Questions related to Alzheimer's Disease
Alzheimer's disease is a devasting neurogenerative disorder that continues to affect millions of people every year. But despite its prevalence, there is no medications on the market to prevent the disease or reverse the damage it causes. I wish to hear what may be the best treatment options for the Alzheimer's disease.
I'm evaluating a 57 year old male with complaints of memory loss, and family hx of Alzheimer's (father). He produced a rather unusual cognitive profile that has me scratching my head. Any feedback/thoughts that folks are able to provide would be very much appreciated. This is a basic battery, and additional testing is obviously necessary. I will provide testing data in the form of percentile rank:
***I am particularly baffled by the discrepancy between verbal IQ and verbal fluency tests
Full-scale IQ: 73 (premorbid IQ estimate- 34)
Verbal comp. index: 37 (similarities-25, vocab-50, info-37)
Perceptual reasoning index: 73 (block design-91, matrix reasoning-63, visual puzzles-50)
Working memory index: 98 (digits forward-91, digits backward-95, arithmetic-95)
Processing speed: 55 (Symbol search-63, coding-50)
Visual Memory: 55 (visual reproduction I-95, visual reproduction II-9)
Visual Working Memory: 87
Auditory Memory: 10 (logical memory I-25, logical memory II-5, VPA I-16, VPA II-16)
Immediate Memory: 47
Delayed Memory: 5
*** VPA II recognition: 10-16%
*** Aphasia screening normal
fine motor assessment-bilateral impairment, but he has carpal tunnel
Currently we are working on a review that surveys the cognitive/neural mechanisms of tactile working memory. We propose a sensory recruitment model, which suggests that prefrontal regions interact with somatosensory cortex to encode, maintain and retrieve tactile working memory. Please leave your email address if of interests.
I need a stack of black and white .jpeg/.tiff/.jpg/.png images across time of either action potentials, neurons firing, or brain scans (comparing disease and normal brain, disease progression, etc.) that I can colorize and overlay for a project in a data visualization course. It wouldn't be published and only for submission to the instructor.
I'm starting to research rating scales to assess symptoms of agitation or anxiety in patients with dementia. If you know any papers or resources Id be very grateful for suggestions
Substance-P is an example of peptide neurotransmitter present in hippocampus, neocortex region of brain which involved in perception of pain. I want to know is any link between this neurotransmitter to Alzheimer's or other type of dementia?
i am having difficulties with staining for Phospho TAU in KA-induced animal model.
I am using free floating immuno histochemistry method.
I am using AT-270, At-180, AT-100, AT-08 antibody (1:200, 1:500, 1:1000)
I have tried antigen retrival (sod citrate ph6)
i have tried 3%H2O2
I am trying blocking next lets see..
And Doing DAB staining.
Can any one help me ..or is there any specific technique????
Hello, this is Jean who is new to use ADNI data + DTI data.
I downloaded Axial DTI data of AD & CN, and I drop those data in dcm2niigui, but it does not work to covert to 4d nil image.
So I checked the data and it has 2,714 of dcm, which is different from what I got in PPMI DTI files.
Is it a matter of axial dti files? or is there any other issue regarding this??
I need EEG data of normal patients as well as those suffering from Alzheimer's disease for my research. Can anyone suggest where can I find these?
The association of free radicals in the pathophysiology of chronic diseases like degenerative brain disorders (AD, PD, HD, Stroke) has been evident by a substantial research.
I am using a CNN for MRI image recognition. After running the model I stumbled upon some strange outcomes (at least, to me they seem strange).
1. The accuracy is very low. I have a binary classification task and the accuracy is below 50%. I'm using MRI's but haven't been able to apply skull stripping. Can the irrelevant information in the pictures be so distracting that the model actually learns nothing? Some additional info about my data:
- I'm using a pre-processed dataset from ADNI (ADNI1 complete yr 3, 1.5T)
- The data is balanced
- I have ~900 images of which 450 sick and 450 healthy
- I have tried different models but all models seem to achieve around the same results (under which the tutorial from Tensorflow: https://www.tensorflow.org/tutorials/images/cnn and datacamp: https://www.datacamp.com/community/tutorials/cnn-tensorflow-python)
2. The model is not showing a normal learning curve (see graphs). Instead of a slowly increasing accuracy and decreasing loss, these values seem quite random. Again, I have tried many different models, most of them were not learning at all (the accuracy remained the same in every epoch), this algorithm does learn but I don't understand these outcomes. Can someone help me understand what my models does?
