bluuebunny/crossref_metadata_2025_split huggingface dataset:
Kidney Failure Risk Equation in vascular access planning: a population-based study supporting value in decision making
Authors: Atiquzzaman Mohammad , Zhu Bingyue , Romann Alexandra , Er Lee , Djurdjev Ognjenka , Bevilacqua Micheli , Wong Michelle M Y , Birks Peter , Yi Tae Won , Singh Anurag , Tangri Navdeep , Levin Adeera 
Published: January 2024

ABSTRACT

Background
The Kidney Failure Risk Equation (KFRE) can play a better role in vascular access (VA) planning in patients with chronic kidney disease (CKD) requiring hemodialysis (HD). We described the VA creation and utilization pattern under existing estimated glomerular filtration rate (eGFR)-based referral, and investigated the utility of KFRE score as an adjunct variable in VA planning.

Methods
Patients with CKD aged ≥18 years with eGFR &lt;20 mL/min/1.73 m2 who chose HD as dialysis modality from January 2010 to August 2020 were included from a population-based database in British Columbia, Canada. Modality selection date was the index date. Exposures were categorized as (i) current eGFR-based referral, (ii) eGFR-based referral plus KRFE 2-year risk score on index date (KFRE-2) &gt;40% and (iii) eGFR-based referral plus KFRE-2 ≤40%. We estimated the proportion of patients who started HD on arteriovenous fistula/graft (AVF/G) within 2 years, indicating timely pre-emptive creation, and the proportion of patients in whom AVF/G was created but did not start HD within 2 years, indicating too-early creation.

Results
Study included 2581 patients, median age 71 years, 60% male. Overall, 1562(61%) started HD and 276 (11%) experienced death before HD initiation within 2 years. Compared with current referral, the proportion of patients who started HD on AVF/G was significantly higher when KFRE-2 was considered in addition to current referral (49% vs 58%, P-value &lt;.001). Adjunct KFRE-2 significantly reduced too-early creation (31% vs 18%, P-value &lt;.001).

Conclusions
KFRE in addition to existing eGFR-based referral for VA creation has the potential to improve VA resource utilization by ensuring more patients start HD on AVF/G and may minimize too-early/unnecessary creation. Prospective research is necessary to validate these findings.
Shared decision-making performance of general practice residents: an observational study combining observer, resident, and patient perspectives
Authors: Baghus Anouk , Giroldi Esther , van Geel Jasper , Leferink Arthur , van de Pol Marjolein H J , Sanders Ariëtte , Dielissen Patrick W , Bisschop Isabella , Pieterse Arwen H , Muris Jean W M , Timmerman Angelique A , van der Weijden Trudy 
Published: January 2024

Abstract

Background
Shared decision making (SDM) is considered fundamental to person-centred care. However, applying SDM may be a challenge for residents in general practice, since it is a complex competence that requires the integration of knowledge and skills from several competency domains.

Objective
To support learning of SDM during medical residency, we aimed to gain insight in Dutch residents’ observed and perceived SDM performance in general practice.

Methods
We evaluated residents’ SDM performance from an observer, resident, and patient perspective. Consultations of first- and third-year residents were recorded. Trained observers used the validated Observing Patient Involvement (OPTION5) scale to assess observed SDM performance of residents in 98 actual recorded consultations. Perceived SDM performance was evaluated by residents and patients completing validated SDM questionnaires, supplemented with questions about (the context of) the consultation and perceived relevance of SDM immediately after the consultation. The data were analysed using descriptive statistics (mean, SD, minimums, and maximums) and explorative bivariate analyses.

Results
The residents’ observed mean SDM performance was 19.1 (range, 0–100, SD = 10.9), mean resident self-reported SDM performance was 56.9 (range, 0–100, SD = 18.5), and mean patient-reported SDM performance was 73.3 (range, 0–100, SD = 26.8). We found a significant and positive correlation between observed SDM performance and residents’ perceived relevance of SDM for the consultation (t = 4.571, P ≤ 0.001) and the duration of the consultation (r = 0.390, P ≤ 0.001).

