bluuebunny/crossref_metadata_2025 huggingface dataset:
Clinical properties of the Short Mood and Feelings Questionnaire: Development of a free calculator based on a Brazilian High-Risk Cohort Study
Authors: Jobim Gabriele dos Santos , do Amaral João Villanova , Gonçalves Pacheco João Pedro , Gadelha Ary , Miguel Euripedes Constantino , Affonseca Bressan Rodrigo , Pan Pedro Mario , Rohde Luis Augusto , Salum Giovanni Abrahão , Scopel Hoffmann Mauricio
Published: February 2025

Background

The Short Mood and Feelings Questionnaire (SMFQ) is a validated tool for assessing depressive symptoms in youth, though no specific cut-point exists for the Brazilian population. Item response theory (IRT) and interval likelihood ratios (ILRs) offer refined methods to monitor symptoms but involve complex calculations that hinder clinical implementation.

Methods

Cross-sectional data were drawn from an urban school-based sample (Brazilian High-Risk Cohort Study in 2018-2019, n=1,905, aged 14-23, 46.6% females). Diagnoses were based on Development and Well-Being Assessment (DAWBA) clinical ratings. SMFQ factor scores were estimated using IRT and transformed into T-scores. ROC curves evaluated diagnostic properties for internalizing- and externalizing-spectrum disorders. A calculator was developed to estimate post-test probabilities from T-scores using ILRs. Sensitivity analysis excluded MDD as a comorbid diagnosis.

Results

ROC curve analyses suggested a sum score cut-off of >6 and a T-score of >55 for detecting MDD. The SMFQ showed good accuracy for internalizing conditions (AUC > 0.8) but low for attention and externalizing disorders (AUC < 0.7). ILRs for internalizing conditions ranged from 0.12 (95% CI: 0.07–0.19) to 29.98 (95% CI: 11.99–75), with post-test probabilities exceeding pre-test probabilities for scores above the cut-off. Sensitivity analysis confirmed findings when excluding MDD. Including ILRs significantly improved predictive models over dichotomous cut-offs.

Conclusion

The application of ILRs based on IRT T-scores improved SMFQ’s predictive ability for internalizing-spectrum conditions, regardless of comorbidity. A calculator can integrate these methods into clinical practice, supporting real-time data-driven decisions.
Role of the ETV5/p38 signaling axis in aggressive thyroid cancer cells
Authors: Houl Jerry H , Bagheri-Yarmand Rozita , Kunnimalaiyaan Muthusamy , Miranda Mendez Paola , Kidd Joseph L , Dadbin Ali , Jurado-Ruiz Andrea , Parekh Parag A , Henderson Ying C , Chari Nikhil S , Thennavan Aatish , Powell Reid T , Stephan Clifford C , Zhao Xiao , Maniakas Anastasios , Nurieva Roza , Busaidy Naifa L , Cabanillas Maria E , Dadu Ramona , Zafereo Mark , Wang Jennifer R , Lai Stephen Y , Hofmann Marie-Claude
Published: February 2025

Poorly differentiated thyroid cancer (PDTC) and anaplastic thyroid cancer (ATC) patients face a much poorer prognosis compared to those with differentiated thyroid cancers. Around 25% of PDTCs and 35% of ATCs carry theBRAFV600Emutation, which constitutively activates the MAPK pathway, a key driver of cell growth. While combining BRAF and MEK inhibitors can shrink tumors, resistance often develops. The exact cause of this resistance remains unclear.

We previously found that in PDTC and ATC cells theBRAFV600Emutation is strongly linked to the expression of ETV5, a transcription factor that is downstream of the MAPK pathway. In the current study, we observed a significant association between ETV5 expression and the activation of p38, a central component of the MAPK14 pathway. Upon reduction of ETV5 levels, p38 expression and activation also decreased, along with its upstream regulators MKK3/MKK6. This suggests that the MAPK and p38/MAPK14 pathways are interconnected and that p38 has oncogenic properties in these cancers.

Using high-throughput screening, we established that combining p38 inhibitors with the BRAF inhibitor dabrafenib showed strong synergyin vitro, including in cells resistant to dabrafenib and trametinib that had acquired a secondaryTP53mutation. We then tested this combination in a genetically engineered mouse model (GEMM) of ATC.

Overall, our findings suggest an oncogenic link between the MAPK and p38/MAPK14 pathways and that combining p38 pathway inhibitors with dabrafenib targeted therapy could improve treatment outcomes for aggressive thyroid cancers. However, more specific and effective p38 inhibitors are needed to fully harness this potential.
Corticospinal, reticulospinal, and motoneuronal contributions to fatigability during a sustained contraction of the elbow flexors
Authors: Hayman Oliver , Brownson-Smith Rosiered , Atkinson Elliott I , Spillane Padraig , Baker Stuart , Goodall Stuart , Howatson Glyn , Thomas Kevin , Ansdell Paul
Published: February 2025

Synaptic input to the motoneuron pool is altered during fatiguing muscle contractions. In humans, the corticospinal tract is often studied, with equivocal findings regarding its role in the reduction of force. To date, the involvement of the reticulospinal tract during states of fatigue has not been explored.

Fourteen participants (28±6 years, nine males) visited the laboratory twice, first for a familiarisation, then an experimental trial. Participants completed a 5-min sustained elbow flexor contraction at an intensity eliciting 40% of the EMG recorded during a maximal isometric voluntary contraction (MVC). Before, during, and after the contraction, transcranial magnetic stimulation and electrical cervicomedullary stimulation were used to elicit motor evoked potentials (MEPs) and cervicomedullary evoked potentials during the silent period (SP-CMEPs) respectively, with CMEPs also being evoked in combination with a startling acoustic sound (CMEPcon). Electrical stimulation of the brachial plexus was used to evoke maximal compound action potentials of the elbow flexors (Mmax).

