bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Semi-Parametric Approach to Model-Based Sensitivity Analysis in Observational Studies
Authors: Zhang Bo , Tchetgen Tchetgen Eric J. 
Published: November 2022

AbstractWhen drawing causal inference from observational data, there is almost always concern about unmeasured confounding. One way to tackle this is to conduct a sensitivity analysis. One widely used sensitivity analysis framework hypothesises the existence of a scalar unmeasured confounder U and asks how the causal conclusion would change were U measured and included in the primary analysis. Work along this line often makes various parametric assumptions on U, for the sake of mathematical and computational convenience. In this article, we further this line of research by developing a valid sensitivity analysis that leaves the distribution of U unrestricted. Compared to many existing methods in the literature, our method allows for a larger and more flexible family of models, mitigates observable implications, and works seamlessly with any primary analysis that models the outcome regression parametrically. We construct both pointwise confidence intervals and confidence bands that are uniformly valid over a given sensitivity parameter space, thus formally accounting for unknown sensitivity parameters. We apply our proposed method on an influential yet controversial study of the causal relationship between war experiences and political activeness using observational data from Uganda.
Pilot Collection and Evaluation of Head Kinematics in Stock Car Racing
Authors: Miller Logan E. , Patalak John P. , Harper Matthew G. , Urban Jillian E. , Stitzel Joel D. 
Published: November 2022

Abstract
The goal of this work was to collect on-track driver head kinematics using instrumented mouthpieces and characterize environmental exposure to accelerations and vibrations. Six NASCAR drivers were instrumented with custom-fit mouthpieces to collect head kinematic data. Devices were deployed at four tracks during practice and testing environments and configured to collect approximately 11 min of linear acceleration and rotational velocity data at 200 Hz. This continuous data collection, combined with film review, allowed extraction of complete laps of data. In addition to typical data processing methods, a moving-point average was calculated and subtracted from the overall signal for both linear acceleration and rotational velocity to determine the environmental component of head motion. The current analysis focuses on 42 full laps of data collected at four data collection events. The number of laps per track ranged from 2 to 23. Linear acceleration magnitudes for all 42 laps ranged from 2.46 to 7.48 g and rotational velocity ranged from 1.25 to 3.35 rad/s. After subtracting the moving average, linear acceleration ranged from 0.92 to 5.45 g and rotational velocity ranged from 0.57 to 2.05 rad/s. This study has established the feasibility of using an instrumented mouthpiece to measure head kinematics in NASCAR and presented a technique for isolating head motion due to cornering acceleration from those due to short-term perturbations experienced by the driver.
Five-Point Correlation Numbers in Minimal Liouville Gravity
Authors: Artemev A. A. , Belavin A. A. 
Published: November 2022

N-point correlation numbers in minimal Liouville gravity have been studied. It has been demonstrated how to use Al. Zamolodchikov’s higher equations of motion in Liouville field theory to explicitly calculate these numbers. An explicit expression has been obtained for the case of N = 5.
Prophylactic surfactant nebulisation for the early aeration of the preterm lung: a randomised clinical trial
Authors: Gaertner Vincent D , Minocchieri Stefan , Waldmann Andreas D , Mühlbacher Tobias , Bassler Dirk , Rüegger Christoph Martin 
Published: November 2022