If more information required, please ask.
P.s. I'm fairly new to programming and neural networks in particular, so any suggestions (also for pre-processing techniques) are more than welcome!
I've been testing my A-beta 25-35 samples with ThT assay on a black 96-well plate to monitor its aggregation state, the fluorescence in 3 replicate wells differ dramatically unless I pipette the wells right before assay.
I've read about shaking the plate before each ThT assay, but I'm not sure in what ways this method helps, and how can I shake a 96-well plate sufficiently without spilling the contents?
I find very interesting the idea that intestinal microbiota might influence brain development and behaviour. There are research groups or studies that explore a link between the gut miocrobioma and dementia?
For decades the AD theory of accumulation of A beta plaques and phosphorylated tau tangles has dominated the research on AD. Notwithstanding the tremendous amount of exciting studies in the field, the progress to understand the cellular and molecular mechanisms underlying AD has not still yielded desirable treatment. Some researchers started to suspect that maybe there are other different or parallel unknown mechanisms to focus on in order to pinpoint the etiology of AD.
In this regard, a recent study has shown that the isomerization and epimerization of long-lived proteins prevent lysosomal degradation which result in the accumulation of dysfunctional lysosomes in neurons and lead to AD symptoms.
The team stated in their paper that: "Lysosomal failure caused by the iso/epi modifications documented to exist in both Aβ and Tau offers a direct connection between these observations and a potential new pathway to explore for the underlying cause and treatment of AD."
Now, this discussion forum is open to opinions and arguments regarding this new hypothesis, and possibly a comparison of other rival hypotheses about mechanisms or etiology of AD.
As a health researcher I have been long concerned at the lack of proper diagnosis of Alzheimer's Disease in older adults that pervades the mental health field. Up to 92% of those suffering from memory disorders have been found to also suffer from hearing impairment, almost all of them un-/under-corrected. This renders any diagnosis of AD in an older adult inconclusive or over-diagnosed. My symptomatic charts comparing the behaviors arising from late onset AD and moderate hearing impairment in older adults have been published by NIH entities, yet the practice of disregarding the auditory component persists throughout the mental health field. How may be best to remedy this pervasive oversight?
My dataset consists of EEG electrode power features in all power bands(alpha, beta, delta..both relative and absolute) and source power features (obtained after sLoreta analysis) in addition to connectivity strengths between the different sources (brain regions). There are as many as 20k features in all.
If i have to predict disease (dementia) based on all above features, what approach will yield best accuracy on test sets? I initially thought that maybe i must fit seperate classifiers for each type of feature set (after dimension reduction) and then use the output probabilities obtained to write a meta classifier on top to predict the final disease state.
However, i think that may perhaps not be so great as all features are correlated (as source estimates and connectivity measures are obtained from the electrodes themselves). Is this correct?
I used KernelPCA to select a few components from the entire dataset and then run a classifier on top of the transformed dataset with cross validation. I get an accuracy of around 75% only on test sets. I have to improve accuracy atleast by another 15%. I used extremely randomized trees but the accuracy was not that much.
What other approaches can i use?
I am looking for a good discussion on possible approaches and/or a sample solution. Thank you.
I am trying to detect Amyloid oligomers in brain tissue extract of APP mice by ELISA kit but the outcome is mostly undetectable.
I am using IBL-Elisa kit: Amyloid Beta (82E1-specific) Aβ Oligomers (ref27725) and I have problems detecting it. I homogenize 5-10mg of tissue in Tris buffer pH7.4 (20mM Tris; 140mM NaCl) with a pestle (not sonication).
I have searched for publications about this form of samples processing but I don’t get any clear suggestion about it.
Anyone knows if it is necessary some other protocol or previous-step for low-weight samples?
Any advice are welcome.
Thanks in advance!
Limbic-predominant age-related TDP-43 encephalopathy (LATE) is a quite hot topic these days among those who are concerned with dementia, memory deficits and neurodegenerative diseases.
