bluuebunny/crossref_metadata_2025 huggingface dataset:
Biosynth Pipeline: An integrated platform for merging the computational design of chimeric type I polyketide synthases with enzymatic pathways for chemical biosynthesis
Authors: Chainani Yash , Diaz Jacob , Guilarte-Silva Margaret , Blay Vincent , Tyo Keith E. J. , Broadbelt Linda J. , Mukhopadhyay Aindrila , Keasling Jay D. , Martin Hector Garcia , Backman Tyler W. H.
Published: November 2024

Synthetic biology offers the promise of manufacturing chemicals sustainably than petrochemistry. Yet, both the rate at which biomanufacturing synthesize these molecules and the net chemical accessible space limited by existing pathway discovery methods which rely arduous literature searches. Here, present automated retrobiosynthesis tool, Biosynth Pipeline, that simultaneously tackles both problems by integrating multifunctional type I polyketide synthases (PKSs) with monofunctional enzymes to propose the synthesis of desired target chemicals via two tools: DORAnet and RetroTide. While monofunctional enzymes valuable for carefully decorating substrate’s carbon backbone, they typically cannot expand the backbone itself. PKSs can, instead, predictably do this through their unique ability to catalyze carbon-carbon bond formation reactions iteratively. We evaluated the performance of Biosynth Pipeline against previously published set of 155 molecules of interest for biomanufacturing, and report that Biosynth Pipeline could produce exact designs for 93 of them, well pipelines to chemically similar product for most of the remaining molecules. Furthermore, Biosynth Pipeline successfully proposes biosynthetic routes for complex therapeutic natural products (cryptofolione and basidalin) for which no known biosynthetic pathway currently exists.
A cross-study transcriptional patient map of heart failure defines conserved multicellular coordination in cardiac remodeling
Authors: Lanzer Jan D. , Ramirez Flores Ricardo O. , Liñares Blanco José , Saez-Rodriguez Julio
Published: November 2024

Heart failure (HF) is characterized by severely reduced cardiac function and tissue remodeling, driven by complex multicellular regulatory processes. Extensive studies have generated molecular profiles at both bulk and single-cell levels; however, systematic integration that describes tissue-wide changes as a function of cell type coordination remains challenging. This disconnect hampers our understanding of the complex multicellular interactions driving heart failure, limiting our ability to translate molecular insights into actionable therapeutic strategies. Here, we integrated bulk and single-cell transcriptional profiles from cardiac tissues of HF and control patients across 25 studies, covering 1,524 individuals and seven cell-types, to delineate consensus multicellular transcriptional changes associated with cardiac remodeling. Our analyses revealed conserved cellular coordination events involving fibrotic, metabolic, inflammatory, and hypertrophic mechanisms, with fibroblasts playing a central role in predicting cardiomyocyte stress. Further analysis of fibroblast populations suggested that their activation in HF represents a broad phenotypic shift rather than solely accumulating distinct cell states. The integration of bulk and single-cell data within our data collection indicated that transcriptional responses to HF across cell types occur independently of tissue composition. Mapping independent data into our consensus programs demonstrated that recovery after left ventricular assist device implantation aligns with molecular recovery, highlighting the clinical relevance of the multicellular molecular state. Overall, our work synthesizes independent cardiac transcriptomics studies and makes the conserved HF associated insights available, establishing a reference for detailed exploration of HF-related multicellular molecular events.Graphical Abstract
mcBERT: Patient-Level Single-cell Transcriptomics Data Representation
Authors: Querfurth Benedikt von , Lohmöller Johannes , Pennekamp Jan , Bleckwehl Tore , Kramann Rafael , Wehrle Klaus , Hayat Sikander
Published: November 2024

Single-cell RNA sequencing (scRNA-seq) transcriptomics improves our understanding of cellular heterogeneity in healthy and pathological states. However, most scRNA-seq analyses remain confined to single cells or distinct cell populations, limiting their clinical applicability. Addressing the need to translate single-cell insights into a patient-level disease understanding, we introduce mcBERT, a new method that leverages scRNA-seq data and a transformer-based model to generate integrative patient representations using a self-supervised learning phase followed by contrastive learning to refine these representations. Our evaluations of mcBERT across 7 million cells from 1223 individuals encompassing diverse disease states in heart, kidney, blood cell, and lung tissues show that learned representations facilitate a robust identification of disease cohorts and enable comparisons of patient similarity. Moreover, our findings indicate that mcBERT can accurately classify disease phenotypes, also in previously unseen biospecimens and patients. Independent of the specific tissue, mcBERT extends the utility of scRNA-seq data from cellular analysis to potentially actionable patient-centric applications.
Towards a standardised method for the characterisation and isolation of colorectal cancer stem cells by SdFFF and UHF-DEP: highlighted by transcriptomic analysis
Authors: Jemfer Charlotte , Blasco Nina , Durand Stéphanie , Blin Elisa , Mas Robin , Basly Isabelle , Boutaud Marie , Daverat Héloïse , Pothier Arnaud , Dalmay Claire , Mathonnet Muriel , Begaud Gaelle , Battu Serge
Published: November 2024

