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BackgroundOverdose Fatality Review (OFR) is an important public health tool for shaping overdose prevention strategies in communities. However, OFR teams review only a few cases at a time, which typically represent a small fraction of the total fatalities in their jurisdiction. Such limited review could result in a partial understanding of local overdose patterns, leading to policy recommendations that do not fully address the broader community needs. ObjectiveThis study explored the potential to enhance conventional OFRs with a data dashboard, incorporating visualizations of touchpoints—events that precede overdoses—to highlight prevention opportunities. MethodsWe conducted 2 focus groups and a survey of OFR experts to characterize their information needs and design a real-time dashboard that tracks and measures decedents’ past interactions with services in Indiana. Experts (N=27) were engaged, yielding insights on essential data features to incorporate and providing feedback to guide the development of visualizations. ResultsThe findings highlighted the importance of showing decedents’ interactions with health services (emergency medical services) and the justice system (incarcerations). Emphasis was also placed on maintaining decedent anonymity, particularly in small communities, and the need for training OFR members in data interpretation. The developed dashboard summarizes key touchpoint metrics, including prevalence, interaction frequency, and time intervals between touchpoints and overdoses, with data viewable at the county and state levels. In an initial evaluation, the dashboard was well received for its comprehensive data coverage and its potential for enhancing OFR recommendations and case selection. ConclusionsThe Indiana touchpoints dashboard is the first to display real-time visualizations that link administrative and overdose mortality data across the state. This resource equips local health officials and OFRs with timely, quantitative, and spatiotemporal insights into overdose risk factors in their communities, facilitating data-driven interventions and policy changes. However, fully integrating the dashboard into OFR practices will likely require training teams in data interpretation and decision-making.

Mapping the chromosomal locations of transcription factors, nucleosomes, histone modifications, chromatin remodeling enzymes, chaperones, and polymerases is one of the key tasks of modern biology, as evidenced by the Encyclopedia of DNA Elements (ENCODE) Project. To this end, chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is the standard methodology. Mapping such protein-DNA interactions in vivo using ChIP-seq presents multiple challenges not only in sample preparation and sequencing but also for computational analysis. Here, we present step-by-step guidelines for the computational analysis of ChIP-seq data. We address all the major steps in the analysis of ChIP-seq data: sequencing depth selection, quality checking, mapping, data normalization, assessment of reproducibility, peak calling, differential binding analysis, controlling the false discovery rate, peak annotation, visualization, and motif analysis. At each step in our guidelines we discuss some of the software tools most frequently used. We also highlight the challenges and problems associated with each step in ChIP-seq data analysis. We present a concise workflow for the analysis of ChIP-seq data in Figure 1 that complements and expands on the recommendations of the ENCODE and modENCODE projects. Each step in the workflow is described in detail in the following sections.

Spider neurotoxins are commonly used as pharmacological tools and are a popular source of novel compounds with therapeutic and agrochemical potential. Since venom peptides are inherently toxic, the host spider must employ strategies to avoid adverse effects prior to venom use. It is partly for this reason that most spider toxins encode a protective proregion that upon enzymatic cleavage is excised from the mature peptide. In order to identify the mature toxin sequence directly from toxin transcripts, without resorting to protein sequencing, the propeptide cleavage site in the toxin precursor must be predicted bioinformatically. We evaluated different machine learning strategies (support vector machines, hidden Markov model and decision tree) and developed an algorithm (SpiderP) for prediction of propeptide cleavage sites in spider toxins. Our strategy uses a support vector machine (SVM) framework that combines both local and global sequence information. Our method is superior or comparable to current tools for prediction of propeptide sequences in spider toxins. Evaluation of the SVM method on an independent test set of known toxin sequences yielded 96% sensitivity and 100% specificity. Furthermore, we sequenced five novel peptides (not used to train the final predictor) from the venom of the Australian tarantula Selenotypus plumipes to test the accuracy of the predictor and found 80% sensitivity and 99.6% 8-mer specificity. Finally, we used the predictor together with homology information to predict and characterize seven groups of novel toxins from the deeply sequenced venom gland transcriptome of S. plumipes, which revealed structural complexity and innovations in the evolution of the toxins. The precursor prediction tool (SpiderP) is freely available on ArachnoServer (http://www.arachnoserver.org/spiderP.html), a web portal to a comprehensive relational database of spider toxins. All training data, test data, and scripts used are available from the SpiderP website.

