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Objective To develop and test a statistical model which correctly predicts the approval of outpatient referrals when reviewed by a specialty service based on nine discriminating variables. Design Retrospective cross-sectional study. Setting Large public county hospital system in a southern US city. Participants Written documents and associated data from 500 random adult referrals made by primary care providers to various specialty services during the course of one month. Main outcome measures The resulting correct prediction rates obtained by the model. Results The model correctly predicted 78.6% of approved referrals using all nine discriminating variables, 75.3% of approved referrals using all variables in a stepwise manner and 74.7% of approved referrals using only the referral total word count as a single discriminating variable. Conclusions Three iterations of the model correctly predicted at least 75% of the approved referrals in the validation set. A correct prediction of whether or not a referral will be approved can be made in three out of four cases.

Medical record abstraction (MRA) is often cited as a significant source of error in research data, yet MRA methodology has rarely been the subject of investigation. Lack of a common framework has hindered application of the extant literature in practice, and, until now, there were no evidence-based guidelines for ensuring data quality in MRA. We aimed to identify the factors affecting the accuracy of data abstracted from medical records and to generate a framework for data quality assurance and control in MRA.Candidate factors were identified from published reports of MRA. Content validity of the top candidate factors was assessed via a four-round two-group Delphi process with expert abstractors with experience in clinical research, registries, and quality improvement. The resulting coded factors were categorized into a control theory-based framework of MRA. Coverage of the framework was evaluated using the recent published literature.Analysis of the identified articles yielded 292 unique factors that affect the accuracy of abstracted data. Delphi processes overall refuted three of the top factors identified from the literature based on importance and five based on reliability (six total factors refuted). Four new factors were identified by the Delphi. The generated framework demonstrated comprehensive coverage. Significant underreporting of MRA methodology in recent studies was discovered.The framework generated from this research provides a guide for planning data quality assurance and control for studies using MRA. The large number and variability of factors indicate that while prospective quality assurance likely increases the accuracy of abstracted data, monitoring the accuracy during the abstraction process is also required. Recent studies reporting research results based on MRA rarely reported data quality assurance or control measures, and even less frequently reported data quality metrics with research results. Given the demonstrated variability, these methods and measures should be reported with research results.

RAF (Ras activating factor) kinases are important and attractive targets for cancer therapy. With the aim of discovering RAF inhibitors that bind to DFG-out inactive conformation created by the movement of Asp-Phe-Gly (DFG), we conducted structure-based drug design using the X-ray cocrystal structures of BRAF (v-raf murine sarcoma viral oncogene homolog B1), starting from bisarylurea derivative based on 1H-pyrazolo[3,4-d]pyrimidine scaffold 1a. Most of the synthesized compounds showed good to excellent inhibitory activities against BRAFV600E kinase, possessed moderate to potent anti-proliferative activities against four tumor cell lines (A375, HT-29, PC-3 and A549) and good selectivity towards cancer cells rather normal cells (Madin-Darby canine kidney, MDCK). The most promising compound, 1v, exhibited potent inhibitory activity against not only BRAFV600E (half maximal inhibitory concentration, IC50 = 23.6 nM) but also wild-type BRAF (IC50 = 51.5 nM) and C-RAF (IC50 = 8.5 nM), and effective cellular anti-proliferative activities against A375, HT-29, PC-3 and A549 cell lines as well as a very good selectivity profile. Moreover, compound 1v mainly arrested the A375 cell line in the G0/G1 stage, and showed significant suppression of MEK (mitogen-activated protein kinase kinase) phosphorylation in A375 and HT-29 cell lines. Taken together, the optimal compound 1v showed excellent in vitro potency as a pan-RAF inhibitor. In addition, the promise of compound 1v was further confirmed by molecular dynamics simulation and binding free energy calculations.

It is commonly hypothesized that external representations serve as memory aids and improve task performance by means of expanding the limited capacity of working memory. However, very few studies have directly examined this memory aid hypothesis. By systematically manipulating how information is available externally versus internally in a sequential number comparison task, three experiments were designed to investigate the relation between external representations and working memory. The experimental results show that when the task requires information from both external representations and working memory, it is the interaction of information from the two sources that determines task performance. In particular, when information from the two sources does not match well, external representations hinder instead of enhance task performance. The study highlights the important role the coordination among different representations plays in distributed cognition. The general relations between external representations and working memory are discussed.