ObjectiveThe effect of prophylactic surfactant nebulisation (SN) is unclear. We aimed to determine whether prophylactic SN improves early lung aeration.DesignParallel, randomised clinical trial, conducted between March 2021 and January 2022.SettingDelivery room (DR) of a tertiary neonatal centre in Zurich, Switzerland.PatientsPreterm infants between 260/7and 316/7weeks gestationInterventionsInfants were randomised to receive positive distending pressure alone or positive distending pressure and additional SN (200 mg/kg; poractant alfa) using a customised vibrating membrane nebuliser. SN commenced with the first application of a face mask immediately after birth.Main outcome measuresPrimary outcome was the difference in end-expiratory lung impedance from birth to 30 min after birth (∆EELI30min). EELI correlates well with functional residual capacity. Secondary outcomes included physiological and clinical outcomes.ResultsData from 35 infants were collected, and primary outcome data were analysed from 32 infants (n=16/group). Primary outcome was not different between intervention and control group (median (IQR): 25 (7–62) vs 10 (0–26) AU/kg, p=0.21). ∆EELI was slightly higher in the intervention group at 6 and 12 hours after birth, particularly in the central areas of the lung. There were no differences in cardiorespiratory and clinical parameters. Two adverse events were noted in the intervention group.ConclusionsProphylactic SN in the DR did not significantly affect ∆EELI30minand showed only minimal effects on lung physiology. Prophylactic SN in the DR was feasible. There were no differences in clinical outcomes.Trial registration numberNCT04315636.
Impact of the COVID-19 pandemic on psychosocial work factors and emotional exhaustion among workers in the healthcare sector: a longitudinal study among 1915 Dutch workers
Authors: van Elk Fleur , Robroek Suzan J W , Burdorf Alex , Oude Hengel Karen M 
Published: November 2022

ObjectivesThis study aims to investigate across subgroups of healthcare workers (1) the changes in psychosocial working conditions and emotional exhaustion during the pandemic compared with the situation before, and (2) the impact of different stages of the COVID-19 pandemic in terms of hospital pressure on psychosocial working conditions and emotional exhaustion.MethodsFive questionnaire measurements during 2 years from 1915 healthcare workers in the longitudinal study ‘the Netherlands Working Conditions Survey-COVID-19’ were used. At each measurement, three subgroups were defined: working with patients with COVID-19, working with other patients and not working with patients. For each measurement, hospital pressure was determined by number of hospitalisations per day. Linear mixed models were fitted to analyse differences across subgroups of healthcare workers.ResultsDuring COVID-19, psychosocial working conditions deteriorated among healthcare workers working with patients, in particular with patients with COVID-19, compared with healthcare workers not working with patients after correcting for the situation before COVID-19. No changes were observed for emotional exhaustion in any of the subgroups. An increasing hospital pressure improved job autonomy and reduced emotional demands among healthcare workers in COVID-19 wards, but had no influence on other psychosocial working conditions and emotional exhaustion.ConclusionPsychosocial working conditions deteriorated for healthcare workers working with (COVID-19) patients during the pandemic, while emotional exhaustion did not change among all groups of healthcare workers.
Mortality in non-exacerbating COPD: a longitudinal analysis of UK primary care data
Authors: Lenoir Alexandra , Whittaker Hannah , Gayle Alicia , Jarvis Debbie , Quint Jennifer K 
Published: November 2022

IntroductionNon-exacerbating patients with chronic obstructive pulmonary disease (COPD) are a less studied phenotype. We investigated clinical characteristics, mortality rates and causes of death among non-exacerbating compared with exacerbating patients with COPD.MethodsWe used data from the Clinical Practice Research Datalink, Hospital Episode Statistics and Office for National Statistics between 1 January 2004 and 31 December 2018. Ever smokers with a COPD diagnosis with minimum 3 years of baseline information were included. We compared overall using Cox regression and cause-specific mortality rates using competing risk analysis, adjusted for age, sex, deprivation, smoking status, body mass index, GOLD stage and comorbidities. Causes of death were identified using International Classification of Diseases-10 codes.ResultsAmong 67 516 patients, 17.3% did not exacerbate during the 3-year baseline period. Mean follow-up was 4 years. Non-exacerbators were more likely to be male (63.3% vs 52.4%, p<0.001) and less often had a history of asthma (33.9% vs 43.6%, p<0.001) or FEV1<50% predicted (23.7 vs 31.8%) compared with exacerbators. Adjusted HR for overall mortality in non-exacerbators compared with exacerbators was 0.62 (95% CI 0.56 to 0.70) in the first year of follow-up and 0.87 (95% CI 0.83 to 0.91) thereafter. Non-exacerbating patients with COPD died less of respiratory causes than exacerbators (29.2% vs 40.3%) and more of malignancies (29.4% vs 23.4%) and cardiovascular diseases (26.2% vs 22.9%). HRs for malignant and circulatory causes of death were increased after the first year of follow-up.DiscussionIn this primary care cohort, non-exacerbators showed distinct clinical characteristics and lower mortality rates. Non-exacerbators were equally likely to die of respiratory, malignant or cardiovascular diseases.
The Tensor Brain: A Unified Theory of Perception, Memory, and Semantic Decoding
Authors: Tresp Volker , Sharifzadeh Sahand , Li Hang , Konopatzki Dario , Ma Yunpu 
Published: November 2022

