Wide spectrum of novel and rare hemoglobin variants in the multi‐ethnic Indian population: A review
Bibliographic record
Abstract
Abstract The hemoglobin (Hb) variants are qualitative abnormalities due to production of structurally abnormal globin proteins. They are categorized based on the type of mutation present in the α1, α2, β, Gγ, Aγ and δ globin genes. So far, more than 1550 Hb variants are reported in the database. They could lead to Hb polymerization, Hb instability, altered oxygen affinity and decreased oxygen‐carrying capacity of Hb or have no clinical manifestations. In India, ethnic diversity, consanguinity, regional variations and migration result in the presence of different Hb variants. We have compiled all the variants of α, β and δ globin chains in heterozygous, homozygous and in compound heterozygous forms reported from India in the last 52 years. Of the 63 rare and novel hemoglobin variants reported from India, 22 were α‐globin chain variants, 37 were β‐globin chain variants and 4 were δ‐globin chain variants. Twelve novel Hb variants (Hb J Rajappan, Hb Koya Dora, Hb Rampa, Hb Godavari, Hb Chandigarh, Hb D Agri, Hb Lucknow, Hb Vellore, Hb Midnapore, Hb Bijnor, Hb A2Tianhe and Hb A2Saurashtra) were identified among persons of Indian origin. Majority of them were picked up on HPLC. Some of the variants like Hb Titusville, Hb Shimonoseki, Hb Chandigarh, Hb D Agri, Hb Yaizu and Hb Vellore eluted in the HbS window whereas variants like HbD Iran, Hb St. Louis, Hb G Coushata, HbM Saskatoon, Hb Lucknow, Hb Grange‐Blanche and Hb Tianshui showed falsely elevated HbA2. Hence, careful and systematic investigations are required to identify them.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".