bluuebunny/crossref_metadata_2025_split huggingface dataset:
Resituating the Relevance of Alternatives for Causal Attributions
Authors: Sytsma Justin 
Published: July 2024

Abstract
Phillips et al. (2015) provide what looks like compelling evidence for explaining the impact of broadly moral evaluations on causal attributions in terms of the relevance of alternative possibilities. As part of a series of manipulation studies, they found that asking participants to describe what an agent could have done differently in a neutral case showed a similar effect to varying the morality of the agent’s action. Phillips and colleagues take this to show that broadly moral evaluations impact the alternative possibilities people see as relevant, which in turn impact their attributions. This leaves open the possibility that the manipulation impacts people’s broadly moral evaluations which in turn impact their attributions, however, rather than directly impacting attributions. But this alternative model conflicts with Phillips et al.’s account, while being compatible with competing explanations. These two models are tested using the same manipulation method and the results support the alternative model.
Truth-Conditional Variability of Color Ascriptions
Authors: Ziółkowski Adrian , Zyglewicz Tomasz 
Published: July 2024

Abstract
Recent experimental work has shown that the truth-value judgments regarding color predications (e.g., “the leaves on my tree are green”) are influenced by the context of utterance (Hansen & Chemla, 2013; Ziółkowski, 2021). Most explanations of this phenomenon focus on the semantics of color adjectives. However, it is not clear if these explanations do justice to the nuances of the empirical data collected thus far. In contrast to the adjectival explanations, Agustín Vicente (2015) argues that the context-sensitivity of color predications can result from the polysemy of the noun. We present the results of three studies designed to test this hypothesis: a traditional survey experiment (Study 1), an exploratory correlational study inspired by the semantic integration paradigm (Study 2a), and a follow-up experiment (Study 2b) that was designed to mitigate possible shortcomings of Study 2a. The results of our studies present preliminary evidence against Vicente’s theory.
Efficient risk-based collection of biospecimens in cohort studies: designing a prospective study of diagnostic performance for multicancer detection tests
Authors: Ramos Mark Louie F , Chaturvedi Anil K , Graubard Barry I , Katki Hormuzd A 
Published: July 2024

Abstract
In cohort studies, it can be infeasible to collect specimens on an entire cohort. For example, to estimate sensitivity of multiple multi-cancer detection (MCD) assays, we desire an extra 80 mL of cell-free DNA (cfDNA) blood, but this much extra blood is too expensive for us to collect on everyone. We propose a novel epidemiologic study design that efficiently oversamples those at highest baseline disease risk from whom to collect specimens, to increase the number of future cases with cfDNA blood collection. The variance reduction ratio from our risk-based subsample versus a simple random (sub)sample (SRS) depends primarily on the ratio of risk model sensitivity to the fraction of the cohort selected for specimen collection subject to constraining the risk model specificity. In a simulation where we chose 34% of the Prostate, Lung, Colorectal, and Ovarian Screening Trial cohort at highest risk of lung cancer for cfDNA blood collection, we could enrich the number of lung cancers 2.42-fold. The standard deviation of lung-cancer MCD sensitivity was 31%-33% reduced versus SRS. Risk-based collection of specimens on a subsample of the cohort could be a feasible and efficient approach to collecting extra specimens for molecular epidemiology.
Should regression calibration or multiple imputation be used when calibrating different devices in a longitudinal study?
Authors: Loop Matthew Shane , Lotspeich Sarah C , Garcia Tanya P , Meyer Michelle L 
Published: July 2024

Abstract
In longitudinal studies, the devices used to measure exposures can change from visit to visit. Calibration studies, wherein a subset of participants is measured using both devices at follow-up, may be used to assess between-device differences (ie, errors). Then, statistical methods are needed to adjust for between-device differences and the missing measurement data that often appear in calibration studies. Regression calibration and multiple imputation are two possible methods. We compared both methods in linear regression with a simulation study, considering various real-world scenarios for a longitudinal study of pulse wave velocity. Regression calibration and multiple imputation were both essentially unbiased, but correctly estimating the standard errors posed challenges. Multiple imputation with predicted mean matching produced close agreement with the empirical standard error. Fully stochastic multiple imputation underestimated the standard error by up to 50%, and regression calibration with bootstrapped standard errors performed slightly better than fully stochastic multiple imputation. Regression calibration was slightly more efficient than either multiple imputation method. The results suggest use of multiple imputation with predictive mean matching over fully stochastic imputation or regression calibration in longitudinal studies where a new device at follow-up might be error-prone compared to the device used at baseline.
Production and molecular weight variation of poly-γ-glutamic acid using a recombinant Bacillus subtilis with various Pgs-component ratios
Authors: Sawada Kazuhisa , Hagihara Hiroshi , Takimura Yasushi , Kataoka Masakazu 
Published: July 2024

