Brain Tumors - Science topic

Self-answer

Retroviral proteins can be fusogenic and cause the entry of viral RNA when two cells, one permissive and the other non-permissive are in contact. This leads to integration, and, if the ASLV has an oncogene, to oncogenesis in the host cells but apparently not to viral replication (Despite the fact that most transcription factors are very conserved between mammals and avians, I still don't know the answer about why it happens).

Svoboda, J. (2015). Cell association in Rous Sarcoma Virus (RSV) rescue and cell infection. Folia Biologica (Czech Republic), 61(5), 161–167.

From https://portal.gdc.cancer.gov/ brain collection

you can find information for Diagnoses / Treatments, Family Histories, Exposures

https://radiopaedia.org/articles/mr-spectroscopy-1

This should help

Peritumoral edema -> FLAIR

Enhancing tumor -> T1 CE

Presumably non enhancing tumor core would also come from T1 Contrast enhanced.

I'd gently suggest you get the help of a radiologist.

Aqeel Kadhim Al Hamaidah

سلام عقیل عزیز

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آرزوی موفقیت

If you use the absorbance differences (the absorbance of the sample minus the absorbance of the control) at each wavelength, you would require a different equation to calculate the % reduced. The equation you showed earlier includes the control absorbances, so you should enter them into the equation.

As for the protocol used by your supervisor, I don't think any calculation of % reduced is involved. It simply uses the change in the absorbance measurement at 570 nm (minus the background from the culture medium, measured at 600 nm) to represent the degree of reduction. The extinction coefficient at 570 nm of reduced Alamar Blue is higher than that of oxidized Alamar Blue by almost 2-fold, so the more reduction occurs, the more the absorbance at 570 nm increases. To be honest, I don't understand why the background from the culture medium measured at 570 nm instead of 600 nm isn't subtracted in this method.

If you want to, it would actually be pretty easy to derive equations for the concentrations of oxidized and reduced Alamar Blue from absorbance measurements at 570 and 600 nm and the provided extinction coefficients if you first subtract the background from the culture medium at each wavelength (in other words the ∆absorbances.) It just involves a pair of equations and high school algebra for dealing with simultaneous equations.

∆A570 = (E_570,ox)C_ox + (E_570,red)C_red

∆A600 = (E_600,ox)C_ox + (E_600,red)C_red

where C stands for concentration and E stands for extinction coefficient.

To solve for C_red, for example_:

C_ox = [∆A570 - (E_570,red)C_red]/(E_570,ox)

C_ox = [∆A600 - (E_600,red)C_red]/(E_600,ox)

[∆A570 - (E_570,red)C_red]/(E_570,ox) = [∆A600 - (E_600,red)C_red]/(E_600,ox)

C_red = [∆A570(E_600,ox) - ∆A600(E_570,ox)]/[(E_570,red)(E_600,ox) - (E_570,ox)(E_600,red)]

The denominator is a constant, with the value 1.706 x 10¹⁰ in whatever units the given extinction coefficients are in, presumably M^-1cm^-1. Putting in all the constants gives:

C_red = (6.896 x 10^-6)∆A570 - (4.739 x 10^-6)∆A600

Convert from molar to micromolar to get rid of the 10^-6s, and

C_red = (6.896)∆A570 - (4.739)∆A600.

Thank you A.B Bayazid for your recommendation! However, I am looking for microglia of adult origin, and HMC3 is fetal. Do you know any lines derived from adult brain?

In current technology era, to sustain and provide healthy life to humans it is necessary to detect the diseases in early stages. We are focused on Brain tumour detection process, it is very challenging task in medical image processing. Through early diagnosis of brain, we can improve treatment possibilities and increase the survival rate of the patients. Recently, deep learning plays a major role in computer vision, using deep learning techniques to reduction of human judgements in the process of diagnosis. Proposed model is efficient than traditional model and provides best accuracy values. The experimental results are clearly showing that, the proposed model outperforms in the detection of brain tumour images.

PFA should be able to fix the tissue. you could also fix before you cryosection that way you could do both cryosectioning and IHC. It is also possible that you may be try dropping the cry tissue block in PFA so that as it melts, it is already coming into contact with the PFA. Ia m not sure if things like OTC will dissolve in PFA like it does in water. I would then transfer the tissue to fresh fixative once it has thawed and then proceed with the IHC.

