bluuebunny/crossref_metadata_2025_split huggingface dataset:
AI-based prediction of herbarium sequencing success across the plant tree of life
Authors: Ranjbaran Yasaman , Maurin Olivier , Canadelli Elena , Morosinotto Tomas , Weech Marie-Helen , Kersey Paul , Antonelli Alexandre , Baker William J. , Sales Gabriele , Dal Grande Francesco 
Published: February 2025

AbstractDNA recovered from herbarium specimens represents a vital asset in botanical research, playing a pivotal role in unravelling the evolution, diversity, and ecological dynamics of plants. Despite its importance, challenges such as fragmented DNA and insufficient sequencing yields render molecular data retrieval a high-risk and costly endeavour involving the use of non-replaceable herbarium specimens. Here, we propose a framework based on Artificial Intelligence (AI) to forecast the success of genomic DNA extraction suitable for sequencing from herbarium samples. Our model integrates morphological characteristics and sample colour derived from scanned herbarium images, metadata including sample age and locality, and DNA quantity measurements of samples. We train a deep learning algorithm with ca. 2,000 specimens that have been digitized and sequenced in the framework of the Plant and Fungal Trees of Life (PAFTOL) Project, spanning from year 1832 to the present. As training datasets increase with ongoing digitization and genomic sequencing efforts, our AI predictive model can support researchers in selecting the herbarium samples with the highest likelihood of yielding high-quality genomic DNA from amongst a vast array of globally distributed candidate specimens. Our approach enhances the contribution of herbarium-derived DNA in large-scale studies and facilitates the utilisation of historical collections for a deeper understanding of plant evolution and ecology, with implications for conservation.
Vertical RAS-pathway inhibition in pancreatic cancer drives therapeutically exploitable mitochondrial alterations
Authors: Hafner Philipp , Keller Steffen J. , Chen Xun , Alrawashdeh Asma , Jumaa Huda , Nollmann Friederike I. , Besson Solène , Kemming Judith , Gorka Oliver , Das Tonmoy , Appiah Bismark , Lehmann Ariane , Li Mujia , Apostolova Petya , Bengsch Bertram , Tholen Stefan , Schilling Oliver , Groß Olaf , Vlachos Andreas , Wittel Uwe A. , von Elverfeldt Dominik , Reichardt Wilfried , Boerries Melanie , Andrieux Geoffroy , Heynen Guus J. , Fichtner-Feigl Stefan , Hannibal Luciana , Ruess Dietrich A. 
Published: February 2025

AbstractBackground & AimsOncogenic KRAS mutations drive metabolic rewiring in pancreatic ductal adenocarcinoma (PDAC). Src-homology 2 domain-containing phosphatase 2 (SHP2) is essential for full KRAS activity and promising dual SHP2/mitogen-activated protein kinase (MAPK) inhibition is currently being tested in clinical trials. Exploitable metabolic adaptations may contribute to an invariably evolving resistance.MethodsTo understand the metabolic changes induced by dual inhibition, we comprehensively tested cell lines, endogenous tumor models, and patient-derived organoids representing the full spectrum of PDAC molecular subtypes.ResultsWe find that dual SHP2/mitogen-activated protein kinase kinase (MEK1/2) inhibition induces major mitochondrial alterations, elevates reactive oxygen species (ROS) levels and triggers a lipid peroxidase dependency. While anabolic pathways, glycolysis and autophagy were also affected, mitochondrial alterations persisted longterm into a therapy resistant state.ConclusionsThe resulting vulnerability to induction of ferroptotic cell death via combined SHP2/MEK1/2 and glutathione peroxidase (GPX4) inhibition provides a metabolic lever to reinforce RAS-pathway inhibition for targeted PDAC treatment.
A thermodynamic cycle to predict the competitive inhibition outcomes of an evolving enzyme
Authors: Cetin Ebru , Abdizadeh Haleh , Atilgan Ali Rana , Atilgan Canan 
Published: February 2025

