bluuebunny/crossref_metadata_2025_split huggingface dataset:
Aiding Recruitment: A Comparative Case Study of Non‐State Actors in Lebanon and the United States After Disaster
Authors: Pudlo Jason M. , Kassab Hanna Samir 
Published: January 2025

ABSTRACTObjectiveWhat do earthquakes in Syria share with wildfires in the mountain west of the United States? The article's objective is to show how disasters serve as recruiting events for anti‐government and militia movements.MethodologyThe methodology uses a comparative case study alongside discourse analysis to demonstrate how disaster response serves as a recruiting tool. The comparative approach for this paper first establishes how anti‐government movements use the provision of social services to establish trust, gain legitimacy, and recruit members. Discourse analysis analyzes texts and other media as it relates to the social and political context of a particular time and place.ResultsWe find Hezbollah and American militias are driven by different ideologies but share seven post‐disaster recruitment strategies. First, both rely structural violence to use their social programs to expand their legitimacy; second, both cooperate with the state to expand legitimacy; third, both try to persuade society of their goodness; fourth, reshaping identity expands recruitment opportunity; fifth, the state fails to deliver social programs opening an opportunity for recruitment; sixth, both actors cooperate with the state to further their ends, not just a source of legitimacy, but a process of learning for the eventual collapse of the state as per group ideology; last, both actors rely on and hope for state failure to justify existence.ConclusionWe conclude that disasters can serve as recruiting events for anti‐government and militia movements.
Discrete quantum subgroups of free unitary quantum groups
Authors: Freslon Amaury , Weber Moritz 
Published: January 2025

AbstractWe classify all compact quantum groups whose C*‐algebra sits inside that of the free unitary quantum groups . In other words, we classify all discrete quantum subgroups of , thereby proving a quantum variant of Kurosh's theorem to some extent. This yields interesting families which can be described using free wreath products and free complexifications. They can also be seen as quantum automorphism groups of specific quantum graphs which generalize finite rooted regular trees, providing explicit examples of quantum trees.
Investigation of thermal cut-off energy for accurate analysis of High Temperature Engineering Test Reactor
Authors: Takeda Satoshi , Kitada Takanori , Yamamoto Akio , Yamaji Kazuya , Koike Hiroki , Asano Koji 
Published: January 2025

Abstract
This study investigates the appropriate thermal cut-off energy for neutron transport calculations in the High Temperature Engineering Test Reactor (HTTR). Using the Monte Carlo calculation code MVP3.0, the impact of changing thermal cut-off energy on the multiplication factor was evaluated for the single fuel element geometry of HTTR, focusing on variations in fuel and moderator temperatures at the beginning of life (BOL) and end of life (EOL). In the default model of MVP3.0, resonance scattering is approximated by the free-monatomic-gas model with constant cross section. Therefore, the impact of using the exact model for resonance scattering was additionally examined. In the free-monatomic-gas model, a thermal cut-off energy of 30 eV is at least required to maintain the multiplication factor error within approximately ±50 pcm for both BOL and EOL. In addition, the results show that the impact of using the exact model instead of the free-monatomic-gas model on the multiplication factor is more than 200 pcm in the 30 to 40 eV range where U-238 has large resonance at 37 eV, and the impact becomes less than 50 pcm above 40 eV. These results indicate that a thermal cut-off energy of at least 30 eV is necessary without considering the effects of the exact model, and the energy range up to the 37 eV resonance needs to be considered in the case of applying the exact model to obtain the saturated results on multiplication factor for HTTR.
Mixed-mode fracture analysis of notched components - An empirical failure equation
Authors: Xiangqiao Yan 
Published: January 2025

Abstract
The mixed-mode failure problem of notched components remains a complex subject. On the basis of the multiaxial fatigue limit equation by Liu and Yan, in this study, an empirical failure equation to assess mixed-mode fracture of notched components is proposed. By using the test data of mixed-mode fracture failure of notched components from the literature, including the rounded-tip V-notched Brazilian disc specimens, rectangular plate specimens with a central blunt U-notch with different notch radii and notch angles, the empirical failure equation has been verified to be not only simple in computation form but also high in accuracy.
Machine learning reveals the dynamic importance of accessory sequences for
Salmonella
outbreak clustering
Authors: Liu Chao Chun , Hsiao William W. L. 
Published: January 2025

