bluuebunny/crossref_metadata_2025_split huggingface dataset:
Domain-specific Schema Reuse Supports Flexible Learning to Learn in Primate Brain
Authors: Tian Kaixi , Zhao Zhiping , Chen Yang , Ge Ningling , Cao Shenghao , Han Xinyong , Gu Jianwen , Yu Shan 
Published: October 2024

AbstractPrior knowledge accelerates subsequent learning of similarly structured problems - a phenomenon termed “learning to learn” - by forming and reusing generalizable neural representations, i.e., the schemas. However, the stability-plasticity dilemma, i.e., how to exploit stable schemas to facilitate learning while remaining flexible towards possible changes, is not well understood. We hypothesize that restricting schemas to specific functional, e.g., decision-making, subspace and making it orthogonal to other subspaces allows the brain to balance stability and plasticity. To test it, we trained three macaques on visuomotor mapping tasks and recorded neural activity in the dorsolateral premotor cortex. By delineating decision and stimulus subspaces, we identified a schema-like manifold within only the decision subspace. The reuse of decision schemas significantly facilitated subsequent learning. In addition, the decision subspace exhibited a trend to be orthogonal to the stimulus subspace, minimizing interference between these two domains. Our results revealed that restricting schemas to specific functional domains can preserve useful knowledge while maintaining orthogonality with other subspaces, allowing for flexible adaptation to new environments, thereby resolving the stability-plasticity dilemma. This finding provides new insights into the mechanisms underlying brain’s capability to learn both fast and flexibly, which can also inspire more efficient learning algorithms for artificial intelligence systems towards working in open, dynamic environments.
Foxi1 regulates multiple steps of mucociliary development and ionocyte specification through transcriptional and epigenetic mechanisms
Authors: Bowden Sarah , Brislinger-Engelhardt Magdalena Maria , Hansen Mona , Temporal-Plo Africa , Weber Damian , Hägele Sandra , Lorenz Fabian , Litwin Tim , Kreutz Clemens , Walentek Peter 
Published: October 2024

AbstractFoxi1 is a master regulator of ionocytes (ISCs / INCs) across species and organs. Two subtypes of ISCs exist, and both α- and β-ISCs regulate pH- and ion-homeostasis in epithelia. Gain and loss of FOXI1 function are associated with human diseases, including Pendred syndrome, male infertility, renal acidosis and cancers. Foxi1 functions were predominantly studied in the context of ISC specification, however, reports indicate additional functions in early and ectodermal development. Here, we re-investigated the functions of Foxi1 inXenopus laevisembryonic mucociliary epidermis development and found a novel function for Foxi1 in the generation of Notch-ligand expressing mucociliary multipotent progenitors (MPPs). We demonstrate that Foxi1 has multiple concentration-dependent functions: At low levels, Foxi1 confers ectodermal competence through transcriptional and epigenetic mechanisms, while at high levels, Foxi1 induces a multi-step process of ISC specification and differentiation. We further describe howfoxi1expression is affected through auto- and Notch-regulation, how Ubp1 and Dmrt2 regulate ISC subtype differentiation, and how this developmental program affects Notch signaling as well as mucociliary patterning. Together, we reveal novel functions for Foxi1 inXenopusmucociliary epidermis formation, relevant to our understanding of vertebrate development and human disease.
Fibroblast activation protein defines aggressive EMT-associated cancer cell state and prognosis in localized ccRCC
Authors: Pellinen Teijo , Luomala Lassi , Mattila Kalle E , Hemmes Annabrita , Välimäki Katja , Brück Oscar , Paavolainen Lassi , Kankkunen Elisa , Nisén Harry , Järvinen Petrus , Castillon Leticia , Vanharanta Sakari , Vainio Paula , Kallioniemi Olli , Jaakkola Panu M. , Mirtti Tuomas 
Published: October 2024