The 5-min contraction induced a 53% loss of force (p<0.001), with no change in background EMG (∼4% Mmax,p=0.293). Neither MEP amplitude (p=0.246) nor CMEPcon ratio (p=0.489) were altered during the contraction. Whereas CMEP and SP-CMEP amplitudes were reduced by ∼20 and 50%, respectively (p<0.001) and remained depressed post-task.

The results suggest that neither corticospinal nor reticulospinal tract excitability was altered during a 5-min constant-EMG task at 40% maximal EMG. Instead, the aetiology of the neural contribution to fatigability appeared to be primarily related to the loss of motoneuron excitability.
Synergistic RAS-MAPK and AKT Activation in MYC-Driven Tumors via Adjacent PVT1 Rearrangements
Authors: Tiwari Ashutosh , Paithane Utkarsha , Friedlein Jordan , Tashiro Kojiro , Saulnier Olivier , Barbosa Karina , Trinh Quang , Hall Bryan , Saha Shrawantee , Soni Aditi , Nakashima Takuma , Bobkov Andrey , Fujimoto Lynn Miya , Murad Rabi , Maurya Svetlana , Saraswat Mayank , Sarmashghi Shahab , Lange Joshua T. , Wu Sihan , Masihi Meher Beigi , Ghosh Srija , Hemmati Gazal , Chapman Owen , Hendrikse Liam , James Brian , Luebeck Jens , Eisemann Tanja , Tzaridis Theophilos , Rohila Deepak , Leary Robyn , Varshney Jyotika , Konety Badrinath , Dehm Scott M. , Kawakami Yasuhiko , Beroukhim Rameen , Largaespada David A , Stein Lincoln , Chavez Lukas , Suzuki Hiromichi , Weiss William A , Zhao Jianhua , Deshpande Aniruddha , Wechsler-Reya Robert J. , Taylor Michael D. , Bagchi Anindya
Published: February 2025

MYC-driven (MYC+) cancers are aggressive and often fatal. MYC dysregulation is a key event in these cancers, but overexpression of MYC alone is not always enough to cause cancer.Plasmocytoma Variant Translocation 1(PVT1), a long non-coding RNA (lncRNA) adjacent to MYC on chromosome 8 is a rearrangement hotspot in many MYC+ cancers. In addition to being co-amplified with MYC, the genomic rearrangement at PVT1 involves translocation, which has had obscure functional consequences. We report that translocation at the PVT1 locus cause asymmetric enrichment of 5’-PVT1 and loss of 3’-PVT1. Despite being classified as a non-coding RNA, the retained 5’ region of PVT1 generates a circular RNA (CircPVT1) that codes for the novel peptide we call Firefox (FFX). FFX augments AKT signaling and synergistically activates MYC and mTORC1 in these cells. Further, the 3’ end of PVT1, which is lost during the translocation, codes for a tumor-suppressing micropeptide we named as Honeybadger (HNB). We demonstrate that HNB interacts with KRAS and disrupts the activation of KRAS effectors. Loss of HNB leads to activation of RAS/MAPK signaling pathway, and enhances MYC stability by promoting phosphorylation of MYC at Ser62. These findings identify PVT1 as a critical node that synchronizes MYC, AKT, and RAS-MAPK activities in cancer. Our study thus identifies a key mechanism by which rearrangements at the PVT1 locus activate additional oncogenic pathways that synergize with MYC to exacerbate the aggressiveness of MYC+ cancers. This newfound understanding explains the poor prognosis associated with MYC+ cancers and offers potential therapeutic targets that could be leveraged in treatment strategies for these cancers.
Which plant traits increase soil carbon sequestration? Empirical evidence from a long-term poplar genetic diversity trial
Authors: Field John L , Sloan Brandon P , Craig Matthew E , Calloway Parker , Ottinger Sarah L , Mead Thomas , Abramoff Rose Z , Venegas Mirko Pavicic , Chhetri Hari B , Haiby Kathy , Kalluri Udaya C , Muchero Wellington , Schadt Christopher W , Mayes Melanie A
Published: February 2025

Breeding or engineering crops to increase soil organic carbon (SOC) storage is a potential route to land-based carbon dioxide removal on working agricultural lands. However, due to limited observational datasets plus shifting paradigms of SOC stabilization, there is a lack of understanding of which plant traits to target for SOC enhancement or the ultimate sequestration potential of such measures. Existing long-term common gardens of genetically diverse plant populations may provide an opportunity to evaluate biological controls on SOC outcomes, separate from environmental or management variability. Here we report on soil carbon and root chemical data collected for 24 genotypes within a 13-year-old common garden in northwestern Oregon planted with over a thousand natural variants of Populus trichocarpa. Fractionating surface soil (0-15 cm) revealed substantial variation in stocks of mineral-associated organic matter (MAOM; 18-67 tonnes C/ha) and particulate organic matter (POM; 2-22 tonnes C/ha). Tree genotype explained 24 and 26% of the MAOM and POM stock variability, respectively, after controlling for background variability. We found minimal association between SOC concentration and either aboveground tree productivity or conventional metrics of root biomass recalcitrance (C/N ratios and lignin content). However, root elemental content appeared influential for MAOM-C, which showed a strong positive association with root aluminum (Al), and strong negative association with root boron (B) and magnesium (Mg). Furthermore, root concentrations of these elements were highly heritable (57-78%) and not simply a reflection of background variation in bulk soil elemental concentrations. We estimate that surface SOC stocks under these 24 genotypes have diverged at rates of up to 1.2-4.3 tonnes C/ha/yr. These results suggest that genetic diversity trials have value for elucidating biological controls on SOC dynamics, and that traits associated with root elemental content may be an important target for enhancing SOC.
Extraction of biological terms using large language models enhances the usability of metadata in the BioSample database
Authors: Ikeda Shuya , Zou Zhaonan , Bono Hidemasa , Moriya Yuki , Kawashima Shuichi , Katayama Toshiaki , Oki Shinya , Ohta Tazro
Published: February 2025