ABSTRACT

Bacterial typing at whole-genome scales is now feasible owing to decreasing costs in high-throughput sequencing and the recent advances in computation. The unprecedented resolution of whole-genome typing is achieved by genotyping the variable segments of bacterial genomes that can fluctuate significantly in gene content. However, due to the transient and hypervariable nature of many accessory elements, the value of the added resolution in outbreak investigations remains disputed. To assess the analytical value of bacterial accessory genomes in clustering epidemiologically related cases, we trained classifiers on a set of genomes collected from 24
Salmonella enterica
outbreaks of food, animal, or environmental origin. The models demonstrated high precision and recall on unseen test data with near-perfect accuracy in classifying clonal and short-term outbreaks. Annotating the genomic features important for cluster classification revealed functional enrichment of molecular fingerprints in genes involved in membrane transportation, trafficking, and carbohydrate metabolism. Importantly, we discovered polymorphisms in mobile genetic elements (MGEs) and gain/loss of MGEs to be informative in defining outbreak clusters. To quantify the ability of MGE variations to cluster outbreak clones, we devised a reference-free tree-building algorithm inspired by colored de Bruijn graphs, which enabled topological comparisons between MGE and standard typing methods. Systematic evaluation of clustering MGEs on an unseen dataset of 34
Salmonella
outbreaks yielded mixed results that exemplified the power of accessory sequence variations when core genomes of unrelated cases are insufficiently discriminatory, as well as the distortion of outbreak signals by microevolution events or the incomplete assembly of MGEs.

IMPORTANCE

Gene-by-gene typing is widely used to detect clusters of foodborne illnesses that share a common origin. It remains actively debated whether the inclusion of accessory sequences in bacterial typing schema is informative or deleterious for cluster definitions in outbreak investigations due to the potential confounding effects of horizontal gene transfer. By training machine learning models on a curated set of historical
Salmonella
outbreaks, we revealed an enriched presence of outbreak distinguishing features in a wide range of mobile genetic elements. Systematic comparison of the efficacy of clustering different accessory elements against standard sequence typing methods led to our cataloging of scenarios where accessory sequence variations were beneficial and uninformative to resolving outbreak clusters. The presented work underscores the complexity of the molecular trends in enteric outbreaks and seeks to inspire novel computational ways to exploit whole-genome sequencing data in enteric disease surveillance and management.
Inhibiting NLRP3 enhances cellular autophagy induced by outer membrane vesicles from
Pseudomonas aeruginosa
Authors: Ge Jing , Cao Min , Zhang Yuyao , Wu Tianqi , Liu Jiayi , Pu Jiang , He Hongye , Guo Zhibin , Ju Shaoqing , Yu Juan 
Published: January 2025

ABSTRACT

The bacterium
Pseudomonas aeruginosa
is able to invade lung epithelial cells and survive intracellularly. During this process, it secretes outer membrane vesicles (OMVs), however, it is currently unclear how OMVs from
P. aeruginosa
(PA-OMVs) affect lung epithelial cells and their impact on oxidative stress, autophagy, and other physiological activities of lung epithelial cells. In this study, we found that PA-OMVs activated oxidative stress and autophagy in cells. We demonstrated that the NLRP3 (NLR family, pyrin domain containing 3) inhibitor MCC950 can enhance autophagy induced by PA-OMVs. The main function of NLRP3 is related to the body’s immune response and inflammation regulation. MCC950 is the most common inhibitor of NLRP3. Additionally, we showed that PA-OMVs not only enhanced the expression of AMP-activated protein kinase, a key regulator of cellular energy homeostasis, and reactive oxygen species, which play a crucial role in cellular signaling and oxidative stress, but also significantly enhanced the expression of NLRP3. Inhibiting the expression of NLRP3 further enhanced the process of PA-OMVs induced autophagy. These results demonstrate that PA-OMVs activate both autophagy and the NLRP3 inflammasome, with NLRP3 suppressing autophagy to a certain extent, hoping to provide broad ideas for the future applications of PA-OMVs.

