bluuebunny/crossref_metadata_2025_split huggingface dataset:
The curious case of selenium hyperaccumulation in Coelospermum decipiens from the Cape York Peninsula (Queensland, Australia)
Authors: Harvey Maggie-Anne , Pinto Irish Katherine , Harris Hugh H , Erskine Peter D , van der Ent Antony 
Published: June 2024

Abstract

Background and Aims
The tropical shrub Coelospermum decipiens (Rubiaceae) is an extreme selenium (Se) hyperaccumulator, reported to accumulate up to 1140 µg Se g−1 when found growing on soils with levels of Se below the limit of detection (i.e. &lt;0.01 mg Se kg−1) leading to a bioconcentration factor of &gt;100 000.

Methods
Coelospermum decipiens plants were sampled from different populations in far north Queensland and analysed for Se concentrations. Plant material was subjected to synchrotron X-ray fluorescence microscopy (XFM) and synchrotron X-ray absorption spectroscopy (XAS) investigations to gain insights into the elemental distribution and chemical speciation of Se.

Results
The foliar Se concentrations ranged from 100 to 1000 µg Se g−1, except for the seeds, which had up to 28 000 µg Se g−1. The soils from the Hope Vale area were locally Se-enriched up to 48 mg Se kg−1, but there was no relationship between soil and plant Se concentrations. Synchrotron XFM analysis revealed that Se was localized in the blade margin tissue of the younger leaves, whilst the XAS analysis determined that Se occurs as an organo-Se compound.

Conclusions
We report the occurrence of seleniferous soils in the Cape York Peninsula soils for the first time, which may partly explain the evolution of Se hyperaccumulation in C. decipiens. The extremely high concentrations of Se in the seeds is suggestive of a herbivory protection function. The capacity of this species to accumulate and hyperaccumulate Se from non-seleniferous soils is akin to that of other ‘seed’-based accumulators, such as some members of the Lecythidaceae family.
Inference of gene regulatory networks based on directed graph convolutional networks
Authors: Wei Pi-Jing , Guo Ziqiang , Gao Zhen , Ding Zheng , Cao Rui-Fen , Su Yansen , Zheng Chun-Hou 
Published: June 2024

Abstract
Inferring gene regulatory network (GRN) is one of the important challenges in systems biology, and many outstanding computational methods have been proposed; however there remains some challenges especially in real datasets. In this study, we propose Directed Graph Convolutional neural network-based method for GRN inference (DGCGRN). To better understand and process the directed graph structure data of GRN, a directed graph convolutional neural network is conducted which retains the structural information of the directed graph while also making full use of neighbor node features. The local augmentation strategy is adopted in graph neural network to solve the problem of poor prediction accuracy caused by a large number of low-degree nodes in GRN. In addition, for real data such as E.coli, sequence features are obtained by extracting hidden features using Bi-GRU and calculating the statistical physicochemical characteristics of gene sequence. At the training stage, a dynamic update strategy is used to convert the obtained edge prediction scores into edge weights to guide the subsequent training process of the model. The results on synthetic benchmark datasets and real datasets show that the prediction performance of DGCGRN is significantly better than existing models. Furthermore, the case studies on bladder uroepithelial carcinoma and lung cancer cells also illustrate the performance of the proposed model.
Optimal linear ensemble of binary classifiers
Authors: Ahsen Mehmet Eren , Vogel Robert , Stolovitzky Gustavo 
Published: June 2024

Abstract

Motivation
The integration of vast, complex biological data with computational models offers profound insights and predictive accuracy. Yet, such models face challenges: poor generalization and limited labeled data.

Results
To overcome these difficulties in binary classification tasks, we developed the Method for Optimal Classification by Aggregation (MOCA) algorithm, which addresses the problem of generalization by virtue of being an ensemble learning method and can be used in problems with limited or no labeled data. We developed both an unsupervised (uMOCA) and a supervised (sMOCA) variant of MOCA. For uMOCA, we show how to infer the MOCA weights in an unsupervised way, which are optimal under the assumption of class-conditioned independent classifier predictions. When it is possible to use labels, sMOCA uses empirically computed MOCA weights. We demonstrate the performance of uMOCA and sMOCA using simulated data as well as actual data previously used in Dialogue on Reverse Engineering and Methods (DREAM) challenges. We also propose an application of sMOCA for transfer learning where we use pre-trained computational models from a domain where labeled data are abundant and apply them to a different domain with less abundant labeled data.