It has been suggested that LATE is distinguished from frontotemporal lobar degeneration (FTLD) with TDP-43 pathology based on its epidemiology.
What do you think about this newly recognized disease?
Any idea about the potential or promising diagnostic approaches?
Possible future biomarkers and mechanisms...
We are trying to replicate the endogenous tau found in TgF344 AD rats (Cohen et al. J Neurosci. 2013 Apr 10;33(15):6245-56. doi: 10.1523/JNEUROSCI.3672-12.2013). We have used many antibodies - CP13, AT8, MC1, PHF1 - with DAB &/or tyramide booster, and haven't found anything. Please let me know if you have tried anything that works.
I am working on immune reaction in Alzheimer's disease in mouse models at UCL. Currently I am doing co-immunostaining with antibodies against Iba1 (green) and CD68 (red).
My question is:
How to evaluate whether the microglia cell is activated or not? The signal varies quite highly, and can be either punctuate or globular, either in the cell body or in the processes or both.
As it is a phagocytocic marker I am aware that there is variation. However I am unsure of where to draw a line between unactivated to activated.
Thank you for advice!
Please tell me where can I get EEG data for Alzheimer's disease , because I am working on designing an automatic diagnosis system for detecting diseases.
Should i exclude them from analysis? does LPS iP injection increases Thigmotaxis behavior?
I am interested in using machine learning to analyze MRI data in order
to extract pathological changes for neurodegenerative diseases (i.e Alzheimer's, Huntington's )
Can someone please give some advice on what (bioinformatic,statistical) methods from your experience would be best for an initial analysis and to extract disease specific features ?
Also what would be the most useful platform and what visualization tools or popular packages are best for data extraction and presentation in this case ?
I have about 500 samples from Philips and Siemens scanners ... Could you also suggest the processing power that I would typically require ... for example If I want to train my data and create module or signature prediction algorithms and what MRI parameters would be most informative in each case ( i.e FLAIR, DTI ?)
Any help would be greatly appreciated
I am currently collecting brain tissue from HFD/STZ induced T2D mice. I am noticing a trend for lower brain weight in the more severely diabetic mice. I am aware of the impact T2D can have on cognitive function and may be a contributing factor in Alzheimer's development. I am also aware that late stage Alzheimer's patients have significantly less brain mass.
Can anyone provide some insight or link to some papers that address this?
As previous research indicates that the bilingual people are more resilient to dementia, developing several years after the monolingual, so is it a proportional correlation?
Is more languages practice associated with further reduction in dementia future risk?
The age of onset of HSP varies tremendously, ranging from very early in life up to old age.
There are various mechanisms causing HSP, summarized
e.g. in Fig. 2 of S.Klebe, G.Stevanin and C.Depienne, Revue neurologique 171 (2015) 505.
There should probably be different reasons for different cases.
If some gene (protein) is wrong, one can imagine that trouble starts right at the beginning.
In a late onset case one could imagine that some kind of toxic substance ('Placques' in Alzheimer disease e.g.) accumulate over time and cannot be removed fast enough.
Does anyone have more concrete ideas about what is going on?
When plotting a bifurcation diagram in nonlinear dynamics, the axis x displays a given phase parameter. Are there examples in which the phase parameter stands for time passing (for example, from the value T0 to the value T200 seconds, or months, or years)?
To make an example, I was thinking to something like the one in the Figure below, concerning the phase transitions among liquids, solids and gases: if you leave, e.g,., that the temperature raises of one degree every second, can we say that the axis x displays time (apart temperature values)?
I am trying to use IL-6 and CD163 as a microglia marker in Alzheimer's Disease mice model, but it seems not to be working. If anyone has succeeded before, please give me some suggestion about the detailed protocol? Thanks a lot!
I am not sure if we are supposed to change staining protocol for different mouse strains, but I am having difficulty staining (free floating immunofluorescent staining) on my 5XFAD mouse brain sample.
Basically, I see high background staining (auto-fluorescence) when I use confocal.
My samples were previously exposed to 4% PFA (perfusion + overnight post fixation) then washed and stored in 1XPBS with 1% sodium azide.Tissues were embedded into LMP 3% agar and sliced (50 um), using vibrating microtome.
