bluuebunny/crossref_metadata_2025_split huggingface dataset:
Role of the Microbiome in Immunotherapy of Melanoma
Authors: Jiminez Victoria , Yusuf Nabiha 
Published: March 2023

Abstract
Novel immunotherapeutics for advanced melanoma have drastically changed survival rates and management strategies in recent years. Immune checkpoint inhibitors have emerged as efficacious agents for some patients but have not been proven to be as beneficial in other patient cohorts. Recent investigation into this observation has implicated the gut microbiome as a potential immunomodulator in regulating patient response to therapy. Numerous studies have provided evidence for this link. Bacterial colonization patterns have been associated with therapeutic outcomes, under the notion that favorable commensal organisms improve host immune response. This review aims to report the most recent and pertinent findings related to the relationship between gut microbial communities and melanoma therapy efficacy. This article also highlights the emerging frontier of artificial intelligence in its application regarding patient microbial composition evaluation, predictive models for therapy response, and recommendations for the future of probiotics and dietary interventions to optimize melanoma survival and outcomes.
Short- and Long-term Repercussions of Vancomycin on Immune Surveillance and the Efficacy of Antitumor Treatments
Authors: Paz del Socorro Thomas , Tonneau Marion , Pasquier David , Chamaillard Mathias 
Published: March 2023

Abstract
Although antibiotic is a major contributor to shifts in the intestinal flora that may persist for up to several months after cessation, it is now increasingly recognized that its prescription may differentially influence clinical outcome of different anticancer treatments. Intense clinical and basic research efforts aim then at gaining sufficient insights about how the cooperative action between the intestinal ecosystem and immune surveillance modulates the efficacy of anticancer treatments. In this review, we summarize multiple levels of knowledge between vancomycin exposure, the gut microbiota, and a meaningful therapeutic response. Furthermore, we discuss the mode of action of antibiotic therapy that is prescribed for prophylaxis of bacteremia and neutropenia and outline the opportunity for judiciously improving the efficacy of anticancer drugs.
Precise Monitoring of Returning Sensation in Digital Nerve Lesions by 3-D Imaging: A Proof-of-Concept Study
Authors: Ruewe Marc , Eigenberger Andreas , Klein Silvan M. , von Riedheim Antonia , Gugg Christine , Prantl Lukas , Palm Christoph , Weiherer Maximilian , Zeman Florian , Anker Alexandra M. 
Published: March 2023

Summary:
Digital nerve lesions result in a loss of tactile sensation reflected by an anesthetic area (AA) at the radial or ulnar aspect of the respective digit. Yet, available tools to monitor the recovery of tactile sense have been criticized for their lack of validity. However, the precise quantification of AA dynamics by three-dimensional (3-D) imaging could serve as an accurate surrogate to monitor recovery following digital nerve repair.
For validation, AAs were marked on digits of healthy volunteers to simulate the AA of an impaired cutaneous innervation. Three dimensional models were composed from raw images that had been acquired with a 3-D camera (Vectra H2) to precisely quantify relative AA for each digit (3-D models, n= 80). Operator properties varied regarding individual experience in 3-D imaging and image processing. Additionally, the concept was applied in a clinical case study.
Images taken by experienced photographers were rated better quality (p< 0.001) and needed less processing time (p= 0.020). Quantification of the relative AA was neither altered significantly by experience levels of the photographer (p= 0.425) nor the image assembler (p= 0.749).
The proposed concept allows precise and reliable surface quantification of digits and can be performed consistently without relevant distortion by lack of examiner experience. Routine 3-D imaging of the AA has the great potential to provide visual evidence of various returning states of sensation and to convert sensory nerve recovery into a metric variable with high responsiveness to temporal progress.
Correlation Between Apparent Diffusion Coefficient and the Ki-67 Proliferation Index in Grading Pediatric Glioma
Authors: Yao Rong , Cheng Ailan , Zhang Zhengwei , Jin Biao , Yu Hong 
Published: March 2023

Objective
This study aimed to investigate the correlation between apparent diffusion coefficient (ADC) and the Ki-67 proliferation index with the pathologic grades of pediatric glioma and to compare their diagnostic performance in differentiating grades of pediatric glioma.

