A novel method for measuring patients' adherence to insulin dosing guidelines: introducing indicators of adherence

<p>Abstract</p> <p>Background</p> <p>Diabetic type 1 patients are often advised to use dose adjustment guidelines to calculate their doses of insulin. Conventional methods of measuring patients' adherence are not applicable to these cases, because insulin doses are not determined in advance. We propose a method and a number of indicators to measure patients' conformance to these insulin dosing guidelines.</p> <p>Methods</p> <p>We used a database of logbooks of type 1 diabetic patients who participated in a summer camp. Patients used a guideline to calculate the doses of insulin lispro and glargine four times a day, and registered their injected doses in the database. We implemented the guideline in a computer system to calculate recommended doses. We then compared injected and recommended doses by using five indicators that we designed for this purpose: absolute agreement (AA): the two doses are the same; relative agreement (RA): there is a slight difference between them; extreme disagreement (ED): the administered and recommended doses are merely opposite; Under-treatment (UT) and over-treatment (OT): the injected dose is not enough or too high, respectively. We used weighted linear regression model to study the evolution of these indicators over time.</p> <p>Results</p> <p>We analyzed 1656 insulin doses injected by 28 patients during a three weeks camp. Overall indicator rates were AA = 45%, RA = 30%, ED = 2%, UT = 26% and OT = 30%. The highest rate of absolute agreement is obtained for insulin glargine (AA = 70%). One patient with alarming behavior (AA = 29%, RA = 24% and ED = 8%) was detected. The monitoring of these indicators over time revealed a crescendo curve of adherence rate which fitted well in a weighted linear model (slope = 0.85, significance = 0.002). This shows an improvement in the quality of therapeutic decision-making of patients during the camp.</p> <p>Conclusion</p> <p>Our method allowed the measurement of patients' adherence to their insulin adjustment guidelines. The indicators that we introduced were capable of providing quantitative data on the quality of patients' decision-making for the studied population as a whole, for each individual patient, for all injections, and for each time of injection separately. They can be implemented in monitoring systems to detect non-adherent patients.</p

Ancient Migratory Events in the Middle East: New Clues from the Y-Chromosome Variation of Modern Iranians

Knowledge of high resolution Y-chromosome haplogroup diversification within Iran provides important geographic context regarding the spread and compartmentalization of male lineages in the Middle East and southwestern Asia. At present, the Iranian population is characterized by an extraordinary mix of different ethnic groups speaking a variety of Indo-Iranian, Semitic and Turkic languages. Despite these features, only few studies have investigated the multiethnic components of the Iranian gene pool. In this survey 938 Iranian male DNAs belonging to 15 ethnic groups from 14 Iranian provinces were analyzed for 84 Y-chromosome biallelic markers and 10 STRs. The results show an autochthonous but non-homogeneous ancient background mainly composed by J2a sub-clades with different external contributions. The phylogeography of the main haplogroups allowed identifying post-glacial and Neolithic expansions toward western Eurasia but also recent movements towards the Iranian region from western Eurasia (R1b-L23), Central Asia (Q-M25), Asia Minor (J2a-M92) and southern Mesopotamia (J1-Page08). In spite of the presence of important geographic barriers (Zagros and Alborz mountain ranges, and the Dasht-e Kavir and Dash-e Lut deserts) which may have limited gene flow, AMOVA analysis revealed that language, in addition to geography, has played an important role in shaping the nowadays Iranian gene pool. Overall, this study provides a portrait of the Y-chromosomal variation in Iran, useful for depicting a more comprehensive history of the peoples of this area as well as for reconstructing ancient migration routes. In addition, our results evidence the important role of the Iranian plateau as source and recipient of gene flow between culturally and genetically distinct population

The Preclinical Natural History of Serous Ovarian Cancer: Defining the Target for Early Detection

Pat Brown and colleagues carry out a modeling study and define what properties a biomarker-based screening test would require in order to be clinically useful

Qualitative study on the implementation of professional pharmacy services in Australian community pharmacies using framework analysis

Abbreviations: BCT, Behavioural change techniques taxonomy; BCW, Behavioural change wheel; CFIR, Consolidated framework for implementation research; EPOC, Cochrane effective practice and organisation of care; FISpH, Framework for the implementation of services in pharmacy; GIF, Generic implementation framework; KPI, Key performance indicator; TDF, Theoretical domains frameworkBackground: Multiple studies have explored the implementation process and influences, however it appears there is no study investigating these influences across the stages of implementation. Community pharmacy is attempting to implement professional services (pharmaceutical care and other health services). The use of implementation theory may assist the achievement of widespread provision, support and integration. The objective was to investigate professional service implementation in community pharmacy to contextualise and advance the concepts of a generic implementation framework previously published. Methods: Purposeful sampling was used to investigate implementation across a range of levels of implementation in community pharmacies in Australia. Twenty-five semi-structured interviews were conducted and analysed using a framework methodology. Data was charted using implementation stages as overarching themes and each stage was thematically analysed, to investigate the implementation process, the influences and their relationships. Secondary analyses were performed of the factors (barriers and facilitators) using an adapted version of the Consolidated Framework for Implementation Research (CFIR), and implementation strategies and interventions, using the Expert Recommendations for Implementing Change (ERIC) discrete implementation strategy compilation. Results: Six stages emerged, labelled as development or discovery, exploration, preparation, testing, operation and sustainability. Within the stages, a range of implementation activities/steps and five overarching influences (pharmacys' direction and impetus, internal communication, staffing, community fit and support) were identified. The stages and activities were not applied strictly in a linear fashion. There was a trend towards the greater the number of activities considered, the greater the apparent integration into the pharmacy organization. Implementation factors varied over the implementation stages, and additional factors were added to the CFIR list and definitions modified/contextualised for pharmacy. Implementation strategies employed by pharmacies varied widely. Evaluations were lacking. Conclusions: The process of implementation and five overarching influences of professional services implementation in community pharmacy have been outlined. Framework analysis revealed, outside of the five overarching influences, factors influencing implementation varied across the implementation stages. It is proposed at each stage, for each domain, the factors, strategies and evaluations should be considered. The Framework for the Implementation of Services in Pharmacy incorporates the contextualisation of implementation science for pharmacy.The study was funded as part of a University of Technology Sydney (UTS) Research Excellence Scholarship (RES), comprising of an Australian Postgraduate Award (APA) Scholarship funded by the Australian Government, plus a Top-up funded by the University of Technology Sydney, received from the primary author (JCM)