So far I've tried...(***blocking solution contains 0.1% tritonX-PBS)
- 10% FBS blocking with donkey anti-mouse secondary
- 4% BSA blocking with donkey anti-mouse secondary
- 5% horse serum blocking with donkey anti-mouse secondary
To make it clear, there is no confocal issue. So far I've never encountered this problem when I stained on other mice.
Any suggestions (protocol/reference) would be much appreciated!
While breeding 5xFAD, there is Pde6brd1 mutant homozyous which cause retinal degeneration .
That mutation degenerates eye rod cells which detect bright and dark.
Can I use that mouse in morris water maze?
I want to check cell internalization of Abeta (1-42) peptide w.r.t. However, I do not have fluorescent labeled Abeta peptide to perform this experiment. Is there any other ways by which I can monitor the same.
Or is there any protocol to tag fluorescent dye to a peptide after cleaving it from the resin???
I am interested in doing an ROI-based analysis of ADNI FDG-PET data to examine regional metabolism in their control group. I am using a coregistered volumetric MRI to create anatomic ROIS and exporting these as masks to use on the PET data. Since I'm using ROIs created from each subject’s own MRI scan, is it still necessary to do a partial volume correction, or is that something you do only if you’re warping everyone’s images into a common space (e.g. MNI)? And, if I need to do partial volume correction anyway, is it a reasonable alternative to simply erode each MRI-based ROI mask by 1 voxel all around to avoid the issue, instead of doing a more complicated partial volume correction method (e.g. segmenting a coregistered MRI image, calculating a CSF dilution factor and then correcting the raw time-activity curve of the PET in each region)?
Can neurofibrillary tangles (NFTs) be visualized with Congo Red? What would be the difference between various staining methods used for this (ie. HE, silver stainings,...)? What's the best one?
I can't find any interesting study showing such dependence reliably. Maybe someone know a interesting paper?
Currently I am working on Alzheimer's disease. In the literature i had noticed the staining of both Cresyl violet and H&E for histopathology studies. what are the things we can differentiate through different types mentioned stains.
Neuro fibrillary tangles are formed by the aggregation of tau protein which ultimately results in the death of neuron, and beta amyloid is formed by the cleavage of beta secretase.
Here what happened to the synthesis of alpha secretase, in Alzheimer's patient is there any competition between alpha secretase and beta secretase or alpha secretase is completely absent ?
I am performing western blot analysis to detect the protein expression changes in the brain tissues from several neurodegenerative diseases (e.g Alzheimer's, Parkinson's) as compared to normal control (age-matched). In your experience, which is a better loading control - GAPDH, ßActin or α/ßTubulin?
If you are aware of any articles that addresses above question, please do share.
Thank you for your feedback!!
Currently we are working on Alzheimer's disease. From literature we unable to get conclusion regarding the usage of coordinates, as i have find out lot of difference in the coordinates from article to article.
Ex 1: 4.8 mm anterior to posterior (AP) Bregma, 2.2 mm mid to lateral (ML), and 3.0 mm dorsal to ventral (DV).
Ex 2: −3.6 mm anterior‑posterior to the bregma, 2.4 mm lateral to the sagittal suture, 2.8 mm dorsoventral.
Ex 3: −0.8 mm antero-posterior from bregma and ±1.5 mm medio-lateral from the midline.
I will be using Amyloid beta and Streptozotocin as an inducing agent.
Does anyone know if it is possible to detect mRNA expression levels of Tau variants (e.g. Tau40, Tau42) in non-cerebral cell lines such as HUVEC and THP-1? mRNA expression levels can be detected in transgenic mice expressing such human variants, but I am not sure if it possible in cell lines. Given that Tau is a microtubule‐associated protein found in epithelial cells (an other types), it is possible that Tau expression may be up/down regulated depending on the cellular circumstances, but I am not sure if the splicing events related with Alzheimer has been observed in cell lines and detected by qPCR.
Thank you in advance,
I am Henrique. My current project is Animal-Assisted Therapy for Alzheimer's Disease patients using Virtual Reality.
I am currently validating the effects of a designed tool. I am trying to find any tool or questionnaire that could address the pre and post intervention stress level or agitation level. If you know any other tool for any other interesting aspect other than stress or agitation that could be related in some way please also mention.
The intervention consists in having the subject try out an application during 10-15 minutes and then evaluate if there was any change in mood, stress or agitation, etc.
