bluuebunny/crossref_metadata_2025_split huggingface dataset:
Metagenomic, metabolomic and sensorial characteristics of fermentedCoffea arabicaL. var. Castillo beans inoculated with microbial starter cultures
Authors: Madrid-Restrepo Maria A. , León-Inga Ana M. , Peñuela-Martínez Aida Esther , Cala Mónica P. , Reyes Alejandro 
Published: January 2025

ABSTRACTCoffee is one of the most important and widely consumed drinks around the world, and fermentation plays a pivotal role in shaping its quality. This research explores the impact of co-fermentation with “starter cultures” on the sensory and metabolic profiles, as well as in the microbial communities involved in coffee processing. Freshly harvested Arabica coffee beans were subjected to two wet-fermentation processes, where one was inoculated with a microbial starter culture and the other, spontaneous fermentation was allowed to occur. Quantitative descriptive analysis revealed that the inoculated coffee outperformed the spontaneous fermentation in all sensory attributes, boasting a higher sweetness, reduced acidity and bitterness, and presence of consumer-preferred notes. Untargeted metabolomic analysis identified over a hundred differential metabolites distinguishing both fermentation processes in green and roasted coffee beans. Inoculated coffee displayed elevated levels of compounds such as sucrose, mannitol, methyl phenylacetate, and organic acids like malic, citric, and quinic acid, compounds likely associated with a better sensory perception. The inoculated process featured abundant lactic acid bacteria andKazachstaniayeasts, which are linked to desirable metabolites like lactic, acetic, isobutyric, and hexanoic acids. Our results strongly suggest that the use of starter cultures can enhance coffee beverage quality as determined by standardized cupping and reflected by changes in the metabolic profile and microbial community structures. Future studies should focus on microbial identification and the association between species and resulting metabolic compounds, where specific bacterial and fungal groups could be isolated to be used as commercially available starter cultures for coffee fermentation.IMPORTANCEOur study demonstrates that inoculating coffee fermentation alters the sensory qualities of coffee and affects the dynamics of bacterial and fungal communities during this process. We identified specific changes in microbial diversity and associated metabolite profiles resulting from inoculation. Notably, we found that inoculation influences the metabolite composition of coffee beans and identified key compounds, such as aminophenol and phenol, which are likely linked to phenolic defects. This suggests that inoculation could serve as a tool to control cup defects by modifying the fermentation microbiota. Our findings advance the understanding of coffee fermentation and open opportunities for developing techniques to produce coffee with unique and desirable qualities.
CD4 T cell dysfunction is associated with bacterial recrudescence during chronic tuberculosis
Authors: Chang Evelyn , Cavallo Kelly , Behar Samuel M. 
Published: January 2025

AbstractWhile most people containMycobacterium tuberculosisinfection, some individuals develop active disease, usually within two years of infection. Why immunity fails after initially controlling infection is unknown. C57BL/6 mice controlMycobacterium tuberculosisfor up to a year but ultimately succumb to disease. We hypothesize that the development of CD4 T cell dysfunction permits bacterial recrudescence. We developed a reductionist model to assess antigen-specific T cells during chronic infection and found evidence of CD4 T cell senescence and exhaustion. In C57BL/6 mice, CD4 T cells upregulate coinhibitory receptors and lose effector cytokine production. Single cell RNAseq shows that only a small number of CD4 T cells in the lungs of chronically infected mice are polyfunctional. While the origin and causal relationship between T- cell dysfunction and recrudescence remains uncertain, we propose T cell dysfunction leads to a feed-forward loop that causes increased bacillary numbers, greater T cell dysfunction, and progressive disease.
Dual Probe Ligation In Situ Hybridization with Rolling-Circle Amplification for High-Plex Spatial Transcriptomics
Authors: Maguire Sarah E. , Credle Joel , Bertelson Elizabeth M.W. , Lee Sunny , Cha Boyoung , Xie Dan , Kirk Greg , Ray Debjit , George Logan , Suru Aditya , Maalouf Alexandre , Ikenaga Chiseko , Lloyd Thomas , Llosa Nicolas J. , Larman H. Benjamin 
Published: January 2025

