Reply: Anterior chamber cytokine production and postoperative macular edema in patients with diabetes undergoing FLACS
Bibliographic record
Abstract
We would like to thank Nishi et al. for his interest in our paper and his insightful comments. We agree that it is important to elucidate the sources of cytokines released during cataract surgery and to try and minimize them to ensure safer surgical outcomes. As Nishi et al. point out, cytokines released during cataract surgery may originate from several ocular tissues, including but not limited to lens epithelial cells (LECs), iris epithelial cells, ciliary body epithelial cells, and corneal endothelial cells.1,2 Another important source is the mechanical disruption of the blood–aqueous barrier during surgery, which is especially compromised in diabetes.3 Although we appreciate the importance of elucidating the source of cytokine production, ultimately it is the impact of these inflammatory cytokines (regardless of source) on downstream tissue effects that is of clinical significance (ie, driving cystoid macular edema, anterior chamber inflammation, and retinal microvascular changes). For that reason, our paper did not explore the sources of cytokines. Future studies are encouraged in this area, perhaps using laboratory-based models of cataract surgery to elucidate release of cytokines from different tissues. It is interesting to ponder on the impact of cytokines released from LECs about our dataset. In our femtosecond-laser–assisted cataract surgery (FLACS) group, the cytokine draw happened after femtosecond laser-based capsulotomy, whereas in our manual cataract surgery (MCS) group, the cytokine draw happened only after corneal incision, without any capsulotomy being done. Interleukin (IL)-7, IL-13, and interferon-induced protein-10 (IP-10) were significantly higher in diabetic patients receiving FLACS than those diabetic patients undergoing MCS. Granulocyte colony stimulating factor, interferon-γ, IL-7, IL-8, IL-13, IP-10, monocyte chemoattractant protein (MCP)-1, and macrophage inflammatory protein-1β were significantly higher in the FLACS nondiabetic cohort than in the MCS nondiabetic cohort. As the difference between the surgical procedure of these 2 cohorts includes a capsulotomy, it is possible that LECs contributed to the production of these cytokines. This is an important question that deserves further exploration.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".