bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Long-Term Success of Mandatory Vaccination Laws After Implementing the First Vaccination Campaign in 19th Century Rural Finland
Authors: Ukonaho Susanna , Lummaa Virpi , Briga Michael 
Published: March 2022

AbstractIn high-income countries, childhood infections are on the rise, a phenomenon attributed in part to persistent hesitancy toward vaccines. To combat vaccine hesitancy, several countries recently made vaccinating children mandatory, but the effect of such vaccination laws on vaccination coverage remains debated, and the long-term consequences are unknown. Here we quantified the consequences of vaccination laws on vaccination coverage, monitoring for a period of 63 years (1837–1899) rural Finland’s first vaccination campaign against the highly lethal childhood infection smallpox. We found that annual vaccination campaigns were focused on children up to 1 year old and that their vaccination coverage was low and declined over time until the implementation of the vaccination law, which stopped the declining trend and was associated with an abrupt coverage increase, of 20%, to cover &gt;80% of all children. Our results indicate that vaccination laws can have a long-term beneficial effect of increasing the vaccination coverage and will help public health practitioners to make informed decisions on how to act against vaccine hesitancy and optimize the impact of vaccination programs.
AbDiver: a tool to explore the natural antibody landscape to aid therapeutic design
Authors: Młokosiewicz Jakub , Deszyński Piotr , Wilman Wiktoria , Jaszczyszyn Igor , Ganesan Rajkumar , Kovaltsuk Aleksandr , Leem Jinwoo , Galson Jacob D , Krawczyk Konrad 
Published: March 2022

AbstractMotivationRational design of therapeutic antibodies can be improved by harnessing the natural sequence diversity of these molecules. Our understanding of the diversity of antibodies has recently been greatly facilitated through the deposition of hundreds of millions of human antibody sequences in next-generation sequencing (NGS) repositories. Contrasting a query therapeutic antibody sequence to naturally observed diversity in similar antibody sequences from NGS can provide a mutational roadmap for antibody engineers designing biotherapeutics. Because of the sheer scale of the antibody NGS datasets, performing queries across them is computationally challenging.ResultsTo facilitate harnessing antibody NGS data, we developed AbDiver (http://naturalantibody.com/abdiver), a free portal allowing users to compare their query sequences to those observed in the natural repertoires. AbDiver offers three antibody-specific use-cases: (i) compare a query antibody to positional variability statistics precomputed from multiple independent studies, (ii) retrieve close full variable sequence matches to a query antibody and (iii) retrieve CDR3 or clonotype matches to a query antibody. We applied our system to a set of 742 therapeutic antibodies, demonstrating that for each use-case our system can retrieve relevant results for most sequences. AbDiver facilitates the navigation of vast antibody mutation space for the purpose of rational therapeutic antibody design.Availability and implementationAbDiver is freely accessible at http://naturalantibody.com/abdiver.Supplementary informationSupplementary data are available at Bioinformatics online.
Cost-effectiveness of Fecal Microbiota Transplantation for First RecurrentClostridioides difficileInfection
Authors: Aby Elizabeth S , Vaughn Byron P , Enns Eva A , Rajasingham Radha 
Published: March 2022