ABSTRACTNew biological insights are increasingly dependent upon a deeper understanding of tissue architectures. Critical to such studies are spatial transcriptomics technologies, especially those amenable to analysis of the most widely available human tissue type, formalin-fixed and paraffin-embedded (FFPE) clinical specimens. Here we build on our previous oligonucleotide probe ligation-based approach to accurately analyze FFPE mRNA, which suffers from variable levels of degradation. LigationIn SituHybridization followed by rolling circle amplification (LISH-Lock’n’Roll or LISH-LnR), provides a streamlined method to detect the spatial location of specific mRNA isoforms within FFPE tissue architectures. Iterative fluorescent probe hybridization and imaging enables highly multiplexed spatial transcriptomic studies, as demonstrated herein for fixed specimens from inclusion body myositis patients and pediatric rhabdomyosarcoma patients. We additionally demonstrate a system of molecular rheostats that can be used to fine tune the performance of the LISH-LnR assay. Combined with LISH-seq and LISH-QC, the LISH-LnR methodology provides a powerful approach to spatial transcriptomics.
Smooth Muscle Cells and Fibroblasts in the Proximal Thoracic Aorta Exhibit Minor Differences Between Embryonic Origins in Angiotensin II-driven Transcriptional Alterations
Authors: Ito Sohei , Graf David B. , Katsumata Yuriko , Moorleghen Jessica J. , Zhang Chen , Li Yanming , LeMaire Scott A. , Shen Ying H. , Lu Hong S. , Daugherty Alan , Sawada Hisashi 
Published: January 2025

ABSTRACTBackgroundThoracic aortopathy is influenced by angiotensin II (AngII) and exhibits regional heterogeneity with the proximal region of the thoracic aorta being susceptible. Smooth muscle cells (SMCs) and selected fibroblasts in this region are derived from two embryonic origins: second heart field (SHF) and cardiac neural crest (CNC). While our previous study revealed a critical role of SHF-derived cells in AngII-mediated aortopathy formation, the contribution of CNC-derived cells remains unclear.MethodsMef2c-Cre R26RmT/mGmice were infused with AngII (1,000 ng/kg/min). Proximal thoracic aortas were harvested at baseline or after 3 days of infusion, representing the prepathological phase. Cells were sorted by origins using mGFP (SHF-derived) and mTomato (other origins, nSHF-derived) signals, respectively. After sorting cells by origin, single-cell RNA sequencing was performed and analyzed.ResultsShort-term AngII infusion induced significant transcriptomic changes in both SHF- and nSHF-derived SMCs, but differences between origins were modest. Fibroblast transcriptomes also underwent notable changes by AngII infusion, but differences between SHF and nSHF origins remained modest. Interestingly, AngII infusion resulted in the emergence of a new fibroblast sub-population. Several molecules related to the extracellular matrix, such asElnandCol3a1, were downregulated in SHF-derived fibroblasts compared to nSHF-derived fibroblasts in the new subcluster.ConclusionFibroblasts in the new subcluster exhibited lineage-specific differences in extracellular matrix-related genes; however, overall transcriptomic differences between origins in SMCs and fibroblasts in response to AngII were modest in the pre-pathological phase of AngII-induced thoracic aortopathy.GRAPHIC ABSTRACT
The fractionation dependence of tumor control in proton therapy for early-stage non-small cell lung cancer
Authors: Jeong Jeho , Taasti Vicki T. , Jackson Andrew , Gouw Zeno A. R. , Simone Charles B. , Lambin Philippe , Deasy Joseph O. 
Published: January 2025