Cancer stem cells (CSCs) play a crucial role in tumor heterogeneity and the progression of colorectal cancer (CRC). However, identifying and isolating CSCs remains challenging, as conventional methods, such as fluorescent or magnetic labeling, are time-consuming and require substantial technical and biological resources, limiting their clinical applicability. In this study, we evaluated the potential application of a previously established approach with glioma cells, combining sedimentation field-flow fractionation (SdFFF) with a label-free Ultra-High Frequency dielectrophoresis (UHF-DEP) biosensor, for isolating and identifying CRC CSC. The integration of the UHF-DEP biosensor with SdFFF enables the identification of CSCs without specific labeling, simplifying their analysis. To optimize this coupling, we standardized the mobile phase between the two technologies. Producing two CSC sub-populations eluted in Fraction 1 and Fraction 3. For the first time, transcriptomic analysis was employed to deepen our understanding of the genetic composition of the cells, complementing functional and phenotypic characterizations. From these characteristics, it emerged that F1 cells corresponded to precursors, while F3 cells could be considered CSC. The UHF-DEP biosensor demonstrated its ability to detect these differences, linking F3 to cells cultivated in defined medium (DM), used as a reference standard. Finally, transcriptomic analysis (RNA-seq) has deepened our understanding of the genetic profiles of these subpopulations, enriching the interpretation of their characteristics as CSCs. This in-depth approach will also contribute to a better understanding of the results obtained by the UHF-DEP biosensor.
Holotomographic microscopy reveals label-free quantitative dynamics of endothelial cells during endothelialization
Authors: Leineweber William D. , Munares Gabriela Acevedo , Leycam Christian , Noyer Juliette , Jurney Patrick
Published: November 2024

Holotomograhic microscopy (HTM) has emerged as a non-invasive imaging technique that offers high-resolution, quantitative 3D imaging of biological samples. This study explores the application of HTM in examining endothelial cells (ECs). HTM overcomes the limitations of traditional microscopy methods in capturing the real-time dynamics of ECs by leveraging the refractive index (RI) to map 3D distributions label-free. This work demonstrates the utility of HTM in visualizing key cellular processes during endothelialization, wherein ECs anchor, adhere, migrate, and proliferate. Leveraging the high resolution and quantitative power of HTM, we show that lipid droplets and mitochondria are readily visualized, enabling more comprehensive studies on their respective roles during endothelialization. The study highlights how HTM can uncover novel insights into EC behavior, offering potential applications in medical diagnostics and research, particularly in developing treatments for cardiovascular diseases. This advanced imaging technique not only enhances our understanding of EC biology but also presents a significant step forward in the study of cardiovascular diseases, providing a robust platform for future research and therapeutic development.
Hallmarks of uterine receptivity predate placental mammals
Authors: Basanta Silvia , Stadtmauer Daniel J. , Maziarz Jamie D. , McDonough-Goldstein Caitlin E. , Cole Alison G. , Dagdas Gülay , Wagner° Günter P. , Pavličev Mihaela
Published: November 2024

Embryo implantation requires tightly coordinated signaling between the blastocyst and the endometrium, and is crucial for the establishment of a uteroplacental unit that persists until term in eutherian mammals. In contrast, marsupials, with a unique life cycle and short gestation, make only brief fetal-maternal contact and lack implantation. To better understand the evolutionary link between eutherian implantation and its ancestral equivalent in marsupials, we compare single-cell transcriptomes from the receptive and non-receptive endometrium of the mouse and guinea pig with that of the opossum, a marsupial. We identify substantial differences between rodent peri-implantation endometrium and opossum placental attachment, including differences in the diversity and abundance of stromal and epithelial cells which parallel the difference between histotrophic and hemotrophic provisioning strategies. We also identify a window of conserved epithelial gene expression between the opossum shelled blastocyst stage and rodent peri-implantation, includingIHHandLIF. We find strong conservation of blastocyst proteases, steroid synthetases, Wnt and BMP signals between eutherians and the opossum despite its lack of implantation. Finally, we show that the signaling repertoire of the maternal uterine epithelium during implantation displays substantial overlap with that of the post-implantation placental trophoblast, suggesting that the fetal trophoblast can compensate for the loss of endometrial epithelium in eutherian invasive placentation. Together, our results suggest that eutherian implantation primarily involved the re-wiring of maternal signaling networks, some of which were already present in the therian ancestor, and points towards an essential role of maternal innovations in the evolution of invasive placentation.
Tenascin-C potentiates Wnt signaling in thyroid cancer
Authors: Hartmann Heather A. , Loberg Matthew A. , Xu George J. , Schwarzkopf Anna C. , Chen Sheau-Chiann , Phifer Courtney J. , Caroland Kailey , Chen Hua-Chang , Diaz Diana , Tigue Megan L. , Hesterberg Amanda B. , Gallant Jean-Nicolas , Shaddy Sophia M. , Sheng Quanhu , Netterville James L. , Rohde Sarah L. , Solórzano Carmen C. , Bischoff Lindsay A. , Baregamian Naira , Hurley Paula J. , Murphy Barbara A. , Choe Jennifer H. , Huang Eric C. , Ye Fei , Lee Ethan , Weiss Vivian L.
Published: November 2024