AbstractUnderstanding competitive inhibition at the molecular level is essential for unraveling the dynamics of enzyme-inhibitor interactions and predicting the evolutionary outcomes of resistance mutations. In this study, we present a framework linking competitive inhibition to alchemical free energy perturbation (FEP) calculations, focusing onE. colidihydrofolate reductase (DHFR) and its inhibition by trimethoprim (TMP). Using thermodynamic cycles, we relate experimentally measured binding constants (KiandKm) to free energy differences associated with wild-type and mutant forms of DHFR with a mean error of 0.9 kcal/mol, providing insights into the molecular underpinnings of TMP resistance. Our findings highlight the importance of local conformational dynamics in competitive inhibition. Mutations in DHFR affect substrate and inhibitor binding affinities differently, influencing the fitness landscape under selective pressure from TMP. Our FEP simulations reveal that resistance mutations stabilize inhibitor-bound or substrate-bound states through specific structural and/or dynamical effects. The interplay of these effects showcases significant epistasis in certain cases. The ability to separately assess substrate and inhibitor binding provides valuable insights, allowing for a more precise interpretation of mutation effects and epistatic interactions. Furthermore, we identify key challenges in FEP simulations, including convergence issues arising from charge-changing mutations and long-range allosteric effects. By integrating computational and experimental data, we provide an effective approach for predicting the functional impact of resistance mutations and their contributions to evolutionary fitness landscapes. These insights pave the way for constructing robust mutational scanning protocols and designing more effective therapeutic strategies against resistant bacterial strains.
Interaction of lncRNA LENT with DHX36 regulates translation and suppresses autophagy in melanoma
Authors: Haller Alexandre , Gambi Giovanni , D’Agostino Mattia , Davidson Guillaume , Lallement Antonin , Mengus Gabrielle , Nahy Chadia , Messaddeq Nadia , Bec Guillaume , Simonetti Angelita , Ennifar Eric , Davidson Irwin 
Published: February 2025

AbstractThe melanocyte lineage determining Microphthalmia-associated transcription factor (MITF) drives proliferation and survival of melanocytic melanoma cells through regulation of both coding genes and long non-coding RNAs (LncRNAs). Here we characterize LINC00520 (hereafter calledLncRNAENhancerofTranslation, LENT) regulated by MITF and strongly expressed in melanocytic melanoma cells. LENT is essential for proliferation and survival of cultured melanocytic melanoma cells and xenograft tumours. LENT interacts with the G4 quadruplex resolvase DHX36 and both associate with the ribosome in the 80S and light polysome fractions. LENT modulates DHX36 association with a collection of mRNAs regulating their engagement with polysomes and fine-tuning their subsequent translation. These mRNAs encode proteins involved in endoplasmic reticulum (ER) and mitochondrial homeostasis as well as autophagy. Consequently, LENT silencing leads to extensive autophagy and mitophagy, compromised oxidative metabolic capacity accompanied by an accumulation and mis-localization of mitochondrial proteins leading to proteotoxic stress and apoptosis. The LENT-DHX36 axis therefore fine-tunes translation of proteins involved in ER and mitochondrial homeostasis suppressing autophagy and promoting survival and proliferation of melanoma cells.
Machine Learning-Based Tumor Segmentation and Classification Using Dynamic Optical Contrast Imaging (DOCI) for Thyroid Cancer
Authors: Vasse Tyler , Alhiyari Yazeed , Evans Lauran K. , Shori Ramesh , St. John Maie , Vo-Dinh Tuan 
Published: February 2025

AbstractThyroid cancer presents significant diagnostic challenges due to its complex anatomy and diverse tissue types. This study leverages Dynamic Optical Contrast Imaging (DOCI), a label-free, real-time imaging technology, with machine learning to enhance tumor detection and segmentation. Using 23 DOCI filters, we applied Principal Component Analysis (PCA) for dimensionality reduction, k-nearest neighbors (k-NN) for classification, and U-Net models for segmentation. The approach achieved high accuracy in distinguishing tissue types, with PCA enabling clear clustering, k-NN classifying normal, follicular, and papillary tissues, and U-Net models achieving 96.34% and 92.02% accuracy for papillary and follicular segmentation, respectively. Filter importance analysis reduced input dimensionality without significantly compromising performance, highlighting the potential for optimized imaging protocols. These findings demonstrate DOCI’s utility in improving diagnostic accuracy and tumor characterization in thyroid cancer and beyond, offering a foundation for personalized treatment planning and surgical precision.
Classification of skin transcriptome reveals two molecular subtypes in hidradenitis suppurativa
Authors: Wang Jing , Guay Heath , Chang Dan 
Published: February 2025