This question is very wide, hence, in the following, it gets narrowed into two specific areas: biosignal prediction of ECG recordings, and the theory of robust massive parallel computations.

We arrived at the point when complex systems measure enables us to distill a very rich set of information from biosignals. As an example, in some cases the information provided by ECG recordings is so rich that we can predict arrhythmia up to one hour before their actual onset in a rabbit model, see the paper of Kroc & Bobir.

The second very deep area of my research deals with developing a better understanding of robust emergent computations that occur in massively parallel computational environments, including biology. In plain words, the main problem in all biology describing mathematical models is their lack of resilience to the faults occurring within the underlying, unreliable computing medium.

This topic get studied in the paper dealing with a cellular automaton called the 'Game of Life' and its robust generalization called r-GoL, see the relevant paper when interested and Python code available on the RG profile. Surprisingly, a cellular automaton that is highly resilient to the faults of underlying computing massively parallel information processing medium was found.

Hello

1. Change the image format.

2. Modify the modules.

3. If the image still encounters an error, you certainly did not observe a point in the defined code section, it will probably explain the reason for the error in the error section.

In the ([]) imshow field, set the resolution value range, put a number that may be so low that the image is completely dark, for example, write imshow (squeeze (V (:,:, round (end / 2))), [4000]).

Muhammad Javaid Iqbal

I suggest reading these articles first:

1. https://www.turcomat.org/index.php/turkbilmat/article/download/5447/4559

2. https://www.frontiersin.org/articles/10.3389/fncom.2020.00025/full

3. https://ieeexplore.ieee.org/document/9154030

4.

I recommend that you use another lysis buffer, in our Lab we use triton buffer plus phosphatase and protease inhibitors,

in WB it's important the size of the proteins and then make the accurate concentration of your gel.

By deep coverage NGS it is possible to find a primary mutations in the higer value, theorically, they must be more than the subsequently mutations, according to the time of occurence, comparison of the ct DNA vs cf DNA. is important too. The most newer mutations must not be detected, because of the cell degradation time and the number of the degraded new tumor cells, therefore, investigating on primary driver mutatons in serum is rational.

With time, tumor growth produces major tissue disruption that hematoxylin/eosin or trichrome staining will show clearly in comparison with controls and non-tumor implanted samples. 40 um sections may be a bit too thick for high mag, high resolution imaging, however. The attached paper reference shows examples of the disruption.

Yes I can

Many thanks for nice question. I think : there are no proved evidences that show any specific factors such as food or diet is associated with the development, management or treatment of brain tumours yet , but surely working with hazardous materials such as heavy metals and other toxins can do it !

Try American society of radiology website

You can find what you ask for in databases like https://portal.brain-map.org/explore/toolkit/neuroimaging OR you can use the healthy hemisphere for control

There is multiple attempt to do that, but few follow or ķnow about it

Thank you so much James O'Callaghan

I also encountered this problem.

I injected 10^5 GL261 cells 0.5mm anterior, 2mm lateral to the bregma, and at a depth of 3mm.

I only have 2/5 of the successful tumour model.

Did you find a way for quality GL261 glioma model in C57BL/6J?

Shweta Singh Fantastic. Thank you very much. We are asking (neuro)psychologists, neurosurgeons, speech-language therapists, occupational therapists, physiotherapists, and psychotherapists to participate. If you have a few contacts you would like to share, please message me privately. We will be happy to reach out to these people directly, if it helps save your time. I am also providing my email address: MPolczynska@mendet.ucla.edu just in case. Best wishes, Monika

Thanks Mr. Ali for your reply!

Hi Rodrigo.

I‘m having the same problem in my lab. Did you have some answer? I’m looking for someone in Brazil that is working with this model. Can I contact you?

Best regards,

Dear Celine!

BIT Admixture - 100 is a complete medium formulated for optimal growth of tumor stem cells, e.g. glioblastoma stem cells and in cases where defined medium compositions are required such as colony forming assays or growth of hematopoietic progenitors. It contains essential components that help to replace serum.

If you have a good serum, you can simply use a medium serum without BIT supplement

Dear Ashly Mathew

Have a look at these articles

If I understood well your question, you mean why there's no enhancement in edema itself. The enhancement around the lesion shows the disruption of BBB. That means in that area you have the maximum blood flow due to extravasation. But the oozed fluid is in perilesional interstitial space and won't enhance. You see it as hyperintense signal in T2 or FLAIR sequences.