ABSTRACTDespite being highly vascularized and immune-rich, the prognostic impact of immune infiltration and tumor microenvironment heterogeneity in localized clear cell renal cell carcinoma (ccRCC) remains unclear. Using 33-marker immunofluorescence imaging, we analyzed spatial distributions in 1,728 tissue cores from 435 localized ccRCC cases. Higher CD45⁺ infiltration correlated with worse survival, establishing CD45⁺ density as a prognostic marker. In CD45hightumors, ccRCC cells losing epithelial markers showed increased expression of mesenchymal markers such as fibroblast activation protein (FAP), secreted protein acidic and rich in cysteine (SPARC), vimentin (VIM), and PD-L1, indicating epithelial-to-mesenchymal transition (EMT). The FAP⁺EMT⁺ state further stratified CD45highpatients toward poorer outcomes and was associated with immunosuppressive elements, including M2 macrophages, exhausted and regulatory T cells, and FAP⁺ cancer-associated fibroblasts. Our study identifies high CD45⁺ infiltration and a FAP⁺EMT⁺ cancer cell state as indicators of poor survival in localized ccRCC, highlighting their potential to refine patient stratification and guide immuno-oncology treatment strategies.
DDO-adjuvanted influenza A virus nucleoprotein mRNA vaccine induces robust humoral and cellular type 1 immune responses and protects mice from challenge
Authors: Gnazzo Victoria , Saleh Hanaa , Castro Ítalo , Boon Adrianus C.M. , Pinto Amelia K , Brien James D. , López Carolina B. 
Published: October 2024

ABSTRACTA challenge in viral vaccine development is to produce vaccines that generate both neutralizing antibodies to prevent infection and cytotoxic CD8+T-cells that target conserved viral proteins and can eliminate infected cells to control virus spread. mRNA vaccines offer an opportunity to design vaccines based on conserved CD8-targeting epitopes, but achieving robust antigen-specific CD8+T-cells remains a challenge. Here we tested the viral-derived oligonucleotide DDO268 as an adjuvant in the context of a model influenza A virus (IAV) nucleoprotein (NP) mRNA vaccine in C57BL/6 mice. DDO268 safely induced local type I interferon (IFN) production, stimulated dendritic cells type 1 (DC1) activation and migration to the draining lymph nodes, and improved the generation of IgG2c antibodies and antigen-specific effector Th1 CD4+and CD8+T-cells (IFNγ+TNFα+IL2+) when co-packaged with NP mRNA. The DDO268 adjuvanted vaccine provided enhanced protection against lethal IAV challenge and reduced the antigen dose required to achieve this protection. These results highlight the potential of DDO268 as an effective mRNA vaccine adjuvant and show that an IAV NP mRNA/DDO268 vaccine is a promising approach for generating protective immunity against conserved IAV epitopes.IMPORTANCEVaccines that generate neutralizing antibodies and cytotoxic CD8+T-cells targeting conserved epitopes are ideal for effective protection against viruses. mRNA vaccines combined with the right adjuvant offer a promising solution to this challenge. We show that the virus-derived oligonucleotide DDO268 enhances antibody and T cell responses to an influenza A virus (IAV) nucleoprotein (NP) mRNA vaccine in mice. DDO268 safely induces local type I interferon production and stimulates dendritic cell activation providing enhanced protection against IAV challenge. In addition, the adjuvant activity of DDO268 allows for the use of lower antigen doses during vaccination.
VAPOR: Variational autoencoder with transport operators decouples co-occurring biological processes in development
Authors: Sheng Jie , Wang Daifeng 
Published: October 2024

