bluuebunny/crossref_metadata_2025_split huggingface dataset:
AGPs as molecular determinants of reproductive development
Authors: Lopes Ana Lúcia , Moreira Diana , Pereira Ana Marta , Ferraz Ricardo , Mendes Sara , Pereira Luís Gustavo , Colombo Lucia , Coimbra Sílvia 
Published: March 2023

Abstract

Background and Aims
Morphogenesis occurs through accurate interaction between essential players to generate highly specialized plant organs. Fruit structure and function are triggered by a neat transcriptional control involving distinct regulator genes encoding transcription factors (TFs) or signalling proteins, such as the C2H2/C2HC zinc-finger NO TRANSMITTING TRACT (NTT) or the MADS-box protein SEEDSTICK (STK), which are important in setting plant reproductive competence, feasibly by affecting cell wall polysaccharide and lipid distribution. Arabinogalactan proteins (AGPs) are major components of the cell wall and are thought to be involved in the reproductive process as important players in specific stages of development. The detection of AGPs epitopes in reproductive tissues of NTT and other fruit development-related TFs, such as MADS-box proteins including SHATTERPROOF1 (SHP1), SHP2 and STK, was the focus of this study.

Methods
We used fluorescence microscopy to perform immunolocalization analyses on stk and ntt single mutants, on the ntt stk double mutant and on the stk shp1 shp2 triple mutant using specific anti-AGP monoclonal antibodies. In these mutants, the expression levels of selected AGP genes were also measured by quantitative real-time PCR and compared with the respective expression in wild-type (WT) plants.

Key Results
The present immunolocalization study collects information on the distribution patterns of specific AGPs in Arabidopsis female reproductive tissues, complemented by the quantification of AGP expression levels, comparing WT, stk and ntt single mutants, the ntt stk double mutant and the stk shp1 shp2 triple mutant.

Conclusions
These findings reveal distinct AGP distribution patterns in different developmental mutants related to the female reproductive unit in Arabidopsis. The value of the immunofluorescence labelling technique is highlighted in this study as an invaluable tool to dissect the remodelling nature of the cell wall in developmental processes.
Breast Augmentation in the Digital Era: The Power of Social Media in a Surgeon's New Practice
Authors: Montemurro Paolo , Savani Luca , Toninello Paolo 
Published: March 2023

Abstract

Background
Opening a new practice is always challenging, and one of the main problems is how to engage patients. Most of them use social media to gather information about surgery and surgeons.

Objectives
The aim was to evaluate social media's impact on a new practice, compared with a long-standing practice run by the same surgeon. Furthermore, changes in patients’ and surgeons’ perspectives regarding social media in recent years were studied.

Methods
In the 2 aforementioned practices, a questionnaire was administered to patients seen in consultation for primary breast augmentation regarding their interaction with social media before booking the visit. Another questionnaire was administered to 152 surgeons to assess their perceptions of social media.

Results
Two hundred forty-seven patients in Italy and 129 in Sweden answered the questionnaire. In the first year of the Italian practice, 97.2% of patients booked a consultation with the surgeon thanks to social media; after 3 years, the percentage dropped to 68.02%. Comparing Italian and Swedish patients, 68.02% vs 28.68%, respectively, booked a consultation with the surgeon specifically thanks to social media, 91.09% vs 79.84% did research about the surgeon before booking a consultation, and 36.03% vs 10.08% contacted the surgeon before booking an appointment. One hundred fifty-two surgeons from 24 different countries answered the questionnaire, and 77.9% opined that social media positively affected their practice.

Conclusions
Social media is fundamental in patient-surgeon interaction and can strongly influence patient inflow, especially at the beginning of a new practice. Surgeons should be capable of using these tools to engage patients, bearing in mind the important role of these media in patients’ education.
easyPheno: An easy-to-use and easy-to-extendPythonframework for phenotype prediction using Bayesian optimization
Authors: Haselbeck Florian , John Maura , Grimm Dominik G 
Published: March 2023