Hi, I have the same question. Can anyone help me getting the genetic information from REMBRANDT dataset especially IDH mutation and 1p19q mutation.

Regards

Request the pertinent permission from its Author or Authors and then make it reliable, validate it, etc. Pisometrically in its new modification and with its own "ad hoc" Normative Groups.

Many head CT datasets contain brain and you can find several public head and neck CT datasets as follows:

https://www.cancerimagingarchive.net/

https://imaging.nci.nih.gov/nbia-search-cover/

Follow this link please:

thank you all for the response

Hi! From clinical experience I would think there is no tumor. in that image. If you radiologically slice the head for the MRI, so to speak, you start and end with a slice that may not yet or may not any more contain either tumor, brain, skull or skin -or even hair. so it can look black. Usually in clinical practice that slice is ignored -probably you can do the same.

Lescher et al. Quantitative T1 and T2 Mapping in Recurrent Glioblastomas Under Bevacizumab: Earlier Detection of Tumor Progression Compared to Conventional MRI Neuroradiology. 2015

Kjaer et al. Tissue Characterization of Intracranial Tumors by MR Imaging. In Vivo Evaluation of T1- And T2-relaxation Behavior at 1.5 T Acta Radiol. 1991

Just et al. Tissue Characterization With T1, T2, and Proton Density Values: Results in 160 Patients With Brain Tumors Radiology. 1988

You will need to find another software for image segmentation/contouring. Here is a previous question discussing this: https://www.researchgate.net/post/Can_anyone_suggest_free_software_for_medical_images_segmentation_and_volume

Here are a few choices (all are free):

Thank you @Arash Safari and @Michele Avanzo for the answers

Akshath M J You may follow these

http://cgm.cs.mcgill.ca/~godfried/teaching/cg-projects/98/normand/main.html

http://web.stanford.edu/class/cs273/scribing/2004/class8/scribe8.pdf

While I do not know if brain tumour segmentation programs will have a direct benefit to doctors, they would allow for a quick and reliable method of determining the volume of a tumour. The size of a tumour is an important predictor of survival. In assessing for a benefit of a certain treatment, it is good to account for certain variables that may also influence survival outcome.

YOU ARE WELCOME

Linear

I'm not aware if any person was formally diagnosed with PTSD after neurosurgery at our institution, but I believe that some people may manifest similar symptoms. From my experience with patients, I reckon that the first year after brain surgery is extremely difficult at cognitive, pychological and social levels, but I dont think that a thouroughfly planned surgery with well prepared medical team is traumatizing per se. Dear Roxana Badea, with regard to psychological well-being of patients after the intervention, I really like this paper by Campanella ( https://www.ncbi.nlm.nih.gov/pubmed/28411105 ). Dear Maria Pąchalska , I'm eager to read your case study and I'm looking forward to reading other professionals opinions in this sense.

Yes, miRNAs could be most promising and ideal biomarker for a range of disease conditions and developmental processes.

Today, most of available biomarker specially being used in clinical practice are either enzyme or radio-immuno based techniques. Few major limitations of these biomarkers are Non-disease condition fluctuation in their level, sensitivity issue, genetic level variation among population, non-availability of enzyme isoforms etc.

In this scenario, there is need of biomarkers which highly specific, sensitive, accurate and advance in nature.

So, for sure, miRNAs will be promsing biomarkers in near future

you will need libraries like nibabel, Simple ITK, nilearn for processing

but just for viewing and looking at 3D you can use ITK-SNAP and Slicer3D

Hi

any one help me to doxnload the dataset Isles 2015 or 2016 or 2017 or Atlas, for the segmentation of ischemia stroke brain?

Thanks dear Khurram ejaz ch it's best

The more the better

Dear Jovanka, in order to study spatial navigation in humans you can use virtual mazes.

Here you can find a virtual reality version of the Morris Water Maze, generally used for monkeys.

Several groups have utilized virtual Morris Water maze on humans. For example:

Here you can find a virtual Morris Water Maze for humans:

Another option is the virtual radial maze for humans, which you can find here:

Good luck!

1)Are they able to attach in the first place? If yes then is there any possibility of contamination or uncharacteristic cell growth you observed? Do DAPI staining for identifying cryptic contaminants like mycoplasma

2) Is there a chance by any means that you forgot to add serum to your incomplete media?