Patients and Methods
Magnetic resonance imaging examinations and histopathologies of 121 surgically treated pediatric gliomas (87 low-grade gliomas [LGGs; grades 1 and 2] and 34 high-grade gliomas [HGGs; grades 3 and 4]) were retrospectively reviewed. The mean tumor ADC (ADCmean), minimum tumor ADC (ADCmin), tumor/normal brain ADC ratio (ADC ratio), and value of the Ki-67 proliferation index of LGGs and HGGs were compared. Correlation coefficients were calculated for ADC parameters and Ki-67 values. The receiver operating characteristic curve was used to determine the diagnostic value of ADCmean, ADCmin, ADC ratio, and Ki-67 proliferation index for differentiating LGGs and HGGs.

Results
The ADC values were significantly negatively correlated with glioma grade, and the Ki-67 proliferation index had a significant positive correlation with glioma grade. A significant negative correlation was observed between ADCmean and Ki-67 proliferation index, between ADCmin and Ki-67 proliferation index, and between ADC ratio and Ki-67 proliferation index. The receiver operating characteristic analysis demonstrated moderate to good accuracy for ADCmean in discriminating LGGs from HGGs (area under the curve [AUC], 0.875; sensitivity, 79.3%; specificity, 82.4%; accuracy, 80.2%; positive predictive value [PPV], 92.0%; and negative predictive value [NPV], 60.9% [cutoff value, 1.187] [×10−3 mm2/s]). Minimum tumor ADC showed very good to excellent accuracy with AUC of 0.946, sensitivity of 86.2%, specificity of 94.1%, accuracy of 88.4%, PPV of 97.4%, and NPV of 72.7% (cutoff value, 0.970) (×10−3 mm2/s). The ADC ratio showed moderate to good accuracy with AUC of 0.854, sensitivity of 72.4%, specificity of 88.2%, accuracy of 76.9%, PPV of 94.0%, and NPV of 55.6% (cutoff value, 1.426). For the parameter of the Ki-67 proliferation index, in discriminating LGGs from HGGs, very good to excellent diagnostic accuracy was observed (AUC, 0.962; sensitivity, 94.1%; specificity, 89.7%; accuracy, 90.9%; PPV, 97.5%; and NPV, 78.0% [cutoff value, 7]).

Conclusions
Apparent diffusion coefficient parameters and the Ki-67 proliferation index were significantly correlated with histological grade in pediatric gliomas. Apparent diffusion coefficient was closely correlated with the proliferative potential of pediatric gliomas. In addition, ADCmin showed superior performance compared with ADCmean and ADC ratio in differentiating pediatric glioma grade, with a close diagnostic efficacy to the Ki-67 proliferation index.
KIR2DL1gene is a surrogate marker of protection against infection-related hospitalisation among HIV-1 unexposed versus exposed uninfected infants in Cameroon
Authors: Simeni Luc-Aimé Kagoué , Yengo Clauvis Kunkeng , Wouambo Rodrigue Kamga , Fischer Janett , A Bessong Oumarou M’rikam , Fokam Joseph , Assob Nguedia Jules Clément 
Published: March 2023

