bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influenza Vaccination and Major Cardiovascular Risk: A Systematic Review and Meta-Analysis of Clinical Trials Studies
Authors: Omidi Fatemeh , Zangiabadian Moein , Shahidi Bonjar Amir Hasehm , Nasiri Mohammad Javad , Sarmastzadeh Tala 
Published: August 2023

AbstractBackgroundCardiovascular events remain a substantial global health concern, necessitating innovative strategies for prevention. This study aims to assess the potential impact of influenza vaccination on major cardiovascular events.MethodsA search of the medical English literature was conducted using PubMed/MEDLINE, EMBASE, and the Cochrane CENTRAL up to 1 August 2023. Meta-analysis and stratified analyses were performed to investigate specific outcomes, including myocardial infarction (MI), cardiovascular death, and stroke. Pooled relative risks (RR) along with their 95% confidence intervals (CI) were calculated to evaluate the associations.ResultsA comprehensive analysis was conducted on a total of 9059 patients, with 4529 patients receiving the influenza vaccine and 4530 patients receiving a placebo. Among patients who received the influenza vaccine, a notable reduction in the occurrence of major cardiovascular events was observed, with 517 cases compared to 621 cases in the placebo group (RR, 0.70; 95%CI, 0.55-0.91). The stratified analysis revealed a decreased risk of MI in vaccinated patients (RR, 0.74; 95%CI, 0.56-0.97) and a significant reduction in cardiovascular death events (RR, 0.67; 95% CI 0.45–0.98).ConclusionThis study provides compelling evidence that influenza vaccination is associated with a decreased risk of major cardiovascular events, particularly myocardial infarction, and cardiovascular death. These findings highlight the potential of influenza vaccination as an adjunctive strategy in cardiovascular disease prevention. Further research and exploration of underlying mechanisms are warranted to elucidate the observed beneficial effects.
Diagnostic test accuracy in longitudinal study settings: Theoretical approaches with use cases from clinical practice
Authors: Böhnke Julia , Zapf Antonia , Kramer Katharina , Weber Philipp ,   ELISE Study Group, Karch André , Rübsamen Nicole , Bode Louisa , Mast Marcel , Wulff Antje , Marschollek Michael , Schamer Sven , Rathert Henning , Jack Thomas , Beerbaum Philipp , Rübsamen Nicole , Böhnke Julia , Karch André , Das Pronaya Prosun , Wiese Lena , Groszweski-Anders Christian , Haller Andreas , Frank Torsten 
Published: August 2023

ABSTRACTIn this study we evaluate how to estimate diagnostic test accuracy (DTA) correctly in the presence of longitudinal patient data (i.e., repeated test applications per patient). We used a nonparametric approach to estimate sensitivity and specificity of diagnostic tests for three use cases with different characteristics (i.e., episode length and intervals between episodes): 1) systemic inflammatory response syndrome, 2) depression, and 3) epilepsy. DTA was estimated on the levels ‘time’, ‘event’, and ‘patient-time’ for each diagnosis, representing different research questions. A comparison of DTA for these levels per and across use cases showed variations in the estimates, which resulted from the used level, the time unit (i.e., per minute/hour/day), the resulting number of observations per patient, and the diagnosis-specific characteristics. Researchers need to predefine their choices (i.e., estimation levels and time units) based on their individual research aims, including the estimand definitions, and give an appropriate rationale considering the diagnosis-specific characteristics of the target outcomes and the number of observations per patient to make sure that unbiased and clinically relevant measures are communicated. Nonetheless, researchers could report the DTA of the test using more than one estimation level and/or time unit if this still complies with the research aim.
Arbovirus surveillance in pregnant women in north-central Nigeria, 2019-2022
Authors: Ogwuche Jerry , Chang Charlotte Ajeong , Ige Olukemi , Sagay Atiene S. , Chaplin Beth , Kahansim Makshwar L. , Paul Michael , Elujoba Michael , Imade Godwin , Kweashi Georgenia , Dai Yu-Ching , Hsieh Szu-Chia , Wang Wei-Kung , Hamel Donald J. , Kanki Phyllis J. 
Published: August 2023