3) What is the passage number of cells that you are working with? Also u have not mentioned the cell (which glioblastoma cell line?). Maybe it has some extra requirement of a component that you failed to notice?

4) Was the cell number seeded when you last passaged the cells too low since cancer cells like to remain in close proximity with each other for proper growth

5) Lastly reensure that your culture dish/flask are 'treated' ones.

6) If you are experiencing lot of problem then you must thaw a new batch of the cells and possibly before that decontaminate your laminar hood,culture room and incubator as well

Are these cell the only one facing this problem or you have any other cells as well which are under such stress?

Hope it helps!!

Just plotted histogram of entire image for other image

Plz anyone help who are doing research in this domain

Hi,

You need to contact any Radiology department. They have patients who come for follow-up and evaluation.

Thank you

Good Luck

Sam

Salam

Here is some interesting links to see:

(PDF) Image Analysis for MRI Based Brain Tumor Detection and ...

https://www.researchgate.net/.../314257965_Image_Analysis_for_... - Traduire cette page30 mars 2017 - PDF | The segmentation, detection, and extraction of infected tumor area frommagnetic resonance (MR) images are a ... Berkeley wavelet transformation (BWT) based brain tumor segmentation. ... Application of ANN and ANFIS for detection of brain tumors in MRIs by using DWT and GLCM texture analysis.[PDF]

Brain tumour detection using discrete wavelet transform based ...

https://www.alliedacademies.org/.../brain-tumour-detection-using-d...

Traduire cette pagede P Rangarajan - ‎2017 - ‎Cité 15 fois - ‎Autres articles11 juin 2016 - Brain tumour detection using discrete wavelet transform based medical ... MRI and. PET images are fused based on image enhancement and fusion technique that has been implemented and simulated in MATLAB. The fused ...Termes manquants : berkeley

Image Analysis for MRI Based Brain Tumor Detection and Feature ...

Traduire cette pagede NB Bahadure - ‎2017 - ‎Cité 40 fois - ‎Autres articles16 févr. 2017 - The benign brain tumor has a uniformity in structure and does not contain active .... ofbiologically inspired Berkeley wavelet transformation (BWT) and SVM as a ..... The proposed algorithm was carried out using Matlab 7.12.0 ...

I recommended the following article

Best Regards Catia Cillóniz

Thank you Heidi

this is really useful. I'll try to look for specific markers.

With best wishes

Omar

Dear Eduard,

There are some great recent advancements regarding the role of DTI to determine the glioblastoma infiltration zones that are more prone to recur and are not visible on classical MR imaging studies.

Take a look on the following papers.

References:

Dear Mohamed,

You can use Ginkgo-cadx software it is free and can download from this site

it is useful and very easy

Regards,

this may be helpful

Dear Sweetlin,

Pfa, few papers which may help you

Thanks

Po-Yu Kao : You can get in touch with the Director of the Radiology department of your University and present your request. But as a practicing neurologist I do not see how doing this type of study on CT scans will help us. The CT scan is of very limited use to us now. Even MRI, except for fMRI, is becoming less valuable from research point of view. Brain PET, SPECT scans using specific radioisotopes for specific neurotransmitters, receptors, transporters is what translational research in neuroimaging has become in neurology. There are now medical centers where only MRI is being used for clinical neurology, even for stroke, whether ischemic or hemorrhagic. My intention is not to discourage you, but just to tell you what we neurologists are interested in regarding brain imaging. thanks.

You can use an weighted cost-function.

Look at this link: https://blog.bigml.com/2017/08/30/using-a-customized-cost-function-to-deal-with-unbalanced-data/

Dear Guevara,

Thank you for your reply, unfortunately there is no MRI multi modal images with DTI with tumors ground truth in NITRC Image Repository .