AbstractWe present a unified computational theory of an agent's perception and memory. In our model, both perception and memory are realized by different operational modes of the oscillating interactions between a symbolic index layer and a subsymbolic representation layer. The two layers form a bilayer tensor network (BTN). The index layer encodes indices for concepts, predicates, and episodic instances. The representation layer broadcasts information and reflects the cognitive brain state; it is our model of what authors have called the “mental canvas” or the “global workspace.” As a bridge between perceptual input and the index layer, the representation layer enables the grounding of indices by their subsymbolic embeddings, which are implemented as connection weights linking both layers. The propagation of activation to earlier perceptual processing layers in the brain can lead to embodiments of indices. Perception and memories first create subsymbolic representations, which are subsequently decoded semantically to produce sequences of activated indices that form symbolic triple statements. The brain is a sampling engine: only activated indices are communicated to the remaining parts of the brain. Triple statements are dynamically embedded in the representation layer and embodied in earlier processing layers: the brain speaks to itself. Although memory appears to be about the past, its main purpose is to support the agent in the present and the future. Recent episodic memory provides the agent with a sense of the here and now. Remote episodic memory retrieves relevant past experiences to provide information about possible future scenarios. This aids the agent in decision making. “Future” episodic memory, based on expected future events, guides planning and action. Semantic memory retrieves specific information, which is not delivered by current perception, and defines priors for future observations. We argue that it is important for the agent to encode individual entities, not just classes and attributes. Perception is learning: episodic memories are constantly being formed, and we demonstrate that a form of self-supervised learning can acquire new concepts and refine existing ones. We test our model on a standard benchmark data set, which we expanded to contain richer representations for attributes, classes, and individuals. Our key hypothesis is that obtaining a better understanding of perception and memory is a crucial prerequisite to comprehending human-level intelligence.
Analysis of long non-coding RNA expression profile of bovine monocyte-macrophage infected by Mycobacterium avium subsp. paratuberculosis
Authors: Bao Yanhong , Wu Shuiyin , Yang Tianze , Wang Zi , Wang Yiming , Jiang Xiuyun , Ma Hongxia 
Published: November 2022

