Miracle-dz/UniFAR-FTUs huggingface dataset:
Visual stimuli modulate local field potentials but drive no high-frequency activity in human auditory cortex

Neuroimaging studies suggest cross-sensory visual influences in human auditory cortices. Whether these influences reflect active visual processing in human auditory cortices (ACs), which drives neuronal firing and concurrent broadband high-frequency activity (BHFA; >70 Hz), or whether they merely modulate sound processing is still debatable. Here, we presented auditory, visual, and audiovisual stimuli to 16 participants (7 women, 9 men) with stereo-EEG depth electrodes implanted near ACs for presurgical monitoring. Anatomically normalized group analyses were facilitated by inverse modeling of intracranial source currents. Analyses of intracranial event-related potentials (iERP) suggested cross-sensory responses to visual stimuli in ACs, which lagged the earliest auditory responses by several tens of milliseconds. Visual stimuli also modulated the phase of intrinsic low-frequency oscillations and triggered 15–30-Hz event-related desynchronization in ACs. However, BHFA, a putative correlate of neuronal firing, was not significantly increased in ACs after visual stimuli, not even when they coincided with auditory stimuli. Intracranial recordings demonstrate cross-sensory modulations, but no indication of active visual processing in human ACs. Significance Statement Visual information has a profound influence on auditory processing, particularly in noisy conditions. These “cross-sensory” influences start already in auditory cortices, the brain area that processes sound signals. It has, however, been unclear whether auditory cortex actively processes visual information or whether visual signals only change the way sounds are processed. We studied this question by neurophysiological recordings from 16 participants with epilepsy who had electrodes implanted in their brains due to medical reasons. Using these intracranial recordings, we show that cross-sensory visual information modulates sound processing but triggers no high-frequency activity -- a correlate of local neuronal firing -- in auditory cortex. This result provides important information on the role of sensory areas in multisensory processing in the human brain.
Leaf trichome diversity, acylsugar concentration, and their relationships to leaf area in Solanum galapagense

Glandular trichomes are physical and chemical barriers used by some tomato wild relatives to confer resistance against insect pests and diseases transmitted by them. Solanum galapagense has been identified as one of the potential sources of insect pest resistance. The present study aimed to examine the trichome diversity and acylsugar concentration of 26 accessions of S. galapagense along with one cultivated tomato (S. lycopersicum) and one cherry tomato (S. l. cerasiforme) cultivar. The results revealed large genetic variation among S. galapagense accessions for all studied traits. The S. galapagense accessions had significantly higher trichome types IV on the adaxial and abaxial surfaces of the leaf and greater acylsugar concentration but smaller leaflet area than cultivated tomato. The selected cherry tomato line represents greater trichome type IV and acylsugar than other groups. The acylsugar concentration was positively associated with trichome type IV but negatively associated with trichome type V on both leaf surfaces. Leaflet area was negatively associated with trichome IV density and acylsugar concentration. Analysis of DNA markers revealed the presence of two previously identified whitefly-resistance alleles in S. galapagense accessions. This study will support breeding programs aiming to improve insect pest resistance in tomato cultivars using crop wild relatives.
Predicting the unpredictable: heatwaves and history of variability shape phytoplankton community thermal responses within one generation

Predicting the effect of increased thermal unpredictability, for example in the shape of heatwaves on phytoplankton metabolic responses is ripe with challenges. While single genotypes in laboratory environments will respond to environmental fluctuations in predictable and repeatable ways, it is difficult to relate rapid evolutionary responses of whole communities to their ecological history. Previously experienced environments, including fluctuations therein, can shape an organism’s specific niche as well as their responses to further environmental changes. This is a testable hypothesis as long as samples can be obtained where the environmental history is known, sufficiently diverse, and not obscured by confounding parameters such as day length and precipitation patterns. Here, we tested immediate (i.e. within one generation) metabolic temperature responses of natural phytoplankton assemblages from two thermally distinct regions in the Baltic Sea: the warmer and less predictable Kiel Area, and the overall colder and more predictable Bornholm Basin. Our approach allows us to investigate effects on immediate physiological time scales (responses curves), ecological and evolutionary processes on longer time scales (seasonal differences between basins) as well as mid-term responses during a natural occurring heatwave. We found evidence for a higher degree of phenotypic plasticity in samples from unpredictable environments (Kiel Area).
Two major extinction events in the evolutionary history of turtles: one caused by a meteorite, the other by hominins