IMPORTANCE

The discovery that lung epithelial cells exposed to outer membrane vesicles from
Pseudomonas aeruginosa
(PA-OMVs) activate cellular autophagy and induce protective immunity is significant. Specifically, the addition of an NLRP3 inhibitor, MCC950, has been found to decrease NLRP3 targets while simultaneously enhancing the autophagy activity induced by PA-OMVs. This finding unveils a novel theoretical framework for the development of PA-OMVs vaccines, highlighting new targets for enhancing the body’s anti-infective responses. By elucidating the mechanisms through which PA-OMVs trigger autophagy and bolster immune defenses, this research opens avenues for innovative vaccine design strategies aimed at combatting infections effectively.
Exploring the growing phase forest musk deer (
Moschus berezovskii
) dietary energy requirements based on growth performance and gut microbiota analysis
Authors: Gong Ruiguang , Di Xiaocao , Ping Xinxin , Han Haodong , Song Bing , Wang Shuhui , Dong Xianggui , Ren Zhan Jun 
Published: January 2025

ABSTRACT

The forest musk deer (FMD) farming industry is currently experiencing rapid growth, yet the dietary energy requirements for FMD remain unclear. Therefore, we explored the optimal dietary digestible energy (DE) for growing phase FMD by providing three diets with different DE levels and analyzing changes in gut microbiota. A total of 20 six-month-old FMD were used in a 62-day trial. Animals were fed either traditional feed (CON, 10.38 MJ/kg DE) or pelleted diets with low (L, 8.87 MJ/kg), medium (M, 10.38 MJ/kg), or high (H, 11.86 MJ/kg) DE levels. The results showed that feeding pelleted diets significantly reduced the incidence of diarrhea (
P
< 0.05). The average daily gain in the H group was significantly higher than in the M group, and the M group was higher than both the L and CON groups (
P
< 0.05). Additionally, the H group showed the highest nutrient digestibility and the greatest increase in body measurements (
P
< 0.05). Analysis of fecal microbiota revealed that α-diversity and the relative abundance of
Firmicutes
increased with higher dietary energy levels, while the relative abundance of
Bacteroidetes
decreased. Beneficial bacteria such as
Akkermansia
and
Lachnospira
were significantly enriched in the H group. In conclusion, our findings suggest that pelleted diets are suitable for growing phase FMD, with an optimal dietary DE level of 11.86 MJ/kg.

IMPORTANCE
This study underscores the significance of identifying the optimal dietary digestible energy (DE) for growing forest musk deer (FMD). Pelleted diets with a DE level of 11.86 MJ/kg enhanced growth performance, nutrient digestibility, and gut health, while reducing diarrhea and enriching beneficial gut bacteria, offering valuable insights for improving FMD farming practices.
A meta-core outcome set for stillbirth prevention and bereavement care following stillbirth in LMIC
Authors: Dube Kushupika , Marenga Farai , Ayebare Elizabeth Ombeva , Bedwell Carol , Chaudhry Nasim , Chilinda Idesi , Chimwaza Angela , Devane Declan , Fattepur Sudhindrashayana , Goshomi Unice , Kiran Tayyeba , Laisser Rose , Lavender Tina , Mills Tracey A , Nabisere Allen , Un Nisa Zaib , Vwalika Bellington , Wakasiaka Sabina , Kirkham Jamie J 
Published: January 2025

Study objectiveStillbirth is burdensome in low-income and middle-income countries (LMICs), especially in sub-Saharan Africa and South Asia. Currently, there are two core outcome sets (COS) for stillbirth (prevention and bereavement care), but these were developed with limited reflection of the needs of parents in an LMIC setting. To address this gap, the objective of this study was to establish consensus on the most important outcomes for stillbirth prevention and bereavement care following stillbirth in sub-Saharan Africa and South Asia.MethodsPrevious stillbirth outcomes were reviewed for inclusion into the COS by senior research leaders and community engagement and involvement members from six sub-Saharan African and two South Asian countries. An online real-time Delphi survey was then conducted with healthcare professionals, parents who have experienced a stillbirth and researchers in the field to score the agreed list. The results of the Delphi were summarised and then discussed at a virtual consensus meeting where the final COS were agreed.Results287 participants contributed towards the Delphi (143 midwives, 32 obstetricians, 50 mothers, 12 fathers and 50 researchers), with at least 2 parents attending the full consensus meetings. Consensus was reached on 13 core outcomes for stillbirth prevention covering 5 domains: obstetric, fetal, perinatal and neonatal outcomes and maternal complications. For bereavement care following a stillbirth, five core outcomes reached a consensus, which included outcomes related to labour and birth, a postpartum complication, care experience, mental health and emotional and social well-being.DiscussionThese COS will improve the consistency of outcomes for future research in an LMIC setting. Additionally, they will complement existing COS for stillbirth prevention and bereavement care developed in high-income settings. The output from this work will move us towards a global set of outcomes that can be used in stillbirth research worldwide.
The 100 most-cited articles in WALANT hand surgery: A bibliometric and visualized analysis
Authors: Wong Zhen Yu , Adegboye Oluwatobi , Kanapathy Muholan , Nikkhah Dariush , Mosahebi Afshin , Miranda Ben H 
Published: January 2025