AbstractBackgroundHIV-exposed uninfected infants (HEU) experience appear more vulnerable to infections compared to their HIV-unexposed uninfected (HUU) peers, generally attributed to poor passive immunity acquired from the mother. This may be due to some genetic factors that could alter the immune system. We thus sought to determine the distribution of Killer Cells Immunoglobulin-Like Receptor (KIR) genes in HEU versus HUU, and study the association between KIR profiling and occurrence of infection-related hospitalization.MethodsA cohort-study was conducted from May 2019 to April 2020 among HEU and HUU, followed-up at birth, week 6, 12, 24 and 48, in reference pediatric centers in Yaounde, Cameroon. Infant HIV status was determined, types of infections were analyzed, and 15 KIR genes were investigated using the sequence specific primer polymerase chain reaction (PCR-SSP) method. Rate of KIR genes and infection-related hospitalizations were compared in HEU versus HUU, with p<0.05 considered statistically significant.ResultsIn this cohort, a total of 19 infection-related hospitalizations occurred in 66 infants (14.81%, 04/27 HUU and 38.46%, 15/39 HEU, p=0.037), the majority occurring during the first 24 weeks of life: 10 (25.64%) HEU and 03 (11.11%) HUU, p=0.14. At week 48 (39 HEU and 27 HUU), the relative risk (RR) for infection-related hospitalizations was 2.42 (95% CI: 1.028-5.823) for HEU versus HUU, with aOR 3.59 (95% CI: 1.037-12.448). Incidence of hospitalization was 3.2 (95% CI: 1.63–7.14) per 100 infant-months among HEU versus 1.2 (95% CI: 0.57–3.60) in HUU, and RR was 2.22 (95% CI: 0.50–9.39).KIR2DL1gene was significantly higher in HUU versus HEU (OR= 0.183, 95%CI: 0.053-0.629; p=0.003), and the absence ofKIR2DL1was significantly associated with infection-related hospitalization (p<0.001; OR=0.063; 95%CI: 0.017-0.229).ConclusionCompared to HUU, the vulnerability of HEU is driving byKIR2DL1, indicating the protective role of this KIR against infection and hospitalizations.
A standardised differential privacy framework for epidemiological modelling with mobile phone data
Authors: Savi Merveille Koissi , Yadav Akash , Zhang Wanrong , Vembar Navin , Schroeder Andrew , Balsari Satchit , Buckee Caroline O. , Vadhan Salil , Kishore Nishant 
Published: March 2023

AbstractDuring the COVID-19 pandemic, the use of mobile phone data for monitoring human mobility patterns has become increasingly common, both to study the impact of travel restrictions on population movement and epidemiological modelling. Despite the importance of these data, the use of location information to guide public policy can raise issues of privacy and ethical use. Studies have shown that simple aggregation does not protect the privacy of an individual, and there are no universal standards for aggregation that guarantee anonymity. Newer methods, such as differential privacy, can provide statistically verifiable protection against identifiability but have been largely untested as inputs for compartment models used in infectious disease epidemiology. Our study examines the application of differential privacy as an anonymisation tool in epidemiological models, studying the impact of adding quantifiable statistical noise to mobile phone-based location data on the bias of ten common epidemiological metrics. We find that many epidemiological metrics are preserved and remain close to their non-private values when the true noise state is less than 20, in a count transition matrix, which corresponds to a privacy-less parameter∈ = 0.05per release. We show that differential privacy offers a robust approach to preserving individual privacy in mobility data while providing useful population-level insights for public health. Importantly, we have built a modular software pipeline to facilitate the replication and expansion of our framework.Author SummaryHuman mobility data has been used broadly in epidemiological population models to better understand the transmission dynamics of an epidemic, predict its future trajectory, and evaluate potential interventions. The availability and use of these data inherently raises the question of how we can balance individual privacy and the statistical utility of these data. Unfortunately, there are few existing frameworks that allow us to quantify this trade-off. Here, we have developed a framework to implement a differential privacy layer on top of human mobility data which can guarantee a minimum level of privacy protection and evaluate their effects on the statistical utility of model outputs. We show that this set of models and their outputs are resilient to high levels of privacy-preserving noise and suggest a standard privacy threshold with an epsilon of 0.05. Finally, we provide a reproducible framework for public health researchers and data providers to evaluate varying levels of privacy-preserving noise in human mobility data inputs, models, and epidemiological outputs.
Carnosine supplementation improves glucose control in adults with pre-diabetes and type 2 diabetes: a randomised controlled trial
Authors: Hariharan Rohit , Cameron James , Menon Kirthi , Mesinovic Jakub , Jansons Paul , Scott David , Lu Zhong X , de Courten Maximilian , Feehan Jack , de Courten Barbora 
Published: March 2023