Conclusions
This study showed that there is room for increasing awareness of the potential incongruence between observed and perceived SDM performance during medical residency, in order to facilitate the implementation of SDM in clinical practice.
The chromosome-scale genome of Magnolia sinica (Magnoliaceae) provides insights into the conservation of plant species with extremely small populations (PSESP)
Authors: Cai Lei , Liu Detuan , Yang Fengmao , Zhang Rengang , Yun Quanzheng , Dao Zhiling , Ma Yongpeng , Sun Weibang 
Published: January 2024

Abstract
Magnolia sinica (Magnoliaceae) is a highly threatened tree endemic to southeast Yunnan, China. In this study, we generated for the first time a high-quality chromosome-scale genome sequence from M. sinica, by combining Illumina and ONT data with Hi-C scaffolding methods. The final assembled genome size of M. sinica was 1.84 Gb, with a contig N50 of ca. 45 Mb and scaffold N50 of 92 Mb. Identified repeats constituted approximately 57% of the genome, and 43,473 protein-coding genes were predicted. Phylogenetic analysis shows that the magnolias form a sister clade with the eudicots and the order Ceratophyllales, while the monocots are sister to the other core angiosperms. In our study, a total of 21 individuals from the 5 remnant populations of M. sinica, as well as 22 specimens belonging to 8 related Magnoliaceae species, were resequenced. The results showed that M. sinica had higher genetic diversity (θw = 0.01126 and θπ = 0.01158) than other related species in the Magnoliaceae. However, population structure analysis suggested that the genetic differentiation among the 5 M. sinica populations was very low. Analyses of the demographic history of the species using different models consistently revealed that 2 bottleneck events occurred. The contemporary effective population size of M. sinica was estimated to be 10.9. The different patterns of genetic loads (inbreeding and numbers of deleterious mutations) suggested constructive strategies for the conservation of these 5 different populations of M. sinica. Overall, this high-quality genome will be a valuable genomic resource for conservation of M. sinica.
A graph clustering algorithm for detection and genotyping of structural variants from long reads
Authors: Gaitán Nicolás , Duitama Jorge 
Published: January 2024

Abstract

Background
Structural variants (SVs) are genomic polymorphisms defined by their length (&gt;50 bp). The usual types of SVs are deletions, insertions, translocations, inversions, and copy number variants. SV detection and genotyping is fundamental given the role of SVs in phenomena such as phenotypic variation and evolutionary events. Thus, methods to identify SVs using long-read sequencing data have been recently developed.

Findings
We present an accurate and efficient algorithm to predict germline SVs from long-read sequencing data. The algorithm starts collecting evidence (signatures) of SVs from read alignments. Then, signatures are clustered based on a Euclidean graph with coordinates calculated from lengths and genomic positions. Clustering is performed by the DBSCAN algorithm, which provides the advantage of delimiting clusters with high resolution. Clusters are transformed into SVs and a Bayesian model allows to precisely genotype SVs based on their supporting evidence. This algorithm is integrated into the single sample variants detector of the Next Generation Sequencing Experience Platform, which facilitates the integration with other functionalities for genomics analysis. We performed multiple benchmark experiments, including simulation and real data, representing different genome profiles, sequencing technologies (PacBio HiFi, ONT), and read depths.

Conclusion
The results show that our approach outperformed state-of-the-art tools on germline SV calling and genotyping, especially at low depths, and in error-prone repetitive regions. We believe this work significantly contributes to the development of bioinformatic strategies to maximize the use of long-read sequencing technologies.
CD301 and LSECtin glycan-binding receptors of innate immune cells serve as prognostic markers and potential predictors of immune response in breast cancer subtypes
Authors: Wegscheider Anne-Sophie , Wojahn Irina , Gottheil Pablo , Spohn Michael , Käs Joseph Alfons , Rosin Olga , Ulm Bernhard , Nollau Peter , Wagener Christoph , Niendorf Axel , Wolters-Eisfeld Gerrit 
Published: January 2024

