bluuebunny/crossref_metadata_2025 huggingface dataset:
Filamented Light (FLight) Biofabrication of Mini-Tendon Models Show Tunable Matrix Confinement and Nuclear Morphology
Authors: Liu Hao , Scherpe Lynn , Hummer Linnea B. , Snedeker Jess Gerrit , Zenobi-Wong Marcy
Published: February 2025

One hallmark of healthy tendon tissue is the high confinement of tenocytes between tightly packed, highly aligned collagen fibers. During tendinopathy, this organization becomes dysregulated, leading to cells with round-shaped morphology and collagen fibers which exhibit crimping and misalignment. The elongated nuclei in healthy tendons are linked to matrix homeostasis through distinct mechanotransduction pathways, and it is believed that the loss of nuclear confinement could upregulate genes associated with abnormal matrix remodeling. Replicating the cell and nuclear morphology of healthy and diseased states of tendon, however, remains a significant challenge for engineeredin vitrotendon models. Here we report on a high throughput biofabrication of mini-tendons that mimick the tendon core compartment based on the Filamented Light (FLight) approach. Each mini-tendon, with a length of 4 mm, was composed of parallel hydrogel microfilaments (2-5 µm diameter) and microchannels (2-10 µm diameter) that confined the cells. We generated four distinct matrices with varying stiffness (7-40 kPa) and microchannel dimensions. After 14 days of culture, 29% of tenocytes in the softest matrix with the largest microchannel diameter were aligned, exhibiting an average nuclear aspect ratio (nAR) of 2.1. In contrast, 84% of tenocytes in the stiffest matrix with the smallest microchannel diameter were highly aligned, with a mean nAR of 3.4. When tenocytes were cultured on the FLight hydrogels (2D) as opposed to within the hydrogels (3D), the mean nAR was less than 1.9, indicating that nuclear morphology is significantly more confined in 3D environments. By tuning the stiffness and microarchitecture of the FLight matrix, we demonstrated that mechanical confinement can be modulated to exert control over the extent of nuclear confinement. This high-throughput, tunable platform offers a promising approach for studying the mechanobiology of healthy and diseased tendons and for eventual testing of drug compounds against tendinopathy.
Essential role of NLRC5 in cancer immune surveillance and cancer immunoediting
Authors: Shukla Akhil , Cayarga Anny Armas , Lucier Jean-François , Santharam Madanraj Appiya , Lévesque Dominique , Boisvert François-Michel , Ramanathan Sheela , Ilangumaran Subburaj
Published: February 2025

A key mechanism of immune escape from CD8+T cell-mediated tumor control occurs via downregulation of NLRC5, the IFNγ-induced transcriptional activator of MHC class-I. As NLRC5 deficiency does not abrogate CD8+T cell development, we investigated whether NLRC5-dependent antitumor immune mechanisms are required for immune surveillance. Development of 3-methylcholanthrene (MCA)-induced endogenous fibrosarcoma was studied inNlrc5-/-mice withNlrc5+/+andRag1-/-mice serving as controls.Nlrc5-/-andRag1-/-mice showed increased propensity to develop MCA-induced tumors with elevated growth rate compared toNlrc5+/+mice, and displayed significantly reduced survival. Tumors fromNlrc5+/+andNlrc5-/-mice, but not fromRag1-/-mice, contained necrotic areas and displayed T cell infiltration. Tumor cell lines established from MCA- induced tumors were evaluated for their sensitivity to immune-mediated growth control following implantation into immunocompetent C57BL/6 and immunodeficientRag1-/-hosts. Tumors formed byNlrc5+/+tumor cell lines progressed unhindered in C57BL/6 hosts that reflected their immunoedited status, whereas cell lines fromNlrc5-/-andRag1-/-tumors were efficiently controlled, indicating their non-immunoedited status. Proteomic analysis by mass spectrometry followed by pathway analysis revealed enrichment of granzyme-mediated cytolytic pathway inNlrc5+/+tumors that were absent inNlrc5-/-tumors, which showed enrichment of humoral and innate immune pathways. Overall, our findings show that NLRC5 is required for robust tumor immune surveillance and tumor immunoediting and that compensatory humoral and innate immune mechanisms activated by the loss of NLRC5 are insufficient for cancer immune surveillance and cancer immunoediting.
IAP antagonists potentiate TNFα-triggered apoptosis but selectively eliminate senescent tumor cells independently of TNFα
Authors: Ochiiwa Hiroaki , Wakasa Takeshi , Kataoka Yuki , Ando Koji , Oki Eiji , Maehara Yoshihiko , Iimori Makoto , Kitao Hiroyuki
Published: February 2025