Effect of Acinetobacter sp on Metalaxyl Degradation and Metabolite Profile of Potato Seedlings (Solanum tuberosum L.) Alpha Variety

One of the most serious diseases in potato cultivars is caused by the pathogen Phytophthora infestans, which affects leaves, stems and tubers. Metalaxyl is a fungicide that protects potato plants from Phytophthora infestans. In Mexico, farmers apply metalaxyl 35 times during the cycle of potato production and the last application is typically 15 days before harvest. There are no records related to the presence of metalaxyl in potato tubers in Mexico. In the present study, we evaluated the effect of Acinetobacter sp on metalaxyl degradation in potato seedlings. The effect of bacteria and metalaxyl on the growth of potato seedlings was also evaluated. A metabolite profile analysis was conducted to determine potential molecular biomarkers produced by potato seedlings in the presence of Acinetobacter sp and metalaxyl. Metalaxyl did not affect the growth of potato seedlings. However, Acinetobacter sp strongly affected the growth of inoculated seedlings, as confirmed by plant length and plant fresh weights which were lower in inoculated potato seedlings (40% and 27%, respectively) compared to the controls. Acinetobacter sp also affected root formation. Inoculated potato seedlings showed a decrease in root formation compared to the controls. LC-MS/MS analysis of metalaxyl residues in potato seedlings suggests that Acinetobacter sp did not degrade metalaxyl. GC–TOF–MS platform was used in metabolic profiling studies. Statistical data analysis and metabolic pathway analysis allowed suggesting the alteration of metabolic pathways by both Acinetobacter sp infection and metalaxyl treatment. Several hundred metabolites were detected, 137 metabolites were identified and 15 metabolic markers were suggested based on statistical change significance found with PLS-DA analysis. These results are important for better understanding the interactions of putative endophytic bacteria and pesticides on plants and their possible effects on plant metabolism

Crosstalks between Myo-Inositol Metabolism, Programmed Cell Death and Basal Immunity in Arabidopsis

BACKGROUND: Although it is a crucial cellular process required for both normal development and to face stress conditions, the control of programmed cell death in plants is not fully understood. We previously reported the isolation of ATXR5 and ATXR6, two PCNA-binding proteins that could be involved in the regulation of cell cycle or cell death. A yeast two-hybrid screen using ATXR5 as bait captured AtIPS1, an enzyme which catalyses the committed step of myo-inositol (MI) biosynthesis. atips1 mutants form spontaneous lesions on leaves, raising the possibility that MI metabolism may play a role in the control of PCD in plants. In this work, we have characterised atips1 mutants to gain insight regarding the role of MI in PCD regulation. METHODOLOGY/PRINCIPAL FINDINGS: - lesion formation in atips1 mutants depends of light intensity, is due to PCD as evidenced by TUNEL labelling of nuclei, and is regulated by phytohormones such as salicylic acid - MI and galactinol are the only metabolites whose accumulation is significantly reduced in the mutant, and supplementation of the mutant with these compounds is sufficient to prevent PCD - the transcriptome profile of the mutant is extremely similar to that of lesion mimic mutants such as cpr5, or wild-type plants infected with pathogens. CONCLUSION/SIGNIFICANCE: Taken together, our results provide strong evidence for the role of MI or MI derivatives in the regulation of PCD. Interestingly, there are three isoforms of IPS in Arabidopsis, but AtIPS1 is the only one harbouring a nuclear localisation sequence, suggesting that nuclear pools of MI may play a specific role in PCD regulation and opening new research prospects regarding the role of MI in the prevention of tumorigenesis. Nevertheless, the significance of the interaction between AtIPS1 and ATXR5 remains to be established

Conserved genes and pathways in primary human fibroblast strains undergoing replicative and radiation induced senescence

Additional file 3: Figure S3. Regulation of genes of Arrhythmogenic right ventricular cardiomyopathy pathway during senescence induction in HFF strains Genes of the “Arrhythmogenic right ventricular cardiomyopathy” pathway which are significantly up- (green) and down- (red) regulated (log2 fold change >1) during irradiation induced senescence (120 h after 20 Gy irradiation) in HFF strains. Orange color signifies genes which are commonly up-regulated during both, irradiation induced and replicative senescence

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children &lt;18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p&lt;0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p&lt;0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p&lt;0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer