bluuebunny/crossref_metadata_2025_split huggingface dataset:
Density-dependent unidirectional hybridization between the Japanese pond turtle, Mauremys japonica, and the exotic Reeves’ pond turtle, Mauremys reevesii, in Japan, inferred from molecular and morphological analyses
Authors: Matsuda Yunosuke , Kaburagi Shun , Kamezaki Naoki , Ota Hidetoshi , Takahashi Hiroo , Imazu Takeshi , Kagayama Shawichi , Kawamura Kouichi 
Published: June 2024

Abstract
Hybridization between the indigenous Japanese pond turtle, Mauremys japonica, and the exotic Reeves’ pond turtle, Mauremys reevesii, is widespread in Japan. In this study, we examined this hybridization using an analysis of mtDNA and 11 microsatellite markers (MS) combined with morphometry. In a Bayesian clustering analysis of MS, the admixture of two clusters equivalent to the two species was detected in the Seto Inland Sea and Ise Bay regions. While mtDNA showed reciprocal hybridization between the two species, their hybrids tended to possess the mtDNA of the rarer species at each locality. Contrary to preceding studies, F2/later generations outnumbered F1 generations. In addition, the admixture of two mtDNA lineages (Chinese and Korean) of M. reevesii was widely observed in all regions, together with the range expansion of the recently introduced Chinese lineage. A significant correlation was observed between plastron morph and assignment probability of MS, showing that plastron morphology reflects the degree of introgression by M. reevesii in M. japonica. This finding means that the reproductive interference of the dominant species on a rarer species is a major factor driving the hybridization of the two Mauremys species. In addition, the range expansion of the Chinese lineage of M. reevesii appears to enhance the introgression by M. reevesii in M. japonica.
Mining for microbial metabolites associated with disease progression in an age-dependent model of experimental autoimmune encephalomyelitis
Authors: Pu Annie , Fettig Naomi M , Polyzois Alexandros , Naouar Ikbel , Ramaglia Valeria , Hohman Leah S , Zuo Michelle , Copeland Julia , Chan Donny , Davis Katy , Yu Shirley , Popple Sarah , Chao Gary , McCoy Kathy D , Schroeder Frank C , Gommerman Jennifer L , Osborne Lisa C 
Published: June 2024

AbstractPeople with Multiple Sclerosis (pwMS) exhibit alterations in the gut microbiome and its associated metabolites. Identifying causal links between specific fecal microbiome-derived metabolites and disease susceptibility has been shown using fecal microbial transfer (FMT) into animal models of MS (experimental autoimmune encephalomyelitis, EAE). However, a pipeline that identifies microbiome-associated metabolites that can alter age-dependent disease progression is lacking. We recently established a mouse model of MS disease progression that is induced by adoptive transfer of TH17 cells from young SJL/J mice immunized with myelin peptide into aged recipients. Adapting this model to FMT, we tested the role of young versus aged murine and human fecal microbial communities on disease progression. We demonstrate that microbiota derived from aged SJL/J mice is not sufficient to drive the progressive disease phenotype in young mice. However, human fecal microbiota from young versus aged donors induced a range of EAE phenotypes. Taking advantage of this variability, we were able to identify fecal communities that promote an “aged EAE” phenotype in chronologically young mice that were associated with distinct microbiota-derived metabolites. Our findings provide a framework for metabolite discovery associated with EAE disease chronicity and severity.
DeepMol: An Automated Machine and Deep Learning Framework for Computational Chemistry
Authors: Correia João , Capela João , Rocha Miguel 
Published: June 2024

AbstractThe domain of computational chemistry has experienced a significant evolution due to the introduction of Machine Learning (ML) technologies. Despite its potential to revolutionize the field, researchers are often encumbered by obstacles, such as the complexity of selecting optimal algorithms, the automation of data pre-processing steps, the necessity for adaptive feature engineering, and the assurance of model performance consistency across different datasets. Addressing these issues head-on,DeepMolstands out as an Automated ML (AutoML) tool by automating critical steps of the ML pipeline.DeepMolrapidly and automatically identifies the most effective data representation, pre-processing methods and model configurations for a specific molecular property/activity prediction problem. On 22 benchmark datasets,DeepMolobtained competitive pipelines compared with those requiring time-consuming feature engineering, model design and selection processes. As one of the first AutoML tools specifically developed for the computational chemistry domain,DeepMolstands out with its open-source code, in-depth tutorials, detailed documentation, and examples of real-world applications, all available athttps://github.com/BioSystemsUM/DeepMolandhttps://deepmol.readthedocs.io/en/latest/. By introducing AutoML as a ground-breaking feature in computational chemistry, DeepMol establishes itself as the pioneering state-of-the-art tool in the field.
A genome-wide association study of mass spectrometry proteomics using the Seer Proteograph platform
Authors: Suhre Karsten , Chen Qingwen , Halama Anna , Mendez Kevin , Dahlin Amber , Stephan Nisha , Thareja Gaurav , Sarwath Hina , Guturu Harendra , Dwaraka Varun B. , Batzoglou Serafim , Schmidt Frank , Lasky-Su Jessica A. 
Published: June 2024