We live in a time of highly accelerated extinction, which has the potential to mirror past mass extinction events. However, the rarity of these events and the restructuring of diversity that they cause complicate direct comparisons between the current extinction crisis and earlier mass extinctions. Among animals, turtles (Testudinata) are one of few groups which both have a sufficient fossil record and a sufficiently stable ecological importance to enable meaningful comparisons between the end Cretaceous mass extinction and the ongoing extinction event. In this paper we analyze the fossil record of turtles and recover three significant peaks in extinction rate. Two of these are in the Cretaceous, the second of these took place at the Cretaceous–Paleogene transition (K-Pg), reflecting the overall patterns previously reported for many other taxa. The third major extinction event started in the Pliocene and continues until now. This peak only affected terrestrial turtles and started much earlier in Eurasia and Africa lineages than elsewhere. This suggests that it may be linked to co-occurring hominins rather than having been caused by global climate change.
Identification of Prognostic Biomarkers for Suppressing Tumorigenesis and Metastasis of Hepatocellular Carcinoma through Transcriptome Analysis

Cancer is one of the deadliest diseases developed through tumorigenesis and could be fatal if reached at metastatic phase. The novality of present investigation is to explore the prognostic biomarkers in hepatocellular carcinoma (HCC) that could develop glioblastoma multiforme (GBM) due to metastasis. The analysis was done using RNA-Seq datasets for both HCC (PRJNA494560 and PRJNA347513) and GBM (PRJNA494560 and PRJNA414787) from Gene Expression Omnibus (GEO). This study identified 13 hub genes found to be overexpressed in both GBM and HCC. Promoter methylation study showed these genes to be hypomethylated. Validation through genetic alteration and missense mutations resulted in chromosomal instability leading to improper chromosome segregation causing aneuploidy. A 13-gene predictive model was obtained and validated using KM plot. These hub genes could be prognostic biomarkers and potential therapeutic targets, inhibition of which could suppress tumorigenesis and metastasis.
Age-related Macular Degeneration is associated with faster rates of structural brain changes and widespread differences in connectivity

Age-related macular degeneration (AMD) is a prevalent disease impeding vision. More recently, AMD has also been linked to cognitive impairment, such as deficits in language and memory skills. In order to better understand the extent of AMD-related changes in the whole brain structure and connectivity, we have conducted an MRI diffusion acquisition study on 40 participants (20 diagnosed with AMD and 20 controls). These acquisitions were then performed again in a follow up two years later. We developed novel analysis methods for diffusion based tractography and connectomes to better determine which, if any, brain region connections saw the greatest changes between the AMD and the age-matched control groups. Using voxel-based analysis, we identified atrophy in AMD participants in the cuneate gyrus, which has been associated with vision, and the left superior temporal gyrus, which has been associated with language, while later acquisitions compounded this with a deficiency in the bilateral cingulate gyrus, itself linked to higher cognition and memory. These regional atrophy findings support that people with AMD experience widespread neuronal degradation that is not limited to retinal neurons. Regions that saw drastically lowered fractional anisotropy among AMD vs. control included the visual cortex, such as the bilateral occipital lobe and the frontoparietal cortex. Tensor Network Principal Component Analysis (TN-PCA) isolated lingual and temporal connections as important differentiators of AMD connectomes compared to controls, thus supporting our morphometric and texture findings in regions related to vision, but also connectopathies of language and memory brain regions. Bundle based analyses in baseline data revealed that the lingual gyrus had greater spread of tracts overall in the AMD participants, which may be explained by prior reorganization in this area, demonstrating a connection between retinal health and lingual structure. Moreover, we noted group differences in the interhemispheric temporal connections, and lingual cerebellar connections, supporting extensive downstream effects of vision loss. Our bundle-based analyses expand the toolset available for neuroimaging-based phenotyping, and reveal widespread changes in AMD participants beyond brain regions and tractography networks directly involved in vision processing, including those involved in language and memory.
Herbaceous production lost to tree encroachment in United States rangelands