Availability and implementation
GitHub repository, https://github.com/robert-vogel/moca.
Document-level biomedical relation extraction via hierarchical tree graph and relation segmentation module
Authors: Yuan Jianyuan , Zhang Fengyu , Qiu Yimeng , Lin Hongfei , Zhang Yijia 
Published: June 2024

Abstract

Motivation
Biomedical relation extraction at the document level (Bio-DocRE) involves extracting relation instances from biomedical texts that span multiple sentences, often containing various entity concepts such as genes, diseases, chemicals, variants, etc. Currently, this task is usually implemented based on graphs or transformers. However, most work directly models entity features to relation prediction, ignoring the effectiveness of entity pair information as an intermediate state for relation prediction. In this article, we decouple this task into a three-stage process to capture sufficient information for improving relation prediction.

Results
We propose an innovative framework HTGRS for Bio-DocRE, which constructs a hierarchical tree graph (HTG) to integrate key information sources in the document, achieving relation reasoning based on entity. In addition, inspired by the idea of semantic segmentation, we conceptualize the task as a table-filling problem and develop a relation segmentation (RS) module to enhance relation reasoning based on the entity pair. Extensive experiments on three datasets show that the proposed framework outperforms the state-of-the-art methods and achieves superior performance.

Availability and implementation
Our source code is available at https://github.com/passengeryjy/HTGRS.
Multimodal subtypes identified in Alzheimer’s Disease Neuroimaging Initiative participants by missing-data-enabled subtype and stage inference
Authors: Estarellas Mar , Oxtoby Neil P , Schott Jonathan M , Alexander Daniel C , Young Alexandra L 
Published: June 2024

Abstract
Alzheimer’s disease is a highly heterogeneous disease in which different biomarkers are dynamic over different windows of the decades-long pathophysiological processes, and potentially have distinct involvement in different subgroups. Subtype and Stage Inference is an unsupervised learning algorithm that disentangles the phenotypic heterogeneity and temporal progression of disease biomarkers, providing disease insight and quantitative estimates of individual subtype and stage. However, a key limitation of Subtype and Stage Inference is that it requires a complete set of biomarkers for each subject, reducing the number of datapoints available for model fitting and limiting applications of Subtype and Stage Inference to modalities that are widely collected, e.g. volumetric biomarkers derived from structural MRI. In this study, we adapted the Subtype and Stage Inference algorithm to handle missing data, enabling the application of Subtype and Stage Inference to multimodal data (magnetic resonance imaging, positron emission tomography, cerebrospinal fluid and cognitive tests) from 789 participants in the Alzheimer’s Disease Neuroimaging Initiative. Missing-data Subtype and Stage Inference identified five subtypes having distinct progression patterns, which we describe by the earliest unique abnormality as ‘Typical AD with Early Tau’, ‘Typical AD with Late Tau’, ‘Cortical’, ‘Cognitive’ and ‘Subcortical’. These new multimodal subtypes were differentially associated with age, years of education, Apolipoprotein E (APOE4) status, white matter hyperintensity burden and the rate of conversion from mild cognitive impairment to Alzheimer’s disease, with the ‘Cognitive’ subtype showing the fastest clinical progression, and the ‘Subcortical’ subtype the slowest. Overall, we demonstrate that missing-data Subtype and Stage Inference reveals a finer landscape of Alzheimer’s disease subtypes, each of which are associated with different risk factors. Missing-data Subtype and Stage Inference has broad utility, enabling the prediction of progression in a much wider set of individuals, rather than being restricted to those with complete data.
UCP1 expression in human brown adipose tissue is inversely associated with cardiometabolic risk factors
Authors: Kwok T’ng Choong , Ramage Lynne E , Kelman Alexandra , Suchacki Karla J , Gray Calum , Boyle Luke D , Semple Scott I , MacGillivray Tom , MacNaught Gillian , Patel Dilip , van Beek Edwin J R , Semple Robert K , Wakelin Sonia J , Stimson Roland H 
Published: June 2024

Abstract

Objective
Brown adipose tissue (BAT) is a therapeutic target for obesity. 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) is commonly used to quantify human BAT mass and activity. Detectable 18F-FDG uptake by BAT is associated with reduced prevalence of cardiometabolic disease. However, 18F-FDG uptake may not always be a reliable marker of BAT thermogenesis, for example, insulin resistance may reduce glucose uptake. Uncoupling protein 1 (UCP1) is the key thermogenic protein in BAT. Therefore, we hypothesised that UCP1 expression may be altered in individuals with cardiometabolic risk factors.