AbstractMycobacterium avium subsp. paratuberculosis (MAP) is the causative agent of paratuberculosis. As a potential zoonotic pathogen, MAP also seriously threatens human health and social security. At present, long non-coding RNA (lncRNA) has attracted wide attention as an useful biomarker in various diseases. Therefore, our study analyzed the lncRNA expression profiles and lncRNA-mRNA regulatory network of MAP infected bovine monocytes-macrophages and uninfected bovine cells by high-throughput sequencing. A total of 4641 differentially expressed lncRNAs genes were identified, including 3111 up-regulated genes and 1530 down-regulated genes. In addition, lncRNA-mRNA interaction analysis was performed to predict the target genes of lncRNA. Among them, after MAP infection, 86 lncRNAs targeted to mRNA, of which only 6 genes were significantly different. The results of Gene Ontology (GO) enrichment analysis showed that the differentially expressed genes significantly enriched in functional groups were related to immune regulation. Multiple signal pathways including NF-κB, NOD-like receptor, Cytokine-cytokine receptor, Toll-like receptor signaling pathway, Chemokine signaling pathway, and other important biochemical, metabolic and signal transduction pathways were enriched in Kyoto Encyclopedia of Genes and Genomes (KEGG). In this study, analysis of macrophage transcriptomes in response to MAP infection is expected to provide key information to deeply understand role of the pathogen in initiating an inappropriate and persistent infection in susceptible hosts and molecular mechanisms that might underlie the early phases of paratuberculosis.
Maize Lethal Necrosis disease: review of molecular and genetic resistance mechanisms, socio-economic impacts, and mitigation strategies in sub-Saharan Africa
Authors: Biswal Akshaya Kumar , Alakonya Amos Emitati , Mottaleb Khondokar Abdul , Hearne Sarah J. , Sonder Kai , Molnar Terence Luke , Jones Alan M. , Pixley Kevin Vail , Prasanna Boddupalli Maruthi 
Published: November 2022

Abstract
Background
Maize lethal necrosis (MLN) disease is a significant constraint for maize producers in sub-Saharan Africa (SSA). The disease decimates the maize crop, in some cases, causing total crop failure with far-reaching impacts on regional food security.

Results
In this review, we analyze the impacts of MLN in Africa, finding that resource-poor farmers and consumers are the most vulnerable populations. We examine the molecular mechanism of MLN virus transmission, role of vectors and host plant resistance identifying a range of potential opportunities for genetic and phytosanitary interventions to control MLN. We discuss the likely exacerbating effects of climate change on the MLN menace and describe a sobering example of negative genetic association between tolerance to heat/drought and susceptibility to viral infection. We also review role of microRNAs in host plant response to MLN causing viruses as well as heat/drought stress that can be carefully engineered to develop resistant varieties using novel molecular techniques.

Conclusions
With the dual drivers of increased crop loss due to MLN and increased demand of maize for food, the development and deployment of simple and safe technologies, like resistant cultivars developed through accelerated breeding or emerging gene editing technologies, will have substantial positive impact on livelihoods in the region. We have summarized the available genetic resources and identified a few large-effect QTLs that can be further exploited to accelerate conversion of existing farmer-preferred varieties into resistant cultivars.
The application of an age adjusted D-dimer threshold to rule out suspected venous thromboembolism (VTE) in an emergency department setting: a retrospective diagnostic cohort study
Authors: Barrett Liam , Jones Tom , Horner Daniel 
Published: November 2022

Abstract
Background
Venous Thromboembolic disease (VTE) poses a diagnostic challenge for clinicians in acute care. Over reliance on reference standard investigations can lead to over treatment and potential harm.
We sought to evaluate the pragmatic performance and implications of using an age adjusted D-dimer (AADD) strategy to rule out VTE in patients with suspected disease attending an emergency department (ED) setting. We aimed to determine diagnostic test characteristics and assess whether this strategy would result in proportional imaging reduction and potential cost savings.

Methods
Design: Single centre retrospective diagnostic cohort study.
All patients > 50 years old evaluated for possible VTE who presented to the emergency department over a consecutive 12-month period between January and December 2016 with a positive D-dimer result. Clinical assessment records and reference standard imaging results were followed up by multiple independent adjudicators and coded as VTE positive or negative.

Results
During the study period, there were 2132 positive D-dimer results. One thousand two hundred thirty-six patients received reference standard investigations. A total increase of 314/1236 (25.1%) results would have been coded as true negatives as opposed to false positive if the AADD cut off point had been applied, with 314 reference standard tests subsequently avoided. The AADD cut off had comparable sensitivity to the current cut off despite this increase in specificity; sensitivities for the diagnosis of DVT were 99.28% (95% CI 96.06–99.98%) and 97.72% for PE (95% CI 91.94% to 97.72). There were 3 false negative results using the AADD strategy.

