bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine learning-based mortality prediction models for non-alcoholic fatty liver disease in the general United States population
Authors: Zheng Jia-Rui , Wang Zi-Long , Feng Bo 
Published: July 2024

Background & AimsNowadays, the global prevalence of non-alcoholic fatty liver disease (NAFLD) has reached about 25%, which is the most common chronic liver disease worldwide, and the mortality risk of NAFLD patients is higher. Our research created five machine learning (ML) models for predicting overall mortality in ultrasound-proven NAFLD patients and compared their performance with conventional non-invasive scoring systems, aiming to find a generalizable and valuable model for early mortality prediction in NAFLD patients.MethodsNational Health and Nutrition Examination Survey (NHANES)-III from 1988 to 1994 and NHANES-III related mortality data from 2019 were used. 70% of subjects were separated into the training set (N = 2262) for development, while 30% were in the testing set (N= 971) for validation. The outcome was all-cause death at the end of follow-up. Twenty-nine related variables were trained as predictor features for five ML–based models: Logistic regression (LR), K-nearest neighbors (KNN), Gradient-boosted decision tree (XGBoost), Random forest (RF) and Decision tree. Five typical evaluation indexes including area under the curve (AUC), F1 score, accuracy, sensitivity and specificity were used to measure the prediction performance.Results3233 patients with NAFLD in total were eligible for the inclusion criteria, with 1231 death during the average 25.3 years follow up time. AUC of the LR model in predicting the mortality of NAFLD was 0.888 (95% confidence interval [CI] 0.867-0.909), the accuracy was 0.808, the sensitivity was 0.819, the specificity was 0.802, and the F1 score was 0.765, which showed the best performance compared with other models (AUC were: RF, 0.876 [95%CI 0.852-0.897]; XGBoost, 0.875 [95%CI 0.853-0.898]; Decision tree, 0.793 [95%CI 0.766-0.819] and KNN, 0.787 [95%CI 0.759-0.816]) and conventional clinical scores (AUC were: Fibrosis-4 Score (FIB-4), 0.793 [95%CI 0.777-0.809]; NAFLD fibrosis score (NFS), 0.770 [95%CI 0.753-0.787] and aspartate aminotransferase-to-platelet ratio index (APRI), 0.522 [95%CI 0.502-0.543]).ConclusionsML–based models, especially LR model, had better discrimination performance in predicting all-cause mortality in patients with NAFLD compared to the conventional non-invasive scores, and an interpretable model like Decision tree, which only used three predictors: age, systolic pressure and glycated hemoglobin, is simple to use in clinical practice.
Coordinated Response Modulations Enable Flexible Use of Visual Information
Authors: Srinath Ramanujan , Czarnik Martyna M. , Cohen Marlene R. 
Published: July 2024

AbstractWe use sensory information in remarkably flexible ways. We can generalize by ignoring task-irrelevant features, report different features of a stimulus, and use different actions to report a perceptual judgment. These forms of flexible behavior are associated with small modulations of the responses of sensory neurons. While the existence of these response modulations is indisputable, efforts to understand their function have been largely relegated to theory, where they have been posited to change information coding or enable downstream neurons to read out different visual and cognitive information using flexible weights. Here, we tested these ideas using a rich, flexible behavioral paradigm, multi-neuron, multi-area recordings in primary visual cortex (V1) and mid-level visual area V4. We discovered that those response modulations in V4 (but not V1) contain the ingredients necessary to enable flexible behavior, but not via those previously hypothesized mechanisms. Instead, we demonstrated that these response modulations are precisely coordinated across the population such that downstream neurons have ready access to the correct information to flexibly guide behavior without making changes to information coding or synapses. Our results suggest a novel computational role for task-dependent response modulations: they enable flexible behavior by changing the information that gets out of a sensory area, not by changing information coding within it.SignificanceNatural perceptual judgments are continuous, generalized, and flexible. We estimate the ripeness of a piece of fruit on a continuous scale, we generalize by judging the ripeness of either a mango or an avocado even though they look very different, we flexibly judge either the size or the ripeness of the same piece of fruit, and we can flexibly indicate the same perceptual judgment using a variety of behaviors such as by speaking or writing any of many languages. Here, we show that the response modulations in visual cortex long associated with cognitive processes, surround modulation, or motor planning are sufficient to guide all these aspects of natural perceptual decision-making. We find that across the population, these response modulations reorient and reformat visual representations so that the relevant information is used to guide behavior via communication with downstream neurons. Our results are an example of a general computational principle for flexible behavior that emerges from the coordinated activity of large populations of neurons.
Flower visitation through the lens: Exploring the foraging behaviour ofBombus terrestriswith a computer vision-based application
Authors: Varga-Szilay Zsófia , Szövényi Gergely , Pozsgai Gábor 
Published: July 2024

