other relevant stakeholders (principle 18), to carry out impact assessments (principle 19) and to adopt qualitative and quantitative indicators to verify whether adverse human rights impacts are being addressed, including feedback from internal and external sources, including affected stakeholders (principle 20). This resembles a monitoring process that is aimed at the prevention of adverse effects on human rights, as it is similar to the role of a labour inspectorate. This is particularly the case with the last principle, which includes performance contracts, reviews, surveys, audits and operational-level grievance mechanisms. What is lacking is the explicit involvement of workers’ organisations and representatives. Given the background against which this framework has been developed, that of human rights above all and implicitly also labour rights, this is not surprising. Moreover, like the procedure on due diligence within the OECD Guidelines, the monitoring procedure is mostly an internal affair executed by the enterprise with optional involvement of the stakeholders, who could be trade unions (not explicitly mentioned) and external advisors/experts. This leaves some doubt about the reliability of the monitoring since it lacks independence and a publicly rooted third-party presence. What is positive, however, is that as noticed with IFAs, the OECD and UN initiatives seem to foster participatory structures that are open to deliberation, which in itself is potentially able to
Two intensive care physicians who were experienced in sever- ity scoring and formerly involved in composing the NICE data definitions selected three sample patient cases. These cases were modified to include some potential pitfalls in data extrac- tion (e.g. abnormal physiological values just before or 24 hours after admission to the ICU). The NICE dataset consists of 88 variables (37 categorical variables, 43 numerical variables, six date/time variables, and two strings). In order to reduce errors associated with identifying the worst value, NICE requires the lowest and the highest values recorded in the first 24 hours, Subsequently a central computer algorithm selects the worst value. The standardized data definitions used in the NICE registry are in agreement with widely accepted data def- initions used in the severity-of-illness scoring models (e.g.
Congruent with its application to busy clinical and policy environments, the 14 item iCAHE instrument uses a sim- ple, binary form scoring system which can be readily summed and reported as a total raw score (or percentage) of 14. Time taken to score a clinical guideline approxi- mates 3–5 minutes irrespective of the skill of the assessor. On the other hand, the AGREE II score requires value judgement using a 1–7 level scoring system, multiple as- sessors and the application of a scoring rubric to determine quality scores in six domains of 23 questions. Moreover, it is not recommended that a total AGREE II score is calcu- lated, or raw scores used, although this was done for this paper to facilitate comparison between instruments. We believe that evidence supporting our claims of the clinical utility of the iCAHE instrument is provided in Figure 1, which outlines the difficulty that the novice guideline assessor had in making decisions about scoring in the AGREE II scale midpoints (3–5). Given this and the non-significant differences in iCAHE scores found be- tween the three testers (moderate to excellent agreement for 17 of the 18 guideline assessments), it seems that the iCAHE instrument could be applied by anyone, with no prior experience or training. We also suggest that the iCAHE Guideline Quality Checklist may be simpler, more efficient and less prone to ‘guessing’ than the AGREE II instrument.
Abstract: Our goal was to compare the recommendations of the Korean Medication Algorithm Project for Bipolar Disorder 2014 (KMAP-BP 2014) with other recently published guidelines for the treatment of bipolar disorder. We reviewed a total of four recently published global treatment guidelines and compared each treatment recommendation of the KMAP-BP 2014 with those in other guidelines. For the initial treatment of mania, there were no significant differences across treatment guidelines. All recommended mood stabilizer (MS) or atypical antipsychotic (AAP) monotherapy or the combination of an MS with an AAP as a first-line treatment strategy for mania. However, the KMAP-BP 2014 did not prefer monotherapy with MS or AAP for dysphoric/ psychotic mania. Aripiprazole, olanzapine, quetiapine, and risperidone were the first-line AAPs in nearly all of the phases of bipolar disorder across the guidelines. Most guidelines advocated newer AAPs as first-line treatment options in all phases, and lamotrigine in depressive and main- tenance phases. Lithium and valproic acid were commonly used as MSs in all phases of bipolar disorder. As research evidence accumulated over time, recommendations of newer AAPs – such as asenapine, paliperidone, lurasidone, and long-acting injectable risperidone – became prominent. This comparison identifies that the treatment recommendations of the KMAP-BP 2014 are similar to those of other treatment guidelines and reflect current changes in prescription patterns for bipolar disorder based on accumulated research data. Further studies are needed to address several issues identified in our review.