This bibliometric analysis aimed to define important topics and developments across wide awake local anaesthesia no tourniquet (WALANT) hand surgery, an innovative ambulatory technique that gained popularity during the COVID-19 pandemic. Articles were searched and screened using the Web of Science core collection database. VOSviewer 1.6.18 and bibliometrix were used for analysis. In the initial search 419 articles were found. Between 1990 and 2023, 333 writers contributed to the top 100 most-cited articles published. The country with the highest number of published articles (20%) was Canada, followed by the USA (18%) and China (12%). Most articles were published in Plastic and Reconstructive Surgery (15%), Hand Clinics (14%) and the European and American volumes of The Journal of Hand Surgery (9% each). Eighty-two percent of articles had a Level of Evidence of III or V. High-quality randomized controlled trials and systematic reviews of WALANT are needed to broaden and enhance clinical practice and research. Level of evidence: V
Changes in incidence and epidemiology of antimicrobial resistant pathogens before and during the COVID-19 pandemic in Germany, 2015–2022
Authors: Baum Jonathan H. J. , Dörre Achim , Reichert Felix , Noll Ines , Feig Marcel , Eckmanns Tim , Sandfort Mirco , Haller Sebastian 
Published: January 2025

Abstract

Background
Carbapenem-resistant Gram-negative bacteria and methicillin-resistant Staphylococcus aureus (MRSA) are among WHO’s priority pathogens with antimicrobial resistance (AMR). Studies suggest potential impacts of the COVID-19-pandemic on AMR. We described changes in AMR incidence and epidemiology in Germany during the COVID-19-pandemic.

Methods
We used two independent datasets, statutory surveillance and laboratory-based Antibiotic Resistance Surveillance (ARS). We included statutory notifications of infections/colonisations of carbapenem-resistant Acinetobacter spp., Klebsiella pneumoniae, Escherichia coli (CRA/CRKP/CREC) and invasive MRSA. Using Poisson/negative binomial regression and assuming continued pre-pandemic (2015/2017–2020) trends, we projected hypothetical notifications as if the pandemic had not occurred. We quantified annual changes during the pandemic period (2020–2022) by comparing to observed notifications. Additional models considered inpatient reductions, seasonality, infections only, or resistant isolates from ARS.

Results
CRA notified cases were reduced by -30% (95%CI -39%|-20%) in 2020, -23% (-36%|-8%) in 2021, but + 32% (+ 6%|+64%) higher in 2022 relative to hypothetical pre-pandemic projections. Changes were − 35%/-31%/+6% for CRKP, -40%/-61%/-48% for CREC and − 33%/-25%/-20% for MRSA. Statutory-models accounting for fewer inpatients, seasonality and infections only showed similar trends, as did ARS-models for resistant isolates and infections. International mobility for CRA, CRKP and CREC decreased in 2020–2021, then increased in 2022.

Conclusions
We observed significant reductions of AMR notifications and infections during 2020–2021, also when accounting for fewer inpatients. We conclude a genuine reduction of AMR spread occurred during the pandemic. Factors like fewer hospitalisations and reduced international mobility contributed. Rising international mobility may partly explain increases for CRA, CRKP and CREC in 2022. A solid understanding of AMR trends improves infection prevention and control.
Artificial intelligence methods applied to longitudinal data from electronic health records for prediction of cancer: a scoping review
Authors: Moglia Victoria , Johnson Owen , Cook Gordon , de Kamps Marc , Smith Lesley 
Published: January 2025

Abstract

Background
Early detection and diagnosis of cancer are vital to improving outcomes for patients. Artificial intelligence (AI) models have shown promise in the early detection and diagnosis of cancer, but there is limited evidence on methods that fully exploit the longitudinal data stored within electronic health records (EHRs). This review aims to summarise methods currently utilised for prediction of cancer from longitudinal data and provides recommendations on how such models should be developed.