Tenascin-C (TNC) is a secreted extracellular matrix protein that is highly expressed during embryonic development and re-expressed during wound healing, inflammation, and neoplasia. Studies in developmental models suggest that TNC may regulate the Wnt signaling pathway. Our lab has shown high levels of Wnt signaling and TNC expression in anaplastic thyroid cancer (ATC), a highly lethal cancer with an abysmal ∼3-5 month median survival. Here, we investigated the role of TNC in facilitating ligand-dependent Wnt signaling in thyroid cancer. We utilized bulk RNA-sequencing from three independent multi-institutional thyroid cancer patient cohorts. TNC expression was spatially localized in patient tumors with RNA in situ hybridization. The role of TNC was investigated in vitro using Wnt reporter assays and in vivo with a NOD.PrkdcscidIl2rg-/- mouse ATC xenograft tumor model. TNC expression was associated with aggressive thyroid cancer behavior, including anaplastic histology, extrathyroidal extension, and metastasis. Spatial localization of TNC in patient tissue demonstrated a dramatic increase in expression within cancer cells along the invasive edge, adjacent to Wnt ligand-producing fibroblasts. TNC expression was also increased in areas of intravascular invasion. In vitro, TNC bound Wnt ligands and potentiated Wnt signaling. Finally, in an ATC mouse model, TNC increased Wnt signaling, tumor burden, invasion, and metastasis. Altogether, TNC potentiated ligand driven Wnt signaling and promotes cancer cell invasion and metastasis in a mouse model of thyroid cancer. Understanding the role of TNC and its interaction with Wnt ligands could lead to the development of novel biomarkers and targeted therapeutics for thyroid cancer.
Discovering and exploiting active sensing motifs for estimation with empirical observability
Authors: Cellini Benjamin , Boyacıoğlu Burak , Stupski Stanley David , van Breugel Floris
Published: November 2024

Organisms and machines must use measured sensory cues to estimate unknown information about themselves or their environment. Cleverly applied sensor motion can be exploited to enrich the quality of sensory data and improve estimation. However, a major barrier to modeling such active sensing problems is the lack of empirical, yet rigorous, tools for quantifying the relationship between movement and estimation performance. Here, we introduce “BOUNDS: Bounding Observability for Uncertain Nonlinear Dynamic Systems”. BOUNDS can discover patterns of sensor motion that increase information and reduce uncertainty in either real or simulated data. Crucially, it is suitable for high dimensional and partially observable nonlinear systems with sensor noise. We demonstrate BOUNDS through a case study on how flying insects estimate wind properties, showing that specific active sensing motifs improve estimation. Additionally, we present a framework to refine sporadic estimates from active sensing. When combined with an artificial neural network, we show that the information gained via active sensing in realDrosophilaflight trajectories is suitable for precise wind direction estimation. Collectively, our work will help decode active sensing in organisms and inform the design of estimation algorithms for machines.
Protein sequencing with single amino acid resolution discerns peptides that discriminate tropomyosin proteoforms
Authors: Sittipongpittaya Natchanon , Skinner Kenneth A. , Jeffery Erin D. , Watts Emily F. , Sheynkman Gloria M.
Published: November 2024

Protein variants of the same gene—proteoforms—can have high molecular similarity yet exhibit different biological functions. Thus, identifying unique peptides that unambiguously map to proteoforms can provide crucial biological insights. In humans, four human tropomyosin (TPM) genes produce similar proteoforms that can be challenging to distinguish with standard proteomics tools. For example, TPM1 and TPM2 share 85% sequence identity, with amino acid substitutions that play unique roles in muscle contraction and myopathies. In this study, we evaluated the ability of the recently released Platinum single-molecule protein sequencer to detect proteoform-informative peptides. Platinum employs fluorophore-labeled recognizers that reversibly bind to cognate N-terminal amino acids (NAAs), enabling polypeptide sequencing within nanoscale apertures of a semiconductor chip that can accommodate single peptide molecules. As a proof of concept, we evaluated the ability of Platinum to distinguish three main types of proteoform variation: paralog-level, transcript-level, and post-translational modification (PTM). We distinguished paralogous TPM1 and TPM2 peptides differing by a single isobaric residue (leucine/isoleucine). We also distinguished tissue-specific TPM2 spliceforms. Notably, we found that a phosphotyrosine-modified peptide displayed reduced recognizer affinity for tyrosine, showing sensitivity to PTMs. This study paves the way for the targeted detection of proteoform biomarkers at the single molecule level.

Abstract Figure
Phytochemicals fromDaucus carotahave therapeutic potential against Triple-Negative Breast Cancer PDK1 and PLK1
Authors: Raheem Kayode , Abayomi Modinat , Oluwatosin Maryam , Adewunmi Mary , Ali Ijaz , Muddassar Muhammad
Published: November 2024

Triple-negative breast cancer (TNBC) is a deadly form of breast cancer that lacks estrogen, progesterone, and HER2 receptors. The development of drugs for TNBC has been challenging due to the lack of specific therapeutic targets. However, recent studies have shown that targeting the ATP active of the PDK-1 and PLK-1 proteins could be potential drug targets for TNBC treatment. New medications for TNBC have considerable adverse effects, highlighting the need for more targeted and effective therapies.

