bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unraveling Vulnerabilities in Endocrine Therapy-Resistant HER2+/ER+ Breast Cancer
Authors: Bahnassy Shaymaa , Stires Hillary , Jin Lu , Tam Stanley , Mobin Dua , Balachandran Manasi , Podar Mircea , McCoy Matthew D. , Beckman Robert A. , Riggins Rebecca B. 
Published: August 2023

ABSTRACTBackgroundBreast tumors overexpressing human epidermal growth factor receptor (HER2) confer intrinsic resistance to endocrine therapy (ET), and patients with HER2/ estrogen receptor-positive (HER2+/HR+) breast cancer (BCa) are less responsive to ET than HER2−/ER+. However, real-world evidence reveals that a large subset of HER2+/ER+ patients receive ET as monotherapy, positioning this treatment pattern as a clinical challenge. In the present study, we developed and characterized two distinctin vitromodels of ET-resistant (ETR) HER2+/ER+ BCa to identify possible therapeutic vulnerabilities.MethodsTo mimic ETR to aromatase inhibitors (AI), we developed two long-term estrogen-deprived (LTED) cell lines from BT-474 (BT474) and MDA-MB-361 (MM361). Growth assays, PAM50 molecular subtyping, genomic and transcriptomic analyses, followed by validation and functional studies, were used to identify targetable differences between ET-responsive parental and ETR-LTED HER2+/ER+ cells.ResultsCompared to their parental cells, MM361 LTEDs grew faster, lost ER, and increased HER2 expression, whereas BT474 LTEDs grew slower and maintained ER and HER2 expression. Both LTED variants had reduced responsiveness to fulvestrant. Whole-genome sequencing of the more aggressive MM361 LTED model system identified exonic mutations in genes encoding transcription factors and chromatin modifiers. Single-cell RNA sequencing demonstrated a shift towards non-luminal phenotypes, and revealed metabolic remodeling of MM361 LTEDs, with upregulated lipid metabolism and antioxidant genes associated with ferroptosis, includingGPX4. Combining the GPX4 inhibitor RSL3 with anti-HER2 agents induced significant cell death in both the MM361 and BT474 LTEDs.ConclusionsThe BT474 and MM361 AI-resistant models capture distinct phenotypes of HER2+/ER+ BCa and identify altered lipid metabolism and ferroptosis remodeling as vulnerabilities of this type of ETR BCa.
The “Duckweed Dip”: AquaticSpirodela polyrhizaPlants Can Efficiently Uptake Dissolved, DNA-Wrapped Carbon Nanotubes from Their Environment for Transient Gene Expression
Authors: Islam Tasmia , Kalkar Swapna , Tinker-Kulberg Rachel , Ignatova Tetyana , Josephs Eric A. 
Published: August 2023

ABSTRACTDuckweeds (Lemnaceae) are aquatic non-grass monocots that are the smallest and fastest-growing flowering plants in the world. While having simplified morphologies, relatively small genomes, and many other ideal traits for emerging applications in plant biotechnology, duckweeds have been largely overlooked in this era of synthetic biology. Here, we report that Greater Duckweed (Spirodela polyrhiza), when simply incubated in a solution containing plasmid-wrapped carbon nanotubes (DNA-CNTs), can directly up-take the DNA-CNTs from their growth media with high efficiency and that transgenes encoded within the plasmids are expressed by the plants—without the usual need for large doses of nanomaterials or agrobacterium to be directly infiltrated into plant tissue. This process, called the “duckweed dip”, represents a streamlined, ‘hands-off’ tool for transgene delivery to a higher plant that we expect will enhance the throughput of duckweed engineering and help to realize duckweed’s potential as a powerhouse for plant synthetic biology. (148 words)
Joint representation learning for retrieval and annotation of genomic interval sets
Authors: Gharavi Erfaneh , LeRoy Nathan J. , Zheng Guangtao , Zhang Aidong , Brown Donald E. , Sheffield Nathan C. 
Published: August 2023

