bluuebunny/crossref_metadata_2025_split huggingface dataset:
A scoping review of mHealth technologies for opioid overdose prevention, detection and response
Authors: Tas Basak , Lawn Will , Traykova Elena V. , Evans Rebecca A. S. , Murvai Barbara , Walker Hollie , Strang John 
Published: March 2023

AbstractIssuesOpioid overdose kills over 100,000 people each year globally. Mobile health (mHealth) technologies and devices, including wearables, with the capacity to prevent, detect or respond to opioid overdose exist in early form, or could be re‐purposed or designed. These technologies may particularly help those who use alone. For technologies to be successful, they must be effective and acceptable to the at‐risk population. The aim of this scoping review is to identify published studies on mHealth technologies that attempt to prevent, detect or respond to opioid overdose.ApproachA systematic scoping review of literature was conducted up to October 2022. APA PsychInfo, Embase, Web of Science and Medline databases were searched. Inclusion criteria: articles had to report on (i) mHealth technologies that deal with (ii) opioid (iii) overdose.Key FindingsA total of 348 records were identified, with 14 studies eligible for this review across four domains: (i) technologies that require intervention/response from others (four); (ii) devices that use biometric data to detect overdose (five); (iii) devices that automatically respond to an overdose with administration of an antidote (three); (iv) acceptability/willingness to use overdose‐related technologies/devices (five).ImplicationsThere are multiple routes in which these technologies may be deployed, but several factors impact acceptability (e.g., discretion or size) and accuracy of detection (e.g., sensitive parameter/threshold with low false positive rate).ConclusionmHealth technologies for opioid overdose may play a crucial role in responding to the ongoing global opioid crises. This scoping review identifies vital research that will determine the future success of these technologies.
From the tobacco industry's uses of science for public relations purposes to the alcohol industry: Tobacco industry documents study
Authors: Bartlett Andrew , Garry Jack , McCambridge Jim 
Published: March 2023

AbstractIntroductionAssociates for Research in Substances of Enjoyment (ARISE) was formed by tobacco companies in the late 1980s designed to counter public health policy development. This study examines the alcohol content of ARISE and the contribution of ARISE to alcohol industry activities in a key period in the globalisation of the alcohol industry, generating insights into the inter‐relationships between the tobacco and alcohol industries in their involvements in policy‐oriented science.MethodsWe systematically searched the UCSF Truth Tobacco Documents Library for information about ARISE, alcohol and the alcohol industry. This material was supplemented with an analysis of the contributions by ARISE associates to one volume in the International Center for Alcohol Policies (ICAP) book series on alcohol and pleasure.ResultsARISE placed nicotine alongside caffeine, chocolate and other foods, and alcohol as treats which brought pleasure and other benefits. Alcohol was thus intrinsic to the ARISE project for the tobacco industry. This study shows that at a formative moment in the mid‐1990s the major alcohol companies took advantage of the intellectual inheritance and personnel provided by the tobacco industry when establishing ICAP. Key to this was an ICAP conference that resulted in Alcohol and pleasure: A health perspective (1999).Discussion and ConclusionsNot only did ARISE use alcohol to play a supporting role in a sophisticated tobacco industry strategy, the alcohol industry engaged with ARISE as part of its own strategy. This shows the importance of careful attention to corporate activities on the fringes of peer‐reviewed science.
Access to legal cannabis market in Canada over the four years following non‐medical cannabis legalisation
Authors: Myran Daniel Thomas , Friesen Erik Loewen , Dickson Sarah , Konikoff Lauren , Arora Gaurav , Tanuseputro Peter 
Published: March 2023

AbstractIntroductionAn increasing number of countries are inthe process of legalising non‐medical cannabis. We described how the legal market has changed over the first 4 years following legalisation in Canada.MethodsWe collected longitudinal data on operating status and location of all legal cannabis stores in Canada for the first 4 years following legalisation. We examined per capita stores and sales, store closures, and the drive time between stores and each neighbourhood in Canada. We compared measures between public and private retail systems.ResultsFour years after legalisation, there were 3305 cannabis stores open in Canada (10.6 stores per 100,000 individuals aged 15+ years). Canadians spent $11.85CAD a month on cannabis per individual aged 15+ years, and 59% of neighbourhoods were within a 5‐minute drive of a cannabis store. Over 4 years, per capita stores and per capita sales increased each year by an average of 122.3% and 91.7%, respectively, with larger increases in private versus public systems (4.01 times greater for per capita stores and 2.46 times greater for per capita sales). The annual increase in per capita stores and sales during the first 3 years was 6.0 and 15.5 times greater, respectively, than the increase in the fourth year following legalisation. Over 4 years, 7% of retail store locations permanently closed.Discussion and ConclusionThe legal cannabis market in Canada expanded enormously over the first 4 years following legalisation, with considerable variation in access between jurisdictions. The rapid retail expansion has implications for evaluation of health impacts of non‐medical legalisation.
Identification of patients with epilepsy using automated electronic health records phenotyping
Authors: Fernandes Marta , Cardall Aidan , Jing Jin , Ge Wendong , Moura Lidia M. V. R. , Jacobs Claire , McGraw Christopher , Zafar Sahar F. , Westover M. Brandon 
Published: March 2023

