Questions related to Cancer
Hello, I am a new researcher working on an anticancer drug discovery.
I've been reading some papers that cytotoxicity assay is using IC50 as it results to measure the effectiveness of a compound in inhibiting biological/biochemical function.
but my senior colleague asked me to consider using LC50 for the results as well.
should I use the IC50 or the LC50? or both?
or you could give me some advice about the research I conduct at the moment.
That possibility is raised in:
Monikaben Padariya, Mia-Lyn Jooste, Ted Hupp, Robin Fåhraeus, Borek Vojtesek, Fritz Vollrath, Umesh Kalathiya, Konstantinos Karakostis, The Elephant Evolved p53 Isoforms that Escape MDM2-Mediated Repression and Cancer, Molecular Biology and Evolution, Volume 39, Issue 7, July 2022, msac149, https://doi.org/10.1093/molbev/msac149
That would, if it were true, help explain Peto’s Paradox in relation to elephants.
On the other hand: resolution of Peto’s paradox would require co-evolution of genes species by species that impede cancers. Is that likely? Isn’t it more likely that there is a universal mechanism? For example:
What are your views?
Dear Good people,
Which is better for publishing? To test the anti-cancer activity for a drug on a few proteins from two signaling pathways(one or two proteins by maximum for each pathway) or just multiply proteins from the same pathway(two or three proteins by maximum for each pathway)!...
I wish for sure to be able financially to target more in the future. Thanks in advance
Cancer incidence is increasing globally. It is widely believed that increased life span is the main reason cancer risk overall is rising. A paper published in the Lancet reports that delays in screening, diagnosis, and treatment due to the COVID-19 pandemic could lead to excess cancer deaths, and slow or even reverse the declining trend in mortality projected for some cancers. https://www.thelancet.com/journals/lanpub/article/PIIS2468-2667(22)00111-6/fulltext
Furthermore, the report by Harvard Medical School researchers at Dana-Farber Cancer Institute and colleagues from other institutions, suggests that COVID-19 has complicated the treatment for patients with cancer. "In patients with cancer, COVID-19 can be especially harsh. This is likely because many of these patients have a weakened immune system—either as a result of the cancer itself or the therapies used to treat it—and are therefore less able to fight off infection by the new coronavirus". https://hms.harvard.edu/news/covid-19/cancer-interplay#:~:text=In%20patients%20with%20cancer%2C%20COVID,infection%20by%20the%20new%20coronavirus
In 2021, a research team led by Zhou highlighted the clinical and molecular similarities between cancer and COVID-19 and summarized the four major signaling pathways at the intersection of COVID-19 and cancer, namely, cytokine, type I interferon (IFN-I), androgen receptor (AR), and immune checkpoint signaling. They also discussed the advantages and disadvantages of repurposing anticancer treatment for the treatment of COVID-19. https://ijhoscr.tums.ac.ir/index.php/ijhoscr/article/view/1408
Jafarzadeh et al. reported that the patients with some types of cancers may be more vulnerable to SARS-CoV-2 infection compared with the non-cancerous individuals, due to their immunocompromised state resulted from malignancy, chemotherapy, and other concomitant abnormalities as well as perhaps greater expression of angiotensin-converting enzyme 2. Moreover, they reported that clinically recovered COVID-19 individuals display immune abnormalities that persist several months after discharge.
The lymphopenia-related immunosuppression, functional exhaustion of cytotoxic lymphocytes (such as CD8+ cytotoxic T-cells and natural killer cells), hyperinflammatory responses, oxidative stress, downregulation of interferon response, development of the myeloid-derived suppressor cells, downregulation of tumor suppressor proteins and perhaps reactivation of the latent oncogenic viruses may directly and/or indirectly play a role in the cancer development and recurrence in severe COVID-19 patients. https://ijhoscr.tums.ac.ir/index.php/ijhoscr/article/view/1408
I am working on EMT-invasion of cancer cells. I have observed changes in the expression level of ECM-associated genes. Upon submission of a manuscript, one reviewer suggested: " to investigate possible changes to the organization of cell-culture ECM and its ability to support cell migration or invasion".
Can anyone help me to understand this comment? How exactly (specific experiments) can we proceed? What is it that the reviewers want?