AbstractBackground and AimsHidradenitis suppurativa (HS) is an understudied chronic inflammatory skin disease that is characterized by painful bumps and abscesses. Adalimumab and secukinumab are the only two approved biologics for the treatment of HS. Despite these advances in the treatment of disease, there remains significant unmet medical need, with many patients only achieving moderate improvements in disease, or continuing to experience flares. This suggests that there may be distinct patient subsets with unique molecule drivers of disease. The aim of this study is to identify and characterize the molecular subtypes of HS patients to further understand its heterogeneity.MethodsSix public datasets with a total of 100 skin lesional samples were integrated to identify molecular subtypes and build a 36-gene classifier, which was validated by three independent lesional skin datasets. Two out of six training datasets generated from patients treated with adalimumab were used to identify the relationship between subtypes and response status.ResultsTwo molecular subtypes were identified from the training datasets, in which subtype S1 had a higher response rate of adalimumab than subtype S2 in the two adalimumab treatment datasets. Subtype S1 was characterized by three gene modules associated with keratinization, development, and metabolism, and six cell types related to sebocytes, smooth muscle cells, endothelial cells, schwann cells, basal cells, and proliferating cells. Subtype S2 was associated with three modules related to immune response, wound healing, keratinization, and cell cycle, and three cell types related to T lymphocytes, dendritic cells, and fibroblasts. The two subtypes were replicated in three additional independent datasets.ConclusionsThis study discovered and validated two HS subtypes with different molecular mechanisms and drug response, which may aid interpretation of heterogeneous molecular and clinical information in HS patients.
Assessment of critically endangered Northern River Terrapin (Batagur baska) phylogeny through next-generation sequencing-based mitogenome analyses
Authors: Nawani Swati , Balan Amirtha , Bashir Asim , Kolipakam Vishnupriya , Das Abhijit , Mondol Samrat 
Published: February 2025

AbstractThe Northern River Terrapin,Batagur baska(Gray, 1830), is a critically endangered freshwater turtle, primarily found in the estuaries and tidal regions of large rivers in South and Southeast Asia.B. baskahas experienced extensive population declines and extirpations across most of its range, with no confirmed wild populations remaining. To support conservation efforts of this turtle, our study utilizes first complete mitochondrial genome ofB. baskausing next-generation sequencing (NGS). This mitochondrial genome data is combined with existing genetic information to evaluate the species’ phylogenetic position within the Geoemydidae family. The Bayesian phylogenetic analysis, including 38 species sequences, confirmed a close genetic relationship betweenB. baskaand B.affinis(posterior probability = 1). The mitochondrial genome ofB. baskaconsists of 16,503 base pairs, with a typical structure comprising 13 protein-coding genes, two rRNA genes, and 22 tRNA genes, along with a non-coding control region. The protein-coding genes account for 68.9% of the genome, while the ribosomal RNA and tRNA genes cover 15.4%. The control region, located between tRNAPro and tRNAPhe, is 986 bp long and exhibits a distinct base composition.
Relative contributions of correcting the diet and voluntary exercise to myocardial recovery in a two-hit murine model of heart failure with preserved ejection fraction
Authors: Labbé Emylie-Ann , Thibodeau Sara-Ève , Walsh-Wilkinson Élisabeth , Chalifour Maude , Sirois Pierre-Olivier , Leblanc Juliette , Arsenault Marie , Couet Jacques 
Published: February 2025