In this study, we employed various computational approaches, including molecular docking, molecular dynamics (MD) simulations, pharmacokinetic studies, binding free energy calculations, principal component analysis (PCA), and alanine scanning analysis, to identify bioactive compounds fromDaucus carota-extracted natural compounds that can bind to these ATP-binding sites and inhibit the activity of PDK1 and PLK1. Our study revealed that eight compounds showed reasonably good docking scores, binding free energies, and ADMET properties against the PDK1 and PLK1 enzymes. Astragalin and scolimoside showed substantial binding affinity and persistent interactions in the pocket region of the two proteins. Further MD simulation studies for 150 ns also suggested that the compounds were stably bound in the active site with very minor fluctuations. We believe that the identified hits for PDK1 and PLK1 fromDaucus carotawill be effective against TNBC in performing the biological assays.
Comparative transcriptomic insights into the evolutionary origin of the tetrapod double cone
Authors: Tommasini Dario , Yoshimatsu Takeshi , Baden Tom , Shekhar Karthik
Published: November 2024

The tetrapod double cone is a pair of tightly associated cones called the “principal” and the “accessory” member. It is found in amphibians, reptiles, and birds, as well as monotreme and marsupial mammals but is absent in fish and eutherian mammals. To explore the potential evolutionary origins of the double cone, we analyzed single-cell and -nucleus transcriptomic atlases of photoreceptors from six vertebrate species: zebrafish, chicken, lizard, opossum, ground squirrel, and human. Computational analyses separated the principal and accessory members in chicken and lizard, identifying molecular signatures distinguishing either member from single cones and rods in the same species. Comparative transcriptomic analyses suggest that both the principal and accessory originated from ancestral red cones. Furthermore, the gene expression variation among cone subtypes mirrors their spectral order (red→green→blue→UV), suggesting a constraint in their order of emergence during evolution. Finally, we find that rods are equally dissimilar to all cone types, suggesting that they emerged before the spectral diversification of cones.
Phospholipid signaling and multivesicular endolysosomes modulate membrane dynamics at the biotrophic interface in Rice Blast
Authors: Selvaraj Poonguzhali , Yang Fan , Zheng Wenhui , Naqvi Naweed I.
Published: November 2024

Magnaporthe oryzae, the rice blast pathogen, secretes an arsenal of apoplastic and cytoplasmic effector proteins to suppress host immunity during the biotrophy phase. The proposed non-conventional secretion of cytoplasmic effectors into the Biotrophic Interfacial Complex (BIC), remains uncharted except for the involvement of the exocyst complex therein. Recently, the plant endocytic machinery has been implicated in translocation of cytoplasmic effectors to the host. Here, we used live cell imaging and mutant analyses to provide new insight into late endolysosomal mediators as conduits for establishment of the BIC and/or unconventional secretion across the host interface. Rerouting of the late endocytic GTPase Rab7 occurs at the BIC; and the dominant negative Rab7T22Nled to significant defects in focal interface formation. FYVE biosensor and pharmacological interventions revealed that Rab7 membrane trafficking and establishment/integrity of the biotrophy interface requires the PI3 kinase Vps34 and phosphoinositide PI3(P) function. Additional pharmacological evidence supports endolysosomal trafficking to the host interface follows a distinct non-conventional secretion route too. Finally, we show that the Multi-Vesicular Bodies and lysosomal membranes act as downstream modules of the Rab7 function in precise sorting and specialised traffic of cytoplasmic effectors across theMagnaporthe-Rice interface during blast disease.
Exome-wide analysis of congenital kidney anomalies reveals new genes and shared architecture with developmental disorders
Authors: Milo Rasouly Hila , Krishna Murthy Sarath Babu , Vena Natalie , Povysil Gundula , Beenken Andrew , Verbitsky Miguel , Shril Shirlee , Lekkerkerker Iris , Khan Atlas , Fasel David , Wongboonsin Janewit , Martino Jeremiah , Ke Juntao , Elefant Naama , Tomar Nikita , Harnof Ofek , Yang Sandy , Kisselev Sergey , Bheda Shiraz , Reytan-Miron Sivan , Lim Tze Y , Jamry-Dziurla Anna , Lugani Francesca , Zhang Jun Y , Marasa Maddalena , Kolupaeva Victoria , Groopman Emily E. , Jin Gina , Ghavami Iman , Stevens Kelsey O. , Coughlin Arielle C. , Kil Byum Hee , Chatterjee Debanjana , Bradbury Drew , Zheng Jason , Mehl Karla , Morban Maria , Reingold Rachel , Piva Stacy , Mu Xueru , Mittrori Adele , Szmigielska Agnieszka , Gliwińska Aleksandra , Ranghino Andrea , Bomback Andrew S , Badenski Andrzej , Latos-Bielenska Anna , Materna-Kiryluk Anna , Amoroso Antonio , Izzi Claudia , La Scola Claudio , Cohen David Jonathan , Santoro Domenico , Drozdz Dorota , Fiaccadori Enrico , Lin Fangming , Scolari Francesco , Tondolo Francesco , La Manna Gaetano , Appel Gerald B , Ghiggeri Gian Marco , Zaza Gianluigi , Montini Giovanni , Masnata Giuseppe , Krzemien Grażyna , Pisani Isabella , Radhakrishnan Jai , Zachwieja Katarzyna , Monaco Lauren , Gesualdo Loreto , Biancone Luigi , Murer Luisa , Mizerska-Wasiak Malgorzata , Tkaczyk Marcin , Zaniew Marcin , Borszewska-Kornacka Maria K. , Szczepanska Maria , Saraga Marijan , Rao Maya K , Bodria Monica , Miklaszewska Monika , Uy Natalie S , Baraldi Olga , Bjanid Omar , Esposito Pasquale , Zamboli Pasquale , Marzuillo Pierluigi , Canetta Pietro A , Sikora Przemyslaw , Westland Rik , Crew Russell J , Alam Shumyle , Guarino Stefano , Negrisolo Susanna , Hays Thomas , Grandinetti Valeria , Tasic Velibor , Lozanovski Vladimir J. , Caliskan Yasar , Goldstein David , Lifton Richard P , Ionita-Laza Iuliana , Kiryluk Krzysztof , van Eerde Albertien , Hildebrandt Friedhelm , Sanna-Cherchi Simone , Gharavi Ali G
Published: November 2024