AbstractBackgroundEmerging single-cell and spatial transcriptomic data enable the investigation of gene expression dynamics of various biological processes, especially for development. To this end, existing computational methods typically infer trajectories that sequentially order cells for revealing gene expression changes in development, e.g., to assign a pseudotime to each cell indicating the ordering. However, these trajectories can aggregate different biological processes that cells undergo simultaneously–such as maturation for specialized function and differentiation into specific cell types–which do not occur on the same timescale. Therefore, a single pseudotime axis may not distinguish gene expression dynamics from co-occurring processes.MethodsWe introduce a method, VAPOR (variational autoencoder with transport operators), to decouple dynamic patterns from developmental gene expression data. Particularly, VAPOR learns a latent space for gene expression dynamics and decomposes the space into multiple subspaces. The dynamics on each subspace are governed by an ordinary differential equation model, attempting to recapitulate specific biological processes. Furthermore, we can infer the process-specific pseudotimes, revealing multifaceted timescales of distinct processes in which cells may simultaneously be involved during development.ResultsInitially tested on simulated datasets, VAPOR effectively recovered the topology and decoupled distinct dynamic patterns in the data. We then applied VAPOR to a developmental human brain scRNA-seq dataset across postconceptional weeks and identified gene expression dynamics for several key processes, such as differentiation and maturation. Moreover, our benchmarking analyses also demonstrated the outperformance of VAPOR over other methods. Additionally, we applied VAPOR to spatial transcriptomics data in the human dorsolateral prefrontal cortex. VAPOR captured the ‘inside-out’ pattern across cortical layers, potentially revealing how layers were formed, characterized by their gene expression dynamics.ConclusionVAPOR is open source for general use (https://github.com/daifengwanglab/VAPOR) to parameterize and infer developmental gene expression dynamics. It can be further extended for other single-cell and spatial omics such as chromatin accessibility to reveal developmental epigenomic dynamics.
Ribosomal Biogenesis Hyperactivation and ErbB signalling Mediated Network Rewiring Causes Adaptive Resistance to FGFR2 Inhibition
Authors: Zhang Tao , Shin Sung-Young , McCrimmon Callan , Theocharous Mandy , Schittenhelm Ralf B , Jarde Thierry , Daly Roger J , Nguyen Lan K 
Published: October 2024

AbstractFibroblast Growth Factor Receptor 2 inhibition presents a promising therapeutic approach for restraining the growth and survival of cancer cells, particularly in breast tumours. However, the emergence of resistance to FGFR2 inhibitors like PD173074 highlights the importance of understanding the molecular mechanisms driving resistance and identifying effective therapeutic strategies. In this study, we employed temporal quantitative proteomics and phosphoproteomics, complemented by computational clustering, PTM-SEA analysis, and kinase activity prediction, to monitor the response of MFM223 triple negative breast cancer cells to FGFR2 inhibition. Strikingly, we observed a marked enrichment of ribosome biogenesis function modules immediately following treatment, a phenomenon not observed with other inhibitors. Additionally, we discovered that CX-5461, an RNA polymerase I inhibitor, synergistically enhanced the growth inhibition induced by PD173074, mechanistically attributed to its significant suppression of rDNA transcription stimulated by PD173074. Moreover, our phosphoproteomics dynamic profiling identified the clustering of kinases within MAPK and ErbB signalling pathways, indicative of their reactivation in response to FGFR2 inhibition. Experimentally validating this finding, we observed a notable rebound in phosphorylation levels of key kinases such as ERK1/2 and ErbB3, and demonstrated a substantial synergistic effect of PD173074 in combination with Trametinib, a MEK inhibitor, in suppressing cancer cell growth. Collectively, our findings provide critical insights into the network rewiring triggered by FGFR2 inhibition and offer a foundation for the rational design of combinatorial therapeutic strategies to overcome resistance mechanisms associated with FGFR2 inhibitors.
Preliminary Findings from an Augmented Reality (AR) App Delivering Recovery-Oriented Cognitive Therapy for Negative Symptoms in Schizophrenia
Authors: Tang Sunny X. , Foroughi Moein , Brinen Aaron P. , Birnbaum Michael L. , Berretta Sarah , Behbehani Leily M. , Kane John M. , Yoon Edward , Cronin William F. 
Published: October 2024

