bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic growth QTL action in diverse light environments: characterization of light regime-specific and stable QTL in Arabidopsis
Authors: Meyer Rhonda C , Weigelt-Fischer Kathleen , Tschiersch Henning , Topali Georgia , Altschmied Lothar , Heuermann Marc C , Knoch Dominic , Kuhlmann Markus , Zhao Yusheng , Altmann Thomas 
Published: June 2023

Abstract
Plant growth is a complex process affected by a multitude of genetic and environmental factors and their interactions. To identify genetic factors influencing plant performance under different environmental conditions, vegetative growth was assessed in Arabidopsis thaliana cultivated under constant or fluctuating light intensities, using high-throughput phenotyping and genome-wide association studies. Daily automated non-invasive phenotyping of a collection of 382 Arabidopsis accessions provided growth data during developmental progression under different light regimes at high temporal resolution. Quantitative trait loci (QTL) for projected leaf area, relative growth rate, and PSII operating efficiency detected under the two light regimes were predominantly condition-specific and displayed distinct temporal activity patterns, with active phases ranging from 2 d to 9 d. Eighteen protein-coding genes and one miRNA gene were identified as potential candidate genes at 10 QTL regions consistently found under both light regimes. Expression patterns of three candidate genes affecting projected leaf area were analysed in time-series experiments in accessions with contrasting vegetative leaf growth. These observations highlight the importance of considering both environmental and temporal patterns of QTL/allele actions and emphasize the need for detailed time-resolved analyses under diverse well-defined environmental conditions to effectively unravel the complex and stage-specific contributions of genes affecting plant growth processes.
Influence of planets on debris discs in star clusters – I. The 50 au Jupiter
Authors: Wu Kai , Kouwenhoven M B N , Spurzem Rainer , Pang Xiaoying 
Published: June 2023

ABSTRACT
Although debris discs may be common in exoplanet systems, only a few systems are known in which debris discs and planets coexist. Planets and the surrounding stellar population can have a significant impact on debris disc evolution. Here, we study the dynamical evolution of debris structures around stars embedded in star clusters, aiming to determine how the presence of a planet affects the evolution of such structures. We combine NBODY6++GPU and REBOUND to carry out N-body simulations of planetary systems in star clusters ($N=8\, 000$; Rh = 0.78 pc) for a period of 100 Myr, in which 100 solar-type stars are assigned 200 test particles. Simulations are carried out with and without a Jupiter-mass planet at 50 au. We find that the planet destabilizes test particles and speeds up their evolution. The planet expels most particles in nearby and resonant orbits. Remaining test particles tend to retain small inclinations when the planet is present, and fewer test particles obtain retrograde orbits. Most escaping test particles with speeds smaller than the star cluster’s escape speed originate from cold regions of the planetary system or from regions near the planet. We identify three regions within planetary systems in star clusters: (i) the private region of the planet, where few debris particles remain (40–60 au), (ii) the reach of the planet, in which particles are affected by the planet (0–400 au), and (iii) the territory of the planetary system, most particles outside which will eventually escape (0–700 au).
High Coverage Highly Accurate Long-Read Sequencing of a Mouse Neuronal Cell Line Using the PacBio Revio Sequencer
Authors: Manuel Juana G. , Heins Hillary B. , Crocker Sandra , Neidich Julie A. , Sadzewicz Lisa , Tallon Luke , Turner Tychele N. 
Published: June 2023

ABSTRACTRecently, Pacific Biosciences released a new highly accurate long-read sequencer called the Revio System that is projected to generate 30× HiFi whole-genome sequencing for the human genome within one sequencing SMRT Cell. Mouse and human genomes are similar in size. In this study, we sought to test this new sequencer by characterizing the genome and epigenome of the mouse neuronal cell line Neuro-2a. We generated long-read HiFi whole-genome sequencing on three Revio SMRT Cells, achieving a total coverage of 98×, with 30×, 32×, and 36× coverage respectively for each of the three Revio SMRT Cells. We performed several tests on these data including single-nucleotide variant and small insertion detection using GPU-accelerated DeepVariant, structural variant detection with pbsv, methylation detection with pb-CpG-tools, and generatingde novoassemblies with the HiCanu and hifiasm assemblers. Overall, we find consistency across SMRT Cells in coverage, detection of variation, methylation, andde novoassemblies for each of the three SMRT Cells.
Identification of tumor-specific MHC ligands through improved biochemical isolation and incorporation of machine learning
Authors: Mecklenbräuker Shima , Skoczylas Piotr , Biernat Paweł , Zaghla Badeel , Król-Józaga Bartłomiej , Jasiński Maciej , Pienkowski Victor Murcia , Sanecka-Duin Anna , Popp Oliver , Szatanek Rafał , Mertins Philipp , Kaczmarczyk Jan , Blum Agnieszka , Klatt Martin 
Published: June 2023