Therapy-induced senescence (TIS) is a state of cell division arrest induced by chemotherapy that blocks tumor growth. TIS tumor cells affect the tumor microenvironment through their senescence-associated secretory phenotype and independently acquire stemness, which makes them more aggressive and causes relapse once they regrow. To eradicate tumors by chemotherapy, long-lived TIS tumor cells must be efficiently eliminated. Here, we show that AZD5582 and AT406, which are potent antagonists of inhibitor of apoptosis proteins (IAP antagonists) that suppress the activities of cellular inhibitor of apoptosis protein 1 (cIAP1), cellular inhibitor of apoptosis protein 2 (cIAP2), and X-linked inhibitor of apoptosis protein (XIAP), selectively induced apoptosis mediated by caspase 8 and effector caspases in TIS tumor cells, which produced and secreted tumor necrosis factor α (TNFα). However, these IAP antagonists were still selectively cytotoxic to TIS tumor cells even when TNFα was absent (TNFα-knockout cells) or neutralized (by a neutralizing antibody), indicating they have TNFα-independent senolytic activity. Consistently, these IAP antagonists also sensitized tumor cells that had been induced to become senescent by nutlin-3a, which activates p53 but does not trigger TNFα production. Furthermore, TNFα sensitized tumor cells treated with these IAP antagonists irrespective of their senescence status. Collectively, these data indicate that IAP antagonists that inhibit cIAPs and XIAP not only potentiate TNFα-triggered apoptosis but also have TNFα-independent senolytic activity. We propose that IAP antagonists are good concomitant drugs of chemotherapy that induces TIS, not only as senolytic drugs but also as sensitizers of adjacent non-senescent tumor cells mediated by paracrine TNFα.
Optimizing crop varietal mixtures for viral disease management: A case study on cassava virus epidemics
Authors: Israël Tankam C. , Donnelly Ruairí , Gilligan Christopher A.
Published: February 2025

Cassava viral diseases, including Cassava Mosaic Disease (CMD) and Cassava Brown Streak Disease (CBSD), pose significant threats to global food security, particularly in sub-Saharan Africa. This study explores the potential of varietal mixtures as a sustainable disease management strategy by introducingCropMix, a novel web-based application. The application encodes a flexible insect-borne plant pathogen transmission model to predict and optimize yields under scenarios of varietal mixtures. For instance, we use the application to evaluate the ability of virus-resistant cassava varieties to protect more susceptible varieties against CMD and CBSD, and we also consider mixtures involving tolerant varieties and non-host crops. For CMD, the high transmission rates of cassava mosaic begomoviruses limits the efficacy of mixtures, with susceptible monocultures emerging as better than susceptible-resistant mixtures whatever the whitefly pressure. In contrast, for CBSD, varietal mixtures demonstrate substantial benefits, with resistant varieties shielding susceptible ones and mitigating severe yield losses under moderate or high insect pressure. Management strategies involving non-host crops and complementary control measures, such as roguing, can further enhance outcomes. The model’s simplicity and adaptability make it suitable for tailoring recommendations to diverse insect-borne crop viral diseases and agroecological contexts. The study emphasizes the need for integrating real-world data and participatory frameworks to refine and implement disease management strategies. We discuss the critical balance between agronomic potential and farmer acceptability, underscoring the importance of collaborative efforts to ensure sustainable cassava production.
Cytochrome P450 inhibition impedes pyrethroid effects on insects through Nav channel regulation
Authors: Niklas Beata , Moreau Eleonore , Deshayes Caroline , Rydzewski Jakub , Jankowska Milena , Kesy Jacek , Martins Ademir J , Mueller Pie , Corbel Vincent , Nowak Wieslaw , Lapied Bruno
Published: February 2025