AbstractType 2 diabetes (T2DM) is a major cause of morbidity and mortality globally. Carnosine, a naturally occurring dipeptide, has anti-inflammatory, antioxidant, and anti-glycating effects, with preliminary evidence suggesting it may improve important chronic disease risk factors in adults with cardiometabolic conditions. In this randomized controlled trial, 43 adults (30%F) living with prediabetes or T2DM consumed carnosine (2 grams) or a matching placebo daily for 14 weeks to evaluate its effect on glucose metabolism assessed via 2 hr, 75g oral glucose tolerance test. Secondary outcomes included body composition analysis by dual energy x-ray absorptiometry (DEXA), calf muscle density by pQCT and anthropometry. Carnosine supplementation decreased blood glucose at 90 minutes (−1.31mmol/L; p=0.02) and 120 minutes (−1.60mmol/L, p=0.02) and total glucose area under the curve (−3.30mmol/L; p=0.04) following an oral glucose tolerance test. There were no additional changes in secondary outcomes. The carnosine group results remained significant before and after adjustment for age, sex, and change in weight (all>0.05), and in further sensitivity analyses accounting for missing data. There were no significant changes in insulin levels. Likely mechanisms may include changes to hepatic glucose output explaining the observed reduction in blood glucose without changes in insulin secretion following carnosine supplementation. This study provides preliminary support for larger trials evaluating carnosine as a potential treatment for prediabetes and the early stages of T2DM.
escheR: Unified multi-dimensional visualizations with Gestalt principles
Authors: Guo Boyi , Huuki-Myers Louise A. , Grant-Peters Melissa , Collado-Torres Leonardo , Hicks Stephanie C. 
Published: March 2023

AbstractThe creation of effective visualizations is a fundamental component of data analysis. In biomedical research, new challenges are emerging to visualize multi-dimensional data in a 2D space, but current data visualization tools have limited capabilities. To address this problem, we leverage Gestalt principles to improve the design and interpretability of multi-dimensional data in 2D data visualizations, layering aesthetics to display multiple variables. The proposed visualization can be applied to spatially-resolved transcriptomics data, but also broadly to data visualized in 2D space, such as embedding visualizations. We provide an open source R packageescheR, which is built off of the state-of-the-artggplot2visualization framework and can be seamlessly integrated into genomics toolboxes and workflows.Availability and implementationThe open source R packageescheRis freely available on Bioconductor (bioconductor.org/packages/escheR).
Analysis of phage therapy failure in a patient with aPseudomonas aeruginosaprosthetic vascular graft infection
Authors: Blasco Lucia , López-Hernández Inmaculada , Rodríguez-Fernández Miguel , Pérez-Florido Javier , Casimiro-Soriguer Carlos S. , Djebara Sarah , Merabishvili Maya , Pirnay Jean-Paul , Rodríguez-Baño Jesús , Tomás María , López Cortés Luis Eduardo 
Published: March 2023

AbstractClinical case of a patient with aPseudomonas aeruginosamultidrug-resistant prosthetic vascular graft infection which was treated with a cocktail of phages (PT07, 14/01 and PNM) in combination with ceftazidime-avibactam (CAZ/AVI). After the application of the phage treatment and in absence of antimicrobial therapy, a newP. aeruginosabloodstream infection (BSI) with a septic residual limb metastasis occurred, now involving a wild-type strain being susceptible to ß-lactams and quinolones. Clinical strains were analyzed by microbiology and whole genome sequencing techniques. In relation with phage administration, the clinical isolates ofP. aeruginosabefore phage therapy (HE2011471) and post phage therapy (HE2105886) showed a clonal relationship but with important genomic changes which could be involved in the resistance to this therapy. Finally, phenotypic studies showed a decreased in Minimum Inhibitory Concentration (MIC) to ß-lactams and quinolones as well as an increase of the biofilm production and phage resistant mutants in the clinical isolate ofP. aeruginosapost phage therapy.ImportancePhage therapy is a promising new treatment against infections produced by multi-drug resistant pathogens. For that, it would be necessary to know more about the clinical response and host-phage interactions by massive sequencing techniques to improve phage therapy application. In this work, we analyzed the clinical, microbiological and molecular features of theP. aeruginosaisolates in prosthetic vascular graft infection after the phages administration failure against this infection. This knowledge could allow to develop strategies of improvement of the use of phage therapy as treatment of multiple clinical infections.
An Ensemble Learning Approach to perform Link Prediction on Large Scale Biomedical Knowledge Graphs for Drug Repurposing and Discovery
Authors: Prabhakar Vignesh , Vu Chau , Crawford Jennifer , Waite Joseph , Liu Kai 
Published: March 2023