Methods
We quantified UCP1 expression as an alternative marker of thermogenic capacity in BAT and white adipose tissue (WAT) samples (n = 53) and in differentiated brown and white pre-adipocytes (n = 85).

Results
UCP1 expression in BAT, but not in WAT or brown/white differentiated pre-adipocytes, was reduced with increasing age, obesity, and adverse cardiometabolic risk factors such as fasting glucose, insulin, and blood pressure. However, UCP1 expression in BAT was preserved in obese subjects of &lt;40 years of age. To determine if BAT activity was also preserved in vivo, we undertook a case-control study, performing 18F-FDG scanning during mild cold exposure in young (mean age ∼22 years) normal weight and obese volunteers. 18F-FDG uptake by BAT and BAT volume were similar between groups, despite increased insulin resistance.

Conclusion
18F-FDG uptake by BAT and UCP1 expression are preserved in young obese adults. Older subjects retain precursor cells with the capacity to form new thermogenic adipocytes. These data highlight the therapeutic potential of BAT mass expansion and activation in obesity.
HLA investigation in ICI-induced T1D and isolated ACTH deficiency including meta-analysis
Authors: Ono Mayo , Nagao Mototsugu , Takeuchi Haruki , Fukunaga Etsuya , Nagamine Tomoko , Inagaki Kyoko , Fukuda Izumi , Iwabu Masato 
Published: June 2024

Abstract

Objective
Widespread use of immune checkpoint inhibitors (ICIs) in cancer treatment has led to an increase in the number of reported cases of immunotherapy-related endocrinopathies. This study aimed to analyze and compare human leukocyte antigen (HLA) signatures associated with ICI-induced type 1 diabetes (ICI-T1D) and isolated adrenocorticotropic hormone deficiency (ICI-IAD) in patients with both conditions.

Methods
HLA signatures were examined for their frequencies of occurrence in 22 patients with ICI-T1D without concurrent IAD, including 16 patients from nationwide reports (ICI-T1D group) and 14 patients with ICI-IAD without concurrent T1D (ICI-IAD group). The HLA signatures were also compared for their respective frequencies in 11 patients with ICI-T1D and ICI-IAD, including eight from nationwide reports (ICI-T1D/IAD group).

Results
In the ICI-T1D group, HLA-DRB1*09:01-DQB1*03:03 and DQA1*03:02, which are in linkage disequilibrium with DRB1*09:01-DQB1*03:03 and DRB1*13:02-DQB1*06:04, were susceptible to ICI-T1D, whereas DRB1*15:02-DQB1*06:01 was protective against ICI-T1D. In the ICI-IAD group, DPB1*09:01, C*12:02-B*52:01, and DRB1*15:02-DRB1*06:01, which are in strong linkage disequilibrium, were associated with susceptibility to ICI-IAD. Moreover, DRB1*15:02-DRB1*06:01 was not detected in the ICI-T1D/IAD group.

Conclusions
This study revealed specific HLA signatures associated with ICI-T1D and ICI-IAD. Moreover, HLA-DRB1*15:02-DRB1*06:01, an ICI-IAD-susceptible HLA haplotype, coincides with the ICI-T1D-protective HLA haplotype, suggesting that the presence of DRB1*15:02-DRB1*06:01 may protect against the co-occurrence of T1D in patients with ICI-IAD.
Digest: Individual- and population-level effects of SARS-CoV-2 evolution and changing preventative measures
Authors: Punchihewa Sehan 
Published: June 2024

Abstract
Although COVID-19 is no longer classified as a pandemic, variants of SARS-CoV-2 continue to arise. It is critical to understand how changes in viral characteristics, public policy, and behavior affect disease load and mortality. An analysis by Otto et al. (2024) shows that changes in transmission rate and immunological properties have differing effects on disease load, even among variants with similar selective advantages. The impact of various strategies aimed at countering disease spread is also analyzed.
Evolution of species recognition when ecology and sexual selection favor signal stasis
Authors: Singh Pratap , Price Trevor D 
Published: June 2024