AbstractBackgroundNegative symptoms are a primary driver of poor outcomes in schizophrenia spectrum disorders (SSD), but there are no FDA-approved medications or FDA-cleared therapeutics targeting negative symptoms in schizophrenia. NST-SPARK is a novel digital therapeutic targeting negative symptoms in SSD. It is a smartphone application delivering recovery-oriented cognitive therapy (CT-R), via gamified augmented reality (AR) experiences, to provide experiential learning aimed at dismantling maladaptive beliefs. In this study, we assessed a prototype (NST-SPARK v.1.5) in 20 participants with SSD and clinically significant negative symptoms. NST-SPARK v.1.5 delivers a single therapeutic module over a 1-week period. The primary objective was to determine the acceptability and feasibility of this approach. Secondary objectives were to generate descriptive findings for changes in defeatist beliefs, self-esteem, and attitudes toward goal-oriented activities.MethodsRecruitment and all study procedures were completed online. Twenty participants with schizophrenia or schizoaffective disorder were enrolled, with a range of demographic and socioeconomic status and treatment settings. Participants completed self-reports on the acceptability and feasibility of NST-SPARK v.1.5 and provided open-ended feedback through a semi-structured interview. Self-report scales on defeatist beliefs, self-esteem, and attitudes toward goal-oriented activities were completed before and after participants were introduced to NST-SPARK, and then again at a 1-week follow-up.ResultsIn general, participants found NST-SPARK v.1.5 to be feasible and acceptable, responding with an average response of “Agree”, indicating that the intervention was found to meet with the participants’ approval and seemed implementable. Almost all participants (19 of 20) used the app on their own prior to the 1-week follow up despite not being incentivized to do so. In addition, participants responded to open-ended feedback questions in a generally positive way. We also observed shifts in defeatist beliefs (Cohen’s d = 0.12), self-esteem (Cohen’s d = -0.21), and attitudes toward goal attainment consistent (intention: Cohen’s d = 0.13; confidence: Cohen’s d = 0.35) with intended improvements in these targeted areas. Participants were able to make substantive progress toward identified goals in 90% of cases.ConclusionsThis preliminary, single-arm, unblinded study of a single-module prototype for NST-SPARK found that the approach is generally acceptable and feasible for people with SSD and negative symptoms. Engagement of the intended target of defeatist beliefs was supported by our findings but require confirmation in future randomized controlled trials. Overall, NST-SPARK is based on a promising approach and further development is warranted.
TaxonGPT: Taxonomic Classification Using Generative Artificial Intelligence
Authors: Huang Haoyuan , Li Teng , Wang Zhixuan , Seldon David , Rodrigo Allen 
Published: October 2024

AbstractTo address the challenges of consistency and quality in taxonomic classifications, we have developed a Python program called TaxonGPT, that utilizes the natural language processing capabilities of generative artificial intelligence (gAI, specifically, ChatGPT-4o) to generate taxonomic descriptions and taxonomic keys. To counter the propensity for large language model gAIs to “hallucinate”, we use knowledge graph semantic representation and an error-checking module to ensure that accurate taxonomic descriptions and keys are obtained. In this paper, we describe how TaxonGPT embeds ChatGPT-4o’s responses as outputs. We also report on benchmark tests for accuracy, efficiency and reproducibility. These tests demonstrate that TaxonGPT excels in generating taxonomic keys and descriptions.
Mesial-to-lateral patterns of epileptiform activity identify the seizure onset zone in mesial temporal lobe epilepsy
Authors: Aguila Carlos A. , Lucas Alfredo , Lavelle Sarah , Pattnaik Akash R. , Kim Juri , Ojemann William K.S. , Ma Devin , Josyula Mariam , Petillo Nina , LaRocque Joshua J. , Sinha Saurabh R. , Ellis Colin A. , Parashos Alexandra , Gleichgerrcht Ezequiel , Davis Kathryn A. , Litt Brian , Conrad Erin C. 
Published: October 2024

AbstractMesial temporal lobe epilepsy (mTLE) is a common localization of drug-resistant epilepsy in adults. Patients often undergo intracranial EEG (iEEG) monitoring to confirm localization and determine candidacy for focal ablation or resection. Clinicians primarily base surgical decision-making on seizure onset patterns, with imaging abnormalities and information from interictal epileptiform discharge (spikes) used as ancillary data. How the morphology and timing of spikes within multi-electrode sequences may inform surgical planning is unknown, in part due to the lack of measurement methods for large datasets. We hypothesized that patients with mTLE have a distinct mesial-to-lateral spike pattern that differentiates them from other epilepsy localizations. In a multicenter study at the University of Pennsylvania and the Medical University of South Carolina, we analyzed the timing and morphology of spikes and seizure high frequency energy ratio (HFER) in 75 patients with drug-resistant epilepsy. We compared these features across patients with mTLE, temporal neocortical epilepsy, and other localizations. A logistic regression model combining all features predicted a clinical localization of mTLE in unseen patients with an AUC of 0.82 (compared to an AUC of 0.70 for seizure-only features, DeLong’s testp= 0.08). Spike rate was the most important feature in the combined model. Modeled probability of mTLE was similar between patients who had a good versus a poor 12-month outcome after undergoing a mesial temporal resection or ablation (p= 0.34). These findings support quantitative spike analysis to supplement analysis of seizures for use in surgical planning.
Evaluating the environmental impact of clinical research: a life-cycle analysis of a French academic randomised clinical trial
Authors: Fougerou-Leurent Claire , Forteau Louise , Perrot-Loyer Maëlle , Renault Alain , Mouchel Catherine , Rousseau Chloe , Marion Enora , Cochennec Sabrina , Ganivet Anne , Gervais Marie-Laure , Fin Loïc , Laviolle Bruno 
Published: October 2024

