Detection of Brain‐derived Neurotrophic Factor Expression in Insulin‐Resistant SH‐SY5Y Neuroblastoma Cells
Bibliographic record
Abstract
Abstract Background More researchers are coining Alzheimer’s disease (AD) “type 3 diabetes” due to its significant comorbidity and shared pathology with type 2 diabetes mellitus (T2DM). A bi‐directional relationship between T2DM and AD exists, by which 50‐75% of individuals with T2DM have a greater risk of developing AD compared to non‐diabetes and that AD symptoms progress with impaired glucose utilization. Interestingly, brain‐derived neurotrophic factor (BDNF), a small protein that maintains neuron health and glucose homeostasis, has been implicated in both AD and IR. As such, this experiment investigates if insulin resistance (IR) alters BDNF expression in SH‐SY5Y neuroblastoma cells. Method Objective 1: create a model of insulin resistance at 24, 48, 72 and 96 hours (hr) and determine expression of pAkt (S473), tAkt, insulin receptor b (INSRB) and pINSR (T1362) on Western blots. (n = 5) Objective 2: Detect mRNA and protein BDNF via Rt‐PCR and Western blotting. (n = 5) Objectives 3: Determine alterations to BDNF expression via Western blotting and qPCR. (n = 5) Result Levels of pAkt expression were significantly decreased in insulin‐pretreated and activated samples at each timepoint of 24, 48, 72 and 96 hr; although, with each timepoint, pAkt does appear to steadily increase. pro‐BDNF and mature BDNF were detected at their respective sizes, 27kDa and 19kDa, on a Western blot and BDNF mRNA was detected on an agarose gel after PCR. Conclusion It appears that insulin resistance is occurring at 24, 48, 72 and 96 hr solely based off Akt expression. This result will be further confirmed with the the completion of INSR‐B and p‐INSR blots. Ongoing experiments include western blots and qPCRs of BDNF to determine if there is any alteration to expression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".