ABSTRACTGenome-wide association studies (GWAS) with proteomics are essential tools for drug discovery. To date, most studies have used affinity proteomics platforms, which have limited discovery to protein panels covered by the available affinity binders. Furthermore, it is not clear to which extent protein epitope changing variants interfere with the detection of protein quantitative trait loci (pQTLs). Mass spectrometry-based (MS) proteomics can overcome some of these limitations. Here we report a GWAS using the MS-based Seer ProteographTMplatform with blood samples from a discovery cohort of 1,260 American participants and a replication in 325 individuals from Asia, with diverse ethnic backgrounds. We analysed 1,980 proteins quantified in at least 80% of the samples, out of 5,753 proteins quantified across the discovery cohort. We identified 252 and replicated 90 pQTLs, where 30 of the replicated pQTLs have not been reported before. We further investigated 200 of the strongest associated cis-pQTLs previously identified using the SOMAscan and the Olink platforms and found that up to one third of the affinity proteomics pQTLs may be affected by epitope effects, while another third were confirmed by MS proteomics to be consistent with the hypothesis that genetic variants induce changes in protein expression. The present study demonstrates the complementarity of the different proteomics approaches and reports pQTLs not accessible to affinity proteomics, suggesting that many more pQTLs remain to be discovered using MS-based platforms.Graphical AbstractSummarizing the approach taken to identify potential epitope effects.
A cautionary tale on the cost-effectiveness of collaborative AI in real-world medical applications
Authors: Innocenti Lucia , Ourselin Sebastien , Goh Vicky , Antonelli Michela , Lorenzi Marco 
Published: June 2024

AbstractFederated learning (FL) has gained wide popularity as a collaborative learning paradigm enabling trustworthy AI in sensitive healthcare applications. Never-theless, the practical implementation of FL presents technical and organizational challenges, as it generally requires complex communication infrastructures. In this context, consensus-based learning (CBL) may represent a promising collaborative learning alternative, thanks to the ability of combining local knowledge into a federated decision system, while potentially reducing deployment over-head. In this work we propose an extensive benchmark of the accuracy and cost-effectiveness of a panel of FL and CBL methods in a wide range of collaborative medical data analysis scenarios. Our results reveal that CBL is a cost-effective alternative to FL, providing comparable accuracy and significantly reducing training and communication costs. This study opens a novel perspective on the deployment of collaborative AI in real-world applications, whereas the adoption of cost-effective methods is instrumental to achieve sustainability and democratisation of AI by alleviating the need for extensive computational resources.
Exploring Integrin α5β1 as a Potential Therapeutic Target for Pulmonary Arterial Hypertension: Insights from Comprehensive Multicenter Preclinical Studies
Authors: Lemay Sarah-Eve , Montesinos Monica S. , Grobs Yann , Yokokawa Tetsuro , Shimauchi Tsukasa , Romanet Charlotte , Sauvaget Mélanie , Breuils-Bonnet Sandra , Bourgeois Alice , Théberge Charlie , Pelletier Andréanne , El Kabbout Reem , Martineau Sandra , Yamamoto Keiko , Ray Adrian S. , Lippa Blaise , Goodwin Bryan , Lin Fu-Yang , Wang Hua , Dowling James E , Lu Min , Qiao Qi , McTeague T. Andrew , Moy Terence I. , Potus François , Provencher Steeve , Boucherat Olivier , Bonnet Sébastien 
Published: June 2024

