Autologous bone marrow infusion <i>via</i> portal vein combined with splenectomy for decompensated liver cirrhosis: A retrospective study
Bibliographic record
Abstract
Indocyanine green (ICG) is a water-soluble fluorescent dye that is minimally toxic and widely used in gastrointestinal surgery. ICG facilitates anatomical identification of structures (e.g., ureters), assessment of lymph nodes, biliary mapping, organ perfusion and anastomosis assessment, and aids in determining the adequacy of oncological margins. In addition, ICG can be conjugated to artificially created antibodies for tumour markers, such as carcinoembryonic antigen for colorectal, breast, lung, and gastric cancer, prostate-specific antigen for prostate cancer, and cancer antigen 125 for ovarian cancer. Although ICG has shown promising results, the optimization of patient factors, dye factors, equipment, and the method of assessing fluorescence intensity could further enhance its utility. This review summarizes the clinical application of ICG in gastrointestinal surgery and discusses the emergence of novel dyes such as ZW-800 and VM678 that have demonstrated appropriate pharmacokinetic properties and improved target-to-background ratios in animal studies. With the emergence of robotic technology and the increasing reporting of ICG utility, a comprehensive review of clinical application of ICG in gastrointestinal surgery is timely and this review serves that aim.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".