Thanks in advance,
Hi Everyone, I have query regarding the DFI event value (i.e., 1 or o). I know DFI event indicates recurrence event. But, I am getting confused whether DFI event 1 indicates recurrence or 0 indicates recurrence in the sample. my confusion arises because of DFS definition and in general survival event value meaning (where, 1 indicates dead while 0 indicate alive). It would be great help if someone can share some publication where it clearly indicated.
Brain Tumor Imaging Protocol will reduce variability and increase accuracy in determining progression and response of investigational therapies.
In the pictures below, with the FFT and DFT methods and the PCA phase recovery, which is common in optical microscopes, I obtained the magnetic resonance imaging (MRI) phase of the human brain tumor and the phase obtained.
Can the process be performed on MRI without prescribing Jumpstarting Drugs (JBTDDC)?
Dear Good People
Is it possible to study the effect of a compound on the activity of a certain signaling pathway but you only have antibodies for the total protein/nonphosphorylated form involved in that pathway! or it would be a waste of time and money?
"P.S."... No abs for the phosphorylated forms are available📷
Thanks in advance!
The Boyden chamber protocol requires a high budget for us. We want to try modifying this test instead. Can we combine it with a protocol like the filter diffusion protocol?
I am conducting an experiment on testing the cytotoxicity of a drug on brain tumor cells. I am using Thermo Fishers alamarBlue reagent and measuring absorbance at 570nm/600nm to measure cytotoxicity. I have two questions:
-I have attached a photo of the equation that Thermo told me to use when calculating the % reduction. What does this equation mean?
-One of my supervisors is doing the same experiment but with different cells, she calculates percentage by merely averaging the blank values (Media + alamarBlue reagent) at 600nm and subtracting that from 570nm readings.
when it comes to calculating the IC50 value, which method is more accurate? because bot methods give totally different values.
I have attached the protocol from Thermo and the photo of the equation given by Thermo
Any help will be very much appreciated!
Because in my experiments even by adding adhesive molecules such as collagen, gelatin, fibronectin I always get cell aggregates and not adhesion as in the plate. Could the stiffness of the gel have something to do with it? Or is it difficult to see stretched cells on the gel?
Please take a look at the attached file.
I irradiated cells using a fractionation regime of 3 x 1 Gy after exposure to a substance in different concentrations.
I made an XY table with the determined SFs and plotted a graph using the LQ-model.
The equation I used was Y=exp(-3*(A*3*X + B*3*X^2)). Its an edition of the provided equation Y=exp(-1*(A*X + B*X^2)) in regard to the fractionation regime.
To determine the AUC I used the standard analyzing tool that Graphpad provided.
Could someone tell me, if this is right or if I mistaken somewhere?
Tank you very much in advance!
As I know, smoking can cause lung cancer and body cells turn into cancer cells due to mutations. However, what is the name of the carcinogenic substance in cigarettes and how can it make body cells mutate?
I am looking for a way to show truncating mutations in BRCA1/2 via IHC. The idea is to use two slides per sample for each of BRCA1/2, respectively. In theory, samples that have a truncating mutation should show expression on the N-, but not C-terminal IHC slide.
I also found the following publication (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2799150/) by Watson et al. (2009), where they developed a IHC antibody that specifically targets the BRCA2-C terminal region, and showed that this method worked for them.
Unfortunately, the paper is a couple years old - and I cannot find this antibody anywhere - or any other BRCA2-C antibody. There are some that use aa 2400 as the immunogen, but I am looking for something more in the region of aa 3000 to really include all truncations.
Has anyone implemented a similar assay to allow for quick and easy IHC of FFPE samples to check for truncating BRCA1/2 mutations?
Thank you for your help!
Dear fellow researchers,
I wanted to know if I should use basal media for preparing working concentrations of paclitaxel, cisplatin and 5 fu. Are these drugs sensitive to FBS in media? How much percent FBS is allowed to be added along with drugs in basal media. Thanks in advance!
More women in the U.S. are choosing to have their breasts removed for early cancers instead of breast-conserving procedures that deliver equal results, according to a new study.
I am wondering what happens to the frozen Conditioned-media (CM) that is collected from cancer cells and then incubated for 24 hours to 48 hours? Will the secreted proteins in CM such as Chemokines and cytokines be degraded? In other words, does the incubation affect the CM composition?
What are the limitations and disadvantages of Real-Time PCR (RT-PCR)?