BioSample is a comprehensive repository of experimental sample metadata, playing a crucial role in providing a comprehensive archive and enabling experiment searches regardless of type. However, the difficulty in comprehensively defining the rules for describing metadata and limited user awareness of best practices for metadata have resulted in substantial variability depending on the submitter. This inconsistency poses significant challenges to the findability and reusability of the data. Given the vast scale of BioSample, which hosts over 40 million records, manual curation is impractical. Rule-based automatic ontology mapping methods have been proposed to address this issue, but their effectiveness is limited by the heterogeneity of BioSample metadata. Recently, large language models (LLMs) have gained attention in natural language processing and have been expected as promising tools for automating metadata curation. In this study, we evaluated the performance of LLMs in extracting cell line names from BioSample descriptions using a gold-standard dataset derived from ChIP-Atlas, a secondary database of epigenomics experiment data, which manually curates samples. Our results demonstrated that LLM-assisted methods outperformed traditional approaches, achieving higher accuracy and coverage. We further extended this approach to extraction of information about experimentally manipulated genes from metadata where manual curation had not yet been applied in ChIP-Atlas. This also yielded successful results for the usage of the database, which facilitates more precise filtering of data and prevents misinterpretation caused by inclusion of unintended data. These findings underscore the potential of LLMs to improve the findability and reusability of experimental data in general, significantly reducing user workload and enabling more effective scientific data management.
A pan-gene catalogue of Asian cultivated rice
Authors: Contreras-Moreira Bruno , Sharma Eshan , Saraf Shradha , Naamati Guy , Gupta Parul , Elser Justin , Chebotarov Dmytro , Chougule Kapeel , Lu Zhenyuan , Wei Sharon , Olson Andrew , Tsang Ian , Lodha Disha , Zhou Yong , Yu Zhichao , Zhao Wen , Zhang Jianwei , Amberkar Sandeep , Sue-Ob Kawinnat , Martin Maria , McNally Kenneth L. , Ware Doreen , Sun Zhi , Deutsch Eric W , Copetti Dario , Wing Rod A. , Jaiswal Pankaj , Dyer Sarah , Jones Andrew R
Published: February 2025

The rice genome underpins fundamental research and breeding, but the Nipponbare (japonica) reference does not fully encompass the genetic diversity of Asian rice. To address this gap, the Rice Population Reference Panel (RPRP) was developed, comprising high-quality assemblies of 16 rice cultivars to representjaponica,indica,aus, andaromaticvarietal groups.

The RPRP has been consistently annotated, supported by extensive experimental data and here we report the computational assignment, characterization and dissemination of stably identified pan-genes. We identified 25,178 core pan-genes shared across all cultivars, alongside cultivar-specific and family-enriched genes. Core genes exhibit higher gene expression and proteomic evidence, higher confidence protein domains and AlphaFold structures, while cultivar-specific genes were enriched for domains under selective breeding pressure, such as for disease resistance. This resource, integrated into public databases, enables researchers to explore genetic and functional diversity via a population-aware “reference guide” across rice genomes, advancing both basic and applied research.
Accounting for Edge Uncertainty in Stochastic Actor-Oriented Models for Dynamic Network Analysis
Authors: Shappell Heather , Kramer Mark , Chu Catherine , Kolaczyk Eric D
Published: February 2025

Stochastic Actor-Oriented Models (SAOMs) were designed in the social network setting to capture network dynamics representing a variety of influences on network change. The standard framework assumes the observed networks are free of false positive and false negative edges, which may be an unrealistic assumption. We propose a hidden Markov model (HMM) extension to these models, consisting of two components: 1) a latent model, which assumes that the unobserved, true networks evolve according to a Markov process as they do in the SAOM framework; and 2) a measurement model, which describes the conditional distribution of the observed networks given the true networks. An expectation-maximization algorithm is developed for parameter estimation. We address the computational challenge posed by a massive discrete state space, of a size exponentially increasing in the number of vertices, through the use of the missing information principle and particle filtering. We present results from a simulation study, demonstrating our approach offers improvement in accuracy of estimation, in contrast to the standard SAOM, when the underlying networks are observed with noise. We apply our method to functional brain networks inferred from electroencephalogram data, revealing larger effect sizes when compared to the naive approach of fitting the standard SAOM.
Agricultural land use induces broader homogenization of soil microbial functional composition than taxonomic composition
Authors: Ohigashi Takamitsu , Madegwa Yvonne M. , Karuku George N. , Njira Keston , Uchida Yoshitaka
Published: February 2025