MotivationAs available genomic interval data increases in scale, we require fast systems to search it. A common approach is simple string matching to compare a search term to metadata, but this is limited by incomplete or inaccurate annotations. An alternative is to compare data directly through genomic region overlap analysis, but these approaches lead to challenges like sparsity, high dimensionality, and computational expense. We require novel methods to quickly and flexibly query large, messy genomic interval databases.ResultsHere, we develop a genomic interval search system using representation learning. We train numerical embeddings for a collection of region sets simultaneously with their metadata labels, capturing similarity between region sets and their metadata in a low-dimensional space. Using these learned co-embeddings, we develop a system that solves three related information retrieval tasks using embedding distance computations: retrieving region sets related to a user query string; suggesting new labels for database region sets; and retrieving database region sets similar to a query region set. We evaluate these use cases and show that jointly learned representations of region sets and metadata are a promising approach for fast, flexible, and accurate genomic region information retrieval.
Active learning of enhancer and silencer regulatory grammar in photoreceptors
Authors: Friedman Ryan Z. , Ramu Avinash , Lichtarge Sara , Myers Connie A. , Granas David M. , Gause Maria , Corbo Joseph C. , Cohen Barak A. , White Michael A. 
Published: August 2023

ABSTRACTCis-regulatory elements (CREs) direct gene expression in health and disease, and models that can accurately predict their activities from DNA sequences are crucial for biomedicine. Deep learning represents one emerging strategy to model the regulatory grammar that relates CRE sequence to function. However, these models require training data on a scale that exceeds the number of CREs in the genome. We address this problem using active machine learning to iteratively train models on multiple rounds of synthetic DNA sequences assayed in live mammalian retinas. During each round of training the model actively selects sequence perturbations to assay, thereby efficiently generating informative training data. We iteratively trained a model that predicts the activities of sequences containing binding motifs for the photoreceptor transcription factor Cone-rod homeobox (CRX) using an order of magnitude less training data than current approaches. The model’s internal confidence estimates of its predictions are reliable guides for designing sequences with high activity. The model correctly identified critical sequence differences between active and inactive sequences with nearly identical transcription factor binding sites, and revealed order and spacing preferences for combinations of motifs. Our results establish active learning as an effective method to train accurate deep learning models ofcis-regulatory function after exhausting naturally occurring training examples in the genome.
Olfaction regulates peripheral mitophagy and mitochondrial function
Authors: Dishart Julian G. , Pender Corinne , Shen Koning , Zhang Hanlin , Ly Megan , Webb Madison , Dillin Andrew 
Published: August 2023

AbstractThe central nervous system is a master regulator of peripheral homeostasis and cellular-stress responses; however, the contexts for which this regulatory capability evolved remain unknown. The olfactory sensory nervous system has access to privileged information about environmental conditions and can signal to the periphery to prepare for potential metabolic perturbations. The unfolded protein response of the mitochondria (UPRMT) is upregulated upon infection by many pathogens and in metabolic flux, and pathogenic infection and metabolic byproducts are a present hazard in consuming nutrients. Therefore, we asked whether the olfactory nervous system inC. elegansregulates the UPRMTcell nonautonomously. We found that loss of a single olfactory neuron pair, AWC, led to robust induction of the UPRMTdownstream of enhanced, serotonin-dependent mitophagy. Further, AWC ablation confers resistance to the pathogenic bacteriaPseudomonas aeruginosapartially dependent on the UPRMTtranscription factoratfs-1, and fully dependent on mitophagy machinerypdr-1/Parkin. These data demonstrate a novel role for the olfactory nervous system in regulating whole-organism mitochondrial dynamics, perhaps in preparation for postprandial metabolic stress or pathogenic infection.
UBAP2L drives scaffold assembly of nuclear pore complexes at the intact nuclear envelope
Authors: Liao Yongrong , Andronov Leonid , Liu Xiaotian , Lin Junyan , Guerber Lucile , Lu Linjie , Agote-Arán Arantxa , Pangou Evanthia , Ran Li , Kleiss Charlotte , Qu Mengdi , Schmucker Stephane , Cirillo Luca , Zhang Zhirong , Riveline Daniel , Gotta Monica , Klaholz Bruno P. , Sumara Izabela 
Published: August 2023