Insecticides used in various formulations are inevitable in agricultural pest control and prevention of vector-borne diseases. Piperonyl butoxide (PBO) is a synergist widely used to enhance the effectiveness of insecticides, notably pyrethroids, by inhibiting the detoxifying cytochrome P450 enzymes, thus reducing the capacity of insects to metabolize and resist insecticides. Recent studies, however, reveal an unexpectedly weak restoration of pyrethroid efficacy by PBO, but the underlying mechanism is unknown. Here, we demonstrate that the PBO-induced inhibition of cytochrome P450 impedes the effect of deltamethrin by mainly affecting its interaction with the inactivated state of voltage-gated sodium channels (Nav). We describe a new octopamine-dependent regulatory mechanism involving Gαs, PKA, DARPP-32, and PP1-2A, which affect the cytochrome P450 conformation, thus limiting the effect of PBO and modulating the Nav gating. As a result, deltamethrin cannot reach its final binding site in the fenestration to exert its full effect. We confirmed in vivo that under chemical stressor, the level of octopamine is elevated, which decreases the deltamethrin efficacy. Our findings reveal a novel adaptation mechanism that increases insect survival by reducing insecticide efficacy, thus emphasizing the necessity of developing more effective formulations and technologies for pest and vector control.
Formyl-peptide receptor type 2 activation mitigates secondary organ damage in inflammatory arthritis
Authors: Margraf Andreas , Chen Jianmin , Christoforou Marilena , Claria-Ribas Pol , Schneider Ayda Henriques , Cecconello Chiara , Bu Weifeng , Imbert Paul RC , Wright Thomas D , Russo Stefan , Blacksell Isobel A , Koenis Duco S , Dalli Jesmond , Lupisella John A , Wurtz Nicholas R , Garcia Ricardo A , Cooper Dianne , Norling Lucy V , Perretti Mauro
Published: February 2025

Rheumatoid arthritis (RA) is associated with heart and lung dysfunction. Current therapies fail to attenuate such complications. Here, we identify formyl-peptide receptor type 2 (FPR2) as therapeutic target to treat heart and lung dysfunction associated with inflammatory arthritis. Arthritic mice on high levels of dietary homocysteine develop cardiac diastolic dysfunction and reduced lung compliance, mirroring two comorbidities in RA. Therapeutic administration of a small molecule FPR2 agonist (BMS986235) to hyper-homocysteine arthritic mice prevented diastolic dysfunction (monitored by echocardiography) and restored lung compliance. These tissue-specific effects were secondary to reduced neutrophil infiltration, modulation of fibroblast activation and phenotype (in the heart) and attenuation of monocyte and macrophage numbers (in the lung). A dual FPR1/2 agonist (compound 43) failed to prevent the reduction in lung compliance of arthritic mice and promoted accumulation of inflammatory monocytes and pro-fibrotic macrophages in lung parenchyma. This cellular response lies downstream of FPR1-mediated potentiation of CCL2-dependent monocyte chemotaxis and activation. This finding supports therapeutic development of selective FPR2 agonists to mitigate two impactful comorbidities associated with inflammatory arthritides.
Metagenomicc Profiling of Drinking Water Microbiomes: Insights into Microbial Diversity and Antimicrobial Resistance
Authors: Kumar Vikas , Sharma Shradha , Tyagi Kaomud , Lenin Barathi , Ravindran Aarti , Raman Karthik , Tyagi Inderjeet
Published: February 2025