Kidney anomalies (KA) are developmental disorders that commonly cause pediatric chronic kidney disease and mortality. We examined rare coding variants in 248 KA trios and 1,742 singleton KA cases and compared them to 22,258 controls. Diagnostic and candidate diagnostic variants were detected in 14.1% of cases. We detected a significant enrichment of rare damaging variants in constrained genes expressed during kidney development and in genes associated with other developmental disorders, suggesting phenotype expansion. Consistent with these data, 18% of KA patients with diagnostic variants had neurodevelopmental or cardiac phenotypes. Extrarenal developmental phenotypes were associated with a higher burden of rare variants. Statistical analyses identified 40 novel candidate genes, 2 of which were confirmed as new KA genes:ARID3AandNR6A1.This study suggests that many yet-unidentified syndromes would be discoverable with larger cohorts and cross-phenotype analysis, leading to clarification of the genetic and phenotypic spectrum of developmental disorders.
VirNA: a novel Minimum Spanning Networks algorithm for investigating viral evolution
Authors: Mazzotti G. , Bianco L. , Bado M. , Lavezzo E. , Toppo S. , Fontana P.
Published: November 2024

Next Generation Sequencing technologies are essential in public health surveillance for tracking pathogen evolution, spread, and the emergence of new variants. However, the extensive sequencing of viral genomes during recent pandemics has highlighted the limitations of traditional molecular phylogenetic algorithms in capturing fine-grained evolutionary details, emphasizing the urge for more effective approaches to manage these large-scale data. VirNA (Viral Network Analyzer) addresses this challenge by reconstructing detailed mutation patterns and tracing pathogen evolutionary routes in specific regions through Minimum Spanning Networks. It analyzes thousands of sequences, generating networks where nodes represent identical genomic sequences linked to their metadata, while edges represent evolutionary pathways.

AUTHOR SUMMARY

The authors present Viral Network Analyzer (VirNA), a new tool designed to help track the spread of viruses during pandemics. During recent outbreaks, researchers faced challenges due to the sheer volume of viral genome data. Traditional tools struggled to process this massive amount of information effectively. VirNA solves this problem by using a powerful method called Minimum Spanning Networks (MSN) with enhanced features to analyze large datasets quickly and accurately. VirNA allows scientists to map how viruses spread in specific areas, providing critical insights that other tools couldn’t achieve. It complements traditional phylogenetic methods, offering a detailed look at viral transmission routes. This makes it a valuable asset for public health surveillance, helping experts understand and respond to pandemics more effectively. Already tested in previous studies, VirNA represents a significant breakthrough for future pandemic preparedness, offering new ways to handle and interpret big data in viral research.
Neratinib, a clinical drug against breast cancer, protects against atherosclerosis via ASK1 inhibition
Authors: Zhang Fsnshun , Yin Yanjun , Wang Zhihua , Wu Xiumei , Kamato Danielle , Weng Jianping , Xu Suowen
Published: November 2024

Atherosclerosis commences with endothelial dysfunction and the retention of cholesterol within the vessel wall, followed by a chronic inflammatory response. Cholesterol-lowering strategies (such as statins and PCSK9 inhibitors) are primarily used for treating patients with atherosclerotic cardiovascular diseases, but leaving the therapeutic dilemma of residual inflammatory risk. To address this challenge, we employed Connectivity Map (CMap) screening for inflammation mechanism-based anti-atherosclerotic compounds using perturbational datasets obtained from TNFalpha and IL-1beta-stimulated human endothelial cells. This screening process allow us to identify Neratinib, a clinical drug against breast cancer, as the hit compound with potential anti-inflammatory actions in endothelial cells. Further studies reveal that Neratinib inhibited endothelial cell inflammation elicited by three different pro-inflammatory stimuli (TNFalpha, IL-1beta and LPS). Intriguingly, the anti-inflammatory effect of Neratinib was independent of its classical target HER2/ERBB2 inhibition. Mechanistically, Neratinib directly binds ASK1 and suppresses ASK1 activation. In both male and female Ldlr-/- mice, treatment with Neratinib decreased the plaque area, reduced the necrotic core size and mitigated macrophage infiltration to stabilize plaques. Lastly, we observed that Neratinib, in conjunction with the use of Rosuvastatin (a standard lipid-lowering drug), led to a reduction in serum lipids, and produced synergistic anti-atherosclerotic effects. Olink proteomics study suggested that combination treatment alleviated inflammation-related cytokines/chemokines in the serum from Ldlr-/- mice. Taken together, these findings support the concept that Neratinib could be tested for its potential as a "repurposed" drug for vascular inflammation and atherosclerosis, thereby streamlining efforts to translate preclinical discoveries to clinical testing in humans.
Critical Spacing in Cell-Matrix Mechanical Feedback Controls Tissue Condensation
Authors: Peng Xiangjun , Huang Yuxuan , Elson Elliot L. , Genin Guy M. , Feng Xi-Qiao
Published: November 2024