AbstractAssembly of macromolecular complexes at correct cellular sites is crucial for cell function. Nuclear pore complexes (NPCs) are large cylindrical assemblies with eightfold rotational symmetry, built through hierarchical binding of nucleoporins (Nups) forming distinct subcomplexes. Here, we uncover a direct role of ubiquitin-associated protein 2-like (UBAP2L) in the biogenesis of properly organized and functional NPCs at the intact nuclear envelope (NE) in human cells. UBAP2L localizes to the nuclear pores and drives the formation of the Y-complex, an essential scaffold component of the NPC, and its localization to the NE. UBAP2L facilitates the interaction of the Y-complex with POM121 and Nup153, the critical upstream factors in a well-defined sequential order of Nups assembly onto NE during interphase. Timely localization of the cytoplasmic Nup transport factor fragile X-related protein 1 (FXR1) to the NE and its interaction with the Y-complex are likewise dependent on UBAP2L. Thus, this NPC biogenesis mechanism integrates the cytoplasmic and the nuclear NPC assembly signals and ensures efficient nuclear transport, adaptation to nutrient stress and cellular proliferative capacity, highlighting the importance of NPC homeostasis at the intact nuclear envelope.TeaserLiao et al. show how UBAP2L drives the assembly of the scaffold elements into symmetrical and functional NPCs at the nuclear envelope in human cells.
Mutual homeostasis of charged proteins
Authors: Faraway Rupert , Heaven Neve Costello , Digby Holly , Wilkins Oscar G. , Chakrabarti Anob M. , Iosub Ira A. , Knez Lea , Ameres Stefan L. , Plaschka Clemens , Ule Jernej 
Published: August 2023

AbstractProtein dosage is regulated to maintain cellular homeostasis and health. The dosage of proteins containing disordered low complexity domains (LCDs) must be particularly well-controlled to prevent aberrant disease, yet no mechanism to maintain homeostasis has been identified1, 2. Here we report a mutual homeostatic mechanism that controls the concentration of such proteins, termed ’interstasis’, in which proteins with similar LCDs co-regulate their combined dosage through collective negative feedback. We focused on the mechanism that exploits the fundamental multivalency of GA-rich RNA regions that encode charged LCDs, including those with arginine-enriched mixed charge domains (R-MCDs). Modest variations in the abundance of an R-MCD protein change the properties of nuclear speckles, a protein-RNA condensate, selectively trapping multivalent GA-rich mRNAs to promote their nuclear retention. This interstasis depends on conserved codon biases, shared by amniotes, which enhance the multivalency of GA-rich regions encoding charged LCDs. The threshold of interstasis is modulated by CLK kinases, which affect the nuclear speckle localisation of proteins such as TRA2B, key binder of GA-rich RNAs. Notably, many classes of LCDs are encoded by RNA regions containing multivalency-enhancing codon biases, each preferentially bound by specific proteins, suggesting that interstasis might co-regulate many classes of functionally related LCD-containing proteins through dose-sensitivity of various types of protein-RNA condensates.
Improved Estimation of Bird Abundance and Energy Consumption by Combining Point and Transect Observations
Authors: Bolagay Maria Jose Ayala , Brothers Aaron , Quitián Marta , Neuschulz Eike Lena , Schleuning Matthias , Böhning-Gaese Katrin , Alvarez Orlando , Santillán Vinicio , Thron Christopher 
Published: August 2023