AbstractObjective:FlexTouch* (FT) is a new prefilled insulin pen with no push-button extension at any set dose and a low activation force that is designed to improve ease of use and insulin administration. This paper reports the results of two usability studies assessing perceptions of FT compared with KwikPen† (KP)and SoloStar‡ (SS) among healthcare professionals (HCPs; both physicians and nurses) and people with diabetes (both insulin pen-experienced and insulin pen-naïve). *FlexTouch is a registered trade name of Novo Nordisk A/S, Bagsvaerd, Denmark.†KwikPen is a registered trade name of Eli Lilly & Co., Indianapolis, IN, USA.‡SoloStar is a registered trade name of Sanofi, Paris, France.Research design and methods:Participants were randomly assigned to start with FT or KP in one study and FT or SS in the other. Participants performed injections at different doses (20, 40 and 60 International Units [IU] in the FT vs. KP study or 20, 40 and 80 IU in the FT vs. SS study) into a foam cushion before answering questions on ease of use, teaching and learning, confidence and preference.Results:A total of 59 people with diabetes and 61 HCPs took part in the FT vs. SS study, and 79 people with diabetes and 81 HCPs took part in the FT vs. KP study. Considerably more patients and HCPs rated FT as very/fairly easy to inject with than KP or SS, particularly at the maximum dose (≥80% vs. ≤38% and ≤23%, respectively), and more were very/rather confident in the ability to manage daily insulin injections with FT than KP or SS. Overall, FT was rated significantly higher for ease of teaching and learning to use than KP or SS (all p < 0.001 vs. FT), and was preferred for teaching and learning compared with KP or SS (≥39% vs. ≤4% and ≤6%, respectively). More patients and HCPs would recommend FT (≥95%) than KP (≤72%) or SS (≤71%). The same pattern was generally seen across physicians, nurses, insulin pen-experienced and pen-naïve participants.Conclusions:The findings suggest that devices such as FT are easy to use and can be prescribed with relatively few training needs, which may improve ease of insulin initiation, increase pen use, and ultimately improve treatment adherence. A limitation of the usability questionnaire used in this study is that it did not assess the factors that influence preference. Further analyses could be conducted to determine the factors that appeal to different users. [ABSTRACT FROM AUTHOR]

AbstractBackground:The purpose of this study was to evaluate new features and performance of the SEVEN®PLUS System (DexCom, Inc., San Diego, CA), a real-time continuous glucose monitoring (CGM) device. This study is the first to evaluate the SEVEN PLUS device.Methods:Fifty-three subjects were enrolled at three U.S. centers; 43 (81%) of the subjects had type 1 diabetes mellitus, and 10 (19%) had insulin-requiring type 2 diabetes mellitus. Subjects inserted and wore either one or two sensors for 7 days. A subgroup (n= 18) wore two sensors to track precision. Subjects participated in one 8-h in-clinic session with blood draws every 15 min on study Day 1, 4, or 7 to collect laboratory reference YSI instrument (YSI, Yellow Springs, OH) and self-measured plasma glucose (SMPG) reference measurements. For the remainder of the week, CGM was used as an adjunct to SMPG during home use.Results:The overall median absolute relative difference (ARD) versus YSI was 13.0%. Zones A and B of the Clarke Error Grid of CGM measurements were 73.8% and 22.1%, respectively. Precision ARD was 15.3 ± 6.2% (mean ± SD). The median ARD versus SMPG was 12.1%. Sensor life (89% lasted 7 days) was improved compared to the SEVEN device. The lag time obtained with various statistical measures between CGM and YSI were similar and estimated as a median of 8 min (interquartile range, 11 min) using the Pearson correlation coefficient. No serious adverse events or infectious complications were reported.Conclusions:The performance of this new system compares favorably to the previous SEVEN device in terms of accuracy, precision, lag time, sensor life, and rate of data capture. [ABSTRACT FROM AUTHOR]