Land-use changes from natural ecosystems to farmlands significantly alter soil functioning worldwide, especially challenging sub-Saharan Africa with rapid population growth and intensive agriculture. Soil microbial diversity is vital in supporting ecosystem multifunctionality and preventing pathogen growth. Recent studies have revealed that farming activities homogenize microbial communities across distant sites, which may lead to functional homogenization on that scale. However, given the redundancy of microbial functions, functional homogenization driven by farming may occur on a broader scale than taxonomic homogenization. We compared the taxonomic and functional compositions of soil prokaryotic and fungal communities between natural lands and farmlands at scales ranging from within-site (~200 m) to across-site (~1500 km) in Kenya and Malawi, using amplicon sequencing of 16S rRNA and ITS genes and the prediction of microbial functions. Soil microbial functional compositions were homogenized more broadly than taxonomic compositions in farmlands compared to natural lands, suggesting that similar functional responses to farming occur across scales where different taxa thrive. Furthermore, environmental factors predominantly influenced within-site homogeneity, whereas farming itself was a significant contributor to across-site homogeneity, indicating an overriding influence of farming compared to environmental variations. Additionally, pathogenic fungi were relatively more abundant in farmlands, likely due to reduced species competition and farming-induced environmental changes such as low soil pH. Our findings highlight the need to investigate microbial functional diversity alongside taxonomic diversity when assessing the impacts of land-use changes on soil health to develop sustainable land management strategies.
Tracking changes in corticospinal excitability during visuomotor paired associative stimulation to predict motor resonance rewriting
Authors: Guidali Giacomo , Bolognini Nadia
Published: February 2025

Mirror properties of the action observation network (AON) can be modulated through Hebbian-like associative plasticity using paired associative stimulation (PAS). We recently introduced a visuomotor protocol (mirror-PAS, m-PAS), which pairs transcranial magnetic stimulation (TMS) over the primary motor cortex (M1) with visual stimuli of ipsilateral (to TMS) movements, leading to atypical corticospinal excitability (CSE) facilitation (i.e., motor resonance) during PAS-conditioned action observation. While m-PAS aftereffects are robust, little is known about markers of associative plasticity during its administration and their predictive value for subsequent motor resonance rewriting.

In the present study, we analyzed CSE dynamics in 81 healthy participants undergoing the m-PAS before and after passively observing left- or right-hand index finger movements. Here, typical and PAS-conditioned motor resonance was assessed with TMS over the right M1. We examined CSE changes during the m-PAS and used linear regression models to explore their relationship with motor resonance modulations.

Results showed that the m-PAS transiently reshaped both typical and PAS-conditioned motor resonance. Importantly, we found a gradual increase of CSE during m-PAS, which predicted the loss of typical motor resonance but not the emergence of atypical responses after the protocol’s administration.

Our findings suggest that the motor resonance reshaping induced by the m-PAS is not fully predictable by CSE online modulations. Likely, this rewriting is the product of a large-scale reorganization of the AON rather than a phenomenon restricted to the PAS-stimulated motor cortex. This study underlines that monitoring CSE during non-invasive brain stimulation protocols could provide valuable insight into some, but not all, their plastic outcomes.
Triazole 187 is a biased KOR agonist that suppresses itch without sedation and induces anxiolytic-like behaviors in mice
Authors: Volf Allison , Brust Tarsis F. , Kobylski Robin R. , Czekner Kerri M. , Stahl Edward L. , Cameron Michael D. , Trojniak Ashley E. , Aubé Jeffrey , Bohn Laura M.
Published: February 2025

Kappa opioid receptor agonists are clinically used to treat pruritis and have therapeutic potential for the treatment of pain and neuropsychiatric disorders. We have previously shown that triazole 1.1 is a G protein signaling-biased KOR agonist, that can suppress itch without producing signs of sedation in mice. This profile was recapitulated in rats and non-human primates however, triazole 1.1 had limited potency as an antipruritic. Here we describe a more potent, G protein signaling-biased agonist, triazole 187. Triazole 187 is a potent antipruritic agent and does not decrease spontaneous locomotor activity; interestingly, it produces anxiolytic-like behaviors in mice, an effect not observed for triazole 1.1. In addition to curbing sedation, triazole 187 produces only mild diuresis, resulting in 30% of urine output induced by U50,488H at dose that is 188-fold the antipruritic potency dose. Compounds like triazole 187 may present a means to treat anxiety accompanied by persistent chronic itch while avoiding sedation and diuresis accompanied by typical KOR agonists.

Abstract Figure

Graphic Abstract
Alterations in retinal tau phosphorylation in Alzheimer’s disease patients identified by mass spectrometry
Authors: Reis Santiago Jessica Dos , Poceviciute Dovile , Vogel Jacob ,   The Netherlands Brain Bank, Brinkmalm Gunnar , Wennström Malin
Published: February 2025

Background

Most neurodegenerative diseases, including Alzheimer’s disease (AD) and multiple sclerosis (MS), are associated with abnormal post-translational phosphorylation of tau (p-tau) in the brain. Studies using immunostaining techniques have revealed an accumulation of p-tau also in the AD retina and suggested this p-tau accumulation may reflect tau pathology in the brain. However, immunostainings are dependent on antibody specificity and tissue processing. Hence, further validation using additional methods is needed to identify the p-tau species in the retina and verify their relationship to AD pathology.

Methods

We used mass spectrometry to measure p-tau peptides in retinal and hippocampal samples from non-demented controls (NC, n=8), AD ( n=12), and MS (n=4). Peptides were first extracted with Lysis buffer to capture extracellular components and cytoplasm, and then with Ripa buffer to isolate nuclear and organelle proteins. We then analysed the differences in p-tau levels between diagnoses and explored how retinal p-tau variants correlate with hippocampal p-tau and neuropathological changes.

