes which occur during child's development (potentially even before birth) or, in rare cases, inherited DNA changes. Instead of undergoing normal differentiation, neuroblasts then continue to grow and divide - causing the occurence of a tumor. In general, neurons do not develop tumors but rather neuronal precursor cells fail to undergo proper differentiation which leads to their abnormal division and growth.
Suggested readings:
1. Castleberry RP. Neuroblastoma. Eur J Cancer. 1997;33(9):1430-1438. doi:10.1016/s0959-8049(97)00308-0
2. Izbicki T, Mazur J, Izbicka E. Epidemiology and etiology of neuroblastoma: an overview. Anticancer Res. 2003;23(1B):755-760.
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Tumor mutational burden (TMB) is a measure of the number of gene mutations inside the cancer cells. TMB of a tumor sample is calculated by the number of non-synonymous somatic mutations per mega-base in coding regions. The value obtained for TMB always ranges from 0 to 1 which never reaches 1. What is the minimal cut-off that can be assigned to classify TMB as High, Medium and Low?
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Hi,
You will find in the links below a specified cut-off for stratifying the tumor mutation burden.
You can go through these papers:
Hope this may help you.
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Hello everyone,
I see a lot of papers with the spheroid generation topic. I know spheroids are used widely for simulation of tumor condition in body. Can someone say which abilities does the primary cells have which cell line do not have? like generation vascular endotheilal or producing extracellular matrix and which abilities cell line have which primary cells don not have?
Thanks in advance
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I‘m doing my dissertation and the results data are all positive in the reduction of tumor size with a drug I Would like to know what method should I use or any suggestion would be really appreciated
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Unless you have fewer than 3 well-designed RCTS, I suggest you include both RCTS+Cases in your qualitative analysis and only the RCTs in your quantitative analysis to conserve the quality of the evidence. Or you can include it if there is a methodological explanation, then you can perform sensitivity analyses and subgrouping. In that case, you will need to employ the random effect IVhet model and pool the continuous data (mean/SD) as a weighted mean difference, and the binary data (event/total) as a relative risk.
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Can you help with the referencing materials for the mathematical modelling of behavior of 'Tumor size','Toxicity', and 'Drug resistance' during the Chemotherapy cycles. ?
Thanks so much in advance.!!!
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Chamani Shiranthika , have a look at these articles related to drug resistance during chemotherapy.
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I have conducted a binary logistic regression.
There are 294 lesions and logistic regression can separate them as benign and malignant.
For this purpose three of the study parameters produced a formula. As you know it is something like:
Benign/Malign Score = 1/ 1+ exp[(Parameter1*Constant1)+(P2*C2)+(P3*C3)]
During cross validation, 80% of cases constitutes training set and %20 of them are test set.
Training and test set are formed randomly.
The constants in this formula change during each rebuild of the training and test groups as well as Sensitivity, Specificity and Accuracy.
I need help: 1- How would you suggest I manage the validation process so that I can give a single formula that everyone can use? Because the formula is changing in every single validation.
2- I want to study validation process 500 times. I am going to give arithmetic mean of Sensitivity, Specificity and Accuracy of 500 measurements. Do you offer another information to provide in the manuscript (for example min, max, 95CI of Accuracy etc.)?
Many thanks in advance to everyone who showed interest and kindness to respond.
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In my opinion your work is closely related to a simulation study. rather than a cross-validation. You may benefit from the excellent remarks of Mary Davidian attached.
I hope this may help.
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Dear Jose,
In this article the authors claim that alpha-fetoprotein can be absorbed from GI tract into the blood (up to 11%) after per oral administration in an undigested form and travel to tumor sites carrying the non-covalently binded toxin (drug Aimpila) to destroy the tumor:
Do you believe their results?
In the previous article of the same authors the absorbency was 0.1%:
file:///C:/Users/vpak/Downloads/otsenka-internalizatsii-afp-soderzhaschego-nekovalentnogo-kompleksa-aimpila-v-modeli-izolirovannogo-otrezka-tonkoy-kishki-krys.pdf
Thank you,
Vladimir N Pak, PhD
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We have conducted an investigation and found that AFP was not absorbed through GI tract into the mice BLOOD after peroral administration, neither in free form nor in a complex with the toxin.