AbstractIsolation of MHC ligands and subsequent analysis by mass spectrometry is considered the gold standard for defining targets for TCR-T immunotherapies. However, as many targets of high tumor-specificity are only presented at low abundance on the cell surface of tumor cells, the efficient isolation of these peptides is crucial for their successful detection. Here, we demonstrate how different isolation strategies, which consider hydrophobicity and post-translational modifications, can improve the detection of MHC ligands, including cysteinylated MHC ligands from cancer germline antigens or point-mutated neoepitopes. Furthermore, we developed a novel MHC class I ligand prediction algorithm (ARDisplay-I) that outperforms the current state-of-the-art and facilitates the assignment of peptides to the correct MHC allele. The model has other applications, such as the identification of additional MHC ligands not detected from mass spectrometry or determining whether the MHC ligands can be presented on the cell surface via MHC alleles not included in the study. The implementation of these strategies can augment the development of T cell receptor-based therapies (i.a. TIL1-derived T cells, genetically engineered T cells expressing tumor recognizing receptors or TCR-mimic antibodies) by facilitating the identification of novel immunotherapy targets and by enriching the resources available in the field of computational immunology.Significance:This study demonstrates how the isolation of different tumor-specific MHC ligands can be optimized when considering their hydrophobicity and post-translational modification status. Additionally, we developed a novel machine-learning model for the probability prediction of the MHC ligands’ presentation on the cell surface. The algorithm can assign these MHC ligands to their respective MHC alleles which is essential for the design of TCR-T immunotherapies.
Structural basis of CMKLR1 signaling induced by chemerin9
Authors: Zhang Xuan , Weiß Tina , Cheng Mary Hongying , Chen Siqi , Ambrosius Carla Katharina , Czerniak Anne Sophie , Li Kunpeng , Feng Mingye , Bahar Ivet , Beck-Sickinger Annette G. , Zhang Cheng 
Published: June 2023

AbstractChemokine-like receptor 1 (CMKLR1), also known as chemerin receptor 23 (ChemR23) or chemerin receptor 1, is a chemoattractant G protein-coupled receptor (GPCR) that responds to the adipokine chemerin and is highly expressed in innate immune cells, including macrophages and neutrophils. The signaling pathways of CMKLR1 can lead to both pro- and anti-inflammatory effects depending on the ligands and physiological contexts. To understand the molecular mechanisms of CMKLR1 signaling, we determined a high-resolution cryo-electron microscopy (cryo-EM) structure of the CMKLR1-Gisignaling complex with chemerin9, a nanopeptide agonist derived from chemerin, which induced complex phenotypic changes of macrophages in our assays. The cryo-EM structure, together with molecular dynamics simulations and mutagenesis studies, revealed the molecular basis of CMKLR1 signaling by elucidating the interactions at the ligand-binding pocket and the agonist-induced conformational changes. Our results are expected to facilitate the development of small molecule CMKLR1 agonists that mimic the action of chemerin9 to promote the resolution of inflammation.
Kinesin-14 HSET and KlpA are non-processive microtubule motors with load-dependent power strokes
Authors: Liu Xinglei , Rao Lu , Qiu Weihing , Gennerich Arne 
Published: June 2023