AbstractSummaryPredicting complex traits from genotypic information is a major challenge in various biological domains. With easyPheno, we present a comprehensive Python framework enabling the rigorous training, comparison and analysis of phenotype predictions for a variety of different models, ranging from common genomic selection approaches over classical machine learning and modern deep learning-based techniques. Our framework is easy-to-use, also for non-programming-experts, and includes an automatic hyperparameter search using state-of-the-art Bayesian optimization. Moreover, easyPheno provides various benefits for bioinformaticians developing new prediction models. easyPheno enables to quickly integrate novel models and functionalities in a reliable framework and to benchmark against various integrated prediction models in a comparable setup. In addition, the framework allows the assessment of newly developed prediction models under pre-defined settings using simulated data. We provide a detailed documentation with various hands-on tutorials and videos explaining the usage of easyPheno to novice users.Availability and implementationeasyPheno is publicly available at https://github.com/grimmlab/easyPheno and can be easily installed as Python package via https://pypi.org/project/easypheno/ or using Docker. A comprehensive documentation including various tutorials complemented with videos can be found at https://easypheno.readthedocs.io/.Supplementary informationSupplementary data are available at Bioinformatics Advances online.
Identification of a gene expression signature associated with breast cancer survival and risk that improves clinical genomic platforms
Authors: Bueno-Fortes Santiago , Berral-Gonzalez Alberto , Sánchez-Santos José Manuel , Martin-Merino Manuel , De Las Rivas Javier 
Published: March 2023

Abstract

Motivation
Modern genomic technologies allow us to perform genome-wide analysis to find gene markers associated with the risk and survival in cancer patients. Accurate risk prediction and patient stratification based on robust gene signatures is a key path forward in personalized treatment and precision medicine. Several authors have proposed the identification of gene signatures to assign risk in patients with breast cancer (BRCA), and some of these signatures have been implemented within commercial platforms in the clinic, such as Oncotype and Prosigna. However, these platforms are black boxes in which the influence of selected genes as survival markers is unclear and where the risk scores provided cannot be clearly related to the standard clinicopathological tumor markers obtained by immunohistochemistry (IHC), which guide clinical and therapeutic decisions in breast cancer.

Results
Here, we present a framework to discover a robust list of gene expression markers associated with survival that can be biologically interpreted in terms of the three main biomolecular factors (IHC clinical markers: ER, PR and HER2) that define clinical outcome in BRCA. To test and ensure the reproducibility of the results, we compiled and analyzed two independent datasets with a large number of tumor samples (1024 and 879) that include full genome-wide expression profiles and survival data. Using these two cohorts, we obtained a robust subset of gene survival markers that correlate well with the major IHC clinical markers used in breast cancer. The geneset of survival markers that we identify (which includes 34 genes) significantly improves the risk prediction provided by the genesets included in the commercial platforms: Oncotype (16 genes) and Prosigna (50 genes, i.e. PAM50). Furthermore, some of the genes identified have recently been proposed in the literature as new prognostic markers and may deserve more attention in current clinical trials to improve breast cancer risk prediction.

Availability and implementation
All data integrated and analyzed in this research will be available on GitHub (https://github.com/jdelasrivas-lab/breastcancersurvsign), including the R scripts and protocols used for the analyses.

Supplementary information
Supplementary data are available at Bioinformatics Advances online.
TB-ML—a framework for comparing machine learning approaches to predict drug resistance ofMycobacterium tuberculosis
Authors: Libiseller-Egger Julian , Wang Linfeng , Deelder Wouter , Campino Susana , Clark Taane G , Phelan Jody E 
Published: March 2023