Monitoring microbial components in drinking water is as essential as tracking its chemical composition. While traditional culture-based methods can offer valuable insights into the morphology, behavior, and phenotype of organisms, their scope is limited to culturable species. With the advent of high-throughput sequencing, we can now detect a wider range of microbes in any ecosystem, gaining deeper insights into their functional potential and metabolic capabilities more efficiently. In this study, we employed metagenomic analysis to gain a comprehensive understanding of the microbiome of drinking water supplied through public distribution systems in an Indian city. Our findings identified bacteria from the phyla Pseudomonadota, Planctomycetota, Bacteroidota, and Actinomycetota, consistent with previous drinking water microbiome studies. We observed that the composition and diversity of the microbial community were influenced by the temperature of the water samples. No significant correlation between microbial abundance and metal concentration in the sample was detected. Additionally, we assessed the distribution of antibiotic resistance genes (ARGs), finding widespread resistance to aminoglycosides, tetracyclines, and macrolides across samples. However, the risk associated with these ARGs was out of the scope of this study. Overall, this research provides a preliminary analysis of the drinking water microbiome, offering a foundation for future management strategies.
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

DNA 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

Background & Aims

Oncogenic 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.

Methods

To 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.

Results

We 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.

Conclusions

The 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

Understanding 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

The 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

Thyroid 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

Background and Aims

Hidradenitis 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.

Methods

Six 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.

Results

Two 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.

Conclusions

This 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

The 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

We 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

In 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

This 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

Deep 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

Plant 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

Background and Aims

As 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.

Methods

Using 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 Results

Our 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.

Conclusions

These 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.
A Comparative Evaluation of Computational Models for RNA modification detection using Nanopore sequencing with RNA004 Chemistry
Authors: Zou Yongji , Ahsan Mian Umair , Chan Joe , Meng Wen , Gao Shou-Jiang , Huang Yufei , Wang Kai
Published: February 2025

Direct RNA sequencing from Oxford Nanopore Technologies (ONT) has become a valuable method for studying RNA modifications such as N6-methyladenosine (m6A), pseudouridine (ψ), and 5-methylcytosine (m5C). Recent advancements in the RNA004 chemistry substantially reduce sequencing errors compared to previous chemistries (e.g., RNA002), thereby promising enhanced accuracy for epitranscriptomic analysis. In this study, we benchmark the performance of two state-of-the-art RNA modification detection models capable of handling RNA004 data - ONT’s Dorado and m6Anet - using two wild-type (WT) cell lines, HEK293T and HeLa, with respective ground truths from GLORI and eTAM-seq, and their paired in vitro transcribed (IVT) RNA as negative controls. We found that under default settings and considering sites with ≥10% modification ratio and ≥10X coverage, Dorado has higher recall (∼0.92) than m6Anet (∼0.51) for m6A detection. Among the overlapping methylated sites between ground truth and computational predictions, there are high correlations of site-specific m6A modification stoichiometry, with correlation coefficient of ∼0.89 for Dorado-truth comparison and ∼0.72 for m6Anet-truth comparison. However, combined assessment of WT and IVT datasets show that while the per-site false positive rate (FPR) can be lower (∼8% for Dorado and ∼33% for m6Anet), both computational tools can have high per-site false discovery rate (FDR) of m6A (∼40% for Dorado and ∼80% for m6Anet) due to the low prevalence of m6A in transcriptome, with a similar trend observed for pseudouridine (∼95% FDR for Dorado). Additional motif analysis reveals that both Dorado and m6Anet exhibit high heterogeneity of false positive calls across sequence contexts, suggesting that sequence contexts help determine accuracy of specific modification calls. There is also a substantial overlap of false positive calls between the two IVT samples, suggesting a post-filtering strategy to improve modification calling by compiling a set of low-confidence sites with a probabilistic model from several IVT samples across diverse cells/tissues. Our analysis highlights key strengths and limitations of the current generation of m6A detection algorithms and offers insights into optimizing thresholds and interpretability. The IVT datasets generated by the RNA004 chemistry provides a publicly available benchmark resource for further development and refinement of computational methods.
Identification ofAmblyomma americanumantigens after vaccination with tick extracellular vesicles in white-tailed deer
Authors: Oliva Chávez Adela , Gonzalez Julia , Harvey Cristina , Ribeiro-Silva Cárita de Souza , Leal-Galvan Brenda , Persinger Kelly A. , Durski Sarah , Olafson Pia U. , Johnson Tammi L.
Published: February 2025