AbstractBackgroundBoth the American College of Gastroenterology and the Infectious Diseases Society of America (IDSA)/Society for Healthcare Epidemiology of America 2021 Clostridioides difficile infection (CDI) guidelines recommend fecal microbiota transplantation (FMT) for persons with multiple recurrent CDI. Emerging data suggest that FMT may have high cure rates when used for first recurrent CDI. The aim of this study was to assess the cost-effectiveness of FMT for first recurrent CDI.MethodsWe developed a Markov model to simulate a cohort of patients presenting with initial CDI infection. The model estimated the costs, effectiveness, and cost-effectiveness of different CDI treatment regimens recommended in the 2021 IDSA guidelines, with the additional option of FMT for first recurrent CDI. The model includes stratification by the severity of initial infection, estimates of cure, recurrence, and mortality. Data sources were taken from IDSA guidelines and published literature on treatment outcomes. Outcome measures were quality-adjusted life-years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs).ResultsWhen FMT is available for first recurrent CDI, the optimal cost-effective treatment strategy is fidaxomicin for initial nonsevere CDI, vancomycin for initial severe CDI, and FMT for first and subsequent recurrent CDI, with an ICER of $27 135/QALY. In probabilistic sensitivity analysis at a $100 000 cost-effectiveness threshold, FMT for first and subsequent CDI recurrence was cost-effective 90% of the time given parameter uncertainty.ConclusionsFMT is a cost-effective strategy for first recurrent CDI. Prospective evaluation of FMT for first recurrent CDI is warranted to determine the efficacy and risk of recurrence.
Automated Evaluation of p16/Ki-67 Dual-Stain Cytology as a Biomarker for Detection of Anal Precancer in Men Who Have Sex With Men and Are Living With Human Immunodeficiency Virus
Authors: Cohen Camryn M , Wentzensen Nicolas , Lahrmann Bernd , Tokugawa Diane , Poitras Nancy , Bartels Liam , Krauthoff Alexandra , Keil Andreas , Miranda Felipe , Castle Philip E , Lorey Thomas , Hare Brad , Darragh Teresa M , Grabe Niels , Clarke Megan A 
Published: March 2022

Abstract

Background
Human papillomavirus–related biomarkers such as p16/Ki-67 “dual-stain” (DS) cytology have shown promising clinical performance for anal cancer screening. Here, we assessed the performance of automated evaluation of DS cytology (automated DS) to detect anal precancer in men who have sex with men (MSM) and are living with human immunodeficiency virus (HIV).

Methods
We conducted a cross-sectional analysis of 320 MSM with HIV undergoing anal cancer screening and high-resolution anoscopy (HRA) in 2009–2010. We evaluated the performance of automated DS based on a deep-learning classifier compared to manual evaluation of DS cytology (manual DS) to detect anal intraepithelial neoplasia grade 2 or 3 (AIN2+) and grade 3 (AIN3). We evaluated different DS-positive cell thresholds quantified by the automated approach and modeled performance compared with other screening strategies in a hypothetical population of MSM with HIV.

Results
Compared with manual DS, automated DS had significantly higher specificity (50.9% vs 42.2%; P &lt; .001) and similar sensitivity (93.2% vs 92.1%) for detection of AIN2+. Human papillomavirus testing with automated DS triage was significantly more specific than automated DS alone (56.5% vs 50.9%; P &lt; .001), with the same sensitivity (93.2%). In a modeled analysis assuming a 20% AIN2+ prevalence, automated DS detected more precancers than manual DS and anal cytology (186, 184, and 162, respectively) and had the lowest HRA referral rate per AIN2+ case detected (3.1, 3.5, and 3.3, respectively).

Conclusions
Compared with manual DS, automated DS detects the same number of precancers, with a lower HRA referral rate.
Towards a New Qualitative Screening Assay for Synthetic Cannabinoids Using Metabolomics and Machine Learning
Authors: Streun Gabriel L , Steuer Andrea E , Poetzsch Sandra N , Ebert Lars C , Dobay Akos , Kraemer Thomas 
Published: March 2022

Abstract

Background
Synthetic cannabinoids (SCs) are steadily emerging on the drug market. To remain competitive in clinical or forensic toxicology, new screening strategies including high-resolution mass spectrometry (HRMS) are required. Machine learning algorithms can detect and learn chemical signatures in complex datasets and use them as a proxy to predict new samples. We propose a new screening tool based on a SC-specific change of the metabolome and a machine learning algorithm.