Results

The mass spectrometry analysis of the retina revealed peaks corresponding to tau peptides phosphorylated at T181, S199/S202, T231, S396 + T403/S404, and T403/S404. These p-tau peptides were also detected in the hippocampal samples, along with additional p-tau peptides such as T217 and S262. Total tau phosphorylation and phosphorylation at S199/S202 and T231 were significantly higher in the retina of AD cases compared to NC. These two peptides, along with peptides phosphorylated at S396+T403/S404 and T403/S404, were also higher in cases with high amyloid-beta (Aβ) Braak stages compared to those with low Aβ Braak stages. Further analysis showed that higher Aβ Braak stages were associated with higher mass spectrometry peak intensities of peptides phosphorylated at S199/S202 and S396+T403/S404. Additionally, retinal p-tau peptides at S396+T403/S404 and T403/S404 correlated with neurofibrillary tangle (NFT) Braak stages, and p-tau peptides S396+T403/S404 in the retina were linked to corresponding phosphorylation in the CA1 region.

Conclusions

These findings underscore the connection between retinal and brain tau pathology and highlight the potential of retinal tau as a biomarker for AD diagnosis and monitoring while also deepening our understanding of tauopathies in both the retina and brain.
Consequences of phenological shifts are determined by the number of generations per season
Authors: Zou Heng-Xing , Rudolf Volker H.W.
Published: February 2025

The order and timing of species’ arrival in a community can often change species interactions. Termed priority effects, this phenomenon arises in communities with drastically different life histories (e.g., bacteria, insects, and amphibians), yet how such life history traits affect consequences of priority effects in seasonal systems remains understudied. Here, we test how a key aspect of life history, numbers of generations in a growing season, interact with priority effects using two competing flour beetles,Tribolium castaneumandTribolium confusum. We manipulated the sequence and timing of arrivals and collected all adults after one, two, or three generations, simulating phenological shifts in communities with different growing season lengths. The early species always reached a higher population, and in general, its per-capita competition towards the late arriver was stronger, indicating priority effects. However, fitting competition models to the data revealed that more generations in a season led to smaller ranges of the calculated stabilization potentials and fitness differences between species and more positive stabilization potentials, indicating that overlapping generations buffered interactions against strong priority effects from different arrival times. These results suggest that effects of phenological shifts (e.g. due to climate change) on species coexistence mechanisms are contingent on the life-histories of interacting species.
HIV-1 derived replication intermediates/oligonucleotides induce a type I IFN-dependent immune suppression via STING activation that can be restored by targeting IFNARI
Authors: Svanberg Cecilia , Mukku Ravi Prasad , Besler Özkan , Hopkins Francis R. , Sjöwall Christopher , Nyström Sofia , Shankar Esaki M. , Larsson Marie
Published: February 2025

The hallmark of HIV-1 infection is the progressive development of multicellular and systemic immune dysfunction, culminating in AIDS. Dendritic cells (DCs) play a pivotal role in HIV dissemination to CD4+ T cells, which are subsequently depleted by the virus leading to HIV disease progression. Type I interferons (IFNs) are critical for host defense during acute infection but contribute to chronic immune activation during the later stages of HIV disease. This persistent activation leads to immune cell exhaustion. HIV-1 can activate type I IFN responses via several pathways, including the STING pathway, which is activated by e.g., virus-derived oligonucleotides. Here, we investigated the underlying mechanisms creating HIV-1-mediated immune dysfunction and role of type I IFNs using a DC and T cell co-culture model. HIV-1 exposure in the DC-T cell co-culture promoted the expansion of suppressive T cells with diminished proliferation and effector functions. The impairment required type I IFNs and subsequent IFN-α/β receptor signaling, initiated by HIV-derived ssDNA activation of IFI16/cGAS followed by STING signaling in the DCs. Targeting IFNAR1 with Anifrolumab restored the immune functions of both DCs and T cells, as well as T cell proliferation and T cell effector functions, including their secretion of IL-2, IFN-γ, and granzyme B. Our findings support that the immune impairments existing in untreated or antiretroviral therapy (ART) treated HIV-infected individuals are mediated, if not fully in part by type I IFN’s negative effect on DC and T cells. Therapeutics targeting IFN-α/β receptors, such as Anifrolumab, hold potential as combination treatment alongside ART, to achieve a more complete immune restoration and contribute to improved quality of life among people living with HIV.
The nematodeCaenorhabditis eleganscan benefit from its coexisting fungal microbiome memberBarnettozyma californica
Authors: Petersen Carola , Griem-Krey Hanne , Christophersen Christina Martínez , Schulenburg Hinrich , Habig Michael
Published: February 2025

The nematodeCaenorhabditis elegansis known to feed on and interact with bacteria in its environment and has become a model organism for microbiome studies. However, whether and howC. elegansinteracts with co-occurring fungi remains largely unknown, despite the presence of many fungal species in its natural habitat. Here, we isolate the yeastBarnettozyma californicafrom a mesocosm experiment withC. elegansand characterize its genome and interaction with the nematode. We find thatB. californicais ingested byC. elegansand can serve as a sole, albeit poor, food source. Yet, when present together withEscherichia coliOP50, the fungus can lead to higher population growth and altered foraging behavior, suggesting that this fungi-bacteria mixture provides a better food source than bacteria alone. This effect varied between different naturalC. elegansstrains, suggesting a genomic basis for the nematode’s interaction withB. californica. The fully assembled and annotated genome of the isolatedB. californicastrain does not indicate any obvious candidate genes for its interaction withC. elegansand/orE. coliOP50. Overall, our results provide an intriguing example of the complexity and multi-level relationship between naturally interacting fungi, bacteria, and animals.