Methods
The review was conducted following PRISMA-ScR guidance. Six databases (MEDLINE, EMBASE, Web of Science, IEEE Xplore, PubMed and SCOPUS) were searched for relevant records published before 2/2/2024. Search terms related to the concepts “artificial intelligence”, “prediction”, “health records”, “longitudinal”, and “cancer”. Data were extracted relating to several areas of the articles: (1) publication details, (2) study characteristics, (3) input data, (4) model characteristics, (4) reproducibility, and (5) quality assessment using the PROBAST tool. Models were evaluated against a framework for terminology relating to reporting of cancer detection and risk prediction models.

Results
Of 653 records screened, 33 were included in the review; 10 predicted risk of cancer, 18 performed either cancer detection or early detection, 4 predicted recurrence, and 1 predicted metastasis. The most common cancers predicted in the studies were colorectal (n = 9) and pancreatic cancer (n = 9). 16 studies used feature engineering to represent temporal data, with the most common features representing trends. 18 used deep learning models which take a direct sequential input, most commonly recurrent neural networks, but also including convolutional neural networks and transformers. Prediction windows and lead times varied greatly between studies, even for models predicting the same cancer. High risk of bias was found in 90% of the studies. This risk was often introduced due to inappropriate study design (n = 26) and sample size (n = 26).

Conclusion
This review highlights the breadth of approaches to cancer prediction from longitudinal data. We identify areas where reporting of methods could be improved, particularly regarding where in a patients’ trajectory the model is applied. The review shows opportunities for further work, including comparison of these approaches and their applications in other cancers.
Impact of vancomycin area under the curve in early or later phase on efficacy and nephrotoxicity in patients with enterococcal bloodstream infections: a multicenter study
Authors: Tangvichitrerk Piyawadee , Changpradub Dhitiwat , Hemapanpairoa Jatapat , Juntanawiwat Piraporn , Santimaleeworagun Wichai 
Published: January 2025

Abstract

Background
The optimal pharmacokinetic and pharmacodynamic (PK/PD) parameters of vancomycin that can improve outcomes in enterococcal infections remain controversial. To clarify the therapeutic target for this antibiotic, this study aimed to determine vancomycin PK/PD parameters associated with efficacy in the early (during 72 h) or later (after 72 h) phase of treatment and nephrotoxicity in enterococcal bloodstream infection patients.

Methods
This multicenter retrospective study reviewed medical records of patients with enterococcal bloodstream infections treated with intravenous vancomycin infusion for at least 72 h between January 2016 and March 2024 at Phramongkutklao Hospital or Nopparatrajathanee Hospital in Bangkok, and Rachaburi Hospital in Rachaburi Province, Thailand. Patients with data available on serum vancomycin concentration were analyzed. The primary outcomes were 30-day mortality and acute kidney injury. The estimates of the mean 24-h area under the curve in the first 72 h (AUC24) and in steady state (AUCss) were determined by Bayesian theorem.

Results
Overall, 201 vancomycin concentrations were measured within the first 72 h after vancomycin treatment, while 156 were in a steady state (> 72 h). According to Classification and Regression Tree analysis, vancomycin AUC at 420 mg﻿·h/l was the PK/PD target for 30-day mortality. Results reveal that patients with AUC24 (early phase) and AUCss < 420 mg﻿·h/l (later phase) had significantly higher 14-day, 30-day, and in-hospital mortality than AUC ≥ 420 mg﻿·h/l groups. In addition, patients with AUC24 ≥ 420 mg﻿·h/l in the early phase had significantly reduced microbiological failure (p = 0.004). Patients with AUC ≥ 700 mg﻿·h/l in early and later phases had significantly increased acute kidney injury risk. In addition, patients receiving concomitant nephrotoxic drugs had an AUC cutoff value of 650 mg﻿·h/l. Multivariate Cox regression analysis showed that vancomycin AUCss < 420 mg﻿·h/l, unknown source of bacteremia, and acute kidney injury were significantly associated with 30-day mortality.

Conclusions
AUC 420–650 mg﻿·h/l in early and later phases was the target of vancomycin’s PK/PD in enterococcal bacteremia patients for efficacy and to prevent acute kidney injury. This study suggests close monitoring of vancomycin levels to ensure efficacy and safety.