Anti-tick vaccines represent a promising alternative to chemical acaricides for the management of ticks on wildlife; however little progress has been made to produce a vaccine effective in wild hosts that are critical for tick reproduction, such as the white-tailed deer (Odocoileus virginianus; WTD). To date, most tick antigens have been tested using laboratory models (i.e. rabbits); however, their expression in wild hosts has not been confirmed. We recently testedAmblyomma americanumsalivary (SG) and midgut (MG) extracellular vesicles (EVs) as vaccine candidates in WTD, which resulted in on-host female tick mortality. Using a proteomic approach, we show that these SG- and MG-EVs contain a “core-cargo” enriched in chaperones, small GTPases, actin and actin-related proteins, and other proteins previously reported in small EVs. Label-free quantitative proteomics showed significant differences in protein cargo between MG and SG-EVs (333 proteins out of 516). Pre-vaccinated and day 57 post-injection serum samples from three vaccinated and one control WTD were used to immuno-precipitate antigenic proteins from SG- and MG-EV preparations. Proteomic analysis of immunoprecipitated proteins identified thirty antigens with potential for use in anti-tick vaccines, seven of which we have categorized as high priority. These proteins represent promising candidates for anti-tick vaccine design in WTD and other wildlife hosts.
NanoBEP – A Machine Learning Based Tool for Nanobody Binding Energy Prediction
Authors: Sahoo Soma Prasad , Manickavasagam Pratibha , Priya M. Hamsa
Published: February 2025

Nanobody is a special class of antibodies comprising only one variable heavy chain. Its small size and high stability over a wide range of temperature and pH, makes it an ideal candidate for biomedical applications. Designing a nanobody that can bind to a specific target protein, either for therapeutic or diagnostic purposes, requires a quick estimation of binding affinity of nanobody-protein complex. Many predictive models for protein-protein interactions have been developed leveraging the capability of machine learning techniques. The popular protein-protein interaction models, however, could not accurately predict the binding affinity of available nanobody-protein complexes. We, therefore, have developed a random forest based model that can predict the value of dissociation constant (log10Kd) at high accuracy with a Pearson’s correlation coefficient value of 0.95 and a mean absolute error of 0.44. Our cherry-picked model identifies the best protein features for the prediction through two stages of selection strategy that includes elimination of highly correlated features through graph network analysis, followed by the recursive feature elimination through random forest. Despite being a class of antibodies, a model trained only on antigen-antibody complexes couldn’t accurately predict the binding affinity of the nanobody-protein complexes. The predictability improved only when we included the data on monomeric protein complexes and some nanobody-protein complexes during training.
dandelionR: Single-cell immune repertoire trajectory analysis in R
Authors: Yu Jiawei , Xu Xiaohan , Borcherding Nicholas , Tuong Zewen Kelvin
Published: February 2025

Integration of single-cell RNA-sequencing (scRNA-seq) and adaptive immune receptor (AIR) sequencing (scVDJ-seq) is extremely powerful in studying lymphocyte development. A python-based package,Dandelion, introduced VDJ-feature space method, which addresses the challenge in integration of single-cell AIR data with gene expression data and enhanced the trajectory analysis results. However, no R-based equivalent or similar methods currently exist. To fill this gap, we presentdandelionR, an R implementation ofDandelion’s trajectory analysis workflow, bringing the VDJ feature space construction and trajectory analysis using diffusion map and absorbing Markov chain to R, offering a new option for scRNA-seq and scVDJ-seq analysis to R language users.
Enhancing Protein Graph Representations through Static-Dynamic Fusion
Authors: Guo Pengkang , Correia Bruno , Vandergheynst Pierre , Probst Daniel
Published: February 2025