Methods
Authentic human urine samples (n = 474), positive or negative for SCs, were used. These samples were measured with an untargeted metabolomics liquid chromatography (LC)–quadrupole time-of-flight-HRMS method. Progenesis QI software was used to preprocess the raw data. Following feature engineering, a random forest (RF) model was optimized in R using a 10-fold cross-validation method and a training set (n = 369). The performance of the model was assessed with a test (n = 50) and a verification (n = 55) set.

Results
During RF optimization, 49 features, 200 trees, and 7 variables at each branching node were determined as most predictive. The optimized model accuracy, clinical sensitivity, clinical specificity, positive predictive value, and negative predictive value were 88.1%, 83.0%, 92.7%, 91.3%, and 85.6%, respectively. The test set was predicted with an accuracy of 88.0%, and the verification set provided evidence that the model was able to detect cannabinoid-specific changes in the metabolome.

Conclusions
An RF approach combined with metabolomics enables a novel screening strategy for responding effectively to the challenge of new SCs. Biomarkers identified by this approach may also be integrated in routine screening methods.
Gut hormones profile after an Ivor Lewis gastro-esophagectomy and its relationship to delayed gastric emptying
Authors: Tham Ji Chung , Pournaras Dimitri J , Alcocer Bruno , Forbes Rosie , Ariyarathenam Arun V , Humphreys Martyn L , Berrisford Richard G , Wheatley Tim J , Chan David , Sanders Grant , Lewis Stephen J 
Published: March 2022

Abstract
Delayed gastric emptying (DGE) is common after an Ivor Lewis gastro-esophagectomy (ILGO). The risk of a dilated conduit is the much-feared anastomotic leak. Therefore, prompt management of DGE is required. However, the pathophysiology of DGE is unclear. We proposed that post-ILGO patients with/without DGE have different gut hormone profiles (GHP). Consecutive patients undergoing an ILGO from 1 December 2017 to 31 November 2019 were recruited. Blood sampling was conducted on either day 4, 5, or 6 with baseline sample taken prior to a 193-kcal meal and after every 30 minutes for 2 hours. If patients received pyloric dilatation, a repeat profile was performed post-dilatation and were designated as had DGE. Analyses were conducted on the following groups: patient without dilatation (non-dilated) versus dilatation (dilated); and pre-dilatation versus post-dilatation. Gut hormone profiles analyzed were glucagon-like peptide-1 (GLP-1) and peptide tyrosine tyrosine (PYY) using radioimmunoassay. Of 65 patients, 24 (36.9%) had dilatation and 41 (63.1%) did not. For the non-dilated and dilated groups, there were no differences in day 4, 5, or 6 GLP-1 (P = 0.499) (95% confidence interval for non-dilated [2822.64, 4416.40] and dilated [2519.91, 3162.32]). However, PYY levels were raised in the non-dilated group (P = 0.021) (95% confidence interval for non-dilated [1620.38, 3005.75] and dilated [821.53, 1606.18]). Additionally, after pyloric dilatation, paired analysis showed no differences in GLP-1, but PYY levels were different at all time points and had an exaggerated post-prandial response. We conclude that DGE is associated with an obtunded PYY response. However, the exact nature of the association is not yet established.
Volumetric assessment is superior to axial measurements in estimating the outcome of patients with acute uncomplicated type B aortic intramural haematoma
Authors: Chen Min , Yang Fan , Chen Lyufan , Liu Jitao , Luo Songyuan , Li Jie , Huang Wenhui , Liu Yuan , Fan Ruixin , Geng Qingshan , Chen Jiyan , Luo Jianfang 
Published: March 2022

Abstract

OBJECTIVES
Our goal was to investigate the accuracy of the two-dimensional and three-dimensional computed tomography imaging features in predicting the progression of acute uncomplicated type B aortic intramural haematoma (IMH).

METHODS
This study retrospectively screened 140 patients diagnosed with acute uncomplicated type B IMH in our institution from January 2015 to December 2020. Patients were classified as exhibiting progression (aortic dissection, aortic rupture, aneurysm formation, ulcer-like projection depth &gt;10 mm or &gt;10% increase in the initial thickness of the aortic wall) and regression (completely or partially reabsorbed haematoma) based on follow-up computed tomography.