Graphical Abstract

Barnettozyma californicais a member of the fungal microbiome of the model nematodeCaenorhabditiselegans and can serve as food for worms. When combined withE. coli, this fungus can increase population growth and reduce foraging behaviour dependent on C. elegans genotype, revealing a genetic influence on host-fungus-bacterium interactions.
Neutrophil arrest in myocardial capillaries drives hypoxia and impairs diastolic function in a mouse model of heart failure with preserved ejection fraction
Authors: Small David M. , Buglione Anne E. , Allan-Rahill Nathaniel H. , Locke Tyler , Elmagid Laila M. Abd , Hovasapian Soseh , Kim Rachel , Mistry Adina A. , Vaquerano Sofia A. , Schaffer Chris B. , Nishimura Nozomi
Published: February 2025

Myocardial blood flow deficits in heart failure with preserved ejection fraction (HFpEF) patients and related animal models have been recognized for decades, but the underlying mechanisms and resulting consequences for HFpEF pathogenesis remain poorly understood. Using intravital cardiac microcopy in a ‘two-hit’ mouse model of HFpEF, we identified an increased number of neutrophils in capillaries slow moving orstalled, blocking blood flow, as compared to control mice. Administration of antibodies against the neutrophil marker Ly6G reduced the number of arrested neutrophils in myocardial capillaries, leading to both a reduction in myocardial tissue hypoxia and improvement in diastolic function and exercise tolerance. This study identifies a previously uncharacterized cellular mechanism that explains myocardial blood flow deficits in mouse models of HFpEF, and demonstrates that improving myocardial blood flow improves heart function. Restoring myocardial perfusion by preventing neutrophil arrest in coronary capillaries may provide a strategy for improving heart function in HFpEF patients.
Accurate Identification and Mechanistic Evaluation of Pathogenic Missense Variants with Rhapsody-2
Authors: Banerjee Anupam , Bogetti Anthony , Bahar Ivet
Published: February 2025

Understanding the effects of missense mutations or single amino acid variants (SAVs) on protein function is crucial for elucidating the molecular basis of diseases/disorders and designing rational therapies. We introduce here Rhapsody-2, a machine learning tool for discriminating pathogenic and neutral SAVs, significantly expanding on a precursor limited by the availability of structural data. With the advent of AlphaFold2 as a powerful tool for structure prediction, Rhapsody-2 is trained on a significantly expanded dataset of 117,525 SAVs corresponding to 12,094 human proteins reported in the ClinVar database. Adopting a broad set of descriptors, including evolutionary, structural, dynamic, and energetics features in the training algorithm, Rhapsody-2 achieved an AUROC of 0.94 in 10-fold cross-validation when variants of the same protein are not simultaneously included in the training and testing sets. Benchmarking against a variety of testing datasets demonstrated the high performance of Rhapsody-2. While evolutionary descriptors play a dominant role in pathogenicity prediction, structural dynamics features provide a mechanistic interpretation of the predicted effects, pathogenic or neutral, of SAVs. Notably, residues involved in allosteric communication, and those distinguished by pronounced fluctuations in the high frequency modes of motion or subject to spatial constraints in soft modes usually give rise to pathogenicity when mutated. Overall, Rhapsody-2 provides an efficient and transparent tool for accurately predicting the pathogenicity of SAVs and unraveling the mechanistic basis of the observed behavior, thus advancing our understanding of genotype-to-phenotype relations.
hERG-LTN: A New Paradigm in hERG Cardiotoxicity Assessment Using Neuro-Symbolic and Generative AI Embedding (MegaMolBART, Llama3.2, Gemini, DeepSeek) Approach
Authors: Hossain Delower , Al Abir Fuad , Chen Jake Y
Published: February 2025

Assessing adverse drug reactions (ADRs) during drug development is essential for ensuring the safety of new compounds. The blockade of the Ether-a-go-go-related gene (hERG) channel plays a critical role in cardiac repolarization. Computational predictions of hERG inhibition can help foresee drug safety, but current data-driven approaches have limitations. Therefore, a new paradigm that bridges the gap between data and knowledge offers an alternative for advancing precision pharmacogenomics in assessing hERG cardiotoxicity. This study aims to develop a reasoning-based, in silico, robust model for predicting drug-induced hERG inhibition, facilitating new drug development by reducing time and cost, supporting downstream in vitro and in vivo testing. In this study, we constructed a new cohort, UnihERG_DB, by sourcing data from ChEMBL, PubChem, BindingDB, GTP, hERG Karim’s, and hERG Blocker’s bioactivity databases. The final dataset comprises 20,409 structures represented as SMILES (Simplified Molecular Input Line Entry System), labeled as hERG blockers (IC50 < 10 µM) or non-hERG blockers (IC50 ≥ 10 µM). Molecular features were extracted using Morgan and CDK fingerprints. Furthermore, we explored embedding feature computation using cutting-edge Large Language Models, including NVIDIA MegaMolBART, LLaMA 3.2, Gemini, and DeepSeek. Finally, we utilized the Logic Tensor Network (LTN), an advanced AI framework, to train and develop the hERG predictive model. Model performance was evaluated using two benchmarks: External Test-1 and hERG-70. The Logic Tensor Network (LTN) outperformed several models, including CardioTox, M-PNN, DeepHIT, CardPred, OCHEM Predictor-II, Pred-hERG 4.2, Random Forest, and Gradient Boosting. On the External Test-1 dataset, LTN achieved an accuracy of 0.931, a specificity of 0.928, and a sensitivity of 0.933. Furthermore, on the hERG-70 benchmark, LTN achieved an accuracy (ACC) of 0.827, a specificity (SPE) of 0.890, and a correct classification rate (CCR) of 0.833. Overall, the Neuro-Symbolic AI approach sets a new standard for hERG-related cardiotoxicity assessment, yielding competitive results with current state-of-the-art (SOTA) models, and highlights its potential for advancing precision pharmacogenomics in drug discovery and development (GitHub).
Machine learning ensemble identifies distinct age-related response to spaceflight in mammary tissue
Authors: Casaletto James A. , Zhao Tyler , Yeung Jay , Ansari Amaan , Raj Ayush , Mishra Arnav , Fry Amber , Sun Kathryn , Lendahl Sofia , Guan Willy , Lee Abigail , Sanders Lauren M. , Costes Sylvain V.
Published: February 2025

