Antibacterial porous polymeric monolith columns with amphiphilic and polycationic character on cross-linked PMMA substrates for cell lysis applications
Bibliographic record
Abstract
The application of porous polymeric monolith (PPM) columns as an effective tool for bacterial cell lysis within microfluidic chips is demonstrated. By taking advantage of the large surface area and controllable pore size inherent to PPMs, we developed a double mechanism cell lysis technique. The bacterial cell wall is mechanically sheared by flowing through the porous medium of the PPM column, but it is also damaged and disintegrated by physical contact with the antibacterial polymeric biocide covering the porous surface. This leads to leakage of the intracellular contents. The stable and non-leaching antibacterial column introduced in this work alleviates the need for chemical or enzymatic lysins and their potential release of polymerase chain reaction (PCR) inhibitors. The PPM columns were obtained by the photoinitiated free radical copolymerization of n-butyl methacrylate (BuMA) and N-(tert-butyloxycarbonyl)aminoethyl methacrylate (Boc-AEMA) in the presence of a cross-linker and porogenic solvents. The porous network was synthesized directly inside a microfluidic channel fabricated in a cross-linked poly(methyl methacrylate) (X-PMMA) substrate by laser micromachining. After removing the Boc protecting group with phosphoric acid, an amphiphilic and cationic network structure reminiscent of synthetic mimics of antimicrobial peptides (SMAMPs) was obtained. The antibacterial activity of the PPM columns was tested against Bacillus subtilis (B. subtilis) and Escherichia coli (E. coli) cells. Cell lysis was evidenced by DNA release, which was then amplified by PCR and confirmed by gel electrophoresis, to verify that the antibacterial monolithic columns did not strongly interfere with the PCR process.
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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".