Abstract
Glycosylation is a prominent posttranslational modification, and alterations in glycosylation are a hallmark of cancer. Glycan-binding receptors, primarily expressed on immune cells, play a central role in glycan recognition and immune response. Here, we used the recombinant C-type glycan-binding receptors CD301, Langerin, SRCL, LSECtin, and DC-SIGNR to recognize their ligands on tissue microarrays (TMA) of a large cohort (n = 1859) of invasive breast cancer of different histopathological types to systematically determine the relevance of altered glycosylation in breast cancer. Staining frequencies of cancer cells were quantified in an unbiased manner by a computer-based algorithm. CD301 showed the highest overall staining frequency (40%), followed by LSECtin (16%), Langerin (4%) and DC-SIGNR (0.5%). By Kaplan-Meier analyses, we identified LSECtin and CD301 as prognostic markers in different breast cancer subtypes. Positivity for LSECtin was associated with inferior disease-free survival in all cases, particularly in estrogen receptor positive (ER+) breast cancer of higher histological grade. In triple negative breast cancer, positivity for CD301 correlated with a worse prognosis. Based on public RNA single-cell sequencing data of human breast cancer infiltrating immune cells, we found CLEC10A (CD301) and CLEC4G (LSECtin) exclusively expressed in distinct subpopulations, particularly in dendritic cells and macrophages, indicating that specific changes in glycosylation may play a significant role in breast cancer immune response and progression.
Integrated Single-cell Multiomic Analysis of HIV Latency Reversal Reveals Novel Regulators of Viral Reactivation
Authors: Ashokkumar Manickam , Mei Wenwen , Peterson Jackson J , Harigaya Yuriko , Murdoch David M , Margolis David M , Kornfein Caleb , Oesterling Alex , Guo Zhicheng , Rudin Cynthia D , Jiang Yuchao , Browne Edward P 
Published: January 2024

Abstract
Despite the success of antiretroviral therapy, human immunodeficiency virus (HIV) cannot be cured because of a reservoir of latently infected cells that evades therapy. To understand the mechanisms of HIV latency, we employed an integrated single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq) approach to simultaneously profile the transcriptomic and epigenomic characteristics of ∼ 125,000 latently infected primary CD4+ T cells after reactivation using three different latency reversing agents. Differentially expressed genes and differentially accessible motifs were used to examine transcriptional pathways and transcription factor (TF) activities across the cell population. We identified cellular transcripts and TFs whose expression/activity was correlated with viral reactivation and demonstrated that a machine learning model trained on these data was 75%–79% accurate at predicting viral reactivation. Finally, we validated the role of two candidate HIV-regulating factors, FOXP1 and GATA3, in viral transcription. These data demonstrate the power of integrated multimodal single-cell analysis to uncover novel relationships between host cell factors and HIV latency.
MSIsensor-RNA: Microsatellite Instability Detection for Bulk and Single-cell Gene Expression Data
Authors: Jia Peng , Yang Xuanhao , Yang Xiaofei , Wang Tingjie , Xu Yu , Ye Kai 
Published: January 2024

Abstract
Microsatellite instability (MSI) is an indispensable biomarker in cancer immunotherapy. Currently, MSI scoring methods by high-throughput omics methods have gained popularity and demonstrated better performance than the gold standard method for MSI detection. However, the MSI detection method on expression data, especially single-cell expression data, is still lacking, limiting the scope of clinical application and prohibiting the investigation of MSI at a single-cell level. Herein, we developed MSIsensor-RNA, an accurate, robust, adaptable, and standalone software to detect MSI status based on expression values of MSI-associated genes. We demonstrated the favorable performance and promise of MSIsensor-RNA in both bulk and single-cell gene expression data in multiplatform technologies including RNA sequencing (RNA-seq), microarray, and single-cell RNA-seq. MSIsensor-RNA is a versatile, efficient, and robust method for MSI status detection from both bulk and single-cell gene expression data in clinical studies and applications. MSIsensor-RNA is available at https://github.com/xjtu-omics/msisensor-rna.
SMARTdb: An Integrated Database for Exploring Single-cell Multi-omics Data of Reproductive Medicine
Authors: Liu Zekai , Yuan Zhen , Guo Yunlei , Wang Ruilin , Guan Yusheng , Wang Zhanglian , Chen Yunan , Wang Tianlu , Jiang Meining , Bian Shuhui 
Published: January 2024