AbstractObjectiveUnstructured data present in electronic health records (EHR) are a rich source of medical information; however, their abstraction is labor intensive. Automated EHR phenotyping (AEP) can reduce the need for manual chart review. We present an AEP model that is designed to automatically identify patients diagnosed with epilepsy.MethodsThe ground truth for model training and evaluation was captured from a combination of structured questionnaires filled out by physicians for a subset of patients and manual chart review using customized software. Modeling features included indicators of the presence of keywords and phrases in unstructured clinical notes, prescriptions for antiseizure medications (ASMs), International Classification of Diseases (ICD) codes for seizures and epilepsy, number of ASMs and epilepsy‐related ICD codes, age, and sex. Data were randomly divided into training (70%) and hold‐out testing (30%) sets, with distinct patients in each set. We trained regularized logistic regression and an extreme gradient boosting models. Model performance was measured using area under the receiver operating curve (AUROC) and area under the precision–recall curve (AUPRC), with 95% confidence intervals (CI) estimated via bootstrapping.ResultsOur study cohort included 3903 adults drawn from outpatient departments of nine hospitals between February 2015 and June 2022 (mean age = 47 ± 18 years, 57% women, 82% White, 84% non‐Hispanic, 70% with epilepsy). The final models included 285 features, including 246 keywords and phrases captured from 8415 encounters. Both models achieved AUROC and AUPRC of 1 (95% CI = .99–1.00) in the hold‐out testing set.SignificanceA machine learning‐based AEP approach accurately identifies patients with epilepsy from notes, ICD codes, and ASMs. This model can enable large‐scale epilepsy research using EHR databases.
Baseline clinical, hormonal and molecular markers associated with clinical response to IL‐23 antagonism in hidradenitis suppurativa: A prospective cohort study
Authors: Flora A. , Kozera E. K. , Jepsen R. , Gill K. , Xu J. , Frew J. W. 
Published: March 2023

AbstractHidradenitis suppurativa is a complex inflammatory disease in which predicting therapeutic response remains challenging. IL‐23 interacts with sex hormones but the relationships between the two in HS remains uninvestigated. To assess whether baseline clinical, hormonal or molecular markers are associated with clinical response to IL‐23 antagonism with risankizumab in hidradenitis suppurativa. Twenty six individuals with Hurley stage 2/3 disease were administered risankizumab 150 mg Week 0, 4, 12. Baseline sex hormones and skin biopsies were taken. Clinical response at Week 16 assessed by the HiSCR, and differences between responders and non‐responders assessed. Eighteen of 26 participants achieved HiSCR50 at week 16 (69.2%). Clinical response to IL‐23 antagonism was associated with male gender, elevated total serum testosterone and decreased levels of FSH. Stratification by clinical responders/nonresponders identified differentially expressed genes including PLPP4 and MAPK10. Immunohistochemistry identified elevated numbers of CD11c, IL‐17A and IL‐17F positive cells compared to nonresponders. CD11c + cells significantly correlated with serum levels of total testosterone and inversely correlated with serum FSH. Clinical response to IL‐23 antagonism in HS is associated with serum sex hormones, Th17 polarized inflammation in lesional tissue and CD11c + cells. These potential therapeutic biomarkers require further validation in larger cohorts but may suggest potential targeted HS therapy.
Microbial necromass under global change and implications for soil organic matter
Authors: Hu Junxi , Du Meilin , Chen Jun , Tie Liehua , Zhou Shixing , Buckeridge Kate M. , Cornelissen J. Hans C. , Huang Congde , Kuzyakov Yakov 
Published: March 2023