The mechanical interplay between cells and their extracellular matrix (ECM) presents a fundamental paradox in mechanobiology: while individual cells respond monotonically to increasing mechanical stimulus, collective cellular behaviors exhibit sharp transitions at critical cell densities. This is particularly evident in tissue condensation, where cell-seeded collagen matrices either dramatically contract or remain unchanged depending on whether the initial cell spacing falls below or above a critical threshold. Here we resolve this apparent contradiction through bio-chemo-mechanical modeling of cell-ECM interactions. We show that while increasing ECM stiffness enhances individual cell activation, it simultaneously weakens the mechanical cross-talk between cells, creating a non-monotonic relationship that governs collective behavior. This competition between local activation and neighbor communication establishes a critical spacing threshold below which cells can mechanically polarize their neighbors through ECM remodeling. The predicted critical spacing aligns with experimental observations of the cell density required for tissue condensation, reconciling single-cell and collective responses. Our model reveals how recursive interactions between cellular contractility and ECM mechanics give rise to emergent spatial ordering, demonstrating how complex multicellular behaviors can emerge from simple mechanical principles. These findings provide a physical basis for understanding mechanobiological signaling, with implications for tissue development and disease progression.
An SH3-binding allosteric modulator stabilizes the global conformation of the AML-associated Src-family kinase, Hck
Authors: Selzer Ari M. , Gerlach Gabriella , Gonzalez-Areizaga Giancarlo , Wales Thomas E. , Cui Stephanie Y. , Iyer Prema , Engen John R. , Camacho Carlos , Ishima Rieko , Smithgall Thomas E.
Published: November 2024

While ATP-site inhibitors for protein-tyrosine kinases are often effective drugs, their clinical utility can be limited by off-target activity and acquired resistance mutations due to the conserved nature of the ATP-binding site. However, combining ATP-site and allosteric kinase inhibitors can overcome these shortcomings in a double-drugging framework. Here we explored the allosteric effects of two pyrimidine diamines, PDA1 and PDA2, on the conformational dynamics and activity of the Src-family tyrosine kinase Hck, a promising drug target for acute myeloid leukemia. Using1H-15N HSQC NMR, we mapped the binding site for both analogs to the SH3 domain. Despite the shared binding site, PDA1 and PDA2 had opposing effects on near-full-length Hck dynamics by hydrogen-deuterium exchange mass spectrometry, with PDA1 stabilizing and PDA2 disrupting the overall kinase conformation. Kinase activity assays were consistent with these observations, with PDA2 enhancing kinase activity while PDA1 was without effect. Molecular dynamics simulations predicted selective bridging of the kinase domain N-lobe and SH3 domain by PDA1, a mechanism of allosteric stabilization supported by site-directed mutagenesis of N-lobe contact sites. Cellular thermal shift assays confirmed SH3 domaindependent interaction of PDA1 with wild-type Hck in myeloid leukemia cells and with a kinase domain gatekeeper mutant (T338M). These results identify PDA1 as a starting point for Src-family kinase allosteric inhibitor development that may work in concert with ATP-site inhibitors to suppress the evolution of resistance.
Oral exposure to PET microplastics alters the pancreatic transcriptome – implications for the pathogenesis of type 1 diabetes
Authors: Mierzejewski Karol , Kurzyńska Aleksandra , Golubska Monika , Gałęcka Ismena , Całka Jarosław , Bogacka Iwona
Published: November 2024

Type 1 diabetes is a chronic autoimmune disease, the incidence of which has been steadily increasing in recent years, particularly among adolescents. The disease results from a combination of genetic and environmental factors that lead to the destruction of insulin-producing beta cells in the pancreas. Recently, the potential role of microplastics in the pathogenesis of various diseases has gained attention. Therefore, the aim of this study was to investigate the impact of PET microplastics on the pancreas using immature pigs as a model organism. The global transcriptomic profile of the pancreas was analyzed in piglets treated with either a low (0.1 g/day) or high dose (1 g/day) of PET microplastics for 4 weeks using RNA-Seq. The analysis revealed a dose-dependent effect of PET microplastics on gene expression. A low dose affected the expression of one gene, while a high dose impacted the expression of 86 genes. The differentially expressed genes, including immune cell markers, cytokines and chemokines, may activate the immune system in the pancreas in a way that is characteristic of the pathogenesis of type 1 diabetes. It suggests that oral exposure to PET microplastics may be a new risk factor for the development of this disease.
Evolution of vocal production learning in parrots
Authors: Krasheninnikova A , Smeele SQ , Snijders M , Haldar E , Carpenter J , Zamora R , Naguib M , Wolf JBW , Gahr M , von Bayern AMP
Published: November 2024

Vocal production learning (VPL), the capacity to imitate sounds, is a crucial, but not exclusive component of human language. VPL is rare in animals but common in birds, where it evolved independently in songbirds, hummingbirds, and parrots. Parrots (Psittaciformes) learn new vocalizations throughout their lives and exhibit astonishing vocal flexibility and imitation capacity. They can copy allospecific sounds, e.g., human words and learn their associated meanings. Parrots, therefore, present an intriguing model to shed light on how VPL evolved and how it may relate to other language-relevant traits. How widely VPL is distributed across Psittaciformes and to what extent (qualitative) species differences exist, remains unknown. Here, we provide the first comprehensive overview of the phylogenetic distribution of (allospecific) VPL in this clade by conducting surveys of publicly available video footage. Out of the 398 currently recognized extant species, we found videos for 163, of which 136 showed evidence of VPL. Phylogenetic analyses suggest secondary losses and reacquisitions of VPL covarying with socioecological parameters (gregariousness), life-history (longevity), and morphological (body size) traits. This study provides the first insights into interspecific variation in vocal learning across all parrot species and reveals potential socio-ecological drivers of its evolution.