AbstractGenerating knowledge graph embeddings (KGEs) to represent entities (nodes) and relations (edges) in large scale knowledge graph datasets has been a challenging problem in representation learning. This is primarily because the embeddings / vector representations that are required to encode the full scope of data in a large heterogeneous graph needs to have a high dimensionality. The orientation of a large number of vectors requires a lot of space which is achieved by projecting the embeddings to higher dimensions. This is not a scalable solution especially when we expect the knowledge graph to grow in size in order to incorporate more data. Any efforts to constrain the embeddings to lower number of dimensions could be problematic as insufficient space to spatially orient the large number of embeddings / vector representations within limited number of dimensions could lead to poor inferencing on downstream tasks such as link prediction which leverage these embeddings to predict the likelihood of existence of a link between two or more entities in a knowledge graph. This is especially the case with large biomedical knowledge graphs which relate several diverse entities such as genes, diseases, signaling pathways, biological functions etc. that are clinically relevant for the application of KGs to drug discovery. The size of the biomedical knowledge graphs are therefore much larger compared to typical benchmark knowledge graph datasets. This poses a huge challenge in generating embeddings / vector representations of good quality to represent the latent semantic structure of the graph. Attempts to circumvent this challenge by increasing the dimensionality of the embeddings often render hardware limitations as generating high dimensional embeddings is computationally expensive and often times infeasible. To practically deal with representing the latent structure of such large scale knowledge graphs (KGs), our work proposes an ensemble learning model in which the full knowledge graph is sampled into several smaller subgraphs and KGE models generate embeddings for each individual subgraph. The results of link prediction from the KGE models trained on each subgraph are then aggregated to generate a consolidated set of link predictions across the full knowledge graph. The experimental results demonstrated significant improvement in rank-based evaluation metrics on task specific link predictions as well as general link predictions on four open-sourced biomedical knowledge graph datasets.
Genomic clustering by geography not species in taxonomically complex British and Irish eyebrights (Euphrasia)
Authors: Ding Yanqian , Metherell Chris , Huang Wu , Hollingsworth Peter M. , Twyford Alex D. 
Published: March 2023

AbstractGenomic studies of incipient speciation are fundamental to understand the origin and establishment of species. However, a wide range of evolutionary processes and complex evolutionary interactions remain to be explored outside of genetically tractable evolutionary and ecological model systems. Here, we study taxonomically complex British and Irish eyebrights (Euphrasia), as a test case for how different evolutionary factors influence species boundaries across geographic space.Euphrasiais a plant genus that has remarkable diversity in ploidy, mating system and ecology. There are 21 British and IrishEuphrasiaspecies, but with species that are exceptionally difficult to identify based on morphology or DNA barcoding. Here, we test the hypothesis that species boundaries are highly permeable, and taxa experience extensive gene flow despite potential barriers such as ploidy and contrasting mating systems. To understand geographic genetic structure and the nature of species differences, we applied genotyping-by-sequencing (GBS) and spatial-aware clustering methods to 378 population samples from 18 British and Irish species. We find the selfing heathland specialistE. micranthademonstrates genome-wide divergence in Northern Scotland, indicative of a distinct post-glacial colonisation history and the role of a highly selfing mating system in divergence. In contrast, all other genetic clusters correspond to geographic regions, with extensive gene flow between species and a complete absence of species-specific SNPs. Our results reveal the highly permeable species boundaries present in a recently diverging group, with an overriding signal of geographic genetic structure over and above genetic clustering by species.