AbstractMicrobial necromass is an important source and component of soil organic matter (SOM), especially within the most stable pools. Global change factors such as anthropogenic nitrogen (N), phosphorus (P), and potassium (K) inputs, climate warming, elevated atmospheric carbon dioxide (eCO2), and periodic precipitation reduction (drought) strongly affect soil microorganisms and consequently, influence microbial necromass formation. The impacts of these global change factors on microbial necromass are poorly understood despite their critical role in the cycling and sequestration of soil carbon (C) and nutrients. Here, we conducted a meta‐analysis to reveal general patterns of the effects of nutrient addition, warming, eCO2, and drought on amino sugars (biomarkers of microbial necromass) in soils under croplands, forests, and grasslands. Nitrogen addition combined with P and K increased the content of fungal (+21%), bacterial (+22%), and total amino sugars (+9%), consequently leading to increased SOM formation. Nitrogen addition alone increased solely bacterial necromass (+10%) because the decrease of N limitation stimulated bacterial more than fungal growth. Warming increased bacterial necromass, because bacteria have competitive advantages at high temperatures compared to fungi. Other global change factors (P and NP addition, eCO2, and drought) had minor effects on microbial necromass because of: (i) compensation of the impacts by opposite processes, and (ii) the short duration of experiments compared to the slow microbial necromass turnover. Future studies should focus on: (i) the stronger response of bacterial necromass to N addition and warming compared to that of fungi, and (ii) the increased microbial necromass contribution to SOM accumulation and stability under NPK fertilization, and thereby for negative feedback to climate warming.
Incidental left atrial appendage isolation after catheter ablation of persistent atrial fibrillation: Mechanisms and long‐term risk of thromboembolism
Authors: Ghannam Michael , Jongnarangsin Krit , Emami Hamed , Yokokawa Miki , Liang Jackson J. , Saeed Mohammed , Oral Hakan , Morady Fred , Chugh Aman 
Published: March 2023

AbstractIntroductionIncidental left atrial appendage (LAA) isolation may occur during radiofrequency ablation of persistent atrial fibrillation (AF). The study aims to describe the mechanisms and long‐term thromboembolic risk related to incidental LAA isolation.MethodsPatients who experienced incidental LAA isolation after AF ablation were included. Culprit sites where ablation resulted in LAA isolation were identified. Thromboembolic risk despite oral anticoagulation (OAC) was compared to that in a propensity‐matched control group without LAA isolation.ResultsForty‐one patients with LAA isolation, and 82 matched patients without LAA isolation were included. The patient age, ejection fraction, LA diameter, and CHA2DS2‐VASc score were 64 ± 11 years, 55 ± 12%, 45.0 ± 7 mm and 2.62 ± 1.5, respectively. Culprit sites included the LAA base, mitral isthmus, inferior LA, Bachmann′s bundle, coronary sinus, and Marshall vein. After 4.2 ± 3.6 years follow‐up, thromboembolism occurred in 7 of 41 patients (17%) with LAA isolation versus 3 of 82 patients (4%) without isolation (log rank p < .009, HR 5.14, 95% CI [1.32–19.94], p = .02). Patients with and without thromboembolism had similar CHA2DS2‐VASc scores (2.65 ± 1.3 vs. 2.71 ± 0.76, p = .89). Thromboembolism occurred during noncompliance with or temporary discontinuation of OAC in four of the seven patients.ConclusionsIncidental LAA isolation may occur during ablation of atrial arrhythmias in the vicinity of, or even at sites remote from the appendage. Patients with incidental LAA isolation had higher rates of thromboembolism compared to patients without isolation. Since thromboembolism may occur despite prescription for OAC, the risks of LAA isolation must be weighed against clinical benefit and appendage occlusion devices should be considered in vulnerable patients.
Atrial fibrillation ablation outcome prediction with a machine learning fusion framework incorporating cardiac computed tomography
Authors: Razeghi Orod , Kapoor Ridhima , Alhusseini Mahmood I. , Fazal Muhammad , Tang Siyi , Roney Caroline H. , Rogers Albert J. , Lee Anson , Wang Paul J. , Clopton Paul , Rubin Daniel L. , Narayan Sanjiv M. , Niederer Steven , Baykaner Tina 
Published: March 2023