Significance

Little is known about the selective forces that favor the evolution of vocal production learning (VPL), a rare trait in animals and a prerequisite for the evolution of human language. We provide the first insights into interspecific variation in VPL in the evolutionary history of parrots and uncover candidate evolutionary drivers. The current data suggest that the evolution of VPL within parrots has been highly dynamic, with multiple secondary losses and reacquisitions. Our model showed that VPL most likely was the ancestral state. Sociality, longevity and body size explain variation in VPL together with a highly uncertain effect of brain size. The findings may motivate comparative work in other taxa and contribute to research into the evolutionary origins of human language.
Metapredict enables accurate disorder prediction across the Tree of Life
Authors: Lotthammer Jeffrey M. , Hernández-García Jorge , Griffith Daniel , Weijers Dolf , Holehouse Alex S. , Emenecker Ryan J.
Published: November 2024

Intrinsically disordered proteins and protein regions (collectively IDRs) are critical in numerous cellular processes. To understand how IDRs facilitate function, we need tools to accurately and rapidly identify them from sequence. While many methods for disorder prediction exist, we are currently limited by throughput and accuracy for evolutionary scale analyses. To bridge this gap, we developed metapredict V3, an updated version of our disorder predictor that enables evolutionary-scale disorder prediction. Metapredict V3 enables proteome-scale prediction with state-of-the-art accuracy in seconds and was developed with a focus on usability. It is distributed as a web server, Python software package, command-line interface, and Google Colab notebook. Here, we leverage the accuracy and throughput of metapredict V3 to predict disorder for over 20,000 proteomes to evaluate the prevalence of disorder across the kingdoms of life.
Early Life Predictors of Child Development at Kindergarten: A Structural Equation Model using a Longitudinal Cohort
Authors: Turner Sarah E. , Goguen Stephanie , Dufault Brenden , Mayer Teresa , Mandhane Piushkumar J. , Moraes Theo J. , Turvey Stuart E. , Simons Elinor , Subbarao Padmaja , Azad Meghan B.
Published: November 2024

Introduction

Early child development sets the stage for lifelong health. Identifying early life factors related to child development can help guide programs and policies to bolster child health and wellbeing. The objective of this research was to examine how a broad range of predictors, measured prenatally to the third year of life, are related to child development at kindergarten.

Methods

We linked survey data from the Manitoba site of the CHILD Cohort Study with data from the Early Development Instrument (EDI) assessment, completed in kindergarten by the Manitoba public school system (n=442 children). The EDI measures five domains of development (ex. language, physical), scored to indicate the bottom 10% (i.e. ‘vulnerable’) of the population on one or more domains. Using structural equation modelling, we grouped 23 predictors of child development into six latent factors including prenatal exposures, child health and lifestyle, family stress, and socioeconomic status. We examined the associations between each latent factor and EDI vulnerability.

Results

Overall, 20.1% of children were vulnerable on one or more EDI domains. Higher family stress at 1 year and 3 years was related to a 0.20 (p-value ≤ 0.001) and 0.33 (p-value ≤ 0.001) standardized increase of EDI vulnerability. Higher socioeconomic status was related to a - 0.26 (p-value =0.01) standardized increase of EDI vulnerability, and this link was partially mediated through family stress at three years (10.6% mediated). Prenatal exposures (e.g. maternal diet quality), as well as child health and lifestyle factors (e.g. weekday sleep) were not related to EDI vulnerability.

Conclusions

Supporting parental mental health throughout early life, universal screening for early life stress, as well as targeting programs and supports for those living with low SES appear to be priority areas that could help to improve early child development.
ENCODE guided WGS analysis can identify trait associated regulatory regions driven by rare-variants
Authors: Flanagan Jack Thomas , Nam Kisung , Lee Seunggeun
Published: November 2024

Large-scale whole-genome sequencing (WGS) data provides unprecedented opportunity to explore the role of rare variants in non-coding regions on complex traits. However, unlike gene-based exome analysis, non-coding regions lack a well-defined unit for rare-variant testing. Here, we utilized 1,036,913 candidate Cis-Regulatory Elements (cCREs) from ENCODE as analysis units and conducted rare-variant association analysis for 100 traits with SAIGE-GENE+. In a discovery set of 150K White-British samples we identified 1,987 significant associations and replicated 88% of them in a validation set of 250K White-British samples. Associations were enriched in promoter-like signals (PLS) and proximal enhancer- like signals (pELS). Conditional analyses of 230 cCREs across five traits on GWAS variants identified 68 independent cCRE associations. A leukemia case study highlighted key loci, including a PLS for SRSF2 and a pELS for BCL6, demonstrating the effectiveness of cCRE- based analysis.
Making the Exercise Experience More Pleasant: Effects of Open-Label Placebos on Affective Responses to Exercise Induced through Verbal Suggestions
Authors: Yue QIU , Dong-Ting YUN , Jiao LIU , Zhi-Xiong MAO
Published: November 2024

Objective

By manipulating psychological factors—such as fostering positive expectations about exercise outcomes through verbal suggestions—it is possible to induce placebo effects without the use of traditional placebos, such as inert substances (closed-label placebos, CLPs). This can be achieved even when individuals are aware they are receiving a placebo through verbal suggestions (open-label placebo, OLP). This proof-of-principle study investigated whether the effects of OLPs on affective responses to exercise can be induced solely through verbal suggestions.