What is a more specific and sensitive technique that can be used in the laboratory instead, particularly in cancer diagnosis?
Hello, I am trying to apply vcftools --diff in order to extract the different variants between two VCF files.
vcftools --vcf marked_I_tumor-pe.vcf --diff marked_I_normal-pe.vcf --diff-site --out t_v_n
I am getting this as result :
VCFtools - 0.1.16 (C) Adam Auton and Anthony Marcketta 2009 Parameters as interpreted: --vcf marked_I_tumor-pe.vcf --out out.diff.sites --diff marked_I_normal-pe.vcf --diff-site Comparing sites in VCF files... Found 75584 sites common to both files. Found 419593 sites only in main file. Found 84102 sites only in second file. Found 2908 non-matching overlapping sites. After filtering, kept 498085 out of a possible 498085 Sites Run Time = 6.00 seconds 0
I want to extract these 419593 sites which only belong to the main file (the first file) do you know if there is a way to do that? Can these sites that I want to extract be in a new vcf file? If you could help me, I would be more than thankful!
I have two vcf files corresponding to the results of healthy tissue and tumor tissue. I want to compare these vcf files and remove their similarities. More specific I want to remove the information of the healthy tissue from the tumor one. Have you any suggestions on which tool I should use or any way that I can do my analysis?
Thanks in advance.
In case of mTOR I notice cancer research wants to block this pathway right? So would resistance training, amino acids and insuline be dangerous to some extent? Someone with genes for cancer growth can he or she also have more danger with training?
Or is it only when high doses of insulin, growth hormon and such are ingested or injected?
I am fairly new to cell culturing. For my experiments, I plate cells in 35 mm dishes. A crucial step in data analysis is cell-segmentation using the Stardist plug-in on ImageJ. However, I am struggling to obtain proper segmentation because all my cells tend to grow in clusters, making the segmentation processes highly unprecise.
To overcome this, when plating cells, I'd like to obtain single cells (similar to the image I attached.)
Does anybody have any suggestion on how this can be done?
I usually work with OVCAR cells.
Thank you in advance,
I am updating my earlier review on the role of Fluoride doped Hydroxyapatite in Cancer and my current focus is on Psammoma Bodies which have been found, and identifed as high risk, in a very wide range of Cancers. These include Cancers of the Bone, Spine, Brain, Choroid Plexus, Dura Mater, Gliofibroma, Medulloblastoma, Meningioma, Cervix and Endometrium, Ovary, Kidney, Lung, Mesothelioma, Pancreas, Skin, Hemangioendothelioma, Olfactory Neuroblastoma, Duodenal Somatostatinoma, Stomach and Thyroid. Early studies did not have the benefit of advanced analytical techniques, or did not even consider the Fluoride content or composition of the mineralization. Can anyone help by supplying analytical data based on Raman spectroscopy, neutron activation, x-ray or wet analysis?
We want to know if one protein can be used as a breast cancer biomarker or not. So we'll have to compare normal and patients, and our question is whether we can get samples from patients who received chemotherapy before?
I am working with differentially expressed miRNAs where I only have the name of the mir itself without further details, for example mir-204.
Now for target prediction analysis using databases, there is mir-204-3p and mir-204-5p based on the 3p/5p strand position (forward or reverse). Regarding the functionality of both strands, it seems that both could be biologically functional, yet I read somewhere (https://www.biostars.org/p/150526/) that the 5p is the original arrangement and therefore it is more likely to be the active option. Is it reasonable to conclude that I should always take the 5p strand, or should I maybe take both into consideration?
Would appreciate your insight on this matter!
Could someone kindly clarify why aerobic glycolysis is required for cancer cells? That is, if tumor cells used OXPHOS, would they be unable to grow and metastasize as well?
The most commonly cited benefit of aerobic glycolysis seems to be accelerated glucose uptake, but why is this required for long-term growth as opposed to short-term spurts? The timeline for cancer progression is normally months or years, not hours or days.
Moreover, despite consuming glucose faster, total ATP production from aerobic glycolysis is lower. That is, during the time OXPHOS consumes 1 glucose molecule, aerobic glycolysis may consume 13 glucose molecules -- yet this yields fewer ATP molecules.
If correct, total energy production inadequately explains the relationship between cancer cells and aerobic glycolysis.
Is the timing of ATP essential? Perhaps cancer cells need fewer shots of ATP molecules but at a higher frequency rather than wait for one large batch from OXPHOS?