Findings from local survey participants about their preferences for dissemination of research to inform re- source allocation decisions are provided in Additional file 1: Section 4. Most respondents wanted to receive critical appraisals and full text articles of both primary and secondary research; fewer wanted abstracts only. A range of responses were received regarding the focus of research content. These were, in descending order of preference, condition specific information (e.g. Diabetes), professional group information (e.g. Emergency Depart- ment Nursing), program relevant information (e.g. Mental Health), organisation-wide information (e.g. In- fection Control) and unit relevant information (e.g. Newborn Services); however more than half of the respondents selected these within their first three prefer- ences so all would be considered of some importance to the target audience. Email broadcasts were clearly preferred over paper-based options for dissemination of research, with short pdf attachments containing titles and hyperlinks preferred over long pdf attachments with titles, abstracts and hyperlinks.
Photoperiodism is one of the most fascinating biological questions: the reproduction of practically all organisms, ranging from single cell algae to humans is controlled by a temporal machinery optimizing the time of annual events (Bünning, 1960; Thomas, 1998). The use of daylength (or nightlength) allows organisms to assess the season- of-year and to process relatively predictable annual variations with a reliable envi- ronmental cue – the photoperiod. Our knowledge about this phenomenon is abundant, yet no ideal molecular model exists to explain the mechanisms. There have been re- cent studies of photoperiodic gene regulation in the plant model Arabidopsis, which, compared to Neurospora crassa, is more complicated for studying photoperiodism at the molecular level. We assumed that the circadian model organism of the simple fungus Neurospora crassa is a potential for the question: 1). The circadian clock is well described in the molecular and genetic levels (e.g., the critical clock gene frq, the blue light photoreceptor WC-1, the basic transcription/translation feedback, etc.); 2). Its relatively small genome (43Mb) has been published (Galagan, et al., 2003); 3). There are wealth of genetic and biochemical tools available.
Figure 2.—Levels of frq mRNA and protein in strains containing various wc-2 alleles following a light pulse (LP). (A) Northern blots of frq mRNA in strains containing wc-2 alleles ER33, ER24, ER44, and wild type. Ethidium bromide (EtBr) staining of rRNA bands on the blotted membrane is shown below the Northern blot. Cultures were treated such that at harvesting all cultures had been grown for a similar length of time. DD con- trols were treated identically to the LP samples, but received no LP. Time in DD varied for each strain dependent on strain period length such that the time of LP fell at CT18. Wild type was held in DD for 28 hr, ER24 for 37 hr, and ER33 and ER44, which are arrhythmic, for the same length of time as wild type. Also included is an ER24 DD28 control (the first ER24 DD sample). All samples were grown at 25⬚. Light pulses were given to groups of four cultures and were stag- gered by 3 min for logistical reasons; thus each lane represents RNA from an individual culture, but the samples for ER33 and WT are duplicated on the left and right blots as reference samples. Due to the high level of variability in amplitude of the response, LP samples are shown in tripli- cate. (B) Western blot of FRQ in strains con- taining wc-2 alleles ER33, ER44, ER24, and wild type. Two different exposures are shown to reveal FRQ in DD controls. The amido black-stained membrane is shown below the FRQ blots. Cultures were treated as in A, but tissue was harvested 4 hr after the LP. Each lane represents protein from an individual culture. (C) Densitometric analysis of data in A, relevant samples from Figure 4A and other experiments plotting the amount of frqmRNA normalized against EtBr-stained rRNA. (D) Densito- metric analysis of data in B, relevant LP samples from Figure 4B and other experiments plotting the amount of FRQ normalized against amido black-stained total protein. For C and D, n ⫽ 3–5 for most samples and values shown are the mean ⫾ SEM. DD samples were quantified from longer exposures of the blots shown and then normalized to reference samples. Solid bars correspond to DD, hatched bars to LP.