AbstractPurposeThe relative biological effectiveness (RBE) of tumor control for proton beam therapy (PBT) compared to photon radiotherapy (RT) is typically assumed to be independent of fractionation. To test this, we modeled published PBT outcome results for early-stage non-small cell lung cancer (NSCLC) treatments across a range of fractionation schedules.Materials and MethodsAll published and analyzable cohorts were included (399 patients, 413 treated lesions). Two models were used to fit the data: a previously published tumor simulation model that fits photon RT results of NSCLC across all fractionation regimes and the Fowler LQ model with a kick-off time term. The treatment effect of each cohort was referenced to the photon equivalent dose through mechanistic model simulations in a 2 Gy/weekday scenario, with radiobiological parameters determined to simultaneously best-fit all fractionation results. The tumor control RBE of each published treatment schedule, compared to the modeled photon RT effect of the same schedule, was then estimated.ResultsFor cohorts whose treatments lasted less than three weeks (i.e., 12 fractions or less), the RBE of PBT was in the range of 1.08 to 1.11. However, for fractionated treatments stretching over four weeks or more (20-25 fractions), the relative effectiveness was much lower, with RBEs in the range of 0.82-0.89. This conclusion was unchanged using the simpler Fowler LQ + time model.ConclusionsThe proton RBE for hypo-fractionated schedules was 20-30% higher than for conventional schedules. The derived radiobiological parameters of PBT differ significantly from those of photon RT, indicating that PBT is influenced differentially by radiobiological mechanisms which require further investigation.
Experimental wildflower additions increase pollination in urban agroecosystems
Authors: Ellis Emilie E. , Edmondson Jill L. , Campbell Stuart A. 
Published: January 2025

SummaryThe addition of nectar-rich flower patches in human-modified ecosystems is a common practice to mitigate pollinator declines and boost pollination. However, the benefits of these additions for pollinator communities and pollination services are rarely tested, especially in urban environments.In a city-scale experiment we added floral resources to urban allotments and monitored the effects on bees, hoverflies and moths, and tested for improved seed set in a model crop (tomato,Solanum lycopersicum).The addition of wildflowers did not benefit all insect communities. Only social bee abundance (BombusandApis) benefitted from increasing floral resource area whereas other insect taxa showed no changes in abundance potentially due to the divergence in foraging patterns of moths, hoverflies, social bees and solitary bees. The addition of wildflower patches enhanced pollination by supporting a 25.3% increase in tomato seed set, providing evidence that wildflower interventions can improve urban pollination. Seed set was higher in more urban sites, suggesting an “oasis effect” where pollinating insects are concentrated into limited greenspaces. This highlights the precarity of pollination services in highly urban areas.Our results suggest that the practice of planting wildflower patches can positively affect pollination services in urban areas. The continued promotion of flower patch addition is likely to benefit some key insect taxa, however, the common wildflower species in seed mixes may not benefit hoverflies and moths compared to bees. The taxon-specific foraging patterns we observed should inform the design and development of pollinator-friendly wildflower seed mixes.Societal impact statementEnhancing urban greenspaces for pollinator communities by planting wildflower patches is increasingly common, but their efficacy for different groups of insects (bees, hoverflies and moths) is unclear. Our city-scale experiment demonstrated that wildflower patches benefitted the abundance of social bees, but did not increase other groups. Wildflower addition increased pollination services, with an increase in seed-set in our model crop, particularly in more urban areas. Wildflower patches do benefit pollinator communities and in turn humans, through the pollination services, but the species mix may not benefit some insect groups. This suggests there is potential to improve the benefit provided by wildflower patches by redesigning pollinator-friendly seed mixes.
Interplay between high-energy quenching and state transitions inChlamydomonas reinhardtii: a single-cell approach
Authors: Lahlou Aliénor , Orlando Marcelo , Bujaldon Sandrine , Gaultier William , Israelievitch Eliora , Hanappe Peter , Le Saux Thomas , Jullien Ludovic , Colliaux David , Bailleul Benjamin 
Published: January 2025

AbstractStudying cell-to-cell heterogeneity is essential to understand how unicellular organisms respond to stresses. Here, we combine single-cell measurements of chlorophyllafluorescence with machine learning to study light stress responses in the model green algaChlamydomonas reinhardtii. This framework allows us to score the extent of three high-light responses at the single cell level – state transitions, high-energy quenching, and photoinhibition – and reveals significant cell-to-cell response heterogeneity. The unexpectedly strong correlation between state transitions and high-energy quenching also indicates a cellular control over the relative extent of these processes that cannot be detected by bulk measurements. Accordingly, new models were derived for the coordinated functional response to light stress inChlamydomonas. The improved phenotypic characterization allowed by this approach will facilitate the identification of genetic determinants of intercellular heterogeneity through single cell–omics and isolation of cells displaying traits of interest for biotechnology.TeaserScoring of NPQ components in single cells algae unveils the general orchestration of high light photosynthetic responses.
Unsupervised learning reveals rapid gait adaption after leg loss and regrowth in spiders
Authors: Kane Suzanne Amador , Quinn Brooke L. , Wu Xuanyi Kris , Xi Sarah Y. , Ochs Michael F. , Hsieh S. Tonia 
Published: January 2025