AbstractPoint counts and transect surveys are both common methods for estimating bird abundance (by species, genus, or family) in a given environment. Sometimes both methods are used in the same study. Point counts reflect abundance directly, while transect observations of bird feeding instances reflect both the bird abundance and the mean energy consumption rate per bird.In this paper we exploit the relationship between these two types of observations to draw inferences about bird energy consumption; to develop an improved estimator of bird abundance; and to derive error bars for abundance estimates. The mathematical methods developed are applied to a dataset consisting of point counts and transect surveys of Ecuadorian frugivore bird species in six different types of environment (three elevations and two degrees of forestation). By comparing transect-based and point count-based estimates of energy consumption across species, we show that mean fruit weight consumed does not have a significant effect on number of feeding instances. We also derive a procedure for forming an optimal linear combination of two relative abundance estimators based on point counts and transect observations respectively. The improvement in accuracy achieved by this combined estimator is verified by simulations applied to bird family data from the above-mentioned survey. Finally, we use simulations to obtain 90% confidence intervals for the bird family relative abundance estimates. These confidence intervals were also verified using simulations.
High-density genetic linkage mapping in Sitka spruce advances the integration of genomic resources in conifers
Authors: Tumas Hayley , Ilska Joana J. , Girardi Sebastien , Laroche Jerome , A’Hara Stuart , Boyle Brian , Janes Mateja , McLean Paul , Lopez Gustavo , Lee Steve J. , Cottrell Joan , Gorjanc Gregor , Bousquet Jean , Woolliams John A. , MacKay John J. 
Published: August 2023

AbstractIn species with large and complex genomes such as conifers, dense linkage maps are a useful for supporting genome assembly and laying the genomic groundwork at the structural, populational and functional levels. However, most of the 600+ extant conifer species still lack extensive genotyping resources, which hampers the development of high-density linkage maps. In this study, we developed a linkage map relying on 21,570 SNP makers in Sitka spruce (Picea sitchensis[Bong.] Carr.), a long-lived conifer from western North America that is widely planted for productive forestry in the British Isles. We used a single-step mapping approach to efficiently combine RAD-Seq and genotyping array SNP data for 528 individuals from two full-sib families. As expected for spruce taxa, the saturated map contained 12 linkages groups with a total length of 2,142 cM. The positioning of 5,414 unique gene coding sequences allowed us to compare our map with that of other Pinaceae species, which provided evidence for high levels of synteny and gene order conservation in this family. We then developed an integrated map forP. sitchensisandP. glaucabased on 27,052 makers and 11,609 gene sequences. Altogether, these two linkage maps, the accompanying catalog of 286,159 SNPs and the genotyping chip developed herein opens new perspectives for a variety of fundamental and more applied research objectives, such as for the improvement of spruce genome assemblies, or for marker-assisted sustainable management of genetic resources in Sitka spruce and related species.
Phenotypic and genomic evidence for transparent cellulose, metabolic diversity, and stable cellulose production in the Acetobacteraceae
Authors: Keating Kevin W. , van Zyl Elizabeth M. , Collins Joseph H. , Nakagawa Carter , Weintraub Sarah J. , Coburn Jeannine M. , Young Eric M. 
Published: August 2023

ABSTRACTThe Acetobacteraceae are a family of microbes that use sugars from fruits, beverages and fermented foods to overproduce bacterial nanocellulose (BNC), a living material with broad applications in medicine and industry. Yet, the family has few complete, contiguous genome sequences available. Here, three different strains – a high production strain NQ5, a metabolic engineering host NCIB 8034, and a new isolate DS12 from kombucha were characterized and completede novogenomes assembled. Initial growth and yield experiments reveal a diversity of carbon source utilization profiles and BNC production rates, with NQ5 achieving the highest yield on glucose and DS12 having the narrowest utilization profile. All strains synthesize optically clear BNC. Genomic evidence assigns the DS12 isolate toKomagataeibacter nataicola,reassigns NCIB 8034 fromKomagataeibacter xylinustoKomagataeibacter oboediens,and supports NQ5 asNovacetimonas hansenii.Thebcsgene clusters that encode BNC synthesis are also diverse. The highest producing strain,N. hanseniiNQ5, has fewerbnccopies thanK. oboediensNQ5, indicating that copy number does not explain high productivity. Analysis also reveals the type and frequency of mobile genetic elements. Notably,N. hanseniiNQ5 has a paucity of transposons relative to other strains, which could explain the BNC production stability ofN. hanseniiNQ5 in culture. Thus, this work argues that Acetobacteraceae are metabolically diverse, and provides genomic evidence explaining beneficial BNC production characteristics ofN. hanseniiNQ5. Therefore, this work provides evidence for selection of appropriate BNC production strains.IMPORTANCEBacterial cellulose is an important material for biomedical applications like wound dressings. This study defines important characteristics of microbes that produce bacterial cellulose, namely their ability to process different sugars and features of their genomes that make cellulose yield more consistent. These findings will aid in the development of better bacterial cellulose production processes.
Predicting student retention in higher education institutions (HEIs)
Authors: Addison Letetia , Williams Densil 
Published: August 2023