Methods

Eighty-nine healthy volunteers were randomized into three groups during a 30-minute session of moderate-intensity running. The first experimental group was informed that the running session would enhance their mood (CLP: positive verbal suggestion), the second experimental group was educated on the concept of an OLP and its anticipated effects during the running session (OLP: positive verbal suggestion), and the third control group received unrelated information about the study (no verbal suggestion). The primary study outcomes were self-reported affective valence during exercise and postexercise enjoyment. In addition, anticipated affect and remembered affect were assessed. Resting-state functional connectivity (RSFC) in the prefrontal cortex was objectively measured via functional near-infrared spectroscopy (fNIRS).

Results

Compared with the control group, both experimental groups presented increased affective valence during exercise, postexercise enjoyment, and anticipated affect, along with lower RSFC in the right prefrontal cortex, and the OLP intervention had a greater effect on remembered affect.

Conclusions

The results illustrate a potential role for OLPs in inducing affective response to exercise and suggest that further study of verbal suggestions through an extensive explanation of placebo effects might be promising for practice.
Vocal markers of schizophrenia: assessing the generalizability of machine learning models and their clinical applicability
Authors: Parola Alberto , Trenckner Jessen Emil , Rybner Astrid , Damsgaard Mortensen Marie , Nyhus Larsen Stine , Simonsen Arndis , Lin Jessica Mary , Zhou Yuan , Wang Huiling , Koelkebeck Katja , Sechidis Konstantinos , Bliksted Vibeke , Fusaroli Riccardo
Published: November 2024

Background and Hypothesis

Machine Learning (ML) models have been argued to reliably predict diagnosis and symptoms of schizophrenia based on voice data only. However, it is unclear to what extent such ML markers would generalize to different clinical samples and different languages, a crucial assessment to move towards clinical applicability. In this study, we systematically assessed the generalizability of ML models of vocal markers of schizophrenia across contexts and languages.

Study Design

We trained models relying on a large cross-linguistic dataset (Danish, German, Chinese) of 217 patients with schizophrenia and 221 controls, and used a conservative pipeline to minimize overfitting. We tested the models’ generalizability on: (i) new participants, speaking the same language; (ii) new participants, speaking a different language; (iii) further, we assessed whether training on data with multiple languages would improve generalizability using Mixture of Expert (MoE) and multilingual models.

Results

Model performance was comparable to state-of-the-art findings (F1-score ∼ 0.75) within the same language; however, models did not generalize well - showing a substantial decrease - when tested on new languages. The performance of MoE and multilingual models was also generally low (F1-score ∼ 0.50).

Conclusions

Overall, the cross-linguistic generalizability of vocal markers of schizophrenia is limited. We argue that more emphasis should be placed on collecting large open cross- linguistic datasets to systematically test the generalizability of voice-based ML models, and on identifying more precise mechanisms of how the clinical features of schizophrenia are expressed in language and voice, and how different languages vary in that expression.
Assessing infant risk of cerebral palsy with video-based motion tracking
Authors: Segado Melanie , Prosser Laura , Duncan Andrea F. , Johnson Michelle J. , Kording Konrad P.
Published: November 2024

Cerebral Palsy (CP) is a common (about 1 in 500 children) health condition caused by abnormal brain development that affects the ability to control movement. Early risk assessment happens through the General Movements Assessment (GMA), a test administered by trained clinicians at 3-4 months of age that has high predictive value for CP. With recent improvements in video-based motion tracking, automated risk assessment for CP based on the GMA is being explored. However, studies generally have used small datasets or were limited in terms of methodological rigor. Here we acquired a large dataset (1060 infants) of videos from a clinical population with elevated CP risk. In a preregistered pipeline using a lock-box set that was not used before algorithm submission we find that our machine learning predictions are highly predictive of the clinician-assessed GMA (AUC=0.79). Given its low cost, our video-based approach may be useful for clinical screening applications, particularly in low-resource settings.
“A baby is like an empty USB. Whatever you do, they store it”: a qualitative study of caregiving practices and beliefs in Soweto, South Africa
Authors: Palmer Tom , Nkosi Nokuthula , Motlhatlhedi Molebogeng , Prost Audrey , Skordis Jolene , Gram Lu , Norris Shane A , Batura Neha , Draper Catherine E
Published: November 2024

The importance of nurturing care for children’s development has been emphasised in the global literature. Although societal risk factors which may hinder nurturing care in South Africa have been extensively documented, the goals, beliefs and practices of caregivers in infancy have received less attention in the literature. This qualitative study was conducted with mothers of children aged 6 to 10 months in Soweto. Data were collected during focus group discussions held in May 2023 with 26 mothers, then analysed using thematic analysis. We found that mothers view themselves as playing an active role in their children’s learning and development, and are broadly aware of the importance of nurturing care. Our findings also emphasise that nurturing care is bidirectional, and based on the relationship between caregivers and children, both of whom should be viewed as individuals. This study contributes to relatively limited literature on infancy in South Africa and can help to inform context-appropriate interventions to improve early childhood development in comparable settings.