Or what are the other benefits of aerobic glycolysis over OXPHOS?
Ultimately, why would cancer cells be less successful with OXPHOS?
Thanks in advance for your help.
perhaps the most useful aspect of epigenetic processes is that they are readily reversible. Unlike genetic effects that also play a role in cancer and aging, epigenetic aberrations can be relatively easily corrected. One of the most widespread approaches to epigenetic alterations in cancer and ageing is dietary control. now, I would like to know more about the types and mechanisms of that nutrition that have a positive impact on epigenetic alteration during cancer???
we transplant (stem) cells to the mouse brain and would like to exclude that these transplants may cause a tumor. What are straightforward methods to assess/exclude tumor formation in the mouse brain?
The tissue is 4% PFA fixed and cut in 40um coronal sections.
Thank you for your help!
MMR - Immunostaining shows loss of MLH1 and PMS2 in the invasive carcinoma. There is positive nuclear staining with MSH2 and MSH6. CDX2 is negative.
crRNA is responsible for recognizing and binding the sequences next to protospacer-adjacent motif (PAM), NGG, on the target DNA, whereas tracrRNA is essential to maintain cas9 nuclease activity. and most of the miRNA does not contain the PAM sequence (5’-NGG-3) 4. so how can you target them by using CRISPR Cas system?
Metabolic rewiring and epigenetic remodeling, which are closely linked and reciprocally regulate each other, are among the well-known cancer hallmarks. Studies have reported use of Onco-metabolites to metabolically reprogram the epigenetic of cancer. I was wondering what might be major limitations of such techniques?
in cancer therapy, sometimes you have to target multi-targets to understand the molecular pathway of the specific protein. CHyMErA can target multi targets but it is not safe and has a high risk of extra mutation!
This generalizable immunotherapy approach to cancer seems compelling:
Unlike many other immunotherapies, this one does not require pre-defining antigens.
Based on research from the Levy lab at Stanford, this method introduces a non-specific technique to attack cancers by injecting immunoenhancing agents (TLR9 and OX40) locally into the tumor site. In mouse models, these agents activated a robust, targeted anti-tumoral response.
Clinical trials were launched in 2019/2020.
What's the best way to track the clinical trials and see how this therapy work on humans?
I recently performed an in vivo experiment in a mouse MC-38 syngeneic tumor model. A drug was compared with a vehicle control. In nearly every drug treated mouse, there was significant blood vessel infiltration in the tumors and noticeable bleeding when the tumors were extracted. In contrast, there was basically no blood in any of tumors from the vehicle treated mouse.
As an example, I attached a photo, the tumor on the left is from a drug treated mouse, on the right is a tumor from a vehicle treated mouse.
I do not have very extensive experience with this type of model, so I asking if any one has any ideas what this might indicate? Has anyone seen similar results in an experiment? Furthermore, what might be a good way to quantify this observation?
I understand that activation of pathways such as HIF-1a and VEGF could increase angiogenesis. this would be the "exciting" answer for this project. But I am wondering if anyone has run into this for other reasons.
I understand that this is extremely difficult to answer with this limited amount of information, but at this early stage of the project any ideas, hypotheses or speculation would be welcome. Thank you!
It has been reported that chemicals used for finishing hardwood furniture and hardwood flooring may potentially cause health effects since they can cause cancer. The California Proposition 65 law outlines potential health risk of such items which are listed as cancer causing. In spite of such regulation, people have been using hardwood for years. Where is the fine line between use and not to use? Does it bother you to use hardwood for residential and commercial purposes? Is there any such regulation (e.g., Prop 65) elsewhere?
I am planning a study where I want to select a few potential miRNAs that are responsible for inhibiting protein translation from a particular gene.
I am new in this area so it would be helpful for me if I get some guidance on how to select the miRNAs for a specific gene and if there is a way to determine miRNA and mRNA interactions with any bioinformatics tool before moving forward.
I have selected a few miRNAs for my gene from TargetScan, Mirdb, and Mirtarbase but I want some other opinions.
Bispecific antibodies, trispecifics or other formats have been and are still explored as powerful drugs against various cancer types. However, potentially these therapeutic agents could have a much broader application range. What are the reasons, researcher focus on cancer (beyond the obvious ones like incidence rate, death toll...)? The concept of bridging two or more epitopes on different cell types could in my mind potentially be extended to quite a vast range of targets. What about engaging bacterial cells? And what about non-peptide epitopes? Curious to hear some interesting thoughts!