Abstract
The process of reproductive character displacement involves divergence and/or the narrowing of variance in traits involved in species recognition, driven by interactions between taxa. However, stabilizing sexual selection may favor stasis and species similarity in these same traits if signals are optimized for transmission through the prevailing environment. Further, sexual selection may promote increased variability within species to facilitate individual recognition. Here we ask how the conflicting selection pressures of species recognition and sexual selection are resolved in a genus of Himalayan birds that sing exceptionally similar songs. We experimentally show that small differences in two traits (note shape and peak frequency) are both necessary and sufficient for species recognition. Song frequency shows remarkable clinal variation along the Himalayan elevational gradient, being most divergent where species co-occur, the classic signature of reproductive character displacement. Note shape shows no such clinal variation but varies more between individuals of an allopatric species than it does among individuals within species that co-occur. We argue that the different note shapes experience similar transmission constraints, and differences produced through species interactions spread back through the entire species range. Our results imply that reproductive character displacement is likely to be common.
Effect of different degumming methods on the chemical composition and physicochemical properties of tiger nut (Cyperus esculentus L.) oil
Authors: Zhang Runyang , Li Jiake , Zhu Wenxue , Chen Pengxiao , Jiang Mengmeng , Liu Huamin 
Published: June 2024

Abstract

Objectives
Tiger nut (Cyperus esculentus L.) oil is a promising edible oil that is rich in oleic acid. This study aimed to clarify the impact of different degumming methods on the chemical composition and physicochemical properties of crude tiger nut oil (CTO).

Materials and Methods
Five degummed tiger nut oils were prepared by high-temperature water (HWDO), medium-temperature water (MWDO), sodium chloride solution (SDO), acidic solution (ADO), and enzymatic method (EDO), respectively.

Results
Compared to that of CTO, the phospholipid contents of HWDO, MWDO, SDO, ADO, and EDO were reduced by 99.39%, 97.18%, 69.95%, 63.77%, and 65.60%, respectively. For CTO and all degummed oils, the fatty acid and endogenous antioxidant (i.e. tocopherols, sterols, flavonoids, total phenolics, and carotenoids) contents showed only small differences, but showed significant differences in quality parameters. Both the oxidative stability index and ferric ion-reducing antioxidant power decreased significantly after degumming; the former decreased from 52.26 to 15.55–19.80 h, and the latter decreased from 5818.91 to 4348.73–4524.34 μmol Trolox (TE)/kg.

Conclusions
These changes are highly related to the removal of hydratable phospholipids. In short, EDO exhibited the lowest turbidity, whereas MWDO showed the best oxidative stability (19.80 h) and highest smoke point (230.0 °C). This information can be utilized to improve the industrial production of tiger nut oil.
A nested reciprocal experimental design to map the genetic architecture of transgenerational phenotypic plasticity
Authors: Che Jincan , Wang Yu , Dong Ang , Cao Yige , Wu Shuang , Wu Rongling 
Published: June 2024

Abstract
Extensive studies have revealed the ecological and evolutionary significance of phenotypic plasticity, but little is known about how it is inherited between generations and the genetic architecture of its transgenerational inheritance. To address these issues, we design a mapping study by growing Arabidopsis thaliana RILs in high- and low-light environments and further growing their offspring RILs from each maternal light environment in the same contrasting environments. This tree-like design of the controlled ecological experiment provides a framework for analysing the genetic regulation of phenotypic plasticity and its non-genetic inheritance. We implement the computational approach of functional mapping to identify specific QTLs for transgenerational phenotypic plasticity. By estimating and comparing the plastic response of leaf-number growth trajectories to light environment between generations, we find that the maternal environment affects phenotypic plasticity, whereas transgenerational plasticity is shaped by the offspring environment. The genetic architecture underlying the light-induced change of leaf number not only changes from parental to offspring generations, but also depends on the maternal environment the parental generation experienced and the offspring environment the offspring generation is experiencing. Most plasticity QTLs are annotated to the genomic regions of candidate genes for specific biological functions. Our computational-experimental design provides a unique insight into dissecting the non-genetic and genetic mechanisms of phenotypic plasticity shaping plant adaptation and evolution in various forms.
Single-cell Transcriptomic Studies Unveil Potential Nodes of the Notochord Gene Regulatory Network
Authors: Negrón-Piñeiro Lenny J , Di Gregorio Anna 
Published: June 2024