RESULTS
During the 11.4-month follow-up [interquartile range (IQR), 2.6–17.8], 55 patients had haematoma progression. The progression group had higher haematoma volume (HV) and total lesion volume [94.8 (IQR, 80.0–108.2) cm3 vs 40.3 (IQR, 30.8–57.9) cm3; 278.0 (IQR, 238.6–369.3) cm3 vs 197.3 (IQR, 152.8–235.9) cm3, both P &lt; 0.001) and longer lesion length [43.2 (IQR, 37.5–46.7) cm vs 30.4 (IQR, 28.1–37.6) cm, P &lt; 0.001)] than the regression group. According to the area under the curve, HV &gt; 66 cm3 is the greatest risk factor for haematoma progression. In multivariable analysis, HV was a powerful independent predictive factor for type B IMH progression, with a hazard ratio of 17.9 (95% confidence interval, 5.5–58.7; P &lt; 0.001).

CONCLUSIONS
Volumetric parameters may help to predict disease progression more precisely for patients with acute uncomplicated type B IMH compared to standard axial measurements, which might optimize the initial treatment and follow-up protocol.
Cheerleading in Cyberspace: How the American Public Judges Attribution Claims for Cyberattacks
Authors: Leal Marcelo , Musgrave Paul 
Published: March 2022

Abstract
How does the US public evaluate claims attributing responsibility for a cyberattack? It seems plausible that political factors complicate how the US public judges attribution claims. In this article, we collect original survey data and use two survey experiments to explore this subject. Specifically, we analyze how cues and endorsements from partisan, intelligence, and independent non-governmental actors affect public confidence in attribution claims regarding the identity of cyberaggressors and support for retribution. We find evidence of polarization, particularly regarding perceptions of Russia's threat in cyberspace. To uncover whether this polarization results from partisan cheerleading or more sincere motivations, we conduct two experiments regarding political factors and attribution claims. In the first experiment, we find that respondents respond similarly to independent observers’ endorsements of attribution claims but that Democrats appear to respond strategically in a test of the link between attribution and retribution rather than endorse a proposal by then-President Trump. In the second experiment, we find that partisans respond similarly to intelligence and independent experts' evaluations of attribution claims, and that both respond much more favorably to independent experts than the intelligence community. Superficial polarization thus turns out to look more like partisan cheerleading.
C-Reactive Protein, Subjective Aging, and Incident Cardiovascular Disease: A Mediation Model
Authors: Skoblow Hanamori F , Proulx Christine M 
Published: March 2022

Abstract

Objectives
Negative self-perceptions of aging (SPA) and an older subjective age are associated with a greater likelihood of cardiovascular disease. We predicted that C-reactive protein (CRP), a marker of stress-related inflammation, would mediate this relation.

Method
Data from up to 6 602 participants ages 50–101 in the Health and Retirement Study (2008–2018) were analyzed using logistic regressions with mediation. Subjective aging was assessed in 2008 or 2010, CRP was assessed 2 years later, and diagnosis of heart disease or stroke was assessed in the years from CRP measurement to 2018.

Results
Significant indirect effects occurred in all models, indicating that negative SPA and older subjective age are associated with a greater likelihood of heart disease and stroke through elevated levels of the inflammatory marker CRP.