I am new to research so I have not much experience in searching or using these evaluation tools/questionnaires.
I want to test the GSK3 activity in neuronal cells. Since the isotope is not authorized in our lab, I wonder whether there is an isotope-free method for detecting GSK3 activity.
Hi, I want to quantify total tau, phospho tau and tubulin in the axon and dendrite of hippocampal and cortical neurons by Confocal microscopy analysis. I'll appreciate if you could suggest me the method to distinguish axon from dendrites, and the method to quantify them using imageJ software.
I have attached the image file/picture I scanned using microscope (red channel: total tau, green channel: tubulin, yellow channel: phospho tau). The image is focused on neurites.
I have done Radial arm test for rats of 5 groups, with 10 animals in each group. I am trying to analyse the results through graph pad prism. On what basis we have to go for selection of either Bonferroni or Turkey test?
I have to use an animal model of Alzheimer's disease that shows beta amyloid plaques and also Tau hyperphosphorylation but the only model that I found has a 129 background and I need a model with c57bl6 background. Tks
I am going to work on geriatric sporadic Alzheimer's disease. Tripple transgenic mice model is good for famillial alzheimer's disease but it is not a good model for sporadic alzheimer's.
I need a non-transgenic model for Alzheimer's disease in order to use it to test the efficiency of stem cell therapy on neuro-degenerative diseases.
It has been suggested that AD is more common in human female population and disease progression is more aggressive in female 3xTg mouse model. However 3xTg males seem to be used quite often in studies as well.
I'm planning to do some behavioral tests on 3xTg mice, there are reports on hyperactivity in aged females, and that estrus cycling may confound assessment of disease-related behavioral dysfunction. I'm not sure if there are any other special concerns with this model regarding the choice of gender.
Also Jax warned that male 3xTg transgenic mice may not exhibit the phenotypic traits originally described, thus I might have to use females since I’m going to purchase from Jax.
Does anyone have experience with this model? How are the females doing in behavioral tests and what are the concerns?
Is there only one pathway of cholinergic available for Alzheimer disease ? there may be a possibility of any other pathway for drug dilevery ?
I know magnetoencephalography (MEG) records magnetic fields-which are very small- produced by electrical currents in brain to map brain activities. how effective the external magnetic fields can be on the response? can we also use them (external magnetic fields) to change brains activity on a good way-such as improving memory?
I am working with PPI network of Alzheimer's disease (AD) and type II Diabetes Mellitus (DM) . But I am facing difficulties to retrieve all risk genes predisposing to AD and DM. Some literature have focused on GWAS database, some have focused on candidate genes. Which method should I need to follow?
There are different types of diagnostic tests for Alzheimer's disease. as far as I know, one of them is positron emission tomography (PET) scanning. what exactly does cause the sign of the disease on a PET image? what percentage of Alzheimer's disease can be diagnosed by this procedure? do prescription drugs affect these signs after we take the test again?
Manually annotating the datapoint of interest using simple edge detection or segmentation techniques for labeling won't be an ideal procedure?
So what's the suitable cost effective step that can be achieved here ?
I am working on a project that may be of great benefit to people with Parkinson's or Alzheimer's Disease but I need some NMR work done on the product(s) to confirm that I have the correct molecule and to determine the amount of it.
I can provide the test material and both standards (a pair of diastereomers) as dried precipitates or in ethanol. A publication (20 years old) gives a complete assignment of the 1H and 13C NMR spectra of both molecules dissolved in chloroform. I'm pretty sure I can produce milligram amounts of the target molecule(s) but do not know how pure it is.
I've out-sourced a “feasibility study” for this NMR work but to continue with this (or any) CRO is too expensive. I cannot offer any contributions to your costs or university overheads. It is impossible to patent this.
I'm looking for someone with an NMR machine who is willing to help in return for being the second author on a paper (to be submitted to a suitable peer-reviewed journal) with the potential to be highly cited in the area of neurology and that might help millions of people burdened with neurodegenerative diseases.
If you are interested and have the machine and skills to create and interpret NMRs, please email me.
we are working on dpp4 inhibitors to target AD. we would like to use sitagliptin as standard. Kindly let us know, on what basis we supposed to select the dose (for rats), as different researchers have used different doses like 10, 30, and 50 mg/kg.