ABSTRACT
Poly-γ-glutamic acid (PGA) has been of interest as a sustainable biopolymer in industrial applications. PGA biosynthesis in Bacillus subtilis is catalyzed by a transmembrane protein complex comprising PgsB, PgsC, and PgsA. To determine the Pgs component responsible for PGA overproduction, we constructed recombinants in which the promoter of the host-derived pgs gene was replaced with another host-derived gene promoter. These recombinants were then transformed using high-copy-number plasmids with various pgs-gene combinations to enhance Pgs component in different ratios. Subsequently, PGA production was investigated in batch cultures with l-glutamate supplemented medium. The recombinant strain enhanced with pgsB alone significantly overproduced PGA (maximum production 35.8 g/L) than either the pgsC- or pgsA-enhanced strain. The molecular weight of the PGA produced with the pgsB-enhanced strain was also greater than that for the pgsC- or pgsA-enhanced strain (approximately 10-fold). Hence, PgsB enhancement alone contributes to PGA overproduction with increased molecular weight.
mLiftOver: harmonizing data across Infinium DNA methylation platforms
Authors: Chen Brian H , Zhou Wanding 
Published: July 2024

Abstract

Motivation
Infinium DNA methylation BeadChips are widely used for genome-wide DNA methylation profiling at the population scale. Recent updates to probe content and naming conventions in the EPIC version 2 (EPICv2) arrays have complicated integrating new data with previous Infinium array platforms, such as the MethylationEPIC (EPIC) and the HumanMethylation450 (HM450) BeadChip.

Results
We present mLiftOver, a user-friendly tool that harmonizes probe ID, methylation level, and signal intensity data across different Infinium platforms. It manages probe replicates, missing data imputation, and platform-specific bias for accurate data conversion. We validated the tool by applying HM450-based cancer classifiers to EPICv2 cancer data, achieving high accuracy. Additionally, we successfully integrated EPICv2 healthy tissue data with legacy HM450 data for tissue identity analysis and produced consistent copy number profiles in cancer cells.

Availability and implementation
mLiftOver is implemented R and available in the Bioconductor package SeSAMe (version 1.21.13+): https://bioconductor.org/packages/release/bioc/html/sesame.html. Analysis of EPIC and EPICv2 platform-specific bias and high-confidence mapping is available at https://github.com/zhou-lab/InfiniumAnnotationV1/raw/main/Anno/EPICv2/EPICv2ToEPIC_conversion.tsv.gz. The source code is available at https://github.com/zwdzwd/sesame/blob/devel/R/mLiftOver.R under the MIT license.
Reverse network diffusion to remove indirect noise for better inference of gene regulatory networks
Authors: Yu Jiating , Leng Jiacheng , Yuan Fan , Sun Duanchen , Wu Ling-Yun 
Published: July 2024

Abstract

Motivation
Gene regulatory networks (GRNs) are vital tools for delineating regulatory relationships between transcription factors and their target genes. The boom in computational biology and various biotechnologies has made inferring GRNs from multi-omics data a hot topic. However, when networks are constructed from gene expression data, they often suffer from false-positive problem due to the transitive effects of correlation. The presence of spurious noise edges obscures the real gene interactions, which makes downstream analyses, such as detecting gene function modules and predicting disease-related genes, difficult and inefficient. Therefore, there is an urgent and compelling need to develop network denoising methods to improve the accuracy of GRN inference.

Results
In this study, we proposed a novel network denoising method named REverse Network Diffusion On Random walks (RENDOR). RENDOR is designed to enhance the accuracy of GRNs afflicted by indirect effects. RENDOR takes noisy networks as input, models higher-order indirect interactions between genes by transitive closure, eliminates false-positive effects using the inverse network diffusion method, and produces refined networks as output. We conducted a comparative assessment of GRN inference accuracy before and after denoising on simulated networks and real GRNs. Our results emphasized that the network derived from RENDOR more accurately and effectively captures gene interactions. This study demonstrates the significance of removing network indirect noise and highlights the effectiveness of the proposed method in enhancing the signal-to-noise ratio of noisy networks.