AbstractWe recently proposed a new two-hit murine model of heart failure with preserved ejection fraction (HFpEF) amenable for both male and female animals. Using this model, we studied cardiac reverse remodelling (RR) after stopping the causing stress (Angiotensin II (AngII) + High-fat diet; MHS) after 28 days, and then introducing voluntary exercise (VE) and feeding the animals with a low-fat diet. We showed this could lead to extensive cardiac left ventricle (LV) RR. Revisiting this HFpEF model, we studied the relative contribution to RR of correcting the diet and/or starting VE after stopping AngII. We also evaluate the extent of myocardial recovery after an extended period (12 weeks instead of four) by exposing the animals to a second MHS.Our observations revealed a sex-specific response. Discontinuing AngII but continuing the HFD blocked RR in females, not males. Removing AngII and correcting either the diet or implementing VE normalized most tested gene markers of LV hypertrophy or extracellular matrix, irrespective of sex.Twelve weeks of recovery was associated with normal LV morphology and function, except for abnormal diastolic echocardiographic parameters. A second MHS after these 12 weeks led to a loss of ejection fraction in males and LV dilatation. The response of females was like that after the first MHS, suggesting a better recovery. The MHS changed markers of myocardial glucose metabolism. Pyruvate dehydrogenase (PDH) activity responsible for pyruvate entry in the mitochondria was reduced after MHS, and this was accompanied by an increase of PDH phosphorylation and pyruvate dehydrogenase kinase 4 content. RR mostly normalized these.Our results suggest sex-specific RR after stopping the MHS and that myocardial anomalies remaining in males make them more sensitive to a second HFpEF-inducing stress.
A Bio-inspired Latent TGF-β Conjugated Scaffold Improves Neocartilage Development
Authors: Wang Tianbai , Maldonado Celina C. , Huang Bor-Lin , Budbazar Enkhjargal , Martin Andrew , Layne Matthew D. , Murphy-Ullrich Joanne E. , Grinstaff Mark W. , Albro Michael B. 
Published: February 2025

AbstractIn cartilage tissue engineering, active TGF-β is conventionally supplemented in culture medium at highly supraphysiologic doses to accelerate neocartilage development. While this approach enhances cartilage extracellular matrix (ECM) biosynthesis, it further promotes tissue features detrimental to hyaline cartilage function, including the induction of tissue swelling, hyperplasia, hypertrophy, and ECM heterogeneities. In contrast, during native cartilage development, chondrocytes are surrounded by TGF-β configured in a latent complex (LTGF-β), which undergoes cell-mediated activation, giving rise to moderated, physiologic dosing regimens that enhance ECM biosynthesis while avoiding detrimental features associated with TGF-β excesses. Here, we explore a bio-inspired strategy, consisting of LTGF-β-conjugated scaffolds, providing TGF-β exposure regimens that are moderated and uniformly administered throughout the construct. Specifically, we evaluate the performance of LTGF-β scaffolds to improve neocartilage development with bovine chondrocyte-seeded agarose constructs compared to outcomes from active TGF-β media supplementation (MS) at a physiologic 0.3 ng/mL dose (MS-0.3), supraphysiologic 10 ng/mL dose (MS-10), or TGF-β free. For small-size constructs (∅3×2 mm), LTGF-β scaffolds yield neocartilage that achieves native-matched mechanical properties (800-925 kPa) and sGAG content (6.6%-7.1%), while providing a cell morphology and collagen distribution more reminiscent of hyaline cartilage. LTGF-β scaffolds further afford an optimal chondrogenic phenotype, marked by a 12-to 28-fold reduction of COL-I expression relative to TGF-β-free and a 7-to 17-fold reduction of COL-X expression relative to MS-10. Further, for large-size constructs, which approach the dimensions needed for clinical cartilage repair, LTGF-β scaffolds significantly reduce mechanical and biochemical heterogeneities relative to MS-0.3 and MS-10. Overall, the use of LTGF-β scaffolds improves the composition, structure, material properties, and cell phenotype of neocartilage.
Design, Monitoring, and Application of a Cost-Effective Bioreactor for Biogas Production
Authors: Ventura-Prados Angela , Solís-García Javier 
Published: February 2025

AbstractThis study presents the design and construction of a low-cost bioreactor for biogas production, aimed at regions with abundant organic waste to promote renewable energy use in rural and agricultural communities. The bioreactor is equipped with sensors to monitor critical parameters such as temperature, pH, and Total Dissolved Solids (TDS) to ensure efficient anaerobic digestion, using horse manure as the substrate. Operational conditions were evaluated, maintaining pH between 6 and 7, the optimal range for biogas production, and temperature between 30 and 35°C, ideal for methanogenic activity. TDS values fluctuated between 620 and 780 mg/L, revealing a direct relationship with biogas production and emphasizing the importance of maintaining optimal solid concentrations, as excessive solids reduced efficiency. This work demonstrates the feasibility of implementing low-cost bioreactors for biogas generation in rural areas, contributing to sustainable energy recovery and effective organic waste management.
Have protein-ligand co-folding methods moved beyond memorisation?
Authors: Škrinjar Peter , Eberhardt Jérôme , Durairaj Janani , Schwede Torsten 
Published: February 2025