If possible kindly provide me with proper calculation.
I was trying to find a anti-Tau antibody to stain neuronal axons of frozen brain slices from healthy mice. However, I learned that hyperphosphorylated Tau is also the hallmark of Alzheimer's disease so it is also used to determine pathological state of Alzheimer's disease (eg. 3x-Tg) mouse tissue.
So I was wondering, is there a distinction between the Tau antibodies used in these two cases? It sounds like Tau has different phosphorylated states in two cases, but which antibody should I use if I just want to stain axons of healthy mouse slices?
Thank you very much for your help on this!
If the answer is positive, please describe it. I am looking for any correct answer, please don't hesitate to contact me.
Non-valvular atrial fibrillation (NVAF) is more common with increasing age. Doctors are increasingly asked about anticoagulation in such patients.
Is it appropriate to give anticoagulation in patients aged ≥ 90 years with NVAF who are:
a. Ambulatory and having preserved cognition.
b. Partially dependent with impaired cognition and brain CT evidence of lacunar infarcts.
c. On Nosogastric (NGT) or PEG tube feeding with associated Alzheimer's disease and bedridden status.
Any evidence-based answers will be appreciated.
For studying anti AZ action of drugs through behavioural studies, in articles training (for memory related behavioural studies) has been given after the induction.
Now my doubt is what is the point of logic in giving the training after inducing alzheimer's and what may be the reason behind to do so.
My intention is training should be given prior to the induction, memory should be tested during induction and treatment period as well.
Kindly clarify me with correct method.
We have a project using MC65 cells which are a Tet-OFF line for expression of the C99 fragment of APP. Tetracycline withdrawal produces cell death in this line within 2-4 days.
We want to look at ABeta toxicity but ideally want to look at effects from the full length APP protein instead of the C99 fragment.
Does anyone know if there is a stable transfected line out there with full length APP over-expression that can be used for similar toxicity measures?
I am trying to look for basal ERK phosphorylation in N2a cells. Although, I am able to detect very good intensity of bands for total ERK, but the p-ERK bands are hardly visible. Also, when the basal p-ERK is very low in these cells, the extent of effect of stimulation with any agonist or chemical is very minimal.
I have to repeatedly thaw new vials every week to see which batch of cells give decent p-ERK basal levels.
Is this problem faced by other members here? How can one resolve this issue such that the cells maintain good levels of basal ERK phoshphorylation?
Media used: DMEM+ 10% FBS+ Penicillin/ Streptomycin
Antibodies: p-ERK and t-ERK antibodies from Cell Signaling
Looking forward to your helpful suggestions
Geneticists have made risk assessments of developing Alzheimer's by age, gender, and APOE genotype. Christensen et al. (2008), in "Incorporating ethnicity into genetic risk assessment for Alzheimer disease" have further refined the assessment by ethnicity but only between African American and White. Has anyone also incorporated Hispanic/Latino ethnicity into a risk assessment by APOE genotype?
I'm studying learning potential and cognitive plasticity in elder adults with mild cognitive impairment (MCI), and secondly in Parkinson disease, Alzheimer disease, and healthy subjects. If anyone has recent researchs that could help me with this study, I'll be very grateful.
If I design a peptide for preventing aggregation of Abeta 42 peptide, what are aspects should I consider if I want to suggest it as drug for Alzheimer disease. What all are the properties should that peptide have? What are all the characterizations should I perform?
Standard use of Confabulation questionnaires may sometimes provoke the production of momentary confabulations among patients (McVittie et al., 2014). Provided that clinicians usually have to rely on their observational abilities to detect single symptoms (e.g. confabulations), can quantitative and qualitative research methods implement for a better assessment ?
Epidemiological and basic science evidence suggests a possible shared pathophysiology between type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD). It has even been hypothesized that AD might be ‘type 3 diabetes’. The present review summarizes some of the evidence for the possible link, putative biochemical pathways and ongoing clinical trials of anti-diabetic drugs in AD patients.
Hello every body,
i am going to investigate "the effect of X substance on cell fate (cell death mechanism) in Alzheimeric cell" but im not sure about select of suitable cell line. Please guide me in this area.
Thanks in advance!