Availability and implementation
The R package RENDOR is provided at https://github.com/Wu-Lab/RENDOR and other source code and data are available at https://github.com/Wu-Lab/RENDOR-reproduce
DualNetGO: a dual network model for protein function prediction via effective feature selection
Authors: Chen Zhuoyang , Luo Qiong 
Published: July 2024

Abstract

Motivation
Protein–protein interaction (PPI) networks are crucial for automatically annotating protein functions. As multiple PPI networks exist for the same set of proteins that capture properties from different aspects, it is a challenging task to effectively utilize these heterogeneous networks. Recently, several deep learning models have combined PPI networks from all evidence, or concatenated all graph embeddings for protein function prediction. However, the lack of a judicious selection procedure prevents the effective harness of information from different PPI networks, as these networks vary in densities, structures, and noise levels. Consequently, combining protein features indiscriminately could increase the noise level, leading to decreased model performance.

Results
We develop DualNetGO, a dual-network model comprised of a Classifier and a Selector, to predict protein functions by effectively selecting features from different sources including graph embeddings of PPI networks, protein domain, and subcellular location information. Evaluation of DualNetGO on human and mouse datasets in comparison with other network-based models shows at least 4.5%, 6.2%, and 14.2% improvement on Fmax in BP, MF, and CC gene ontology categories, respectively, for human, and 3.3%, 10.6%, and 7.7% improvement on Fmax for mouse. We demonstrate the generalization capability of our model by training and testing on the CAFA3 data, and show its versatility by incorporating Esm2 embeddings. We further show that our model is insensitive to the choice of graph embedding method and is time- and memory-saving. These results demonstrate that combining a subset of features including PPI networks and protein attributes selected by our model is more effective in utilizing PPI network information than only using one kind of or concatenating graph embeddings from all kinds of PPI networks.

Availability and implementation
The source code of DualNetGO and some of the experiment data are available at: https://github.com/georgedashen/DualNetGO.
259 Comparing the Use of Antibiotics Versus No Antibiotics in the Management of Acute Left-Sided Uncomplicated Diverticulitis: A Systematic Review and Meta-Analysis
Authors: Sokhal B S , Mostafa O E S , Ramasamy S , Spyridon R , Zaman S , Hajibandeh S , Hajibandeh S 
Published: July 2024

Abstract

Background
Acute uncomplicated diverticulitis (AUD) is a common cause of acute abdominal pain. Recent guidelines advise selective use of antibiotics in AUD patients. This meta-analysis aimed to compare the effectiveness of no antibiotics versus antibiotics in AUD patients.

Method
This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses to identify randomised controlled trials (RCTs) involving AUD patients which compared the use of antibiotics with no antibiotics. Pooled outcome data was calculated using a random effects model with 95% confidence intervals (CI).

Results
Five RCTs with 1934 AUD patients were included. 979 patients were managed without antibiotics (50.6%). Patients in the no antibiotic and antibiotic groups had comparable demographics (age, sex and body mass index) and presenting features (temperature, pain score and C-reactive protein levels). There was no significant difference in rates of complicated diverticulitis (OR: 0.61, 95% CI:0.27-1.36, p=0.23), abscess (OR: 0.51, 95% CI: 0.08-3.25, p=0.47) or fistula (OR: 0.33, 95% CI: 0.03-3.15, p=0.33) formation, perforation (OR: 0.98, 95% CI: 0.32-3.07, p=0.98), recurrence (OR: 0.96, 95% CI: 0.66-1.41, p=0.85) need for surgery (OR: 1.36, 95% CI: 0.47-3.95, p=0.37), mortality (OR: 1.27, 95% CI: 0.14-11.76, p=0.82) or length of stay (MD: 0.215, 95% CI: -0.43-0.73, p=0.61) between the two groups. However, the likelihood of readmission was higher in the antibiotics group (OR: 2.13, 95% CI: 1.43-3.18, p=0.0002).