AbstractDeep learning has driven major breakthroughs in protein structure prediction, however the next critical advance is accurately predicting how proteins interact with other molecules, especially small molecule ligands, to enable real-world applications such as drug discovery and design. Recent deep learning all-atom methods have been built to address this challenge, but evaluating their performance on the prediction of protein-ligand complexes has been inconclusive due to the lack of relevant benchmarking datasets. Here we present a comprehensive evaluation of four leading all-atom cofolding deep learning methods using our newly introduced benchmark dataset Runs N’ Poses, which comprises 2,600 high-resolution protein-ligand systems released after the training cutoff used by these methods. We demonstrate that current co-folding approaches largely memorise ligand poses from their training data, hindering their use forde novodrug design. This limitation is especially pronounced for ligands that have only been seen binding in one pocket, whereas more promiscuous ligands such as cofactors show moderately improved performance. With this work and benchmark dataset, we aim to accelerate progress in the field by allowing for a more realistic assessment of the current state-of-the-art deep learning methods for predicting protein-ligand interactions.
Persistent fatty acid catabolism during plant oil synthesis
Authors: Koley Somnath , Jyoti Poonam , Lingwan Maneesh , Wei Michael , Xu Chunhui , Chu Kevin L. , Williams Russell B. , Koo Abraham J. , Thelen Jay J. , Xu Dong , Allen Doug K. 
Published: February 2025

SUMMARYPlant lipids are an essential energy source for diets and are a sustainable alternative to petroleum-based fuels and feed stocks. Fatty acid breakdown during seed germination is crucial for seedling establishment but unexpected during seed filling. Here, we demonstrate that the simultaneous biosynthesis and degradation of fatty acids begins early and continues across all phases of oil filling and throughout the photoperiod. Tests in camelina, rapeseed and engineered high-oil tobacco line confirmed that concomitant synthesis and breakdown in oil-producing tissues over development is the rule rather than the exception. We show that transgenics, designed for significantly higher fatty acid biosynthesis, fail to achieve a proportional increase in storage lipid levels due to increasing degradation, potentially explaining the underperformance of engineered lines compared to expectations.
Extensive clonal reproduction drives liana proliferation following forest fragmentation
Authors: Mori Hideki , Kamijo Takashi 
Published: February 2025

ABSTRACTBackground and AimsAs forest landscapes become increasingly fragmented worldwide, concerns are growing over the cascading effects on biodiversity and ecosystem functioning. While such fragmentation often promotes liana proliferation, the role of clonal reproduction in this process remains poorly understood. In this study, we investigated how a temperate liana,Wisteria floribunda, reproduces and expands its distribution through clonal growth in fragmented forests.MethodsUsing DNA analyses in fragmented forests (21.6 ha) and in a continuous forest plot (6 ha) in central Japan, we examined the distribution and structure of genets to evaluate their contribution to the dominance ofW. floribunda.Key ResultsOur findings revealed that 94% of the apparent individuals (ramets, N = 273 in total) in the fragmented forests, were derived from clonal reproduction, significantly exceeding the 45% observed in the continuous forest. These clonal genets collectively covered 57% of the study area in the fragmented forests, compared to only 7% in the continuous forest. Notably, three large genets in the fragmented forests spanned multiple patches, with the largest covering 9.5 ha across seven patches. These genets were predominantly located in areas historically covered by forests, suggesting that they likely expanded through clonal reproduction before fragmentation. Furthermore, stem density in fragmented forests was approximately three times higher than in the continuous forest.ConclusionsThese results demonstrate that extensive clonal reproduction drives liana proliferation in fragmented forests. This study underscores the importance of considering clonal strategies when assessing and predicting liana dynamics in fragmented landscapes, where historical and ongoing clonal reproduction play critical roles in their dominance.