AbstractTo understand the processes behind pollinator declines, and thus to maintain pollination efficiency, we also have to understand fundamental drivers influencing pollinator behaviour. In this study, we aim to explore the foraging behaviour of wild bumblebees, recognizing its importance from economic and conservation perspectives. We recordedBombus terrestrisonLotus creticus,Persicaria capitata, andTrifolium pratensepatches in five-minute-long slots in urban areas of Terceira (Azores, Portugal). For the automated bumblebee detection, we created computer vision models based on a deep learning algorithm, with custom datasets. We achieved high F1 scores of 0.88 forLotusandPersicaria, and 0.95 forTrifolium, indicating accurate bumblebee detection. We found that flower cover per cent, but not plant species, influenced the attractiveness of flower patches, with a significant positive effect. There were no differences between plant species in the attractiveness of the flower heads. The handling time was longer on the large-headedTrifoliumthan those on the smaller-headedLotusandPersicaria. However, our result did not indicate significant differences in the time bumblebees spent on flowers among the three plant species. Here, we also justify computer vision-based analysis as a reliable tool for studying pollinator behavioural ecology.
H105A peptide eye drops promote photoreceptor survival in murine and human models of retinal degeneration
Authors: Bernardo-Colón Alexandra , Bighinati Andrea , Parween Shama , Debnath Subrata , Piano Ilaria , Adani Elisa , Corsi Francesca , Gargini Claudia , Vergara Natalia , Marigo Valeria , Becerra S. Patricia 
Published: July 2024

AbstractPhotoreceptor death causes blinding inheritable retinal diseases, such as retinitis pigmentosa (RP). As disease progression often outpaces therapeutic advances, finding effective treatments is urgent. This study focuses on developing a targeted approach by evaluating the efficacy of small peptides derived from pigment epithelium-derived factor (PEDF), known to restrict common cell death pathways associated with retinal diseases. Peptides with affinity for the PEDF receptor, PEDF-R, (17-mer and H105A) delivered via eye drops reached the retina, efficiently promoted photoreceptor survival, and improved retinal function in RP mouse models based on both therd10mutation and the rhodopsin P23H mutation. Additionally, intravitreal delivery of AAV-H105A vectors delayed photoreceptor degeneration in the latter RP mouse model. Furthermore, peptide H105A specifically prevented photoreceptor death induced by oxidative stress, a contributing factor to RP progression, in human retinal organoids. This promising approach for peptide eye drop delivery holds significant potential as a therapeutic for preventing photoreceptor death in retinal disorders, offering a high safety profile, low invasiveness and multiple delivery options.One Sentence SummaryNeurotrophic PEDF peptides delivered as eye drops preserve photoreceptor viability, morphology, and function in models of human retinal diseases.
Physical Exercise Improves Working Memory through Ripple-Spindle Coupling
Authors: Che Xinyun , Auer Benedikt , Schmid Paul , Reichert Christoph , Scholz Annemarie , Weischner Tom , Knight Robert T. , Dürschmid Stefan 
Published: July 2024