AbstractThe adverse impact of Zika (ZIKV), dengue (DENV), and chikungunya (CHIKV) virus infection in pregnancy has been recognized in Latin America and Asia but is not well studied in Africa.In Nigeria, we screened 1006 pregnant women for ZIKV, DENV and CHIKV IgM/IgG by rapid test (2019-2022). Women with acute infection were recruited for prospective study and infants were examined for any abnormalities from delivery through six months. A subset of rapid test-reactive samples were confirmed using virus-specific ELISAs and neutralization assays.Prevalence of acute infection (IgM+) was 3.8%, 9.9% and 11.8% for ZIKV, DENV and CHIKV, respectively; co-infections represented 24.5% of all infections. Prevalence in asymptomatic women was twice the level of symptomatic infection. We found a significant association between acute maternal ZIKV/DENV/CHIKV infection and any gross abnormal birth outcome (p=0.014).Further prospective studies will contribute to our understanding of the clinical significance of these endemic arboviruses in Africa.
Large Language Models (LLMs) and Empathy – A Systematic Review
Authors: Sorin Vera , Brin Danna , Barash Yiftach , Konen Eli , Charney Alexander , Nadkarni Girish , Klang Eyal 
Published: August 2023

AbstractPurposeEmpathy, a cornerstone of human interaction, is a unique quality to humans that Large Language Models (LLMs) are believed to lack. Our study aims to review the literature on the capacity of LLMs in demonstrating empathyMethodsWe conducted a literature search on MEDLINE up to July 2023. Seven publications ultimately met the inclusion criteria.ResultsAll studies included in this review were published in 2023. All studies but one focused on ChatGPT-3.5 by OpenAI. Only one study evaluated empathy based on objective metrics, and all others used subjective human assessment. The studies reported LLMs to exhibits elements of empathy, including emotions recognition and providing emotionally supportive responses in diverse contexts, most of which were related to healthcare. In some cases, LLMs were observed to outperform humans in empathy-related tasks.ConclusionLLMs demonstrated some aspects of empathy in variable scenarios, mainly related to healthcare. The empathy may be considered “cognitive” empathy. Social skills are a fundamental aspect of intelligence, thus further research is imperative to enhance these skills in AI.
Exploring Quorum-Sensing-Based Bacterial GMOs for Addressing Bovine Mastitis: A Developmental Approach
Authors: Adhikary Adrija , Dutta Abeg , Ghosh Udit , Chatterjee Sourin , Borkar Shreyash , Das Shubhamay 
Published: August 2023

ABSTRACTBovine mastitis, a prevalent and costly disease affecting dairy cows, severely impacts milk production, quality, and cow health and poses significant challenges to the dairy industry worldwide. Traditional treatment strategies relying on antibiotics face concerns of antibiotic resistance and residual antibiotic residues in dairy products. Therefore, there is an urgent need for innovative and sustainable approaches. Our study undertakes a preliminary investigation into the formulation and efficacy of a GMO-based antibiotic-free treatment in fighting Bovine mastitis. We propose to use the bioengineered defensin Nisin PV as the antimicrobial to specifically target the causative pathogenStaphylococcus aureus. To disrupt the biofilm formation, we have leveraged the potency of DNaseI. By hacking the quorum sensing technique ofStaphylococcus aureus, our proposed genetically modified bacteria would sense the presence of pathogens and initiate their eradication by producing Nisin PV and DNaseI. Results show the efficacy of DNase I against bacterial biofilm formation, in addition to the efficacy of our proposed sensor, which is based on the agr quorum sensing system ofStaphylococcus aureus, a major cause of bovine mastitis. Molecular dynamics and simulations show that our choice of the bacterial defensin, Nisin PV, is less susceptible to cleavage by bacterial strains resistant to the native bacteriocin Nisin A. Additionally, we theoretically propose a lysis-based kill switch to ensure the release of the therapeutic components. The solution proposed in this study has the potential to offer a sustainable and effective alternative to antibiotic-based treatments. Implementation of bioengineered defensins could reduce disease incidence, minimize economic losses, and promote responsible antimicrobial stewardship in the dairy industry.
AI in paleontology
Authors: Yu Congyu , Qin Fangbo , Watanabe Akinobu , Yao Weiqi , Li Ying , Qin Zichuan , Liu Yuming , Wang Haibing , Jiangzuo Qigao , Hsiang Allison Y. , Ma Chao , Rayfield Emily , Benton Michael J. , Xu Xing 
Published: August 2023

