PERILAKU PEMAKAIAN ALAT PELINDUNG DIRI DAN KASUS TUBERKULOSIS PARU PADA PETUGAS LABORATORIUM PUSKESMAS DI KABUPATEN NGADA PROPINSI NTT
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sample amount is often a limiting factor for multi-parametric analyses that encompass at least three areas of '-omics' research: genomics, transcriptomics and proteomics. Limited sample amounts are also an important consideration when these multi-parametric analyses are performed on extracellular vesicles (EVs), as the amount of EVs (and EV cargo) that can be isolated is often very low. It is well understood that a monophasic solution of phenol and guanidine isothiocyanate (i.e. TRIzol©) can simultaneously isolate DNA, RNA and proteins from biological samples; however, it is most commonly used for the extraction of RNA. Validation of this reagent for the isolation of multiple classes of biological molecules from EVs would provide a widely applicable method for performing multi-parametric analyses of EV material. In this report, we describe a comparison of proteins identified from EVs processed with either TRIzol© or the conventional Laemmli buffer protein-extraction reagents. EVs were isolated from 3 mL of cell-culture supernatant derived from MCF-10A, MCF-7 and MDA-MB-231 cells using the Vn96 EV capture technology. For the TRIzol© extraction protocol, proteins were precipitated with acetone from the organic phase and then re-solubilized in a mixture of 8M urea, 0.2% SDS and 1 M Tris-HCl pH 6.8, followed by dilution in 5× loading buffer prior to fractionation with 1D SDS-PAGE. NanoLC-MS/MS of the trypsin-digested proteins was used to generate proteomic profiles from EV protein samples extracted with each method. Of the identified proteins, 57.7%, 69.2% and 57.0% were common to both extraction methods for EVs from MCF-10A, MCF-7 and MDA-MB-231, respectively. Our results suggest that TRIzol© extraction of proteins from EVs has significant equivalence to the traditional Laemmli method. The advantage of using TRIzol
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it