AbstractSpindle-ripple coupling enhances memory consolidation during sleep. Ripples, representing the compressed reactivation of environmental information, provide a mechanism for retaining memory information in chronological order and are also crucial for working memory (WM) during wakefulness. Brief sessions of physical exercise (PE) are proposed to boost WM. In concurrent EEG/MEG sessions, we investigated the role of PE in WM performance and high-frequency-ripple to spindle coupling. Ripples, identified in MEG sensors covering the medial temporal lobe (MTL) region, predicted individual WM performance. Ripples were locked to robust oscillatory patterns in the EEG defined spindle band. Spindle activity and ripples decrease during initial stimulus presentation and rebound after 1 sec. Behaviorally, PE enhanced WM performance. Neurophysiologically, PE scaled the ripple rate with the number of items to be kept in WM and strengthened the coupling between ripple events and spindle oscillations. These findings reveal that PE enhances WM by coordinating ripple-spindle interaction.
Preclinical validation and kinetic modelling of the SV2A PET ligand [18F]UCB-J in mice
Authors: Everix Liesbeth , Elvas Filipe , Menchaca Alan Miranda , Khetarpal Vinod , Liu Longbin , Bard Jonathan , Staelens Steven , Bertoglio Daniele 
Published: July 2024

ABSTRACTSynaptic vesicle protein 2A (SV2A) is ubiquitously expressed in presynaptic terminals where it functions as a neurotransmission regulator protein. Synaptopathy has been reported during healthy ageing and in a variety of neurodegenerative diseases. Positron emission tomography (PET) imaging of SV2A can be used to evaluate synaptic density. The PET ligand [11C]UCB-J has high binding affinity and selectivity for SV2A but has a short physical half-life due to the11C isotope. Here we report the characterization and validation of its18F-labeled equivalent, [18F]UCB-J, in terms of specificity, reproducibility and stability in C57BL/6J mice. Plasma analysis revealed at least one polar radiometabolite. Kinetic modelling was performed using a population-based metabolite corrected image-derived input function (IDIF). [18F]UCB-J showed relatively fast kinetics and a reliable measure of the IDIF-based volume of distribution (VT(IDIF)). [18F]UCB-J specificity for SV2A was confirmed through a levetiracetam blocking assay (50 to 200 mg/kg). Reproducibility of theVT(IDIF)was determined through test-retest analysis, revealing significant correlation (r2=0.773,p<0.0001). Time-stability analyses indicate a scan duration of 60 min to be sufficient to obtain a reliableVT(IDIF). In conclusion, [18F]UCB-J is a selective SV2A ligand with optimal kinetics in mice. Further investigation is warranted for (pre)clinical applicability of [18F]UCB-J in synaptopathies.
The Microbiota of Moon Snail Egg Collars is Shaped by Host-Specific Factors
Authors: Piedl Karla , Aylward Frank O. , Mevers Emily 
Published: July 2024

