Bibliographic record
Abstract
This is my first ‘Editors’ view’ since taking over from the impressive (wicket-keeper's) hands of Jeff Aronson. His is a tough act to follow, and my first resolve is to build on his several excellent innovations for the BJCP, and the second is to try to make it even better. How to go about this? You are our life-blood and we are committed to working hard to serve you well. You, in turn, want to communicate your new work to as many interested readers as possible. Clinical pharmacology is a broad church. Your expertise is likely to be highly specialised, but when you decide that BJCP is the place to target for a particular piece of work, please remember that the readership includes experts from different parts of the discipline, and write so that such readers can grasp the importance of your message. We hope that the introductory sections ‘What is already known about this subject’/‘What this study adds’ help to focus minds on this. If your study addresses a valid question, is well designed and well executed, then hopefully it will have moved the subject forward. If not, it is less likely to be of interest to fellow clinical pharmacologists and less likely to be cited. A short piece that carries a clear take-home message is more likely to get a high priority rating from the executive editor than a longer article with an unfocussed conclusion. This is not a plea to super-specialists to stay away (quite the reverse), but to set your pearls before us in a way that displays them to perfection by giving readers the necessary context to appreciate their true importance. Despite its British origins, of which we are extremely proud [1], BJCP is truly an international journal. The authorship of this present number spans North America, continental Europe, Africa and Australasia. There are papers on human toxicology [2] and on prescribing [3], and papers on large molecular weight biologicals including an overview of studies of recombinant activated factor VII [4] and the first PK-PD study modelling the effect of antilymphocyte globulin in kidney transplant patients [5]. There is also a satisfying diversity of experimental methodologies. We have no bias against the double blind randomised controlled trial (RCT) for proof of efficacy – it is for good reason that such trials form the cornerstone of evidence based medicine – but other methodologies are appropriate to other scientifically important questions. Three examples: Cyr et al. [6] reconstructed a cohort of some 36,500 COPD patients from databases in Quebec and found that the use of theophylline was associated with a reduced risk of exacerbations. Pharmacologists will be intrigued by possible mechanisms (anti-inflammatory [7]?, an influence on histone de-acetylase activity [8]?) and clinicians by the therapeutic potential of such an inexpensive and well studied drug in this rather neglected but very common and disabling disease. Muchohi et al. [9] studied the PK and efficacy of lorazepam (iv or im) in Kenyan children with severe malaria. Not surprisingly, given the logistical, ethical and other complexities, the study had its limitations, but careful analysis (including some elegant PK) led to the conclusion that intramuscular lorazepam may be a particularly useful first line agent for such patients. Corrao et al. [10] performed a nested case-control study in Lombardy, concluding that the potential of HRT to reduce fractures disappears after a few months without treatment. Regular readers of this column are familiar with the sayings of Yogi Berra, and in particular his reservations about predicting the future. Undaunted, I offer a personal choice in the paper by Schwedhelm and colleagues on oral L-citrulline [11]. L-arginine is broken down to NO + L-citrulline by NO synthase. Endogenous arginine is in apparent excess (ie its cytoplasmic concentration is much greater than the Km of its interaction with NOS), but in several situations exogenous L-arginine nevertheless favourably influences endothelial function, perhaps because of the presence of endogenous competitive inhibitors such as asymmetric dimethylarginine (ADMA) [12]. However, oral L-arginine treatment is hampered by extensive pre-systemic elimination by intestinal arginase. Schwedhelm et al neatly exploited the counter-intuitive fact that citrulline can itself act as a precursor for arginine (via the ornithine cycle). Oral L-citrulline (one week oral supplementation in healthy men) did indeed increase plasma L-arginine concentration, and also increased urinary nitrite (an index of NO synthesis) and cGMP (a biomarker of NO, which activates guanylyl cyclase) more than oral L-arginine or placebo. There was a correlation between increased arginine/ADMA ratio and flow-mediated dilatation (FMD – an NO-mediated vascular effect). L-citrulline is thus potentially an attractive alternative to L-arginine in patients with endothelial dysfunction caused by impaired NOS activity. Studies in such patients (eg with diabetes, dyslipidaemia or established coronary artery disease) are eagerly awaited, and if positive will lead to phase III RCTs. A dietary means of reversing endothelial dysfunction, believed to be the common pathway linking diverse vascular risk factors and atheroma [13], really would represent a paradigm shift! So I end by wishing all our readers, authors, reviewers and editorial staff a very happy, prosperous and stimulating 2008.
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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.354 | 0.322 |
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".