AbstractMany arthropods and some vertebrates can voluntarily lose (autotomize) limbs during antagonistic encounters, and some can regenerate functional replacements. Spiders in particular frequently autotomize one or more legs. In this study, we investigated the time course of locomotor recovery after leg loss and regeneration in juvenile tarantulas (Arachnida: Araneae) with no prior experience of autotomy. We recorded high-speed video of spiders running with all legs intact, then immediately after, and again one day after, they autotomized two legs. The legs were allowed to regenerate, and the same sequence of experiments repeated. Running performance, posture, and path tortuosity were measured from video tracking. Spiders were found to resume their pre-autotomy speed and stride frequency after leg regeneration and in ≤1 day after both autotomies; furthermore, path tortuosity was unaffected by these treatments. They adjusted their posture to compensate for missing legs, spreading their remaining legs and running with their bodies rotated 11-15 deg from their velocity. To analyze gaits, we applied unsupervised machine learning for the first time to measured kinematic data in combination with gait space metrics. Spiders were found to robustly adopt new gait patterns immediately after losing legs, with no evidence of learning. This novel clustering approach both demonstrated concordance with previously-hypothesized gaits and revealed transitions between and variations within these patterns. More generally, clustering in gait space enables the identification of patterns of leg motions in large datasets that correspond to either known gaits or undiscovered behaviors.
Impact of missing data correlated with labels to be predicted in neurodegeneration classification tasks
Authors: Prakash Mithilesh , Tohka Jussi ,   Alzheimer’s Disease Neuroimaging Initiative
Published: January 2025

AbstractWe introduce a new subtype of ‘Missing Not at Random’ (MNAR) data, where the missingness is correlated with the labels (y) to be predicted, termed(y)-dependent MNAR. We demonstrate that this subtype can significantly bias the estimation of performance metrics in typical machine learning tasks. Unbiased error estimation is crucial in predictive modeling to accurately assess model performance, identify potential biases, and ensure generalizability to new, unseen data.We explore the effects of imputing this new subtype of MNAR and compare it with general missing types, namely Missing at Random (MAR) and Missing Completely at Random (MCAR). Our comparison analysis employs both synthetic and clinical datasets, including the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset, the Parkinson’s Progression Markers Initiative (PPMI) dataset, and the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s Disease (A4) dataset. After introducing missingness into the datasets, we trained different classifiers paired with various imputation methods and measured repeated cross-validation test metrics.Our findings reveal that datasets with non-ignorable missing types (MNAR) exhibit a strong bias compared to ignorable types (MAR and MCAR) in downstream analysis. Non-linear classifiers tend to exploit patterns from imputed data, particularly when the imputed values correlate with the target label (y), which can lead to unreliable estimation of the generalization error. Mean and median imputations proved to be more robust than tree-based or gradient boosting methods.
Exploring Antibiotic Resistance in Diverse Homologs of the Dihydrofolate Reductase Protein Family through Broad Mutational Scanning
Authors: Romanowicz Karl J. , Resnick Carmen , Hinton Samuel R. , Plesa Calin 
Published: January 2025

AbstractCurrent antibiotic resistance studies often focus on individual protein variants, neglecting broader protein family dynamics. Dihydrofolate reductase (DHFR), a key antibiotic target, has been extensively studied using deep mutational scanning, yet resistance mechanisms across this diverse protein family remain poorly understood. Using DropSynth, a scalable gene synthesis platform, we designed a library of 1,536 synthetic DHFR homologs representing 778 species of bacteria, archaea, and viruses, including clinically relevant pathogens. A multiplexedin vivoassay tested their ability to restore metabolic function and confer trimethoprim resistance in anE. coliΔfolAstrain. Over half of the synthetic homologs rescued the phenotype without supplementation, and mutants with up to five amino acid substitutions increased the rescue rate to 90%, highlighting DHFR’s evolutionary resilience. Broad Mutational Scanning (BMS) of homologs and 100,000 mutants provided critical insights into DHFR’s fitness landscape and resistance pathways, representing the most extensive analysis of homolog complementation and inhibitor tolerance to date and advancing our understanding of antibiotic resistance mechanisms.Graphical AbstractTeaserDropSynth technology enables scalable and cost-effective exploration of antibiotic resistance across the DHFR protein family.
Nucleoporins shape germ granule architecture and balance small RNA silencing pathways
Authors: Shi Kun , Zhang Ying , Du Zhenzhen , Liu Symonne C , Fan Xinyu , Lee Heng-Chi , Zhang Donglei 
Published: January 2025