ABSTRACTPulmonary arterial hypertension (PAH) is characterized by obliterative vascular remodeling of the small pulmonary arteries (PA) and progressive increase in pulmonary vascular resistance (PVR) leading to right ventricular (RV) failure. Although several drugs are approved for the treatment of PAH, mortality remains high. Accumulating evidence supports a pathological function of integrins in vessel remodeling, which are gaining renewed interest as drug targets. However, their role in PAH remains largely unexplored. We found that the arginine-glycine-aspartate (RGD)-binding integrin α5β1 is upregulated in PA endothelial cells (PAEC) and PA smooth muscle cells (PASMC) from PAH patients and remodeled PAs from animal models. Blockade of the integrin α5β1 or depletion of the α5 subunit resulted in mitotic defects and inhibition of the pro-proliferative and apoptosis-resistant phenotype of PAH cells. Using a novel small molecule integrin inhibitor and neutralizing antibodies, we demonstrated that α5β1 integrin blockade attenuates pulmonary vascular remodeling and improves hemodynamics and RV function in multiple preclinical models. Our results provide converging evidence to consider α5β1 integrin inhibition as a promising therapy for pulmonary hypertension.One sentence summaryThe α5β1 integrin plays a crucial role in pulmonary vascular remodeling.
Exploring the therapeutic potential of a novel series of imidazothiadiazoles targeting focal adhesion kinase (FAK) for pancreatic cancer treatment: Synthesis, mechanistic Insights and promising antitumor and safety profile
Authors: Carbone Daniela , Pecoraro Camilla , Scianò Fabio , Terrana Francesca , Xu Geng , Bergonzini Cecilia , Roeten Margot S F , Cascioferro Stella , Cirrincione Girolamo , Diana Patrizia , Giovannetti Elisa , Parrino Barbara 
Published: June 2024

ABSTRACTFocal Adhesion Kinase (FAK) is a non-receptor protein tyrosine kinase that plays a crucial role in various oncogenic processes related to cell adhesion, migration, proliferation, and survival. The strategic targeting of FAK represents a burgeoning approach to address resistant tumors, such as pancreatic ductal adenocarcinoma (PDAC).Herein, we report a new series of twenty imidazo[2,1-b][1,3,4]thiadiazole derivatives assayed for their antiproliferative activity against the National Cancer Institute (NCI-60) panel and a wide panel of PDAC models. Lead compound10lexhibited effective antiproliferative activity against immortalized (SUIT-2, CAPAN-1, PANC-1, PATU-T, BxPC-3), primary (PDAC-3) and gemcitabine-resistant clone (PANC-1-GR) PDAC cells, eliciting IC50values in the low micromolar range (1.04-3.44 µM), associated with a significant reduction in cell-migration and spheroid shrinkagein vitro. High-throughput kinase arrays revealed a significant inhibition of the FAK signalling network, associated to induction of cell cycle arrest in G2/M phase, suppression of tumor cell invasion and apoptosis induction. The low selectivity index/toxicity prompted studies using PDAC mouse xenografts, demonstrating significant inhibition of tumor growth and safety. In conclusion, compound10ldisplayed antitumor activity and safety in bothin vitroandin vivomodels, emerging as a highly promising lead for the development of FAK inhibitors in PDAC.
Horizon: CNV interpretation through rapid automated ACMG-aligned pathogenicity analysis
Authors: Eldesouky Mariam , Shiyas Suhana , Islam Amirul , Hasan Md. Nahid , Hossain Md. Tanvir , Akter Hosneara , Berdiev Bakhrom K. , Kuebler Wolfgang M. , Rahman Proton , Woodbury-Smith Marc , Hasan Syed M. , Nassir Nasna , Uddin Mohammed 
Published: June 2024