Abstract
Single-cell multi-omics sequencing has greatly accelerated reproductive research in recent years, and the data are continually growing. However, utilizing these data resources is challenging for wet-lab researchers. A comprehensive platform for exploring single-cell multi-omics data related to reproduction is urgently needed. Here, we introduce the single-cell multi-omics atlas of reproduction (SMARTdb), an integrative and user-friendly platform for exploring molecular dynamics of reproductive development, aging, and disease, which covers multi-omics, multi-species, and multi-stage data. We curated and analyzed single-cell transcriptomic and epigenomic data of over 2.0 million cells from 6 species across the entire lifespan. A series of powerful functionalities are provided, such as “Query gene expression”, “DIY expression plot”, “DNA methylation plot”, and “Epigenome browser”. With SMARTdb, we found that the male germ cell-specific expression pattern of RPL39L and RPL10L is conserved between human and other model animals. Moreover, DNA hypomethylation and open chromatin may collectively regulate the specific expression pattern of RPL39L in both male and female germ cells. In summary, SMARTdb is a powerful platform for convenient data mining and gaining novel insights into reproductive development, aging, and disease. SMARTdb is publicly available at https://smart-db.cn.
Building a Text and Data Mining Limitation: The Brazilian Case
Authors: Schirru Luca , Rocha de Souza Allan , Chamas Claudia 
Published: January 2024

Abstract
In recent years, there has been a growing body of legal regulation of text and data mining (TDM). Since 2018, Japan, the European Union, Singapore and others have promoted changes to their copyright law and included specific limitations and exceptions for TDM. These changes have been slow in the Global South and the developing world, even though they are urgently needed there. This report aims to present the Brazilian copyright legal framework and the policy documents related to Intellectual Property, Artificial Intelligence and innovation influencing political and public debate. This set of policies and legislative texts provides the grounds for the discussion on the need for a TDM Limitation in Brazil, a debate which has been intensified within the scope of the work carried out by a special commission that was convened by the Brazilian Senate to work on a substitute draft for the AI Bill. Brazil’s TDM provision is focused on uses carried out by public-interest-oriented organizations. It found its place within the Bill on AI as a distinct topic and is currently formally part of Bill 2338/2023, which is being discussed in the Senate. While there is a reasonable possibility that the TDM provision will be voted on and approved in the Senate, recent developments on Generative AI may bring even more complexity to the debate on the interplay between AI and copyright.
EasyDAM_V4: Guided-GAN-based cross-species data labeling for fruit detection with significant shape difference
Authors: Zhang Wenli , Liu Yuxin , Wang Chenhuizi , Zheng Chao , Cui Guoqiang , Guo Wei 
Published: January 2024

Abstract
Traditional agriculture is gradually being combined with artificial intelligence technology. High-performance fruit detection technology is an important basic technology in the practical application of modern smart orchards and has great application value. At this stage, fruit detection models need to rely on a large number of labeled datasets to support the training and learning of detection models, resulting in higher manual labeling costs. Our previous work uses a generative adversarial network to translate the source domain to the target fruit images. Thus, automatic labeling is performed on the actual dataset in the target domain. However, the method still does not achieve satisfactory results for translating fruits with significant shape variance. Therefore, this study proposes an improved fruit automatic labeling method, EasyDAM_V4, which introduces the Across-CycleGAN fruit translation model to achieve spanning translation between phenotypic features such as fruit shape, texture, and color to reduce domain differences effectively. We validated the proposed method using pear fruit as the source domain and three fruits with large phenotypic differences, namely pitaya, eggplant, and cucumber, as the target domain. The results show that the EasyDAM_V4 method achieves substantial cross-fruit shape translation, and the average accuracy of labeling reached 87.8, 87.0, and 80.7% for the three types of target domain datasets, respectively. Therefore, this research method can improve the applicability of the automatic labeling process even if significant shape variance exists between the source and target domain.
CsMYB73 negatively regulates theanine accumulation mediated by CsGGT2 and CsGGT4 in tea shoots (Camellia sinensis)
Authors: Chang Manman , Sun Ying , Fang Kangzhi , Fu Maoyin , Ma Jingyu , Gao Yang , Chen Qi , Liu Linlin , Zhang Zhaoliang , Wan Xiaochun , Sun Jun 
Published: January 2024