AbstractAccumulating data have led to the emergence of data-driven paleontological studies, which reveal an unprecedented picture of evolutionary history. However, the fast-growing quantity and complication of data modalities make data processing laborious and inconsistent, while also lacking clear benchmarks to evaluate data collection and generation, and the performances of different methods on similar tasks. Recently, Artificial Intelligence (AI) is widely practiced across scientific disciplines, but has not become mainstream in paleontology where manual workflows are still typical. In this study, we review more than 70 paleontological AI studies since the 1980s, covering major tasks including micro-and macrofossil classification, image segmentation, and prediction. These studies feature a wide range of techniques such as Knowledge Based Systems (KBS), neural networks, transfer learning, and many other machine learning methods to automate a variety of paleontological research workflows. Here, we discuss their methods, datasets, and performance and compare them with more conventional AI studies. We attribute the recent increase in paleontological AI studies to the lowering bar in training and deployment of AI models rather than real progress. We also present recently developed AI implementations such as diffusion model content generation and Large Language Models (LLMs) to speculate how these approaches may interface with paleontological research. Even though AI has not yet flourished in paleontological research, successful implementation of AI is growing and show promise for transformative effect on the workflow in paleontological research in the years to come.HighlightsFirst systematic review of AI applications in paleontology.There is a 10 to 20-year gap between AI in paleontology and mainstream studies.Recent progress in paleontological AI studies is likely a result of lowering bar in training and deployment.Future direction discussed for interactions between paleontology and AI.
Novel Biomarkers and Distinct Transcriptomic Profile of Barrett’s Esophagus Epithelial Stem Cells
Authors: Alexander Katie L. , Smythies Lesley E. , Kyanam-Kabir-Baig Kondal R. , Poovey Emily , Crossman David K. , Smith Phillip D. , Peter Shajan 
Published: August 2023

AbstractBarrett’s esophagus, a metaplastic condition that originates in the distal esophagus, is the only known precursor lesion for the development of esophageal adenocarcinoma, which has a devasting 5-year survival rate of <20%. The large number of subjects diagnosed with Barrett’s esophagus, and therefore at higher risk for esophageal adenocarcinoma, underscores the necessity for biomarkers that would benefit surveillance and potentially early treatment. To address this, we generated epithelial stem cell organoids from normal gastric cardia, non-dysplastic and dysplastic Barrett’s esophagus, and esophageal and gastric adenocarcinoma. Interestingly, non-dysplastic and dysplastic Barrett’s esophagus displayed higher expression of multiple archetypical cancer-associated genes compared with both esophageal and gastric adenocarcinoma in addition to expression of the novel biomarker CT83. ST6GAL1, a Golgi sialyltransferase upregulated in multiple epithelioid cancers, was strongly upregulated in dysplastic Barrett’s esophagus at both mRNA and protein levels. ST6GAL1 protein also was highly expressed in esophageal adenocarcinoma, suggesting that regulation of ST6GAL1 may play a role in Barrett’s esophagus progression to esophageal adenocarcinoma and serve as a potential biomarker of the development of esophageal cancer.
PhyloMatcher: a tool for resolving conflicts in taxonomic nomenclature
Authors: Rader Jonathan A. , Pivovarnik Madelyn A. , Vantilburg Matias E. , Whitehouse Logan S. 
Published: August 2023