ABSTRACTMoon Snails lay eggs using a mixture of mucus and sediment to form an egg mass commonly referred to as an egg collar. These collars do not appear to experience micro-biofouling or predation and this observation led us to hypothesize that the egg collars possess a chemically-rich microbiota that protect the egg collars from pathogens. Herein, we sought to gain an understanding of the bacterial composition of the egg collars by amplifying and sequencing the 16S rRNA gene from egg collar and sediment samples collected at four distinct geographical regions in SW Florida. Relative abundance and non-metric multidimensional scaling plots revealed distinct differences in the bacterial composition between the egg collar and sediment samples. In addition, the egg collars had a lower α-diversity than the sediment, with specific genera being significantly enriched in the egg collars. Analysis of microorganisms consistent across two seasons suggests thatFlavobacteriaceaemake up a large portion of the core microbiota (36 – 58% of 16S sequences). We also investigated the natural product potential of the egg collar microbiota by sequencing a core biosynthetic gene, the adenylation domains (AD), within the gene clusters of non-ribosomal peptide synthetase (NRPS). AD sequences matched multiple modules within known bioactive NRPs biosynthetic gene clusters, suggesting production is possible within the egg collar system and lays the foundation for future studies into the chemical and ecological role of this microbiota.IMPORTANCEAnimals commonly partner with microorganisms to accomplish essential tasks, including chemically defending the animal host from predation and/or infections. Understanding animal-microbe partnerships and the molecules used by the microbe to defend the animals from pathogens or predation have the potential to lead to new pharmaceutical agents. However, very few of these systems have been investigated. A particularly interesting system are nutrient rich marine egg collars, which often lack visible protections, and are hypothesized to harbor beneficial microbes that protect the eggs. In this study, we gained an understanding of the bacterial strains that form the core microbiota of Moon Snail egg collars and gained a preliminary understanding of their natural product potential. This work lays the foundation for future work to understand the ecological role of the core microbiome and to study the molecules involved in chemically defending the Moon Snail eggs.
Limited protection against early-life cytomegalovirus infection results from deficiency of cytotoxic CD8 T cells
Authors: Brito Luís Fonseca , Ostermann Eleonore , Perez Anna , Tödter Silvia , Virdi Sanamjeet , Indenbirken Daniela , Glau Laura , Gieras Anna , Brixel Renke , Arens Ramon , Grundhoff Adam , Arck Petra , Diemert Anke , Tolosa Eva , Brune Wolfram , Stahl Felix Rolf 
Published: July 2024

SummaryDifferential antiviral T cell immunity in early life impacts the clinical outcome of Cytomegalovirus (CMV) infection, but the underlying mechanisms are not well understood. Here, we found delayed enrichment of early-life murine CMV-specific CD8 T cells due to a general deficiency of αβ T cells. Adoptive transfer of naïve adult T cells into neonates did not protect due to a blockade of CD8 but not of CD4 effector T cell differentiation. Early-life deficiency of critical signal 3 cytokines during T cell priming resulted in the appearance of non-cytotoxic CD8 effector T cells whereas the effector phase of adult-primed T cells was not disrupted in neonates. Accordingly, we found an overall low number of antiviral human CD8 T cells in newborns with congenital CMV. Together, this study suggests defective CD8 T cell immunity as an important factor explaining the higher risk for CMV disease in the early-life phase.
Diverse Genomic Embedding Benchmark for functional evaluation across the tree of life
Authors: West-Roberts Jacob , Kravitz Joshua , Jha Nishant , Cornman Andre , Hwang Yunha 
Published: July 2024

AbstractBiological foundation models hold significant promise for deciphering complex biological functions. However, evaluating their performance on functional tasks remains challenging due to the lack of standardized benchmarks encompassing diverse sequences and functions. Existing functional annotations are often scarce, biased, and susceptible to train-test leakage, hindering robust evaluation. Furthermore, biological functions manifest at multiple scales, from individual residues to large genomic segments. To address these limitations, we introduce the Diverse Genomic Embedding Benchmark (DGEB), inspired by natural language embedding benchmarks. DGEB comprises six embedding tasks across 18 expert curated datasets, spanning sequences from all domains of life and encompassing both nucleic acid and amino acid modalities. Notably, four datasets enable direct comparison between models trained on different modalities. Benchmarking protein and genomic language models (pLMs and gLMs) on DGEB reveals performance saturation with model scaling on numerous tasks, especially on those with underrepresented sequences (e.g. Archaea). This highlights the limitations of existing modeling objectives and training data distributions for capturing diverse biological functions. DGEB is available as an open-source package with a public leaderboard athttps://github.com/TattaBio/DGEB.
Welcome to Hotel Hymenoptera: monitoring cavity-nesting bee and wasp distribution and their trophic interactions using community science and metabarcoding
Authors: Handler Sage , Coveny Katerina , Braukmann Thomas , Raine Nigel E. , Steinke Dirk 
Published: July 2024

