Effect of Low-Temperature-High-Pressure Treatment on the Reduction of Escherichia coli in Milk
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
Non-thermal processing of milk can potentially reduce nutrient loss, and a low-temperature-high-pressure (LTHP) treatment is considered as a promising alternative to thermal treatment, attracting considerable attention in recent years. The effect of LTHP treatment (−25 °C, 100–400 MPa) on the phase transition behavior of frozen milk was evaluated. The lethal and injured effects of different pressures and cycle numbers on E. coli in frozen milk were studied by using selective and non-selective enumeration media. Results from the gathered transient time–temperature–pressure data showed that pressures over 300 MPa could induce a phase transition from Ice I to Ice III. The treatment at −25 °C and 300 MPa could achieve a lethal effect similar to the two-cycle treatment of 400 MPa at room temperature. This meant that LTHP conditions can lower the operating pressure by at least 100 MPa or reduce the operation from two cycle to one cycle. Increasing the number of pressure cycles enhanced the lethal effects, which was not additive, but resulted in a transformation of part of the injured cells into dead cells. Transmission electron microscopy (TEM) and scanning electron microscopy (SEM) provided direct evidence for the breakdown of cell membrane and cell walls by phase transitions. Combined with a designed internal cooling device, the LTHP process can be expected to be a more attractive alternative to non-thermal processing for the dairy industry.
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 | 0.000 | 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 | 0.000 |
| 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