Discussion
These findings suggest that psychological factors such as subjective aging impact cardiovascular health through physiological mechanisms, specifically markers of inflammation.
Evaluating the location capabilities of a regional infrasonic network in Utah, US, using both ray tracing-derived and empirical-derived celerity-range and backazimuth models
Authors: Dannemann Dugick Fransiska K , Blom Philip S , Stump Brian W , Hayward Chris T , Arrowsmith Stephen J , Carmichael Joshua C , Marcillo Omar E 
Published: March 2022

SUMMARYMore realistic models for infrasound signal propagation across a region can be used to improve the precision and accuracy of spatial and temporal source localization estimates. Motivated by incomplete infrasound event bulletins in the Western US, the location capabilities of a regional infrasonic network of stations located between 84–458 km from the Utah Test and Training Range, Utah, USA, is assessed using a series of near-surface explosive events with complementary ground truth (GT) information. Signal arrival times and backazimuth estimates are determined with an automatic F-statistic based signal detector and manually refined by an analyst. This study represents the first application of three distinct celerity-range and backazimuth models to an extensive suite of realistic signal detections for event location purposes. A singular celerity and backazimuth deviation model was previously constructed using ray tracing analysis based on an extensive archive of historical atmospheric specifications and is applied within this study to test location capabilities. Similarly, a set of multivariate, season and location specific models for celerity and backazimuth are compared to an empirical model that depends on the observations across the infrasound network and the GT events, which accounts for atmospheric propagation variations from source to receiver. Discrepancies between observed and predicted signal celerities result in locations with poor accuracy. Application of the empirical model improves both spatial localization precision and accuracy; all but one location estimates retain the true GT location within the 90 per cent confidence bounds. Average mislocation of the events is 15.49 km and average 90 per cent error ellipse areas are 4141 km2. The empirical model additionally reduces origin time residuals; origin time residuals from the other location models are in excess of 160 s while residuals produced with the empirical model are within 30 s of the true origin time. We demonstrate that event location accuracy is driven by a combination of signal propagation model and the azimuthal gap of detecting stations. A direct relationship between mislocation, error ellipse area and increased station azimuthal gaps indicate that for sparse networks, detection backazimuths may drive location biases over traveltime estimates.
Impact of minimum unit pricing on youth alcohol consumption: insights from Lebanon
Authors: Chaaban Jad , Haddad Joanne , Ghandour Lilian , Chalak Ali 
Published: March 2022

Abstract
This paper analyses the impact of introducing an alcohol minimum unit pricing policy on youth’s off-premise alcohol consumption. We rely on price elasticities derived using stated preference alcohol purchase data from a survey of 1024 university students in Lebanon. Selectively targeting drinks with high ethanol concentration by applying a minimum unit pricing (MUP) corresponding to the maximum price that respondents are willing to pay per beverage achieves a reduction in ethanol intake close to 0.23 l/month (∼28% of pre-MUP ethanol intake). Imposing a flat MUP corresponding to the average price respondents are willing to pay for all alcoholic beverages decreases ethanol intake by nearly half the reduction from the previous targeted MUP. This work provides evidence in favour of MUP in conjunction with taxation capable of substantially reducing alcohol consumption. We also document a positive welfare benefit of MUP.
‘Ecological determinants’ of health in the global south: practising sustainable consumption in Kerala, India
Authors: Simon-Kumar Rachel 
Published: March 2022

Summary
Health promotion has long recognized the ecological determinants of health, underscoring the interconnections between planetary health, economic systems and human health. Despite calls for synergy across them, these domains are governed by fundamentally divergent paradigms leading to unaddressed conceptual and institutional gaps. Sustainability, meanwhile, is reduced to personal responsibility and behaviour change. This qualitative research explores ecological determinants through a focus on sustainable consumption in the under-researched context of the global south where rapid modernization has profoundly impacted the natural environment. The article uses the theoretical framework of ‘practice’—namely, the social routines, values, conventions and norms that drive consumption—to critically examine everyday household sustainable consumption in India’s southern state of Kerala. The findings show that in most households, sustainability is a health promotion practice. People practice sustainability fundamentally for its beneficial health outcomes. However, the institutional structures set up in favour of economic development continue to dominate society and is the paradigm that contextualizes everyday social life for consumers. The findings suggest that the practice of sustainable consumption is complex and caught in the space that is neither ‘upstream’ or ‘downstream’; instead, the focus on the ‘mid-stream’ reveals complex calculations that go into everyday negotiation of healthy living.