AbstractEssential ecosystem services are provided by many interactions, including plant-pollinator, predator-prey, and host-parasitoid. These services support food and natural systems through pollination and pest control, however they are challenging to qualify, and previous observational studies may underestimate their complexity. The cavity nesting Hymenoptera are a good example showing all these three interactions and they can be monitored using trap nests. For this study, trap nests were installed at schools across Canada by community scientists to investigate cavity-nesting bee and wasp distributions and interactions. DNA metabarcoding was used to identify the occupants and their food sources. New bee and wasp distributions were found that might be the result of previous under-sampling or recent range expansions. Detailed bipartite and tripartite networks describing species interactions suggest some novel bee, wasp, and parasite associations. These results encourage further investigation into these interactions using molecular methods as detailed range maps and networks provide information to natural historians and conservationists alike.
Metacollinia emscherin. sp., a novel sanguicolous apostome ciliate of freshwater amphipods (Gammarusspp.)
Authors: Prati Sebastian , Rückert Sonja , Grabner Daniel S. , Sures Bernd , Bojko Jamie 
Published: July 2024

AbstractWe describe a novel sanguicolous parasitic ciliate,Metacollinia emscherin. sp., found in the freshwater amphipodsGammarus pulexandG. fossarum. This ciliate infected up to 20% of the amphipods collected in a German stream catchment, the Boye, a tributary of the river Emscher. The ciliate showed morphological characteristics fitting the genusMetacollinia. Different life stages of variable size occurred simultaneously in the hemocoel throughout the hosts’ body. The tomont had 40-47 slightly spiraled kineties, a non-ciliated cortical band, a large macronucleus, and contractile vacuoles arranged in rows or scattered throughout the cytoplasm. The protomites/tomites with nine somatic kineties presented evidence of the buccal kineties x, y, and z reminiscent of those of the order Foettingeriida. Phylogenetic analyses of the 18S rRNA and COI regions confirm the ciliate placement in the Collinidae and a close relatedness to the type species of the genusMetacollinia,Metacollinia lucensis.We formally describe this new parasite asMetacollinia emscherin. sp. using pathological, morphological, and nuclear/mitochondrial genetic data. The systemic infections observed in histological preparations and the pathogenicity ofMetacollinia emscherin. sp. suggest that this parasite might influence host population dynamics. Given the ecological importance of amphipods as keystone species in freshwater ecosystems, an outbreak of this parasite might indirectly impact ecosystem functioning.
Forecasting the Effects of Global Change on a Bee Biodiversity Hotspot
Authors: Buckner Mark A. , Hoge Steven T. , Danforth Bryan N. 
Published: July 2024

AbstractThe Mojave and Sonoran Deserts, recognized as a global hotspot for bee biodiversity, are experiencing habitat degradation from urbanization, utility-scale solar energy (USSE) development, and climate change. In this study, we evaluated the current and future distribution of bee diversity in the region, assessed how protected areas safeguard bee species richness, and predicted how global change may affect bees across the region. Using Joint Species Distribution Models (JSDMs) of 148 bee species, we project changes in species distributions, occurrence area, and richness across the region under four global change scenarios between 1971 and 2050. We evaluated the threat posed by USSE development and predicted how climate change will affect the suitability of protected areas for conservation. Our findings indicate that changes in temperature and precipitation do not uniformly affect bee richness across the region. Protected areas in the Sonoran and Mojave Deserts are projected to experience mean losses of up to 5.8 species, whereas protected areas at higher elevations and transition zones may gain up to 7.8 species. Outside protected areas, bee diversity is threatened by urbanization and USSE development. Areas prioritized for future USSE development have an average species richness of 4.2 species higher than the study area average, and lower priority areas have 8.2 more species. USSE zones are expected to experience declines of 2.7 to 8.0 species by 2050 due to climate change alone. Despite the importance of solitary bees for pollination, their diversity is often overlooked in land management decisions. Our results show the utility of JSDMs for extending the usability of existing data-limited bee species records, easing the inclusion of these species in conservation and land management decision-making. The multiple threats from global change drivers underscore the importance of including ecologically vital, though often data-limited, species in land-use decisions.