AbstractSummaryLarge-scale comparative studies rely on the application of both phylogenetic trees and phenotypic data, both of which come from a variety of sources, but due to the changing nature of phylogenetic classification over time, many taxon names in comparative datasets do not match the nomenclature in phylogenetic trees. Manual curation of taxonomic synonyms in large comparative datasets can be daunting. To address this issue, we introduce PhyloMatcher, a tool which allows for programmatic querying of two commonly used taxonomic databases to find associated synonyms with given target species names.Availability and implementationPhyloMatcher is easily installed as a Python package with pip, or as a standalone GUI application. PhyloMatcher source code and documentation are freely available athttps://github.com/Lswhiteh/PhyloMatcher, the GUI application can be downloaded from the Releases page.ContactLswhiteh@unc.eduSupplemental InformationWe provide documentation for PhyloMatcher, including walkthrough instructions for the GUI application on the Releases page ofhttps://github.com/Lswhiteh/PhyloMatcher.
SonoPrint: Acoustically Assisted Volumetric 3D Printing for Composites
Authors: Agrawal Prajwal , Zhuang Shengyang , Dreher Simon , Mitter Sarthak , Ahmed Daniel 
Published: August 2023

AbstractAdvancements in additive manufacturing in composites have transformed various fields in aerospace, medical devices, tissue engineering, and electronics, enabling fine-tuning material properties by reinforcing internal particles and adjusting their type, orientation, and volume fraction. This capability opens new possibilities for tailoring materials to specific applications and optimizing the performance of 3D-printed objects. Existing reinforcement strategies are restricted to pattern types, alignment areas, and particle characteristics. Alternatively, acoustics provide versatility by controlling particles independent of their size, geometry, and charge and can create intricate pattern formations. Despite the potential of acoustics in most 3D printing, limitation arises from the scattering of the acoustic field between the polymerized hard layers and the unpolymerized resin, leading to undesirable patterning formation. However, this challenge can be addressed by adopting a novel approach that involves simultaneous reinforcement and printing the entire structure. Here, we present SonoPrint, an acoustically-assisted volumetric 3D printer that produces mechanically tunable composite geometries by patterning reinforcement microparticles within the fabricated structure. SonoPrint creates a standing wave field that produces a targeted particle motif in the photosensitive resin while simultaneously printing the object in just a few minutes. We have also demonstrated various patterning configurations such as lines, radial lines, circles, rhombuses, quadrilaterals, and hexagons using microscopic particles such as glass, metal, and polystyrene particles. Furthermore, we fabricated diverse composites using different resins, achieving 87 microns feature size. We have shown that the printed structure with patterned microparticles increased their tensile and compression strength by ∼38% and ∼75%, respectively.
Vascularized tumor on a microfluidic chip to study mechanisms promoting tumor neovascularization and vascular targeted therapies
Authors: Skubal Magdalena , Larney Benedict Mc , Phung Ngan Bao , Desmaras Juan Carlos , Dozic Abdul Vehab , Volpe Alessia , Ogirala Anuja , Machado Camila Longo , Djibankov Jakob , Ponomarev Vladimir , Grimm Jan 
Published: August 2023