I would like investigate the clinical significance of a particular miRNA in colon cancer patients using TCGA repository. I need to compare the miRNA expression of normal tumor tissue with tumor tissue. By using the filters, I had turned ON the filter to show only adjacent normal tissue in the exploration menu. But the same samples (Case IDs) were overlapped with primary tumor, I understand that, the adjacent normal tissue mean the normal tissue adjacent to the tumor tissue of cancer patient. But when I looked for the miRNA seq data, the filesystem contains only one file for miRNA quantification. my question is, whether the miRNA seq (single file) is of cancer tissue or the normal tissue?
If in case, it belongs to adjacent normal tissue, i need to exclude the respective data in tumor cohort? and while analysing the clicopathological significance of specific miRNA, do i need to include the datas of adjacent normal tissue?
If the miRNA quantification file corresponds to the tumor tissue, then where can i find the miRNA expression of of normal tissue.
I am completely new to this. Could you please help me in this regard? Your help is highly appreciated.
Thanks & Regards
Transfections using chemical transfection reagents rely on electrostatic interactions to bind with nucleic acids and to target cell membranes. what is the best and efficient transfection reagent?
For example AI can automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions. But what are the clinical challenges for its application?
#AI #cancer #clinical #oncology #biomedical
I have to measure the concentration of a specific protein inside the blood. And Unfortunately, our lab does not have enough facilities to perform western blotting, so can we use ELISA instead?
What is the best way or techniques to have accurate results????
Can ELISA be used instead of Western-Blotting to measure protein concentration?
This seminal paper by Paul Mischel rediscovered the relationship between extrachromosal DNA (ecDNA) and cancer:
1. How much would it cost to replicate the part of the experiment that generated subcutaneous tumors from seeds containing 200/2000/20000 cells of FACS-sorted EGFRvIII High/EGFRvIII Low subpopulations?
2. How much would it cost to sequence these tumor cells?
Thanks for your help!
The prevailing theory is that cancerous tumors reflect a form of cellular natural selection, where random mutations confer evolutionary advantages to tumor cells. These survival benefits accumulate over time, eventually empowering tumor cells to outcompete healthy cells and defeat the immune system.
Given this theory, one expects a correlation between cell division rate and cancer rate -- tissues with the highest number of cell divisions should show the highest incidence of cancer (environmental and hereditary factors notwithstanding).
However, few papers seem to verify this assumption, or even document cell division rates and lifetime cell divisions among different tissues.
These are the two best papers so far:
However, the same senior author leads both papers, and the papers seem to omit the most common cancer types, breast and prostrate. Furthermore, the methodology seems fragile as they conducted an analysis across different studies that may not have employed uniform methods.
Could anyone recommend more robust or authoritative papers on the subject of cell division rates?
Cas9 nickase can be used to efficiently mutate genes without detectable damage at known off-target sites. This method is applicable for genome editing of any model organism and minimizes confounding problems of off-target mutations. and now I would like to know how can I design a specific gRNA for it?
According to the NK MACS media brochure, NK cells can be grown directly from PBMCs using this media.
there are various bioinformatics tools that show the patients' mortality rate related to gene expression such as prognoscan! if you know other bioinformatics platforms or approaches please let me know!!!
I want to do a simulation of a lipid bilayer representing the lipid membrane of cancer cells.
What are the proportions of different lipids that I should use in my system?
Hyperinsulinemia means the amount of insulin in your blood is higher than what's considered normal. however, it isn't considered diabetes all the time!! so I would like to know the exact mechanism illustrate the correlation between mortality and hyperinsulinemia
Common fragile sites (CFSs) are large chromosomal regions that exhibit breakage on metaphase chromosomes upon replication stress. As a result, they become preferentially unstable at the early stage of cancer development and are hotspots for chromosomal rearrangements in cancers.
The carcinogenic effect of smoking was finally proved in the 1960-/1970-ties. However, at that time DDT, Lindane and the like were sprayed onto the tobacco leaves, and the warming- and burning-products of these substances were inhaled by smokers.
Opposed to mice and rats used in trials, humans have been exposed to smoke from plant parts in thousands of generations. Humans are therefore likely to have evolved smoke resistance.