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I have T1-pre contrast MR images for three patients with gliomas however the tumors in the first patient looks darker while the tumors in two other patients look brighter. I wonder why?
Can anyone help me about this?
I upload the images.
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The first pic. Shows encephalomalacia or a site of previous surgery, normally u see glioma hypointense in T1wi, but sometimes a hyper cellular thick capsule appears hyperintense
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I want to know how to look/analyze different parts in a tumor section like stroma, Ductal epithelial, epithelial lining, luminal epithelial etc etc in a breast cancer tissue slide.
Also is there any handbook/video tutorial for learning IHC slide analysis/ scoring ?
Thanks for your time!!
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To find the tumor stages or growth analysis from initial stage to glioma stage which dataset will helpful.In which dataset will be able to get tumour description.
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I am looking for pathological report data (text based) on histopathological analysis of cancerous tumor whole slide images. If there are any pubic (request based or otherwise) datasets available on this, then kindly inform me. It would be really helpful in my research on Computational Cancer Pathology. Thanks.
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v You can visit the following websie https://archive.ics.uci.edu/ml/datasets/breast+cancer this is one of three domains provided by the Oncology Institute that has repeatedly appeared in the machine learning literature. (See also lymphography and primary-tumor.) This data set includes 201 instances of one class and 85 instances of another class. The instances are described by 9 attributes, some of which are linear and some are nominal.
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I would like to ask if someone could kindly provide me a good protocol, or suggest me a good paper with a proper description of an in vitro INVASION ASSAY to use with a neoplastic cell line.
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Please see the link:
Hope, this helps.
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As N-methyl-N-nitrosourea is a carcinogen used to induced mammary tumor in rats for breast cancer model development and we ran out of carcinogen what could be the possible alternative or the promoters that could help us in tumor induction imparting no other side-effects?
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Many answered correctly ?
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Las células de Schwann normalmente no están presentes en el parénquima cerebelar y es difícil explicar el origen intracraneal de schwannomas intracraneales. Muchas hipótesis han sido planteadas para explicar los shwannomas no relacionados con nervios craneales como el posible origen de células de Schwann en los plexos perivasculares: conversión de las células piales en células de Schwann, origen desde fibras nerviosas ectópicas, células de la cresta neural que han migrado erróneamente durante el desarrollo del sistema nervioso, u origen en células mesenquimales multipotenciales. Redekop y Elisevich propusieron la teoría de la embriogénesis distorsionada. [4]....
...Los shwannomas intraparenquimatosos no asociados a nervios craneales son neoplasias raras, la revisión de la literatura reporta hasta 1998 solo 35 casos descritos en los últimos 30 años [3] y 44 casos hasta el año 2004 localizados en los hemisferios cerebrales, [9] en la medula y 14 en el cerebelo. Todos excepto uno, fueron reportados como benignos, de mayor prevalencia en pacientes jóvenes y de localización vermiana.[2]....
...70 casos de schwannomas intracerebrales reportados hasta el 2011 fueron de localización supratentorial tanto en los hemisferios como en los ventrículos. De los 26 casos reportados en localización infratentorial, 11 estaban en hemisferios cerebelares, 6 vermianos y 9 medulares. Todos los casos fueron benignos excepto dos. [4]...
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Intra- and extra-cranial schwannomas are very rare as you have mentioned in the demographics.
In 1996, Sharma and colleagues demonstrated that "the lesionis usually solitary and in only two cases, an associated neurofibromatosis (NF1 and NF2) was found."
This was a quite fascinating result, and there have been some imaging studies recently that explained the structural and functional deficits of this disease in details:
The following is also a goo case report study showing that the majority of subtentorial schwannomas are located in the brainstem. But even clear conclusions cannot be achieved in each case before operations because of the rareness of the disease.
"Therefore, subtentorial schwannoma is typically diagnosed on the basis of postoperative pathological analysis. If the tumor can be completely removed, the prognosis of the patient is good."
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I'm want to deplete cells only in the periphery but do not know if they will deplete T cells infiltrating tumors
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