AbstractAccurate chromosome segregation during cell division relies on coordinated actions of microtubule (MT)-based motor proteins in the mitotic spindle. Kinesin-14 motors play vital roles in spindle assembly and maintenance by crosslinking antiparallel MTs at the spindle midzone and anchoring spindle MTs’ minus ends at the poles. We investigate the force generation and motility of the Kinesin-14 motors HSET and KlpA, revealing that both motors function as non-processive motors under load, producing single power strokes per MT encounter. Each homodimeric motor generates forces of ∼0.5 pN, but when assembled in teams, they cooperate to generate forces of 1 pN or more. Importantly, cooperative activity among multiple motors leads to increased MT-sliding velocities. Our findings deepen our understanding of the structure-function relationship of Kinesin-14 motors and underscore the significance of cooperative behavior in their cellular functions.
Two-million-year-old microbial communities from the Kap København Formation in North Greenland
Authors: Fernandez-Guerra Antonio , Wörmer Lars , Borrel Guillaume , Delmont Tom O , Elberling Bo , Elvert Marcus , Eren A. Murat , Gribaldo Simonetta , Henriksen Rasmus Amund , Hinrichs Kai-Uwe , Jochheim Annika , Korneliussen Thorfinn S. , Krupovic Mart , Larsen Nicolaj K. , Perez-Laso Rafael , Pedersen Mikkel Winther , Pedersen Vivi K. , Ruter Anthony H. , Sand Karina K. , Sikora Martin , Steinegger Martin , Veseli Iva , Wang Yucheng , Zhao Lei , Žure Marina , Kjær Kurt H. , Willerslev Eske 
Published: June 2023

SummaryEnvironmental DNA (eDNA) from the 2-million-year-old Kap København Formation of northern Greenland has revealed an ecosystem of plants and animals with no contemporary analogue1. Here, we reconstruct the microbial (bacterial, archaeal, and viral) communities that thrived at the site during this time. By leveraging a novel analytical framework that integrates taxonomic profiling, DNA damage estimates, and functional reconstructions, we identify and distinguish pioneer microbial communities from later permafrost microbial assemblages. We show that at the time of sediment deposition, the terrestrial input at the Kap København site originated from a palustrine wetland, suggesting warmer, non-permafrost conditions. During this period, the detection of methanogenic archaea and signals of their carbon metabolism is consistent with Kap København and similar northern ecosystems contributing moderate methane emissions. Intriguingly, we discover a remarkable nucleotide sequence similarity—exceeding 98%—between pioneer methanogens and present-day analogues in thawing permafrost. This aligns with the concept of “time-traveling” microbes2surviving across geological time and waiting for conditions to turn favourable rather than evolving to adapt to changing conditions. Importantly, in contrast to the plant and animal communities of the Kap København, a striking similarity in microbial composition to that of a contemporary thawing Arctic suggests that microbial communities may serve as the first indication of broader climate-driven ecosystem disruptions.
Structure of the N-RNA/P interface reveals mode of L/P attachment to the nucleocapsid of human metapneumovirus
Authors: Whitehead Jack D. , Decool Hortense , Leyrat Cédric , Carrique Loic , Fix Jenna , Eléouët Jean-François , Galloux Marie , Renner Max 
Published: June 2023

AbstractHuman metapneumovirus (HMPV) is a major cause of respiratory illness in young children. The polymerase complex of HMPV consists of two obligate components, the L polymerase and its cofactor, the phosphoprotein P. During replication and transcription, the L/P complex traverses the viral RNA genome, which is encapsidated within multimerized N nucleoproteins. An essential interaction between N and a C-terminal region of P is required for tethering of the L/P polymerase to the RNA template. This N-P interaction is also involved in the formation of cytoplasmic viral factories in infected cells, called inclusion bodies. To define how L/P recognizes N-encapsidated RNA (N-RNA) we employed cryogenic electron microscopy (cryo-EM) and molecular dynamics simulations, coupled to polymerase activity assays and imaging of inclusion bodies in transfected cells. We report a 2.9 Å resolution structure of a triple-complex between multimeric N, bound to both RNA and the C-terminal region of P. Furthermore, we also present cryo-EM structures of assembled N in different oligomeric states, highlighting the plasticity of N. Combined with our functional assays, these structural data delineate in molecular detail how P attaches to N-RNA whilst retaining substantial conformational dynamics. Moreover, the N-RNA-P triple complex structure provides a molecular blueprint for the design of therapeutics to potentially disrupt the attachment of L/P to its template.
Biological embedding of childhood adversity - a multi-omics perspective on stress regulation
Authors: Zang Johannes C.S. , May Caroline , Marcus Katrin , Kumsta Robert 
Published: June 2023