Synopsis
Transcription factors (TFs) are DNA-binding proteins able to modulate the timing, location, and levels of gene expression by binding to regulatory DNA regions. Therefore, the repertoire of TFs present in the genome of a multicellular organism and the expression of variable constellations of TFs in different cellular cohorts determine the distinctive characteristics of developing tissues and organs. The information on tissue-specific assortments of TFs, their cross-regulatory interactions, and the genes/regulatory regions targeted by each TF is summarized in gene regulatory networks (GRNs), which provide genetic blueprints for the specification, development, and differentiation of multicellular structures. In this study, we review recent transcriptomic studies focused on the complement of TFs expressed in the notochord, a distinctive feature of all chordates. We analyzed notochord-specific datasets available from organisms representative of the three chordate subphyla, and highlighted lineage-specific variations in the suite of TFs expressed in their notochord. We framed the resulting findings within a provisional evolutionary scenario, which allows the formulation of hypotheses on the genetic/genomic changes that sculpted the structure and function of the notochord on an evolutionary scale.
Comparing clinical and echocardiographic outcomes following valve-sparing versus transannular patch repair of tetralogy of Fallot: a systematic review and meta-analysis
Authors: Martins Russell Seth , Fatimi Asad Saulat , Mahmud Omar , Qureshi Saleha , Nasim Muhammad Taha , Virani Sehar Salim , Tameezuddin Aimen , Yasin Fatima , Malik Mahim Akmal 
Published: June 2024

Abstract

OBJECTIVES
Transannular patch (TAP) repair of tetralogy of Fallot (ToF)relieves right ventricular tract obstruction but may lead to pulmonary regurgitation. Valve-sparing (VS) procedures can avoid this situation, but there is a potential for residual pulmonary stenosis. Our goal was to evaluate clinical and echocardiographic outcomes of TAP and VS repair for ToF.

METHODS
A systematic search of the PubMed, Embase, Scopus, Cochrane Central Register of Controlled Trials and Web of Science databases was carried out to identify articles comparing conventional TAP repair and VS repair for ToF. Random-effects models were used to perform meta-analyses of the clinical and echocardiographic outcomes.

RESULTS
Forty studies were included in this meta-analysis with data on 11 723 participants (TAP: 6171; VS: 5045). Participants who underwent a VS procedure experienced a significantly lower cardiopulmonary bypass time [mean difference (MD): −14.97; 95% confidence interval (CI): −22.54, −7.41], shorter ventilation duration (MD: −15.33; 95% CI: −30.20, −0.46) and shorter lengths of both intensive care unit (ICU) (MD: −0.67; 95% CI: −1.29, −0.06) and hospital stays (MD: −2.30; 95% CI: [−4.08, −0.52). There was also a lower risk of mortality [risk ratio: 0.40; 95% CI: (0.27, 0.60) and pulmonary regurgitation [risk ratio: 0.35; 95% CI: (0.26, 0.46)] associated with the VS group. Most other clinical and echocardiographic outcomes were comparable in the 2 groups.

CONCLUSIONS
This meta-analysis confirms the well-established increased risk of pulmonary insufficiency following TAP repair while also demonstrating that VS repairs are associated with several improved clinical outcomes. Continued research can identify the criteria for adopting a VS approach as opposed to a traditional TAP repair.
Cellular interactions and evolutionary origins of endosymbiotic relationships with ciliates
Authors: Song Qi , Zhao Fangqing , Hou Lina , Miao Miao 
Published: June 2024

Abstract
As unicellular predators, ciliates engage in close associations with diverse microbes, laying the foundation for the establishment of endosymbiosis. Originally heterotrophic, ciliates demonstrate the ability to acquire phototrophy by phagocytizing unicellular algae or by sequestering algal plastids. This adaptation enables them to gain photosynthate and develop resistance to unfavorable environmental conditions. The integration of acquired phototrophy with intrinsic phagotrophy results in a trophic mode known as mixotrophy. Additionally, ciliates can harbor thousands of bacteria in various intracellular regions, including the cytoplasm and nucleus, exhibiting species specificity. Under prolonged and specific selective pressure within hosts, bacterial endosymbionts evolve unique lifestyles and undergo particular reductions in metabolic activities. Investigating the research advancements in various endosymbiotic cases within ciliates will contribute to elucidate patterns in cellular interaction and unravel the evolutionary origins of complex traits.