Spaceflight presents unique environmental stressors, such as microgravity and radiation, that significantly affect biological systems at the molecular, cellular, and organismal levels. Female astronauts, in particular, face an increased risk of developing breast cancer due to exposure to ionizing radiation and other spaceflight-related factors. Age also plays a crucial role in the mammary gland’s response to these stressors, with younger organisms generally exhibiting more efficient response mechanisms than older ones. In this study, we utilized an ensemble of machine learning algorithms to analyze gene expression profiles from mammary tissue of young and old female mice exposed to spaceflight to predict age (old vs young) and condition (spaceflight vs ground control). Using the genes our ensemble identified as most predictive, we investigate the molecular pathways involved in spaceflight-related health risks, particularly in the context of breast cancer and cardiovascular health. We identified age-dependent differences in the gene expression profiles of spaceflight-exposed mice compared to ground control.

Specifically, younger mice exhibited enriched pathways related to cellular structure, while older mice showed activation of pathways involved in cortisol synthesis and muscle contraction. All mice responded to spaceflight with evidence of elevated lipid metabolic function. These findings highlight the critical role of age in modulating the response to spaceflight-induced stress and suggest that these molecular pathways may contribute to differential outcomes in tissue homeostasis, cardiovascular and metabolic disorders, and breast cancer susceptibility.
SpliceSelectNet: A Hierarchical Transformer-Based Deep Learning Model for Splice Site Prediction
Authors: Miyachi Yuna , Nakai Kenta
Published: February 2025

Accurate RNA splicing is essential for gene expression and protein function, yet the mechanisms governing splice site recognition remain incompletely understood. Aberrant splicing caused by mutations can lead to severe diseases, including cancer and genetic disorders, underscoring the need for accurate computational tools to predict splice sites and detect disruptions. Existing methods have made significant advances in splice site prediction but are often limited in handling long-range dependencies, a factor critical to splicing regulation. Moreover, many models lack interpretability, hindering efforts to elucidate the underlying biological mechanisms. Here, we present SpliceSelectNet (SSNet), a novel deep-learning model that predicts splice sites directly from DNA sequences. This model is capable of handling long-range dependencies (up to 100 kb) using a hierarchical Transformer-based architecture with both local and global attention mechanisms. SSNet offers interpretability at the single nucleotide level, making it particularly effective for identifying aberrant splicing caused by mutations. Our model surpasses the state-of-the-art (SoTA) in splice site prediction on the Gencode test dataset and demonstrates superior performance in aberrant splicing prediction on the BRCA dataset and deep intronic dataset.
A Chk1-Sp1-CD59 axis of the DNA damage response impedes rituximab-mediated complement-dependent cytotoxicity
Authors: Chan Allison S. Y. , Jaynes Patrick W. , Anbuselvan Akshaya , Ong Charmaine Z. Y. , Hoppe Michal M. , Yong Wai Khang , Khanchandani Vartika , Lee Jie Min , Mustafa Nurulhuda , Azaman Irfan , Hoang Phuong M. , Hong Guo , Chng Wee Joo , Cragg Mark S. , Kappei Dennis , Tripodo Claudio , Jeyasekharan Anand D.
Published: February 2025

DNA damage responses primarily coordinate intracellular processes, but their effects on the cell surface remain poorly understood. We uncovered a DNA damage response at the cell surface that regulates complement dependent cytotoxicity (CDC), a key mechanism of antibody-mediated tumor cell killing. We found that several mCRPs, such as CD46, CD55, and CD59, are upregulated in diffuse large B-cell lymphoma (DLBCL) cells following chemotherapy. These mCRPs protect cells from CDC, including CDC triggered by anti-CD20 immunotherapy. Chemotherapy pre-treatment reduced the efficacy of rituximab-induced CDC, with CD59 exerting a dominant function. A high-throughput kinase screen revealed that Chk1 inhibition restored CDC sensitivity. Mechanistically, chemotherapy-induced CD59 expression was Chk1-dependent and regulated at an Sp1-driven promoter site. Inhibition of Sp1 with Mithramycin A abrogated chemotherapy-induced CD59 transcription. Co-immunoprecipitation mass spectrometry revealed that DNA damage releases transcriptional repressors from Sp1, an effect reversed by Chk1 inhibition. These findings define a Chk1-Sp1-CD59 signaling axis linking genotoxic stress to complement modulation. Our study reveals potential antagonism between chemotherapy and antibody-mediated CDC and highlights consideration in sequencing combination therapies and a therapeutic potential of Chk1 inhibitors in maintaining CDC efficacy during chemoimmunotherapy.
The activation of fibroblast growth factor receptor 1 provides therapeutic benefit in a mouse model of Alzheimer’s disease
Authors: Hung Wei-Chien , Sun Wei-Chun , Su Tzu-Ching , Lee Yi-Jung , Cheng Irene Han-Juo
Published: February 2025

Alzheimer’s disease (AD) is a neurodegenerative disease that is characterized by the accumulation of amyloid plaque and neurofibrillary tangles, ultimately impairing multiple cognitive domains. Both plaques and tangles cause neuronal damage and stimulate inflammatory responses in glial cells. The fibroblast growth factor receptor 1 (FGFR1)-mediated signaling pathways support the function of damaged neurons and modulate inflammatory response. The FGFR1 agonists, including Fibroblast growth factor 1 (FGF1) and FG loop peptide (FGL), have been implicated in multiple disease therapy. Whether FGFR1 agonists can improve pathology and cognitive function in AD remains unknown. Here, we showed that administration of FGF1 and FGL to the AD mouse model reversed spatial memory impairment, enhanced neurogenesis, suppressed reactive astrogliosis, and restricted dystrophic neurite. However, only FGF1 treatment reduced the deposition of senile plaque. In microglial culture studies, FGF1 improves the phagocytosis ability of microglia, which contributes to the clearance of plaques. Together, our findings suggested that FGFR1 agonists alleviate pathology and cognitive impairment via immunomodulatory and improve neuronal health in the AD mouse model.