AbstractPurposeOur study assesses the Horizon model, a novel CNV classification tool developed in line with American College of Medical Genetics (ACMG) guidelines, to enhance the classification of pathogenicity in CNVs.MethodsHorizon utilizes a ranking-based algorithm, incorporating multiple proprietary databases and variant inheritance models as per ACMG standards. The model’s effectiveness was verified through Area Under the Curve (AUC) analyses on three datasets comprising 696 pathogenic inherited orde novovariants, as classified by clinical geneticists and several established tools.ResultsHorizon achieved an AUC of 0.97 in the discovery cohort, demonstrating high accuracy in CNV interpretation and proficiency in predicting pathogenicity. We observed an AUC of 0.87 in thede novovariant cohort and an overall AUC of 0.94 across all cohorts, surpassing tools like ClassifyCNV and AnnotSV. It showed particular effectiveness in interpreting duplication CNVs and the highest performance for CNVs sized 3-5 Mb.ConclusionThe Horizon model offers robust and accurate CNV interpretation, outperforming existing tools and aligning closely with clinical evaluations. Its comprehensive approach, integrating a range of genomic features and following ACMG guidelines, makes it a crucial tool in the genomic interpretation landscape, facilitating the rapid and accurate diagnosis of genetic disorders.
A Mimicry-Based Strategy Between Human and Commensal Antigens for the Development of a New Family of Immune Therapies for Cancer
Authors: Talpin Alice , Maia Ana , Carpier Jean-Marie , Kulakowski Guillaume , Gaal Camille , Strozzi Francesco , Billerey Coline , Aubergeon Lucie , Amable Ludivine , Kervevan Jérôme , Mersceman Tifanny , Garnier Alexandrine , Oliveira Catia Pereira , Calderon Carolina , Bachrouche Diana , Ventujol Chloé , Martinez Jennifer , Bonnet Michaël , Noguerol Julie , Laviolette Karl , Boullerot Laura , Malfroy Marine , Chevalier Grégoire , Adotevi Olivier , Joffre Olivier , Idbaih Ahmed , Vieito Maria , Ghiringhelli François , Stradella Agostina , Tabatabai Ghazaleh , Burger Michael C. , Mildenberger Iris , Herrlinger Ulrich , Reardon David A. , Wick Wolfgang , Gouttefangeas Cécile , Bonny Christophe , Chêne Laurent , Gamelas Magalhaes Joao 
Published: June 2024

AbstractPeptide vaccines have emerged as a promising strategy for cancer immunotherapy, yet often lack of strong, specific and sustained immune responses against tumor antigens. To achieve a robust immune response, the effective selection of tumour antigens is crucial. While neoantigens trigger potent immune responses, their use suffers from patient specificity and their rarity in low-mutational tumors. Alternatively, the immunogenic potential of tumor-associated antigens (TAAs) is limited by central immune tolerance. Molecular mimicry and T cell cross-reactivity is a proposed mechanism to trigger a robust T cell-mediated antitumor response. Although molecular mimicry between pathogens and tumor antigens has been described, the potential benefits of exploiting this molecular mimicry with commensal bacterial antigens in antitumor immunity have not been thoroughly investigated despite strong evidence that the composition of the human microbiota significantly influences immune competency. Our new approach called OncoMimics™, which uses molecular mimicry between commensal bacterial and tumoral antigens to induce cross-reactive cytotoxic T cells against tumor cells. In preclinical studies, vaccination with OncoMimic™ peptides (OMPs) led to the expansion of CD8+T cells reacting against homologous tumor-associated antigen peptides and elicits cytotoxic activity against tumor cells. OMPs are efficiently recognized by a prevalent T cell population within the peripheral blood mononuclear cells of healthy individuals. An ongoing clinical trial (NCT04116658) using OncoMimics™ in patients with glioblastoma demonstrates early, durable, and cross-reactive tumor antigen CD8+T cell responses with pronounced memory persistence. By overcoming the current vaccine limitations, OncoMimics™ constitutes a promising strategy for enhancing cancer immunity and improving patient outcomes.Statement of SignificanceThis study introduces OncoMimics™, a peptide-based immunotherapy leveraging molecular mimicry to induce robust, cross-reactive T cell responses against tumor antigens, showing promising early results in an ongoing glioblastoma clinical trial (NCT04116658)
The Impact of Scene Context on Visual Object Recognition: Comparing Humans, Monkeys, and Computational Models
Authors: Djambazovska Sara , Zafer Anaa , Ramezanpour Hamidreza , Kreiman Gabriel , Kar Kohitij 
Published: June 2024