Conclusions
There is no significant difference in baseline characteristics, clinical presentation and adverse health outcomes between AUD patients treated without antibiotics compared to those with antibiotics.
1141 Mortality and Re-Amputation Rates Following Below Knee Amputation: A Systematic Review and Meta-Analysis
Authors: Hennessy C , Pring T , Qureshi B , Kendal A 
Published: July 2024

Abstract

Aim
Below knee amputation (BKA) is undertaken in patients with diabetes or peripheral vascular disease, when limb sparing medical optimisation or vascular interventions are no longer feasible. Mortality and proximal re-amputation rates are poorly defined in the literature. We sought to perform a systematic review to examine mortality and reputation rates across the current literature.

Method
A systematic search was performed of the MEDLINE (via Pubmed), EMBASE, Cochrane and clinicaltrials.gov databases from inception to August 25th, 2022. Articles were screened by two independent reviewers with conflicts reserved by a third party. Inclusion criteria were all non-traumatic causes of lower limb amputation. Outcomes of interest included Mortality and occurrence of more proximal amputation.

Results
Studies from 12 countries encompassing a total of 41832 patients were included for analysis. Study dates ranged from 1987 to 2019. Of the total patient number, 38577 (92.2%) were from the USA, with 2599 (6.2%) from Europe and 656 (1.6%) remainder. The mean age at BKA was 70.46 years (Range 62-86). Weighted mortality was 37% (Range 4%-29%) at 1 year, 58% (Range 12% - 60%) at 2 years, 65% (range 19% - 81%) at 5 years and 84% (Range 71-96%) at 10 years. Five studies reported re-amputation rate at any time point (13% Range 1.16- 22%).

Conclusions
Mortality following BKA is still poor, even in contemporary studies. The few large multicentre studies are US based and in military veteran populations. More robust UK focused studies are needed to accurately inform clinical decision making for patients and clinicians.
564 The Assessment and Management of Anaemia in Patients Who Underwent an Emergency Laparotomy
Authors: Nantha Kumar D L , Cornish J , Da Silva L 
Published: July 2024

Abstract

Aim
Emergency Laparotomies (EmLap) carry a significant risk of morbidity and mortality. Peri and post-operative anaemia are associated with higher complication rates, delayed healing, and lethargy. This study aimed to assess the occurrence of anaemia in EmLap patients upon admission and discharge, as well as to evaluate its management.

Method
Data was collected from 260 participants undergoing EmLap from 2016 to 2019 that completed a follow up questionnaire in 2020, as part of PEEL 2 (Patients Experience of Emergency Laparotomy) in Cardiff, a retrospective cohort study. 34% of patients (n=90) had a Haemoglobin (Hb) level on admission and discharge and were included into the study. Information on transfusions and prescriptions of ferrous fumarate tablets during admission and on discharge were obtained from electronic records.

Results
46.7% (n=42) were anaemic at time of admission and further 19 patients were anaemic after surgery. 61 patients (68%) were discharged with anaemia post EmLap. Of the 61 patients discharged with anaemia only 10 (16%) were given treatment; 7 (11%) were offered a blood transfusion, 2 (3%) were prescribed ferrous fumarate tablets and 1 (1.6%) received a combination of both. Discharge summaries did not highlight the issue and follow up advice was not given to GPs.

Conclusions
2/3 of EmLap patients were discharged with anaemia and was not addressed. A greater understanding is needed to appreciate the impact of anaemia on EmLap patients’ such as fatigue levels. It can be avoided if a closer look at patients’ blood results is conducted and treated aligning with the NICE guidelines.
648 Predictive Factors for Subtotal Cholecystectomy
Authors: Warrell D , Pessoa L , Oh K E , Manson D , Nageswaran H 
Published: July 2024

Abstract

Introduction
Subtotal-cholecystectomy (STC) is a rescue procedure in dealing with difficult gallbladders undertaken when a critical view of safety is not possible to allow complete cholecystectomy, thereby avoiding complications.

Aim
Determine what patient factors increase risk of STC in patients undergoing elective laparoscopic cholecystectomy (LC) and therefore aid prediction in patients reduced suitability for day surgery.

Method
Data was collected between 01/01/2022 and 31/07/2023 from three hospitals throughout the Aneurin-Bevan University Health-Board, Wales, UK. All patients receiving elective LC had data collected on age, BMI, gender, ERCP preceding operation, surgical duration, length of stay and 30-day complications, amongst others.