AbstractMotivationMachine learning (ML) has shown impressive performance in predicting antimicrobial resistance (AMR) from sequence data, including for Mycobacterium tuberculosis, the causative agent of tuberculosis. However, current ML development and publication practices make it difficult for researchers and clinicians to use, test or reproduce published models.ResultsWe packaged a number of published and unpublished ML models for predicting AMR of M.tuberculosis into Docker containers. Similarly, the pipelines required for pre-processing genomic data into the formats required by the models were also packaged into separate containers. By following a minimal container I/O standard, we ensured as much interoperability as possible. We also created a command-line application, TB-ML, which can be used to easily combine pre-processing and prediction containers into complete pipelines ready for predicting resistance from novel, raw data with a single command. As long as there is adherence to this minimal standard for the container interface, containers produced by researchers holding new models can likewise be included in these pipelines, making benchmark comparisons of different models simple and facilitating faster uptake in the clinic.Availability and implementationTB-ML contains a simple Docker API written in Python and is available at https://github.com/jodyphelan/tb-ml. Example Docker containers for resistance prediction and corresponding data pre-processing as well as a tutorial on how to create new containers for TB-ML are available at https://tb-ml.github.io/tb-ml-containers/.Contactjody.phelan@lshtm.ac.uk
A high-performance deep-learning-based pipeline for whole-brain vasculature segmentation at the capillary resolution
Authors: Li Yuxin , Liu Xuhua , Jia Xueyan , Jiang Tao , Wu Jianghao , Zhang Qianlong , Li Junhuai , Li Xiangning , Li Anan 
Published: March 2023

AbstractMotivationReconstructing and analyzing all blood vessels throughout the brain is significant for understanding brain function, revealing the mechanisms of brain disease, and mapping the whole-brain vascular atlas. Vessel segmentation is a fundamental step in reconstruction and analysis. The whole-brain optical microscopic imaging method enables the acquisition of whole-brain vessel images at the capillary resolution. Due to the massive amount of data and the complex vascular features generated by high-resolution whole-brain imaging, achieving rapid and accurate segmentation of whole-brain vasculature becomes a challenge.ResultsWe introduce HP-VSP, a high-performance vessel segmentation pipeline based on deep learning. The pipeline consists of three processes: data blocking, block prediction, and block fusion. We used parallel computing to parallelize this pipeline to improve the efficiency of whole-brain vessel segmentation. We also designed a lightweight deep neural network based on multi-resolution vessel feature extraction to segment vessels at different scales throughout the brain accurately. We validated our approach on whole-brain vascular data from three transgenic mice collected by HD-fMOST. The results show that our proposed segmentation network achieves the state-of-the-art level under various evaluation metrics. In contrast, the parameters of the network are only 1% of those of similar networks. The established segmentation pipeline could be used on various computing platforms and complete the whole-brain vessel segmentation in 3 h. We also demonstrated that our pipeline could be applied to the vascular analysis.Availability and implementationThe dataset is available at http://atlas.brainsmatics.org/a/li2301. The source code is freely available at https://github.com/visionlyx/HP-VSP.
The transcriptomic response of bovine uterine tissue is altered in response to sperm from high- and low-fertility bulls
Authors: Donnellan Eimear M , Cormican Paul , Reid Colm , Duggan Gina , Stiavnicka Miriama , Meade Kieran G , Fair Sean 
Published: March 2023

Abstract
Despite stringent quality control checks, some bulls with apparently normal semen quality yield lower than expected pregnancy rates. This study profiled the transcriptome and performed histological analysis of the bovine uterus in response to sperm from high-fertility (HF) and low-fertility (LF) bulls. Postmortem uterine biopsies and uterine explants were collected from heifers 12 h after a fixed time artificial insemination (AI) to a synchronized estrus with frozen–thawed semen from five HF (fertility rate 4.01% ± 0.25) and five LF (fertility rate − 11.29% ± 1.11; mean ± SEM) bulls. Uterine biopsies were also collected from control (CTRL) heifers, which were not inseminated. RNA-sequencing and histological analysis were performed for differential gene expression and neutrophil quantification. In the HF treatment relative to CTRL heifers, there were 376 genes significantly differentially expressed in the endometrium with just one gene differentially expressed in the LF treatment relative to CTRL heifers. Comparing the HF and LF treatments directly, there were 40 significantly differentially expressed genes (P &lt; 0.05). Transcriptomic analysis shows a predominant role for the inflammatory marker Interleukin-1 alpha, which was further confirmed by immunohistochemistry. Quantification of neutrophils in the endometrium showed a significant effect of sperm; however, there was no difference in neutrophil numbers between HF and LF groups. In conclusion, this novel study clearly shows a distinct inflammatory response to sperm in the endometrium and a divergent transcriptomic response to semen from HF and LF bulls.
Modeling Respiratory Syncytial Virus Adult Vaccination in the United States With a Dynamic Transmission Model
Authors: Van Effelterre T , Hens N , White L J , Gravenstein S , Bastian A R , Buyukkaramikli N , Cheng C Y , Hartnett J , Krishnarajah G , Weber K , Pastor L Hernandez 
Published: March 2023

Abstract

Background
Respiratory syncytial virus (RSV) is shown to cause substantial morbidity, hospitalization, and mortality in infants and older adults. Population-level modeling of RSV allows to estimate the full burden of disease and the potential epidemiological impact of novel prophylactics.