Dear Sir. Concerning your issue about the meaning of biomarkers in MRI brain tumor segmentation . Early biomarkers of tumor response to anti-angiogenic therapy are urgently needed to enable the rapid assessment and tailoring of drug therapies. MRI biomarkers are increasingly being used to assess the efficacy of tumor therapies. In particular, MRI methods for characterizing the tumor vascular structure, including the cerebral blood volume (CBV) , microvascular blood volume (MBV: vascular volume pertaining only to relatively small diameter vessels) , and vessel caliber index (VCI) have been developed and used to study changes in tumor vasculature with therapeutic treatment. In addition, the apparent diffusion coefficient (ADC), determined from diffusion-weighted images (DWI), and the transverse relaxation time (T2) have been used as biomarkers of tumor edema. Finally, I think the following below links may help you in your analysis:

http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0017228

https://www.sciencedirect.com/science/article/pii/S2095882X16301347

Thanks

Detection of brain tumors needs clear history taking, good examinations clinically and finally proper radiological investigations......

how

Dark-Field microscopy may assist with identifying positive cell but it may be difficult to identify where the cells are specifically in the tissue.

Regards

Chris

Better start with traditional FCM method. Then try to implement the FCM within the ROI.

Modifications can be done for the following:

1) Automatically select the number of regions to cluster

2) Automatically initialize the membership functions for the selected clusters

3) Modify the objective function

These are only possible with the application knowledge, here MRI characteristics of brain and brain anatomy.

This supports to converge quickly

I think you can start with a review - there had been many techniques try to improve the segmentation of brain tumors, like different sequence imagining technique using MRI, fMRI mapping, real time intra-operational functional mapping, real time fluoroscent dye (locally or pre-surgical hyper-selective using interventional technique) technique, real time fast frozen histology analysis etc. (These are all old methods, btw, I'm sure if you look, there'll be a lot new ones).

However, I think the highlight of the paper should be the real clinical impact on these segmentation technique: There has been many clinical studies as well (many of them were ignored by scientists, as they usually discourage previous findings), most of them suggest the conventional segmentation is not as helpful to clinical practice. The reason be, even the segmentation were provided via imagining technique, it is not histologically matching the actual tumor border. Take glioma for example, there has been debates on the extent of recession over many years, we all want to complete remove the tumor while preserve as much healthy brain tissue as we could, but this had been proven to be challenging even as the imagining technique advancing. In the old days, they advice us to remove the tumor via the color mismatch on the tissue, then they suggest we could remove the edema region surrounding the tumor, and some study even point out we should perform extensive excision up to a 2 mm radius outside the edema region. All they want is to remove as much more as possible to suppress recurrent and relapse.

Base on my experience, I don't think there is any good technique currently that can be applied as gold standard to determine the ideal border of removal for glioma, but the future trend should be to identify the actual histology border using the imagining technology we have. If anyone could do that, it should be enough to revolutionize the treatment guideline and strategies for glioma.

used as predictive analytics techniques

EEG is noninvasive -but very nonspecific. Brain tumors, strokes, abscesses for example can produce very similar EEGs. It also has severe limitations for distance from surface and volume of tumor and degree of irritation, for example.

If you decide to proceed in this pursuit despite these caveats, you could:

- contact neuro-oncologists at some local University hospital -there seems to be a unit at least in AgaKhan-university.

-contact Neurosurgeons or Oncologists -they should be able to help you

-contact any (older) neurophysiologist; they usually have a lot of EEG data from brain tumor patients

There should be several 10 000 new brain tumor patients annually in Pakistan -so if the problem is not getting anyone of them to consent for an EEG sounds strange.

All the best

Follow two steps:

1. Build the edge map from your image.

2. Compare PSNR and SSIM for the edge map.

I used to use this protocol. I used DMEM+10% FBS and passaged with trypsin. Other use DNAase/papain. For chamberslides, I think I used poly-D or poly-L-lysine coating followed by gelatin but bare tissue culture treated plastic worked basic astrocytes. You are probably actually isolating glial progenitors that mature into astrocytes in the dish. Also, there are irreversible changes when you expose to serum so defined medias (i.e. with DMEM + G2 or N2) also work and will give in vitro morphology closer to in vivo. Ben Barres paper from Neuron in January 2016 was pretty detailed for immunopanning to get purified populations as the cultures below will be mixed.

Day 1:

1. Put 10 ml DMEM/10% FCS in each 75 cm2 flask. Use one flask for every one or two pups (rat).

2. Dissect cortical hemispheres from P1-P4 pups.

3. Using a 10ml pipette, transfer dissected cortices to a 15 ml tube. (Use more tubes if necessary.) Rinse once with cold CMF.

4. Add 7ml CMF/0.25% Trypsin and strongly pipette up and down a few times with a 5 ml pipette.