Highlights

FGFR1 agonists alleviate memory deficits in AD mice.

FGFR1 agonists increase adult neurogenesis and limit dystrophic neurites in AD mice.

FGFR1 agonists increase plaque-associated microgliain vivoand promote phagocytosisin vitro.
Proteomic characterisation of the early rheumatoid arthritis-cardiovascular disease multimorbid axis
Authors: Shukla Rudresh R , Mohammed Amr , Black Nicholas , Erhayiem Bara , Fent Graham , Miller Christopher A , Plein Sven , Plant Darren , Buch Maya H
Published: February 2025

Background

Inflammation contributes to the increased risk of cardiovascular disease (CVD) observed in people with rheumatoid arthritis (RA), with increased prevalence observed from time of diagnosis. Subclinical vascular and myocardial abnormalities can be detected with cardiovascular magnetic resonance (CMR) imaging in otherwise low risk individuals. Identifying associated circulating markers could enable diagnostics and implicate biological pathways of RA-CVD. The study’s objective was to identify blood-based proteins associated with CMR measures of vascular and myocardial abnormality and associated inflammatory and/or cardio-metabolic pathways in a new-onset RA cohort.

Methods

Serum samples (baseline/pre-treatment, N = 75 and year 1, N = 71) from CADERA (Coronary Artery Disease Evaluation in Rheumatoid Arthritis) participants, a subgroup of a randomised controlled trial, who underwent CMR, were used to measure 334 proteins across 4 pre-defined Olink panels (Inflammation, Cardiovascular-II, Cardiovascular-III, Cardiometabolic). Bayesian mixed effects regression analyses, unsupervised hierarchical clustering and protein network analyses were applied. Normalised protein expression from 334 Olink proteins were used as exposures in the regression analyses. CMR measures of vascular stiffness (aortic distensibility and stiffness index) and myocardial tissue characteristics (native T1, myocardial extracellular volume and late gadolinium enhancement) were each used as individual outcomes in regression analyses. Associations were considered significant at 95% threshold for credible intervals. An expanded physical protein-protein interaction (PPI) network created using the significant (seed) proteins was subjected to topological and enrichment analysis to identify enriched biological pathways.

Results

54/334 proteins were associated significantly with CMR measures at baseline (7 - vascular; 48 - myocardial tissue characteristics; Coagulation factor 11 with both). Two proteins, TNFSF13B (B-cell activating factor) and CRTAC1, were associated with CMR measures at baseline, were sensitive to change over time and co-varied with changes in CMR measure. Topological analysis of expanded PPI network revealed GRB2 as most connected (degree score=64; closeness score=118.83) and four key signalling pathways, including JAK-STAT and EGFR tyrosine kinase inhibitor resistance, emerged as significant.

Conclusions

This first proteomic study of treatment-naïve early RA and subclinical cardiovascular pathology identifies proteins that could aid diagnostic test development and implicates signalling pathways in the RA-cardiovascular axis to inform on our understanding of the basis of RA-CVD.
Decoding DNA methylation and non-coding RNAs mediated regulatory landscape of breast tumor and adjacent normal tissues
Authors: Kumar Swapnil , Vindal Vaibhav
Published: February 2025

Tumorigenesis not only involves perturbations of mRNAs but also microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and DNA methylation (DNAm). Additionally, the tumor-adjacent normal tissues (TANTs) that are used as controls in cancer studies are not completely normal and, if explored systematically, can help to understand tumorigenesis better. In this regard, expression and DNAm profiles of breast tumor tissues (viz., Luminal-A, Luminal-B, Her2+, Basal-like, and Normal-like) and TANTs were used to construct and analyze their integrative networks. These networks included regulations among genes, transcription factors, lncRNAs, and miRNAs, along with gene/lncRNA methylations. This followed the identification of candidate genePCLAFhaving transitivity value one across all six tissue networks. Further, 503 common hubs (388 protein-coding, 100 miRNAs, and 15 lncRNAs), including seven methylated genes (SPI1,STAT5A,RORC,SPDEF,ELF5,HOXB2, andRUNX3), and 149 common bottlenecks (145 protein-coding, three miRNAs, and one lncRNA), including three methylated genes (SPI1,SPDEF, andRUNX3) and one methylated lncRNA (PART1), were identified. Moreover, 145 nodes, including three methylated genes (SPI1,SPDEF, andRUNX3) and three miRNAs (hsa-miR-34a, hsa-miR-149, and hsa-miR-141), were identified as both hubs and bottlenecks (HBs) across all six tissues. However, none of the lncRNAs were found HBs therein. Genes and lncRNAs with higher degrees, betweenness, eigenvector centrality, and pagerank were found more preferably methylated than others. Further, pathway analysis of hubs and bottlenecks across all six tissues revealed their significant involvement in the pathway of Transcriptional misregulation in cancer. Overall, these findings uncover new insights into the epigenetic mechanisms of tumorigenesis.