AbstractBackgroundStructural changes in the left atrium (LA) modestly predict outcomes in patients undergoing catheter ablation for atrial fibrillation (AF). Machine learning (ML) is a promising approach to personalize AF management strategies and improve predictive risk models after catheter ablation by integrating atrial geometry from cardiac computed tomography (CT) scans and patient‐specific clinical data. We hypothesized that ML approaches based on a patient's specific data can identify responders to AF ablation.MethodsConsecutive patients undergoing AF ablation, who had preprocedural CT scans, demographics, and 1‐year follow‐up data, were included in the study for a retrospective analysis. The inputs of models were CT‐derived morphological features from left atrial segmentation (including the shape, volume of the LA, LA appendage, and pulmonary vein ostia) along with deep features learned directly from raw CT images, and clinical data. These were merged intelligently in a framework to learn their individual importance and produce the optimal classification.ResultsThree hundred twenty‐one patients (64.2 ± 10.6 years, 69% male, 40% paroxysmal AF) were analyzed. Post 10‐fold nested cross‐validation, the model trained to intelligently merge and learn appropriate weights for clinical, morphological, and imaging data (AUC 0.821) outperformed those trained solely on clinical data (AUC 0.626), morphological (AUC 0.659), or imaging data (AUC 0.764).ConclusionOur ML approach provides an end‐to‐end automated technique to predict AF ablation outcomes using deep learning from CT images, derived structural properties of LA, augmented by incorporation of clinical data in a merged ML framework. This can help develop personalized strategies for patient selection in invasive management of AF.
Associations of sleep quality with the skeletal muscle strength in patients with type 2 diabetes with poor glycemic control
Authors: Hayashi Takanori , Wada Nobuhiro , Kubota Tetsuya , Koizumi Chie , Sakurai Yoshitaka , Aihara Masakazu , Usami Satoshi , Yamauchi Toshimasa , Kubota Naoto 
Published: March 2023

ABSTRACTAims/IntroductionPatients with type 2 diabetes mellitus are reported to be at a high risk for sarcopenia, and are known to have a poorer sleep quality. However, the association between sleep quality and skeletal muscle in patients with type 2 diabetes mellitus is not yet precisely understood.Materials and MethodsA total of 110 inpatients with type 2 diabetes mellitus aged 40–90 years were enrolled. The sleep quality was assessed using the Pittsburgh sleep quality index (PSQI). Skeletal muscle mass was measured using bioelectrical impedance analysis. Muscle strength was evaluated by measuring the grip strength. We also performed dietary surveys and measurements of the plasma amino acid levels.ResultsA high total score on the PSQI was significantly associated with reduced muscle strength, and the association persisted even after adjustments for confounders. On the other hand, adjusted analysis did not reveal any significant associations between the PSQI total score and the skeletal muscle mass. In regard to the associations with subscores of the PSQI, the scores for sleep latency, sleep efficiency, and daytime dysfunction were significantly negatively associated with the muscle strength. Although poor sleep quality was associated with a high confectionery intake and low plasma arginine, citrulline, and ornithine levels, neither confectionery intake levels nor the plasma levels of these amino acids was associated with the muscle strength.ConclusionsOur study revealed a significant association between the sleep quality and muscle strength in patients with type 2 diabetes mellitus. These results suggest that poor sleep quality is an important risk factor for sarcopenia in patients with type 2 diabetes mellitus.
Evaluation of an early flood warning system in Bamako (Mali): Lessons learned from the flood of May 2019
Authors: Chahinian Nanée , Alcoba Matias , Dembélé Ndji dit Jacques , Cazenave Fréderic , Bouvier Christophe 
Published: March 2023

AbstractDevastating floods have plagued many West African cities in the past decades. In an attempt to reduce flood damage in Bamako (Mali), an early warning system (EWS) demonstrator (Raincell App) was developed for flash floods. On 16 May 2019, while the demonstrator was partially operational, an intense rainfall event led to devastating floods. We carried out an experience feedback on this flood event by comparing EWS simulations to the results of a field survey. Given the synoptic situation and the rapid development pattern of the storm, none of the global forecasting systems were able to foresee its occurrence and magnitude. The hydrological model developed as part of the demonstrator correctly identified most of the locations where overbank flow occurred. In the absence of data, the predicted discharge and volume values could not be validated. However, they are realistic based on the water levels reported in the Post‐Disaster Needs Assessment report. It would be advisable to couple it to a two‐dimensional hydraulic model and add discharge and water level monitoring to the already existing rainfall surveillance scheme to further improve the system's performance. Increasing the local population's awareness of the dangers of clogged waterways is also mandatory.
Orexin 2 receptor‐selective agonist danavorexton (TAK‐925) promotes wakefulness in non‐human primates and healthy individuals
Authors: Evans Rebecca , Kimura Haruhide , Nakashima Masato , Ishikawa Takashi , Yukitake Hiroshi , Suzuki Motohisa , Hazel James , Faessel Hélène , Wu Jingtao , Hang Yaming , Alexander Robert , Rosen Laura , Hartman Deborah S. , Ratti Emiliangelo 
Published: March 2023