SUMMARYAnimals have evolved distinct small RNA pathways, including piRNA and siRNA, to silence invasive and selfish nucleic acids. piRNA pathway factors are concentrated in perinuclear germ granules that frequently associate with nuclear pore complexes (NPCs). However, the factors mediating germ granule-NPC association and the functional relevance of such association remain unknown. Here we show that the conserved nucleoporins NPP-14 (NUP-214) and NPP-24 (NUP-88), components of the cytoplasmic filaments of NPC, play critical roles in anchoring germ granule to NPC and in attenuating piRNA silencing InC. elegans. Proximity labeling experiments further identified EPS-1 (enhanced piRNA silencing) as a key germ granule factor contributing to germ granule-NPC interaction. Innpp-14,npp-24,oreps-1mutant animals, we observed fewer but enlarged, unorganized germ granules, accompanied by the over-amplification of secondary small RNAs at piRNA targeting sites. Nonetheless, we found this enhancement of piRNA silencing comes at the cost of dampened RNAi efficiency and RNAi inheritance. Together, our studies uncovered factors contributing to germ granule-NPC association and underscored the importance of spatial organization of germ granules in balancing small RNA silencing pathways.
Gating of hair cell Ca2+channels governs the activity of cochlear neurons
Authors: Karagulyan Nare , Thirumalai Anupriya , Michanski Susann , Qi Yumeng , Fang Qinghua , Wang Haoyu , Ortner Nadine J. , Striessnig Jörg , Strenzke Nicola , Wichmann Carolin , Hua Yunfeng , Moser Tobias 
Published: January 2025

AbstractOur sense of hearing processes sound intensities spanning six orders of magnitude. In the ear, postsynaptic spiral ganglion neurons (SGNs) tile this intensity range with their firing rate codes. Presynaptic inner hair cells (IHCs) vary Ca2+-influx among their active zones (AZs) diversifying glutamate release and likely contributing to SGN firing diversity. Here we show that low-voltage activation of IHC-Ca2+-influx of mice, modeling the human CaV1.3A749Gmutation, increases spontaneous SGN-firing and lowers sound threshold. Altered synaptic morphology in CaV1.3A749G/A749Gmice already at ambient sound levels of standard mouse husbandry indicates a risk for noise-induced alterations in CaV1.3A749Gpatients. We conclude that heterogeneous voltage-dependence of CaV1.3 activation among IHC-AZs contributes to the diversity of SGN firing for sound intensity coding and synaptic vulnerability.
Deep learning models for unbiased sequence-based PPI prediction plateau at an accuracy of 0.65
Authors: Reim Timo , Hartebrodt Anne , Blumenthal David B. , Bernett Judith , List Markus 
Published: January 2025

AbstractAs most proteins interact with other proteins to perform their respective functions, methods to computationally predict these interactions have been developed. However, flawed evaluation schemes and data leakage in test sets have obscured the fact that sequence-based protein-protein interaction (PPI) prediction is still an open problem. Recently, methods achieving better-than-random performance on leakage-free PPI data have been proposed. Here, we show that the use of ESM-2 protein embeddings explains this performance gain irrespective of model architecture. We compared the performance of models with varying complexity, per-protein, and per-token embeddings, as well as the influence of self- or cross-attention, where all models plateaued at an accuracy of 0.65. Moreover, we show that the tested sequence-based models cannot implicitly learn a contact map as an intermediate layer. These results imply that other input types, such as structure, might be necessary for producing reliable PPI predictions.