AbstractDuring natural vision, we rarely see objects in isolation but rather embedded in rich and complex contexts. Understanding how the brain recognizes objects in natural scenes by integrating contextual information remains a key challenge. To elucidate neural mechanisms compatible with human visual processing, we need an animal model that behaves similarly to humans, so that inferred neural mechanisms can provide hypotheses relevant to the human brain. Here we assessed whether rhesus macaques could model human context-driven object recognition by quantifying visual object identification abilities across variations in the amount, quality, and congruency of contextual cues. Behavioral metrics revealed strikingly similar context-dependent patterns between humans and monkeys. However, neural responses in the inferior temporal (IT) cortex of monkeys that were never explicitly trained to discriminate objects in context, as well as current artificial neural network models, could only partially explain this cross-species correspondence. The shared behavioral variance unexplained by context-naive neural data or computational models highlights fundamental knowledge gaps. Our findings demonstrate an intriguing alignment of human and monkey visual object processing that defies full explanation by either brain activity in a key visual region or state-of-the-art models.
Multiple blood feeding bouts in mosquitoes allow for prolonged survival and are predicted to increase viral transmission during drought
Authors: Holmes Christopher J. , Chakraborty Souvik , Ajayi Oluwaseun M. , Uhran Melissa R. , Frigard Ronja , Stacey Crystal L. , Susanto Emily E. , Chen Shyh-Chi , Rasgon Jason L. , DeGennaro Matthew , Xiao Yanyu , Benoit Joshua B. 
Published: June 2024

AbstractSurvival through periods of drought is critical for mosquitoes to reside in semi-arid regions with humans. Dry conditions increase blood feeding propensity in mosquitoes, but it is unknown if dehydration-induced bloodmeals increase feeding beyond what is necessary for reproduction. Following a bloodmeal, prolonged exposure to dry conditions increased secondary blood feeding in mosquitoes by nearly two-fold, and chronic blood feeding allowed mosquitoes to survive up to twenty days without access to water sources. This refeeding did not alter the number of eggs generated, suggesting this refeeding is for hydration and nutrient replenishment. Exposure to desiccating conditions following a bloodmeal resulted in increased activity, decreased sleep levels, and prompted a return of CO2sensing before egg deposition. Increased blood feeding during the vitellogenic stage and higher survival during dry periods are predicted to increase pathogen transmission, allowing for a rapid rebound in mosquito populations when more favorable conditions return. This explains the elevated levels of specific arbovirus cases in association with periodic dry conditions and warrants further consideration as climate change progresses. Overall, these results solidify our understanding of the role of dry periods on mosquito blood feeding and how mosquito dehydration contributes to vectorial capacity and disease transmission dynamicsSignificance statementBouts of dehydration yield substantial changes to insects’ physiology and behavior. Mosquitoes are exceptionally prone to dehydration due to high water loss rates, but few integrative studies have examined the comprehensive impact of drought conditions on mosquitoes. Here, we demonstrate that dry conditions lead to multiple blood feeding events, allowing mosquitoes to survive dry periods. This repeated blood feeding is associated with higher activity and an early return of attraction to vertebrate hosts. Increased dry season survival and more frequent blood feeding are predicted to yield higher transmission of mosquito-borne viruses. This suggests that a higher prevalence of drought associated with climate change will have varying impacts on mosquito-borne diseases.
Substantial Braking Force of Anterior Tibial Translation Induces the Spontaneous Healing of Murine Anterior Cruciate Ligament
Authors: Saito Riku , Nakayama Kazuki , Usami Yuna , Enomoto Saaya , Nogi Koyo , Kokubun Takanori 
Published: June 2024

AbstractThe anterior cruciate ligament (ACL) has been recognized to have no spontaneous healing capacity after complete rupture due to an intra-articular environment. Meanwhile, our group reported that a completely ruptured ACL could heal spontaneously by restabilizing the femur-tibia joint. Several clinical studies have recently reported that ruptured ACL could heal spontaneously by controlling abnormal joint movement. Appropriate mechanical stimulation on the ruptured ACL promotes spontaneous healing, whereas excessive mechanical stress may inhibit the healing response. Here, we investigated how much braking force to control anterior tibial translation (ATT) affects the healing response of the ACL using two different braking forces for controlled ATT (CATT) models. Male and female C57BL/6 mice were ruptured ACL and randomly classified into Tight-CATT, Loose-CATT, and ACL-Rupture (ACL-R) groups. The Tight-CATT group showed a higher success rate of ACL healing than the Loose-CATT group at 4 and 8 weeks. However, collagen maturation and mechanical properties on healed ACL did not differ between the Tight-CATT and Loose-CATT groups. Our results suggested that tight ATT braking immediately after injury is essential for successfully healing the completely ruptured ACL. On the other hand, tightly ATT in the early healing phase was insufficient to improve mechanical strength and collagen maturation. Therefore, we should control mechanical stress tightly in the early phase of ACL spontaneous healing, and it would be necessary to apply higher mechanical stress in the later phases to achieve greater healing of the ACL.Study DesignA controlled laboratory study.