SummaryThe orexin 2 receptor‐selective agonist danavorexton (TAK‐925) has been shown to produce wake‐promoting effects in wild‐type mice, narcolepsy‐model mice, and individuals with narcolepsy type 1 and type 2. Here, we report wake‐promoting effects of danavorexton in non‐human primates and healthy men during their sleep phase. Electroencephalogram analyses revealed that subcutaneous administration of danavorexton significantly increased wakefulness in common marmosets (p < 0.05 at 0.1 mg kg−1, and p < 0.001 at 1 mg kg−1 and 10 mg kg−1) and cynomolgus monkeys (p ≤ 0.05 at 1 mg kg−1 and 3 mg kg−1). In a phase 1b crossover, randomized, double‐blind, placebo‐controlled and active‐controlled study in sleep‐deprived healthy participants (ClinicalTrials.gov identifier: NCT03522506), modafinil 300 mg (used to demonstrate assay sensitivity) and continuous infusion of danavorexton 44 mg and danavorexton 112 mg showed statistically superior wake‐promoting effects to placebo (n = 18). Measured using the Maintenance of Wakefulness Test, mean (standard deviation) sleep latencies during infusion of danavorexton 44 mg, danavorexton 112 mg and placebo were 21.4 (8.9), 31.8 (3.2) and 9.2 (6.4) min, respectively. Least‐squares mean difference from placebo in average sleep latency was 16.8 min with danavorexton 44 mg and 30.2 min with danavorexton 112 mg (both p < 0.001). Karolinska Sleepiness Scale scores were statistically significantly lower (indicating decreased sleepiness) for participants receiving danavorexton than for those receiving placebo during infusion (danavorexton 44 mg, p = 0.010; danavorexton 112 mg, p < 0.001). Together, these results indicate that an orexin 2 receptor agonist increases wakefulness in non‐human primates and healthy individuals during their sleep phase.
Prediction of outcome after ligation or thin film banding of extrahepatic shunts, based on plasma albumin concentration and hematologic expression of 8 target genes in 85 dogs
Authors: van Blokland‐Post Krista , Weber Maarten F. , van Wolferen Monique E. , Penning Louis C. , van Sluijs Freek J. , Kummeling Anne 
Published: March 2023

AbstractBackgroundIn dogs with a congenital extrahepatic portosystemic shunt (EHPSS), outcome after surgical attenuation is difficult to predict.ObjectivesDevelop a minimally invasive test to predict outcome after surgical EHPSS attenuation and establish risk factors for postattenuation seizures (PAS).AnimalsEighty‐five client‐owned dogs referred for surgical attenuation of a single EHPSS.MethodsmRNA expression of 8 genes was measured in preoperatively collected venous blood samples. Outcome was determined at a median of 92 days (range, 26‐208) postoperatively by evaluating clinical performance, blood test results and abdominal ultrasonography. Multivariable logistic regression was used to construct models predicting clinical and complete recovery. The associations between putative predictors and PAS were studied using univariable analyses.ResultsFive of 85 dogs developed PAS. Risk factors were age, white blood cell (WBC) count and expression of hepatocyte growth factor activator and LysM and putative peptidoglycan‐binding domain‐containing protein 2. Clinical recovery was observed in 72 of 85 dogs and complete recovery in 51 of 80 dogs (median follow‐up, 92 days). The model predicting clinical recovery included albumin, WBC count, and methionine adenosyltransferase 2 alpha (MAT2α) expression, whereas the model predicting complete recovery included albumin, and connective tissue growth factor precursor and MAT2α expression. The areas under the receiver operating characteristic curves were 0.886 (95% confidence interval [CI]: 0.783, 0.990) and 0.794 (95% CI: 0.686, 0.902), respectively.Conclusions and Clinical ImportanceTwo models were constructed for predicting outcome after EHPSS attenuation using venous blood samples. The model predicting clinical recovery showed the best diagnostic properties. Clinical application requires further validation.