PurposeThis paper aims to provide a parsimonious but rigorous model to assist decision-makers to determine critical factors which can lead to higher graduation rates amongst higher education institution (HEI) participants. It predicts the odds of dropout amongst university students, using HEI data from a developing country. This is used as a basis for a Student Retention Predictive (SRP) Model to inform HEI administrators about predicted risks of attrition amongst cohorts.Design/methodology/approachA classification tool, the Logistic Regression Model, is fitted to the data set for a particular HEI in a developing country. The model is used to predict significant factors for student dropout and to create a base model for predicted risks by various student demographic variables.FindingsTo reduce dropout and to ensure higher graduation rates, the model suggests that variables such as age group, faculty, academic standing and cumulative GPA are significant. These indicative results can drive intervention strategies to improve student retention in HEIs and lessen the gap between graduates and non-graduates, with the goal of reducing socio-economic inequalities in society.Originality/valueThis research employs risk bands (low, medium and high) to classify students at risk of attrition or drop out. This provides invaluable insights to HEI administrators in the development of intervention strategies to reduce dropout and increase graduation rates to impact the wider public policy issue of socio-economic inequities.
The achievement of sustainable development and business success through rational management decision-making in a circular economy
Authors: Shah Naimatullah , Bhatti Mitho Khan , Saraih Ummi Naiemah , Abdelwahed Nadia A. Abdelmegeed , Soomro Bahadur Ali 
Published: August 2023

Purpose
This study aims to explore sustainable development and business success (BS) through decision-making (DM) in Pakistan’s circular economy.

Design/methodology/approach
This is a co-relational study in which the researchers used cross-sectional data collected from the managers of Pakistan’s manufacturing industries. Accordingly, the authors based this study’s findings on 373 valid samples.

Findings
This study’s structural equation modeling results reveal that DM has a positive and significant effect on sustainable development, which comprises competitiveness, business performance enhancement, flexibility, customer satisfaction and technology development. Moreover, DM positively and significantly affects BS.

Practical implications
This study’s findings support sustainable development, strengthen the socioeconomic conditions and bring about the industries’ well-being through DM. In addition, these findings demonstrate the need for the circular economy to tackle industrial challenges and simultaneously open up economic and environmental growth opportunities for society.

Originality/value
This study offers the original contribution from a circular economy perspective; there needs to be more empirical evidence among managers of manufacturing industries. Besides, this study provides DM’s role in achieving sustainable development in the presence of BS, which has disappeared in an integrated way, particularly in a circular context.
Tool-based mentoring conversations in teacher education: new structures, opportunities and the role of adaptive expertise
Authors: Hunskaar Tove Seiness , Gudmundsdottir Greta Björk 
Published: August 2023

PurposeThis paper aims to investigate how school-based mentors and preservice teachers (PTs) perceive mentoring conversations when applying a set of newly developed digital tools accompanied by discursive tools in mentoring in practicum.Design/methodology/approachThis study performed a thematic analysis of 12 interviews (5 with mentors and 7 with PTs) to explore how the participants perceived mentoring conversations when applying a combination of digital and discursive tools in school-based mentoring conversations. This study uses a model of adaptive expertise to discuss the findings.FindingsThis analysis revealed that the tools could alter the typical order of mentoring conversations. Mentors reported a change in their mentoring routines in which mentees took a more active role in conversations. The use of tools also allowed for richer conversations. From the perspective of PTs, the tools provided a structure for mentoring sessions, provided an alternative opening for mentoring conversations and enhanced their awareness of certain aspects of their own teaching.Originality/valueThis study's results suggest that the application of tools in mentoring enhances mentoring by facilitating reflection among PTs and mentors and fostering the development of adaptive expertise.