The eyelid could be a ”macro-example”. Has smoke resistance been shown in humans at a molecular level?
(I also asked this question as a discussion: https://www.researchgate.net/post/Is_the_carcinogenic_effect_of_smoking_solely_due_to_pesticides_Is_there_any_evidence_that_ecological_tobacco_causes_cancer_in_humans2
Please consider where your answer is most relevant. You can of course also answer both places.
This will be helpful to the readers of RG)
What do you think is the best programming language for cancer informatics for a beginner?
I have found some recommendations for Python, R, MySql, PHP, and Perl, yet as a novice in informatics I couldn't reach a clear conclusion.
I keep reading conflicting papers suggesting that compared to normal cells, intracellular iron is higher in cancer cells (due to increased requirements for haem for cofactors and cellular growth) but other papers saying that intracellular iron is in fact depleted because demand outstrips supply. Does anyone have a paper that clearly states which of these is true? A link to any relevant paper would be appreciated.
What is the best available treatment to get rid of (or limit the development of hepatocellular cancer in babies ( enfants about 1y)? Is the chemotherapy is dangerous for babies? Can a baby survive liver cancer if it is spread over many spots?
- The chloride anion (Cl-) has traditionally been considered a harmful element for agriculture due to its antagonism with the nitrate anion (NO3-), and its toxicity when it accumulates in high concentrations under salinity conditions. On the other hand, Cl- is an essential micronutrient for higher plants, being necessary in small traces to fulfil a number of vital plant functions such as: cofactor of photosystem-II and some enzymes; neutralisation of positive charges in plant cells; and regulation of the electrical potential of cell membranes. Below a specific level in each species, plants suffer symptoms of Cl- deficiency, altering these cellular mechanisms and negatively affecting the capacity for cell division, cell elongation and, in short, the correct development of plants. However, there are indications in the literature that could suggest beneficial effects of Cl- fertilisation at macronutrient levels.
- The results of my thesis have determined a paradigm shift in this respect since Cl- has gone from being considered a detrimental ion for agriculture to being considered a beneficial macronutrient whose transport is finely regulated by plants. Thus, we have shown that Cl- fertilisation in well-irrigated plants promotes growth and leads to anatomical changes (larger leaves with larger cells), improved water relations, increased mesophyll diffusion conductance to CO2 and thus improved water and nitrogen use efficiency (WUE and NUE, respectively).
- Considering that the world's population is expected to reach 9.8 billion people by 2050, global efforts are being made to increase food resources by improving crop productivity. This requires practices that make rational use of available resources, particularly water and nitrogen (N). Only 30-40% of the N applied to the soil is used by plants, and 80% of available freshwater resources are currently being consumed by agriculture. On the one hand, an excess of NO3- fertilisation in crops leads to an increase of NO3- content in the leaves of plants of different species that are consumed fresh (e.g. spinach, lettuce, chard, arugula). The presence of high levels of NO3- in food can cause health problems such as methaemoglobinaemia or promote the accumulation of carcinogenic compounds. These practices also lead to an increase of percolated NO3- in aquifers, causing environmental problems such as eutrophication.
- In broadleaf vegetables, NO3- and its derivatives can accumulate to high concentrations. When ingested, these compounds are processed by enzymes found in saliva and from bacteria of the gastrointestinal microbiota, generating NO2-, nitrosamines and/or N2O5, substances that promote stomach and bladder cancer, causing a serious problem for human health. When NO3- enters the bloodstream, it transforms haemoglobin into methaemoglobin, no longer able to transport oxygen to the lungs, causing babies to suffocate and die, which is what is known as 'methaemoglobinaemia' or 'blue baby disease', and which, as we have already mentioned, was made visible by Greenpeace on numerous occasions. Thanks to these actions, in the European Union there is a very demanding regulation of NO3- content in water for human consumption, as well as in vegetables and processed foods especially dedicated to the production of food products for susceptible groups such as babies, the elderly, vegetarians and vegans. Thus, the European Union has established a series of strict standards (1881/2006 and 1258/2011) that determine a series of thresholds for NO3- content in the most widely consumed vegetables (such as spinach and lettuce), and especially in baby food with much stricter limits, where it is even recommended to avoid the consumption of certain vegetables in babies before the first year of life and to limit their consumption in children from 1 to 3 years of age. At the environmental level, the European Union already created in 1991 the Nitrates Directive (European Directive 91/676/EEC), to protect water quality throughout Europe, encouraging the use of good agricultural practices to prevent NO3- from agriculture from contaminating surface and groundwater.