Methods
We modeled the RSV epidemiology in the United States across all ages using a deterministic compartmental transmission model. Population-level symptomatic RSV acute respiratory tract infection (ARI) cases were projected across different natural history scenarios with and without vaccination of adults aged ≥60 years. The impact of vaccine efficacy against ARIs, infectiousness and vaccine coverage on ARI incidence were assessed. The impact on medical attendance, hospitalization, complications, death, and other outcomes was also derived.

Results
Without a vaccine, we project 17.5–22.6 million symptomatic RSV ARI cases annually in adults aged ≥18 years in the US, with 3.6–4.8 million/year occurring in adults aged ≥60 years. Modeling indicates that up to 2.0 million symptomatic RSV-ARI cases could be prevented annually in ≥60-year-olds with a hypothetical vaccine (70% vaccine efficacy against symptomatic ARI and 60% vaccine coverage) and that up to 0.69 million/year could be prevented in the nonvaccinated population, assuming 50% vaccine impact on infectiousness.

Conclusions
The model provides estimated burden of RSV in the US across all age groups, with substantial burden projected specifically in older adults. Vaccination of adults aged ≥60 years could significantly reduce the burden of disease in this population, with additional indirect effect in adults aged &lt;60 years due to reduced transmissibility.
Isolation and Quarantine for Coronavirus Disease 2019 in the United States, 2020–2022
Authors: Oeltmann John E , Vohra Divya , Matulewicz Holly H , DeLuca Nickolas , Smith Jonathan P , Couzens Chandra , Lash R Ryan , Harvey Barrington , Boyette Melissa , Edwards Alicia , Talboy Philip M , Dubose Odessa , Regan Paul , Loosier Penny , Caruso Elise , Katz Dolores J , Taylor Melanie M , Moonan Patrick K 
Published: March 2023

Abstract

Background
Public health programs varied in ability to reach people with coronavirus disease 2019 (COVID-19) and their contacts to encourage separation from others. For both adult case patients with COVID-19 and their contacts, we estimated the impact of contact tracing activities on separation behaviors from January 2020 until March 2022.

Methods
We used a probability-based panel survey of a nationally representative sample to gather data for estimates and comparisons.

Results
An estimated 64 255 351 adults reported a positive severe acute respiratory syndrome coronavirus 2 test result; 79.6% isolated for ≥5 days, 60.2% isolated for ≥10 days, and 79.2% self-notified contacts. A total of, 24 057 139 (37.7%) completed a case investigation, and 46.2% of them reported contacts to health officials. More adults who completed a case investigation isolated than those who did not complete a case investigation (≥5 days, 82.6% vs 78.2%, respectively; ≥10 days, 69.8% vs 54.8%; both P &lt; .05). A total of 84 946 636 adults were contacts of a COVID-19 case patient. Of these, 73.1% learned of their exposure directly from a case patient; 49.4% quarantined for ≥5 days, 18.7% quarantined for ≥14 days, and 13.5% completed a contact tracing call. More quarantined among those who completed a contact tracing call than among those who did not complete a tracing call (≥5 days, 61.2% vs 48.5%, respectively; ≥14 days, 25.2% vs 18.0%; both P &lt; .05).