AbstractObjective:We evaluated effects of unmasking of continuous display of continuous glucose monitoring (CGM) on quality of glycemic control and glycemic variability.Methods:We reanalyzed CGM data from 85 patients using a 7-day glucose sensor. Glucose values were “masked” during the first week but “unmasked” during the next 2 weeks. We evaluated 48 criteria for quality of glycemic control, including mean glucose, SD, percentage of values within-, above- or below- specified ranges, Schlichtkrull's M100index, mean amplitude of glycemic excursion (MAGE), mean of daily differences (MODD), the Jindex, “Index of Glycemic Control” (IGC), Hyperglycemia Index, Hypoglycemia Index, High Blood Glucose Index (HBGI), Low Blood Glucose Index (LBGI), average daily risk range (ADRR), GRADE scores, and CONGAn. We calculated SD values between daily means, between days-within time points, within days, between time points (for the average glucose profile for several days), and within series for time segments of arbitrary length.Results:Unmasking CGM displays resulted in rapid, highly statistically significant improvement in 29 indices, including percentage within, percentage above, and percentage below target range, mean glucose, SD, SD of daily means, MODD, M100, IGC, GRADE, HBGI, and Jindex. Both hyperglycemia and hypoglycemia improved during the first week after unmasking; further improvement in hypoglycemia was seen during the following week. Results obtained using multiple criteria were consistent and highly correlated.Conclusions:Continuous access to display of CGM sensors dramatically improved 29 indices of glycemic control and glycemic variability. [ABSTRACT FROM AUTHOR]

ABSTRACTObjective:To compare safety and efficacy of biphasic insulin aspart 70/30 (BIAsp 30) with exenatide in subjects with type 2 diabetes mellitus (T2DM) not achieving glycemic targets with metformin and sulfonylurea in a randomized, open-label, 24-week trial.Research design and methods:Subjects (N  372, T2DM > 6 months, age ≥ 18 and ≤ 80 years, HbA1c ≥ 8, insulin naive not achieving glycaemic targets, receiving metformin and sulfonylurea) were randomized 1: 1: 1 to receive either BIAsp 30 QD (12 U before supper); BIAsp 30 BID (12 U divided equally between pre-breakfast and pre-supper); or exenatide (5 µg BID for 4 weeks and 10 µg BID thereafter). Efficacy (HbA1c, fasting plasma glucose [FPG]) and safety (adverse events and hypoglycemic episodes) were assessed.Results:Glycemic control achieved with both BIAsp 30 BID and BIAsp 30 QD was superior to that with exenatide (BIAsp 30 BID-exenatide: HbA1c difference −0.91 [95 CI: −1.23 to −0.59] and BIAsp 30 QD-exenatide: difference: −0.67 [95 CI: −0.99 to −0.34]). At the end of the study, more subjects achieved HbA1c < 7 and ≤ 6.5 in the BIAsp 30 BID group than in the exenatide group (HbA1c < 7: 37 vs. 20, p  0.0060; HbA1c ≤ 6.5: 25 vs. 8, p  0.0004, respectively). Combined hypoglycemic episodes (major, minor, symptoms only) were reported by 56, 61, and 29 of the subjects in the BIAsp 30 QD, BIAsp 30 BID, and exenatide groups, respectively. Weight gain was observed in the BIAsp 30 group (BIAsp 30 QD: 2.85 kg, BIAsp 30 BID: 4.08 kg) and weight loss was observed in the exenatide group (−1.96 kg). Nausea or vomiting was responsible for discontinuation of seven subjects in the exenatide group and one subject in the BIAsp 30 BID group.Conclusions:Significantly more T2DM patients (poorly controlled with combination metformin/sulfonylurea) achieved glycemic goals when treated with BIAsp 30 than with exenatide. The high baseline HbA1cvalues (∼10.2) and the long duration of diabetes (∼9 years) suggests that some subjects may have been in an advanced stage of their diabetes and may not have had sufficient β-cell function for a GLP-1 mimetic to be effective. The insulin-treated groups had more minor hypoglycemic events and weight gain but less gastrointestinal side-effects. In summary, BIAsp 30 was more efficacious in helping patients with high baseline HbA1cachieve glycemic goals.Clinical trial registration: www.clinicaltrials.gov, NCT00097877 [ABSTRACT FROM AUTHOR]