ABSTRACTObjectivesTo assess the environmental impact of an academic clinical trial, by adapting the life-cycle analysis methodology to clinical research.DesignA retrospective, simplified complete life-cycle analysis (LCA), according to the EF 3.0 methodology. LCA is a standardised (ISO14040/44) method for assessing the environmental impacts of a product over its entire life cycle on several environmental issues. It is the balance of inputs and releases associated with the process, from conception to end-of-life.SettingA prospective, double-blind, randomised controlled trial in neurosurgery. The trial included 202 patients in 18 university hospitals across France.ParticipantsNot applicableInterventionNot applicableMain outcome measuresFourteen impact indicators that could be combined into a single score, for the identification of hotspots of interest.ResultsClimate change (or greenhouse gas emissions), was the most important indicator, accounting for almost 30% of the single score. Greenhouse gas emissions were estimated at 31.6 tons of carbon dioxide equivalent. This was followed by the depletion of abiotic resources - fossil fuels (24%), resource use - minerals and metals (12%), and particulate matter emissions (8%). The main hotspots identified were patient’ transport and clinical research assistant travel for source data verification.ConclusionsBy using complete LCA approach, our study confirms that conducting a clinical trial has a significant environmental impact, particularly on climate change. The main identified hotspots were related to the transport of patients and clinical research assistantsARTICLE SUMMARYStrengths and limitations of this study-This study describes the first complete life-cycle analysis of a clinical trial-Fourteen environmental factors were assessed, appraising all trial activities, from conception to close-out-This study complements those previously published in the process of establishing eco-design as a new paradigm for clinical research-Only one clinical trial was assessed, limiting the transposability of the conclusions-Due to the lack of published impact data for some activities, assumptions had to be made to estimate their environmental impact
Proteome-wide and mendelian randomisation analyses of chronic widespread pain: diagnosis, prognosis, and drug target discovery
Authors: Chen Li , Kelleher Eoin , Meng Ruogu , Liu Duanke , Guo Yuchen , Wang Yunhe , Gao Yaoqing , Huang Zhe , Liang Zhu , Yuan Shuai , Zeng Chao , Lei Guanghua , Ma Jun , Dong Yanhui , Irani Anushka , Xie Junqing , Prieto-Alhambra Daniel 
Published: October 2024

AbstractChronic widespread pain (CWP) remains challenging due to its heterogenous causes and complex mechanisms. We analysed 2,923 plasma proteins from 29,254 UK Biobank participants. We first identified 811 proteins correlated with the presence of CWP cross- sectionally. We then created a sparse (top 10 proteins) and intricate (all significant proteins) proteomic-based score (ProtS) for CWP, both outperforming and improving the traditional clinical score (AUC: 0.82 and 0.88 vs 0.81 individually, and 0.87 and 0.92 in combination). Prospectively, the ProtS was associated with increased risks of a spectrum of pain traits, including dimensions from pain onset, progression and intensity, up to 13-years of follow-up; More importantly, we identified distinct proteomic signatures for nociplastic pain compared to nociceptive and neuropathic pain. For the individual proteins, carbonic anhydrase 14 (CA14) and leptin appeared as promising casual CWP biomarkers as triangulated by Mendelian randomisation and colocalization analyses. Lastly, our drug-repurposing analysis identified ten potential candidates for CWP therapies, calling for further research including randomised controlled trials. Although no CA14 agonists are currently available, CA14 remains a promising target, warranting further efforts to explore its role in pain modulation.