Conclusions
Engagement in contact tracing was positively correlated with isolation and quarantine. However, most adults with COVID-19 isolated and self-notified contacts regardless of whether the public health workforce was able to reach them. Identifying and reaching contacts was challenging and limited the ability to promote quarantining, and testing.
Attainment of Target Antibiotic Levels by Oral Treatment of Left-Sided Infective Endocarditis: A POET Substudy
Authors: Bock Magnus , Theut Anna Marie , van Hasselt Johan G C , Wang Hengzhuang , Fuursted Kurt , Høiby Niels , Lerche Christian Johann , Ihlemann Nikolaj , Gill Sabine , Christiansen Ulrik , Nielsen Hans Linde , Lemming Lars , Elming Hanne , Povlsen Jonas A , Bruun Niels Eske , Høfsten Dan , Fosbøl Emil L , Køber Lars , Schultz Martin , Pries-Heje Mia M , Kristensen Jonas Henrik , Christensen Jens Jørgen , Rosenvinge Flemming S , Pedersen Christian Torp , Helweg-Larsen Jannik , Tønder Niels , Iversen Kasper , Bundgaard Henning , Moser Claus 
Published: March 2023

Abstract

Background
In the POET (Partial Oral Endocarditis Treatment) trial, oral step-down therapy was noninferior to full-length intravenous antibiotic administration. The aim of the present study was to perform pharmacokinetic/pharmacodynamic analyses for oral treatments of infective endocarditis to assess the probabilities of target attainment (PTAs).

Methods
Plasma concentrations of oral antibiotics were measured at day 1 and 5. Minimal inhibitory concentrations (MICs) were determined for the bacteria causing infective endocarditis (streptococci, staphylococci, or enterococci). Pharmacokinetic/pharmacodynamic targets were predefined according to literature using time above MIC or the ratio of area under the curve to MIC. Population pharmacokinetic modeling and pharmacokinetic/pharmacodynamic analyses were done for amoxicillin, dicloxacillin, linezolid, moxifloxacin, and rifampicin, and PTAs were calculated.

Results
A total of 236 patients participated in this POET substudy. For amoxicillin and linezolid, the PTAs were 88%–100%. For moxifloxacin and rifampicin, the PTAs were 71%–100%. Using a clinical breakpoint for staphylococci, the PTAs for dicloxacillin were 9%–17%.
Seventy-four patients at day 1 and 65 patients at day 5 had available pharmacokinetic and MIC data for 2 oral antibiotics. Of those, 13 patients at day 1 and 14 patients at day 5 did only reach the target for 1 antibiotic. One patient did not reach target for any of the 2 antibiotics.

Conclusions
For the individual orally administered antibiotic, the majority reached the target level. Patients with sub-target levels were compensated by the administration of 2 different antibiotics. The findings support the efficacy of oral step-down antibiotic treatment in patients with infective endocarditis.
Yield of diagnosis and risk of stroke with screening strategies for atrial fibrillation: a comprehensive review of current evidence
Authors: Corica Bernadette , Bonini Niccolò , Imberti Jacopo Francesco , Romiti Giulio Francesco , Vitolo Marco , Attanasio Lisa , Basili Stefania , Freedman Ben , Potpara Tatjana S , Boriani Giuseppe , Lip Gregory Y H , Proietti Marco 
Published: March 2023

AbstractAtrial fibrillation (AF) is the most prevalent arrhythmia worldwide. The presence of AF is associated with increased risk of systemic thromboembolism, but with the uptake of oral anticoagulant (OAC) and implementation of a holistic and integrated care management, this risk is substantially reduced. The diagnosis of AF requires a 30-s-long electrocardiographic (ECG) trace, irrespective of the presence of symptoms, which may represent the main indication for an ECG tracing. However, almost half patients are asymptomatic at the time of incidental AF diagnosis, with similar risk of stroke of those with clinical AF. This has led to a crucial role of screening for AF, to increase the diagnosis of population at risk of clinical events. The aim of this review is to give a comprehensive overview about the epidemiology of asymptomatic AF, the different screening technologies, the yield of diagnosis in asymptomatic population, and the benefit derived from screening in terms of reduction of clinical adverse events, such as stroke, cardiovascular, and all-cause death. We aim to underline the importance of implementing AF screening programmes and reporting about the debate between scientific societies’ clinical guidelines recommendations and the concerns expressed by the regulatory authorities, which still do not recommend population-wide screening. This review summarizes data on the ongoing trials specifically designed to investigate the benefit of screening in terms of risk of adverse events which will further elucidate the importance of screening in reducing risk of outcomes and influence and inform clinical practice in the next future.