Conclusions
In patients with suspected VTE with a low or moderate pre-test probability, the application of AADD appears to increase the proportion of patients in which VTE can be excluded without the need for reference standard imaging. This management strategy is likely to be associated with substantial reduction in anticoagulation treatment, investigations and cost/time savings.
Using a cohort study of diabetes and peripheral artery disease to compare logistic regression and machine learning via random forest modeling
Authors: Austin Andrea M. , Ramkumar Niveditta , Gladders Barbara , Barnes Jonathan A. , Eid Mark A. , Moore Kayla O. , Feinberg Mark W. , Creager Mark A. , Bonaca Marc , Goodney Philip P. 
Published: November 2022

Abstract
Background
This study illustrates the use of logistic regression and machine learning methods, specifically random forest models, in health services research by analyzing outcomes for a cohort of patients with concomitant peripheral artery disease and diabetes mellitus.

Methods
Cohort study using fee-for-service Medicare beneficiaries in 2015 who were newly diagnosed with peripheral artery disease and diabetes mellitus. Exposure variables include whether patients received preventive measures in the 6 months following their index date: HbA1c test, foot exam, or vascular imaging study. Outcomes include any reintervention, lower extremity amputation, and death. We fit both logistic regression models as well as random forest models.

Results
There were 88,898 fee-for-service Medicare beneficiaries diagnosed with peripheral artery disease and diabetes mellitus in our cohort. The rate of preventative treatments in the first six months following diagnosis were 52% (n = 45,971) with foot exams, 43% (n = 38,393) had vascular imaging, and 50% (n = 44,181) had an HbA1c test. The directionality of the influence for all covariates considered matched those results found with the random forest and logistic regression models. The most predictive covariate in each approach differs as determined by the t-statistics from logistic regression and variable importance (VI) in the random forest model. For amputation we see age 85 + (t = 53.17) urban-residing (VI = 83.42), and for death (t = 65.84, VI = 88.76) and reintervention (t = 34.40, VI = 81.22) both models indicate age is most predictive.

Conclusions
The use of random forest models to analyze data and provide predictions for patients holds great potential in identifying modifiable patient-level and health-system factors and cohorts for increased surveillance and intervention to improve outcomes for patients. Random forests are incredibly high performing models with difficult interpretation most ideally suited for times when accurate prediction is most desirable and can be used in tandem with more common approaches to provide a more thorough analysis of observational data.
Gambling, fast food and alcohol sponsorship in elite sport – perspectives from Australian sporting fans
Authors: Boelsen-Robinson Tara , Thow Anne-Marie , Lee Nancy , Gill Tim , Colagiuri Stephen 
Published: November 2022

Abstract
Background
Public health bodies in Australia remain concerned about marketing of unhealthy commodities; namely unhealthy food, alcohol and gambling products. Children are particularly susceptible to the influence of unhealthy commodity marketing. This study explored adults’ perceptions of unhealthy commodities sponsorship in elite sport and policies to restrict them.

Methods
Four focus groups of 7–8 frequent sport spectators were recruited, including parents and non-parents, and located in inner and outer suburbs of Sydney, Australia. Results were analysed thematically.

Results
Participants identified the contradictions of healthy messages of sport and unhealthy commodities, while highlighting the commercial value of sport sponsorship to sporting clubs. There is concern around children’s exposure to effective and integrated marketing techniques when viewing sport, which encouraged unhealthy habits. Support for restricting sponsorship related to perceived product harm, with gambling viewed as having the greatest health impact. Participants were supportive of policies that reduced exposure of unhealthy commodities to children, but were concerned about the financial risk to sporting clubs. Governments and sports associations were identified as holding responsibility for enacting changes.

Conclusion
A number of options were identified for advocates to gain public and political traction to reduce unhealthy commodity sponsorship. There is potential for shifts away from unhealthy sponsorship by both governments and sports associations.