AbstractThe cascade of events leading to tumor formation includes induction of a tumor supporting neovasculature as a primary hallmark of cancer. Developing vasculature is difficult to evaluatein vivobut can be captured using microfluidic chip technology and patient derived cells. Herein, we established anon chipapproach to investigate the mechanisms promoting tumor vascularization and vascular targeted therapies via co-culture of metastatic renal cell carcinoma spheroids and endothelial cells in a 3D environment. Our model permitted real-time, high-resolution observation and assessment of tumor-induced angiogenesis, where endothelial cells sprout towards the tumor and mimic a vascular network. Bevacizumab, an angiogenic inhibitor, disrupted interactions between vessels and tumors, destroying the vascular network. Theon chipapproach enabled assessment of endothelial cell biology, vessel’s functionality, drug delivery, and molecular expression of PSMA. Finally, observations in the vascularized tumoron chippermitted direct and conclusive quantification of this therapy in weeks as opposed to months in a comparable animal model.TeaserVascularized tumor on microfluidic chip provides opportunity to study targeted therapies and improves preclinical drug discovery.
microRNA profile of endometrial cancer from Indian patients-Identification of potential biomarkers for prognosis
Authors: Hegde Shraddha , Wagh Kalpesh , Abikar Apoorva , Nambiar Sughosha , Ananthamurthy Shriraksha , Narayana Navyashree Hosahalli , Reddihalli Pallavi Venkateshaiah , Chandraiah Savitha , Narayana Suma Mysore , Ranganathan Prathibha 
Published: August 2023

AbstractEndometrial cancer is one of the major cancers in women throughout the world. If diagnosed early, these cancers are treatable and the prognosis is usually good. However, one major problem in treating endometrial cancer is accurate diagnosis and staging. Till date, the choice method for diagnosis and staging is histopathology. Although there are few molecular markers identified, they are not always sufficient in making accurate diagnosis and deciding on therapeutic strategy. As a result, very often patients are under treated or over treated. In this study, our group has profiled microRNAs (miRNA) from Indian patients using NGS-based approach. We have identified differentially expressed microRNAs in endometrial cancer. These microRNAs have also been compared to data from TCGA (The Cancer Genome Atlas), which represent other populations and also correlated to relevance in overall survival. Usingin-silicoapproaches, mRNA targets of the miRNAs have been predicted. After comparing with TCGA, we have identified 16 miRNA-mRNA pairs which could be potential prognostic biomarkers for endometrial cancer. This is the first miRNA profiling report from Indian cohort and one of the very few studies which have identified potential biomarkers of prognosis in endometrial cancer.
Bloodmeal metabarcoding of the argasid tick (Ornithodoros turicataDugès) reveals extensive vector-host associations
Authors: Balasubramanian Sujata , Busselman Rachel E. , Fernandez-Santos Nadia , Grunwald Andy , Wolff Nicholas , Hathaway Nicholas , Hillhouse Andrew , Bailey Jeffrey A. , Teel Pete D. , Ferreira Francisco C. , Hamer Sarah A. , Hamer Gabriel L. 
Published: August 2023

ABSTRACTMolecular methods to understand host feeding patterns of arthropod vectors are critical to assess exposure risk to vector-borne disease and unveil complex ecological interactions. We build on our prior work discovering the utility of PCR-Sanger sequencing bloodmeal analysis that work remarkably well for soft ticks (Acari: Argasidae), unlike for hard ticks (Acari: Ixodidae), thanks to their unique physiology that retains vertebrate DNA from prior bloodmeals viable for years. Here, we capitalize on this feature and apply bloodmeal metabarcoding using amplicon deep sequencing to identify multiple host species in individualOrnithodoros turicatasoft ticks collected from two natural areas in Texas, United States. Of 788 collectedO. turicata, 394 were evaluated for bloodmeal source via metabarcoding, revealing 27 different vertebrate host species (17 mammals, 5 birds, 1 reptile, and 4 amphibians) fed upon by 274 soft ticks. Information on multiple hosts for individualO. turicatawas derived from 168 of these (61%). Metabarcoding revealed more mixed vertebrate bloodmeals inO. turicatapreviously processed using Sanger sequencing. These data reveal wide host range ofO. turicataand demonstrate the value of bloodmeal metabarcoding for understanding the ecology for known and potential tick-borne pathogens circulating among humans, domestic animals and wildlife such as relapsing fever caused byBorrelia turicatae. Our results also document, for the first time an off-host soft tick collected to have evidence of prior feeding on wild pig which is a critical observation in the context of the threat of enzootic transmission of African swine fever virus if it were introduced to the US. This research enhances our understanding of vector-host associations and offers a promising perspective for biodiversity monitoring and disease control strategies.