Abstract
Theanine metabolism is a necessary biological process during the planting and production of tea that determines tea quality. There is currently little knowledge about the transcriptional regulation of theanine metabolism in tea plants. In this study, we demonstrated that γ-glutamyl-transpeptidase CsGGT4, as a homologous protein of the theanine hydrolase CsGGT2, exhibited a higher theanine synthesis catalytic efficiency. Homology modeling and molecular docking showed that differential protein structures between CsGGT2 and CsGGT4 implied their different biological functions in tea plants. Theanine content correlated significantly with the expression of CsGGT2, CsGGT4 and the transcription factor CsMYB73 in tea shoots from different seasons. Additionally, CsMYB73 was confirmed to act as a nucleus-localized transcription factor (TF), directly interacts with the CsGGT2 and CsGGT4 promoters, serving as an activator of CsGGT2 and a suppressor of CsGGT4. Consequently, this leads to a negative association with theanine accumulation in tea shoots. Furthermore, the continuous increase in CsMYB73 produced a significantly increase in CsGGT2 expression and inhibited CsGGT4 expression. The present study reveals that the degradation of theanine has been observed to increase, concomitantly with the inhibition of theanine synthesis, resulting in a significant decline in the accumulation of theanine in tea shoots during the process of seasonal greening in ‘Huangkui’ leaves. This study contributes to the broader comprehension of the intricate transcriptional regulatory hierarchy that governs the metabolism of theanine in tea shoots, offering novel approaches for managing tea plantations and enhancing tea quality.
ChatGPT: a reliable fertility decision-making tool?
Authors: Beilby Kiri , Hammarberg Karin 
Published: January 2024

Abstract
The internet is the primary source of infertility-related information for most people who are experiencing fertility issues. Although no longer shrouded in stigma, the privacy of interacting only with a computer provides a sense of safety when engaging with sensitive content and allows for diverse and geographically dispersed communities to connect and share their experiences. It also provides businesses with a virtual marketplace for their products. The introduction of ChatGPT, a conversational language model developed by OpenAI to understand and generate human-like text in response to user input, in November 2022, and other emerging generative artificial intelligence (AI) language models, has changed and will continue to change the way we interact with large volumes of digital information. When it comes to its application in health information seeking, specifically in relation to fertility in this case, is ChatGPT a friend or foe in helping people make well-informed decisions? Furthermore, if deemed useful, how can we ensure this technology supports fertility-related decision-making? After conducting a study into the quality of the information provided by ChatGPT to people seeking information on fertility, we explore the potential benefits and pitfalls of using generative AI as a tool to support decision-making.
The Impact of Inflammatory Bowel Disease on Intimacy: A Multimethod Examination of Patients’ Sexual Lives and Associated Healthcare Experiences
Authors: Fretz Katherine M , Hunker Katherine E , Tripp Dean A 
Published: January 2024

Abstract

Background
Inflammatory bowel disease (IBD) can negatively impact sexual well-being, and some patients desire healthcare for these issues. Research capturing the lived experiences of patients in these areas is lacking. The present study investigated the sexual well-being impacts of IBD (objective 1) and patients’ experiences accessing support for these concerns in the healthcare system (objective 2) through multimethod analyses.

Methods
A total of 480 adults with IBD were recruited for an online survey study. Reflexive thematic analysis was used to analyze responses to 2 open-ended questions (ie, qualitative data; question 1, n = 326, question 2, n = 309). Frequency analyses and contingency tables were used to analyze quantitative data (n = 436).

Results
Thematic analysis (objective 1) generated 8 themes highlighting the negative impacts of IBD on patients’ sexual/intimate lives (eg, sexual activity, intimate relationships) and the influence of broader psychosocial experiences (eg, self-perception, mental health) on patients’ sexual well-being. Quantitative analyses (objective 2) indicated that 39.2% of participants wanted sexual health information from a healthcare provider, but only 5.7% of our sample reported both wanting and receiving this information. Thematic analysis generated 5 themes highlighting the lack of support and information available for sexuality concerns in IBD healthcare and detailed patients’ perceived barriers to obtaining support in this area.

Conclusions
IBD has myriad impacts on patients’ sexual lives. However, patients who want healthcare in this area rarely receive satisfactory support.