- Substituting certain levels of NO3- for Cl- in fertigation solutions can reduce these problems without negatively affecting plant development. On the other hand, in the context of current climate change, the strong demand for water from agriculture threatens the freshwater supplies available to the population. Therefore, increasing WUE and NUE, as well as preventing water deficit and increasing water stress tolerance in plant tissues are very important traits for crops that could be favoured by the use of Cl- in new agricultural practices. Thus, Cl- could establish a synergistic improvement in a more efficient use of water and nitrogen for a healthier and more sustainable agriculture.
There is a serious need to improve research in the field of metastatic cancer treatment. Being a non-medical person, but being a researcher (also a son of a cancer warrior, but unfortunately lost the whole game), I am feeling that there is a serious need to float fund in the area of cancer research.
When I used to look back in the past I am not finding any reason of occurance of metastatic pancreatic cancer of my father but he had diagnosed with this health ailment, so there was really any root cause of occurance of cancer. Being a student of Environmental Engineering I know there is a significant impact of environmental pollution for cancer disorder and apart from that some studies also shown food habits may be the reason for this deadliest disease.
So, what needs to be done?
How one can win this war?
My serious and sincere questions to all my fellow researchers in the field of cancer cells research, medical practioners and related areas.
If we will able to find out the main precursor behind this deadliest disease then we should start work on this and we have to design some strategies to reach the ultimate goal of no cancer occurance.
If anyone in this group can contribute some valuable comments then I will able to diversify my knowledge in this areas.
I am trying to do annexing-PI staining and I have questions regarding gating.
1-Which controls are necessary for gating?
2-Should we gate with ”unstained” negative control or with “stained” negative control?
3- Do we need to have Annexin stained control and PI stained controls separately?
I would appreciate your information regarding this method.
This might be a very vague question, but I'm trying to understand what the common stumbling blocks are when trying to make full use of cBioPortal?
For example, researchers are limited to querying only 100 genes from the cBioPortal.
What sort of work can you do through R/python environment that you can't do directly through cBIoPortal?
I have a data (shown in attached pic ) where I have RNA seq data of various samples for the same the gene twice.
Now suppose for sample-1 if I want to measure the gene ( which is haplotypic in nature ) how do I consider its RNA seq for the sample no 1. Do I take average or do I consider median or should I consider both these versions of genes as separate genes ? I guess biologist would make better explanations.
Hi All, I am working with A549 cell line and trying to culture spheroids using low attachment 96 well plates. So far I have attempted some different seeding densities from 2000 to 10,000 cells and can either form very large spheroids (700-900um), which are more compact and have a spherical defined shape, or alternatively smaller spheroids (still fairly big though around 500um) are less compact and not completely spherical. However for my experiment where I wish to add drug compounds (2D IC50 approx 1uM) I am not observing significant size/morphology change on the larger spheroids despite at least a 10uM concentration for 1 week. I am thinking possibly I can try to treat smaller spheroids for a more obvious visual change. Does anyone know how i might successfully make small compact spheroids (less than 500um) which are reproducible with this cell line? Thanks in advance for any help someone may be able to provide.
I have 3 group populations.
Group A has marked nuclear pleomorphism (change in nuclear shape and size), like 1 um, 4um, 2 um, 4um, 6um, 1um, 3um. etc
Group B has also nuclear pleomorphism but not as wide of change as group A
Group C the control group has consistent nuclear size of say 1um for example
I would like to use a stat test to evaluate
1. how significantly different are the groups based on rate of differences
Here are my ideas:
T test probably wont help
I can use clustering analysis
I can do regression analysis
Confidence intervals to show spread of values?
Would ANOVA work?
I just want to visualize and get a P value that these three groups can be different based on variance/change.
Goal is to establish diagnostic criteria based on nuclear size cut offs of either length, width, and circumference of nuclei.
end goal is like 1um - 4um = Grade 1 , 4 - 5um = Grade 2, >6 um = grade 3 and to correlate it to progression free survival.
Some of the biochemical processes in our body produce singlet oxygen. This can react with the other substances in body.