Machine learning for protein modeling faces significant challenges due to proteins’ inherently dynamic nature, yet most graph-based machine learning methods rely solely on static structural information. Recently, the growing availability of molecular dynamics trajectories provides new opportunities for understanding the dynamic behavior of proteins; however, computational methods for utilizing this dynamic information remain limited. We propose a novel graph representation that integrates both static structural information and dynamic correlations from molecular dynamics trajectories, enabling more comprehensive modeling of proteins. By applying relational graph neural networks (RGNNs) to process this heterogeneous representation, we demonstrate significant improvements over structure-based approaches across three distinct tasks: atomic adaptability prediction, binding site detection, and binding affinity prediction. Our results validate that combining static and dynamic information provides complementary signals for understanding proteinligand interactions, offering new possibilities for drug design and structural biology applications.
Arbor function of TRANSPARENT TESTA GLABRA 1 and LIGHT REGULATED WD scaffold proteins in the Arabidopsis circadian oscillators includes transcriptional repression through PSEUDO RESPONSE REGULATORS
Authors: Herrero Eva , Cano-Ramirez Dora , Glover Beverley J. , Webb Alex A. R.
Published: February 2025

Arabidopsis circadian oscillators contain DNA-binding proteins that function at specific times of the day. In contrast, we have discovered a unique continuous function of WD40-repeat scaffold proteins from the TRANSPARENT TESTA GLABRA-1 (TTG1), LIGHT REGULATED WD1 and LIGHT REGULATED LWD2 subfamily (TLWD) which is essential to maintain circadian rhythms. Gene expression analyses indicate multifunctional activity of TLWD in both transcriptional activation and repression. TLWD proteins interact with an array of circadian oscillator activators and repressors that act sequentially throughout the diel cycle. While TLWD proteins were known to participate in activator complexes, our data indicate a novel role of TLWD in transcriptional repression through complex formation with repressors from the PSEUDO RESPONSE REGULATOR (PRR) family. In an analogy to mechanical clocks, TLWD scaffold proteins constitute an arbor, or spindle, to which transcription factors, which represent the cogs, bind to sustain circadian rhythms.
IRF7 controls spontaneous autoimmune germinal center and plasma cell checkpoints
Authors: Fike Adam J. , Bricker Kristen N. , Gonzalez Michael V. , Maharjan Anju , Bui Tien , Nuon Keomonyroth , Emrich Scott M. , Weber Julia L. , Luckenbill Sara A. , Choi Nicholas M. , Sauteraud Renan , Liu Dajiang J. , Olsen Nancy J. , Caricchio Roberto , Trebak Mohamed , Chodisetti Sathi Babu , Rahman Ziaur S.M.
Published: February 2025

How IRF7 promotes autoimmune B cell responses and systemic autoimmunity is unclear. Analysis of spontaneous SLE-prone mice deficient in IRF7 uncovered the IRF7 role in regulating autoimmune germinal center (GC), plasma cell (PC) and autoantibody responses and disease. IRF7, however, was dispensable for foreign antigen driven GC, PC and antibody responses. Competitive bone marrow (BM) chimeras highlighted the importance of IRF7 in hematopoietic cells in spontaneous GC and PC differentiation. Single-cell-RNAseq of SLE-prone B cells indicated IRF7 mediated B cell differentiation through GC and PC fates. Mechanistic studies revealed that IRF7 promoted B cell differentiation through GC and PC fates by regulating the transcriptome, translation, and metabolism of SLE-prone B cells. Mixed BM chimeras demonstrated a requirement for B cell-intrinsic IRF7 in IgG autoantibody production but not sufficient for promoting spontaneous GC and PC responses. Altogether, we delineate previously unknown B cell-intrinsic and -extrinsic mechanisms of IRF7-promoted spontaneous GC and PC responses, loss of tolerance, autoantibody production and SLE development.

Fike et al. describe previously unknown mechanisms by which IRF7 controls autoimmune B cell and autoantibody responses. Mechanistic studies guided by single-cell-RNAseq and ChIPseq reveal that IRF7 promotes B cell differentiation through germinal center and plasma cell fates by regulating the transcriptome, translation, and metabolism of lupus-prone B cells.