AbstractThe experience of adversity in childhood can have life-long consequences on health outcomes. In search of mediators of this relationship, alterations of bio-behavioral and cellular regulatory systems came into focus, including those dealing with basic gene regulatory processes. Systems biology oriented approaches have been proposed to gain a more comprehensive understanding of the complex multiple interrelations between and within layers of analysis. We used co-expression based, supervised and unsupervised single and multi-omics system approaches to investigate the influence of childhood adversity on gene expression, protein expression and DNA methylation in CD14+monocytes of healthy adults before and after exposure to an experimental psychosocial stress protocol. Childhood adversity explained some variance at the single analyte level and within gene and protein co-expression structures. A single-omic, post stress gene expression model differentiated best between participants with a history of childhood adversity and controls in supervised analyses. In unsupervised analyses, a multi-omics based model showed best performance but separated participants based on sex only. Multi-omics analyses are a promising concept but might yield different results based on the specific approach taken and the omic-datasets supplied. Here, stress associated gene-expression pattern were most strongly associated with childhood adversity, and integrating multiple cellular layers did not results in better discriminatory performance. Currently, the capacity and yield of different omics-profiling methods might limit the full potential of integrative approaches.
Degree apprenticeships in the UK higher education institutions – are they viable?: Integrative literature review
Authors: Quew-Jones Rebecca Jane 
Published: June 2023

PurposeApprenticeships for higher education institutes (HEIs) at degree and postgraduate levels in the UK have been challenging to provide, requiring increasingly complex collaboration and investment. This questions longer-term viability, creating a new perspective investigating evidence of value and impact for UK HEIs. This integrative literature review examines existing apprenticeship literature and showcases new knowledge for HEIs to update and inform future decision-making. Knowledge created offers a new framework, an “apprenticeship knowledge-based checklist model” and a perspective to explore further.Design/methodology/approachThis integrative literature review examines apprenticeship provision viability for UK HEIs across several disciplines since commencement.FindingsAnalysis of selected studies across three research themes critiques potential apprenticeship practice for HEIs: stakeholder collaboration, widening participation and work-integrated learning. Results provided a new integrated perspective via governance levels: strategic, academic department, and teaching team.Research limitations/implicationsThe research draws from multiple disciplines representing current literature in the HEI Apprenticeships field. However, the context in which programmes are delivered by HEIs and employers differs significantly, so factors continue to emerge.Practical implicationsPractical implications drawn from these findings aim to cultivate dialogue before embarking/withdrawing from HEI Apprenticeship programmes. It offers employers guidance expectations when partnering with university providers. For global apprenticeship provisions, it offers a checklist for re-valuating practice.Originality/valueThe research identified new knowledge implications from existing literature in a field experiencing rapid growth. It offers valuable contributions: a knowledge-based checklist model constructed for HEIs to evaluate existing and future viability provisions at each governance level. It is a catalyst for new practice approaches and an agenda for further research.
A novel approach to automatic seizure detection using computer vision and independent component analysis
Authors: Garção Vicente M. , Abreu Mariana , Peralta Ana R. , Bentes Carla , Fred Ana , P. da Silva Hugo 
Published: June 2023

AbstractObjectiveEpilepsy is a neurological disease that affects ~50 million people worldwide, 30% of which have refractory epilepsy and recurring seizures, which may contribute to higher anxiety levels and poorer quality of life. Seizure detection may contribute to addressing some of the challenges associated with this condition, by providing information to health professionals regarding seizure frequency, type, and/or location in the brain, thereby improving diagnostic accuracy and medication adjustment, and alerting caregivers or emergency services of dangerous seizure episodes. The main focus of this work was the development of an accurate video‐based seizure‐detection method that ensured unobtrusiveness and privacy preservation, and provided novel approaches to reduce confounds and increase reliability.MethodsThe proposed approach is a video‐based seizure‐detection method based on optical flow, principal component analysis, independent component analysis, and machine learning classification. This method was tested on a set of 21 tonic–clonic seizure videos (5–30 min each, total of 4 h and 36 min of recordings) from 12 patients using leave‐one‐subject‐out cross‐validation.ResultsHigh accuracy levels were observed, namely a sensitivity and specificity of 99.06% ± 1.65% at the equal error rate and an average latency of 37.45 ± 1.31 s. When compared to annotations by health care professionals, the beginning and ending of seizures was detected with an average offset of 9.69 ± 0.97 s.SignificanceThe video‐based seizure‐detection method described herein is highly accurate. Moreover, it is intrinsically privacy preserving, due to the use of optical flow motion quantification. In addition, given our novel independence‐based approach, this method is robust to different lighting conditions, partial occlusions of the patient, and other movements in the video frame, thereby setting the base for accurate and unobtrusive seizure detection.
Factors predicting proactive work behaviors among nurses: A descriptive predictive study
Authors: Htet Hsu Yee , Abhicharttibutra Kulwadee , Wichaikum Orn‐Anong 
Published: June 2023