Results
Of a total of 1060 patients were included in this study(77.36%female, 22.64%male), 81 where STC (7.64% of total LC; 56.8%female, 43.2%male). There were three 30-day mortalities, one of whom underwent STC(p= 0.09).
The overall complication rate was 6.41%, significantly raised in the STC group(13.58%vs5.82%;p=0.007). As expected, there was a significant increase in bile-leak following subtotal(12.35%vs1.12%; p=0.0001) , however, there was no increase significance for bleed (0%vs0.41%;p=0.5644), wound infection(0%vs3.68%;p=0.079), collection(0.09%vs0.51%;p=0.404) or bile duct injury(0%vs1.02%; p=0.0001).
Predictors for STC were higher age(70-79years;p=0.0016), male gender(p=0.0001), and ERCP preceding surgery(p=0.0001). Both length of stay(median 1vs 0days;p=0.0001) and length of procedure (median 122vs 76minutes;p=0.0001) were increased following STC. High BMI, diabetes(p=0.1991) and smoking(p=0.7921) had no association.

Conclusions
Subtotal cholecystectomy is a safe alternative when facing difficult cholecystectomy where critical view of safety is not achievable. Factors predicting STC were male gender, advanced age and prior ERCP.
280 Validating Artificial Intelligence Generated Patient Information Leaflets: A Patient Survey
Authors: Spinos D , Okonkwo O 
Published: July 2024

Abstract

Aim
Artificial Intelligence (AI) is a ground-breaking technological advancement known for its prowess in processing extensive datasets, gaining recognition among clinicians for its potential in improving patient care. While AI is successfully employed in analysing medical imaging, its use in developing patient information literature (PIL) is limited. Patient access to information aligns with modern healthcare values, emphasizing shared decision-making, a priority in the NHS. This study, conducted under single-blinded conditions, explores the acceptability of AI-generated patient documentation.

Method
Four PIL examples related to common ENT procedures and conditions were identified. ChatGPT 3.5 modified existing PILs, adjusting for a UK reading age of 14. AI-generated PILs were formatted to match trust documents. Participants were blinded to leaflet sources.

Results
In 59 responses from ENT outpatients over six weeks, both AI and Trust leaflets had comparable appearance scores (AI 6.82, Trust 6.85). Although a slight preference for Trust leaflets existed, it wasn't statistically significant (p=0.47). In overall presentation preference, most participants had no preference (N=27), with one-third favoring Trust leaflets and 13 preferring AI-generated ones. In explaining conditions, over half had no preference (N=36), while 16 favored human-generated and 7 AI-generated leaflets. Readability and understanding were similar, with 25 participants finding both equally easy to read. Overall satisfaction was comparable, with 26 equally satisfied, 18 preferring human-generated, and 15 AI-generated leaflets.

Conclusions
AI technology integrated into clinical practice holds potential to transform PIL quality and quantity. As AI accessibility increases, healthcare services must guide the public to safeguard the standard of provided information.
476 Enhancing Surgical Education: Assessing the Impact of Laparoscopic Simulators in Learning Surgical Anatomy and Improving Surgical Skills
Authors: Zilani N , Khan H 
Published: July 2024

Abstract

Aim
We assessed laparoscopic simulators' efficacy in teaching surgical anatomy and enhancing surgical skills, offering insights into their role in shaping surgical education.

Method
83 medical students and foundation year doctors were surveyed before and after a hands-on laparoscopic simulator session. Using a 5-point Likert scale, perceptions of the simulator's effectiveness in teaching surgical anatomy and the importance of laparoscopic simulator training for improving surgical skills were gauged. Attendees also rated the simulators’ effectiveness in providing information and exposure to Laparoscopic surgery. Scores underwent normality assessment via the Shapiro–Wilk test; a one-tailed T-test gauged statistical significance. Qualitative data was collected for deeper insights.

Results
Attendees exhibited a significant increase in belief in laparoscopic simulators as an effective means to learn surgical anatomy (mean before = 4.26, after = 4.49, p = 2.41 x 10-3). Agreement increased for the necessity of laparoscopic simulator training in medical education for improving surgical skills (mean pre-event = 4.36, after = 4.55, p = 3.31 x 10-3).

Conclusions
A notable surge in support for integrating laparoscopic simulators in medical education emerged, indicating a promising avenue for enhancing anatomical understanding in minimally invasive contexts. The positive shift underscores the increasing recognition of laparoscopic simulators as valuable tools for teaching surgical anatomy and skills. Future research should explore the impact of laparoscopic simulation training on long-term outcomes.