AbstractAimThis study examined the level of proactive work behavior and predictability of education level, work engagement, transformational leadership of nurse managers, and organizational support on proactive work behaviors among nurses.BackgroundNurses face many challenges to provide quality nursing care as numbers of patients increase in particular as a result of COVID‐19 and human resource shortages worldwide, this includes Myanmar. Proactive work behavior is a critical factor in providing quality nursing care.MethodsWe collected data from 183 registered nurses in four university‐affiliated general hospitals in Myanmar by using stratified random sampling. Instruments included the Utrecht Work Engagement Scale, the Global Transformational Leadership Scale, the Survey of Perceived Organizational Support, and the Proactive Work Behavior Scale. Descriptive statistics and multiple regression were used to analyze data. Findings are reported according to the STROBE checklist.ResultsThe overall level of proactive work behavior was perceived as moderate. Transformational leadership and work engagement were significant predictors of proactive work behaviors of nurses, explaining 33.0% of the total variance.ConclusionFindings provide that both transformational leadership and work engagement are significant predictors of proactive work behaviors which are important for improving the quality of patient care and organizational outcomes.Implications for nursing and health policyNurse administrators and hospital directors should encourage nurses to voice ideas for improving the standard of work, provide opportunities for generating ideas, support resources for taking charge and preventing problems whilst also supporting the promotion of nurse managers' transformational leadership and nurses' work engagement.
Screw‐retained ceramic‐veneered/monolithic zirconia partial implant‐supported fixed dental prostheses: A 5 to 10‐year retrospective study on survival and complications
Authors: Zhang Yifan , Luo Jia , Di Ping , Chen Bo , Li Jianhui , Yu Ziyang , Lin Ye 
Published: June 2023

AbstractPurposeTo assess the clinical performance of screw‐retained, ceramic‐veneered, monolithic zirconia partial implant‐supported fixed dental prostheses (ISFDP) over 5–10 years and to evaluate implant‐ and prosthesis‐related factors influencing treatment failure and complications.Materials and methodsPartially edentulous patients treated with screw‐retained all‐ceramic ISFDPs with 2–4 prosthetic units with a documented follow‐up of ≥5 years after implant loading were included in this retrospective study. The outcomes analyzed included implant/prosthesis failure and biological/technical complications. Possible risk factors were identified using the mixed effects Cox regression analysis.ResultsA screened sample of 171 participants with 208 prostheses (95% of the restorations were splinted crowns without a pontic) supported by 451 dental implants were enrolled in this study. The mean follow‐up duration after prosthesis delivery was 82.4 ±17.2 months. By the end of the follow‐up period, 431 (95.57%) of the 451 implants remained functional at the implant level. At the prosthesis level, 185 (88.94%) of the 208 partial ISFDPs remained functional. Biological complications were observed in 67 implants (14.86%), and technical complications were observed in 62 ISFDPs (29.81%). Analysis revealed only emergence profiles (over‐contoured) as a significant risk factor for implant failure (P<0.001) and biological complications (P<0.001). Full‐coverage ceramic‐veneered zirconia prostheses had a significantly greater chance of chipping (P<0.001) compared with buccal‐ceramic‐veneered or monolithic zirconia prostheses.ConclusionsScrew‐retained ceramic‐veneered, monolithic partial ISFDPs have a favorable long‐term survival rate. Over‐contoured emergence profile is a significant risk factor associated with implant failure and biological complications. Buccal‐ceramic‐veneered and monolithic zirconia partial ISFDPs lower the initial prevalence of chipping compared with a full‐coverage veneered design.