Rangelands of the United States provide ecosystem services that benefit society and rural economies. Native tree encroachment is often overlooked as a primary threat to rangelands due to the slow pace of tree cover expansion and the positive public perception of trees. Still, tree encroachment fragments these landscapes and reduces herbaceous production, thereby threatening habitat quality for grassland wildlife and the economic sustainability of animal agriculture. Recent innovations in satellite remote sensing permit the tracking of tree encroachment and the corresponding impact on herbaceous production. We analyzed tree cover change and herbaceous production across the western United States from 1990 to 2019. We show that tree encroachment is widespread in U.S. rangelands; absolute tree cover has increased by 50% (77,323 km2) over 30 years, with more than 25% (684,852 km2) of U.S. rangeland area experiencing tree cover expansion. Since 1990, 302 ± 30 Tg of herbaceous biomass have been lost. Accounting for variability in livestock biomass utilization and forage value reveals that this lost production is valued at between $4.1 - $5.6 billion U.S. dollars. Synthesis and applications: The magnitude of impact of tree encroachment on rangeland loss is similar to conversion to cropland, another well-known and primary mechanism of rangeland loss in the U.S. Prioritizing conservation efforts to prevent tree encroachment can bolster ecosystem and economic sustainability, particularly among privately-owned lands threatened by land-use conversion.
Probabilistic integration of transcriptome-wide association studies and colocalization analysis prioritizes molecular pathways of complex traits

Transcriptome-wide association studies (TWAS) and colocalization analysis are complementary integrative genetic association approaches routinely used to identify functional units underlying complex traits in post-genome-wide association study (post-GWAS) analyses. Recent studies suggest that both approaches are individually imperfect, but joint usage can yield robust and powerful inference results. This paper introduces a new statistical framework, INTACT, to perform probabilistic integration of TWAS and colocalization evidence for implicating putative causal genes. This procedure is flexible and can work with a wide range of existing TWAS and colocalization approaches. It has the unique ability to quantify the uncertainty of implicated genes, enabling rigorous control of false-positive discoveries. Taking advantage of this highly-desirable feature, we describe an efficient algorithm, INTACT-GSE, for gene set enrichment analysis based on the integrated TWAS and colocalization analysis results. We examine the proposed computational methods and illustrate their improved performance over the existing approaches through simulation studies. Finally, we apply the proposed methods to the GTEx data and a variety of GWAS summary statistics derived from complex and molecular traits previously analyzed by Hukku et al. and Sinnott-Armstrong et al. We find empirical evidence that the proposed methods improve and complement existing putative gene implication methods and are advantageous in evaluating and identifying key gene sets and biological pathways.
Molecular dynamics study of phospholipid membrane electroporation induced by bipolar pulses with different intervals

In this study, PM-EP induced by bipolar pulses with different intervals was investigated by all-atom molecular dynamics simulation. Firstly, PM-EP was formed during the positive pulse of 2ns and 0.5V/nm, then the effects of various intervals of 0, 1, 5, 10ns on PM-EP evolution were investigated, and the dynamic changes of different degrees of PM-EP induced by following negative pulses of 2ns and 0.5V/nm were analyzed. The elimination of the PM-EP during the interval of bipolar pulses were determined and it was related to the degrees of PM-EP and the time of intervals, then the degrees of PM-EP at the end of the intervals were classified and quantitatively defined, namely, Resealing, Destabilizing and Retaining state. These three states appeared due to the combined effect of both the preceding positive pulse and the interval. Furthermore, the evolution of PM-EP in resealing state under negative pulses was similar to that of positive pulses as evidenced by EP formation time and degree of PM-EP, the destabilizing state had the same trends as the resealing state except that the re-electroporation of phospholipid membrane appeared faster and larger degree of EP obtained with the same pulse exposure time. Regarding the retaining state, the negative pulses enhanced PM-EP with more profound water bridges, which can be considered as the effect of electric field superposition. These results can improve our understanding of the fundamental mechanism of bipolar pulse-induced PM-EP. Graphical Abstract Highlights Quantitative and qualitative definition of the three states of the phospholipid membrane electroporation at the end of the intervals. Clarification that the states of phospholipid membrane electroporation were generated due to the combined effect of positive pulses and intervals. Quantitative and qualitative comparison the evolution of the states of phospholipid membrane electroporation during the negative pulses.
De novo discovery of traits co-occurring with chronic obstructive pulmonary disease

This paper integrates different levels of biological information to identify shared genetic and biological pathways underlying the diverse clinical presentations of COPD. Thus, it identifies a collection of genetic variants and genes that may aid COPD patient stratification and treatment. Chronic obstructive pulmonary disease (COPD) is a heterogeneous group of chronic lung conditions. Genome-wide association studies have identified single-nucleotide polymorphisms (SNPs) associated with COPD and the co-occurring conditions, suggesting common biological mechanisms underlying COPD and these co-occurring conditions. To identify them, we have integrated information across different biological levels (i.e., genetic variants, lung-specific 3D genome structure, gene expression and protein–protein interactions) to build lung-specific gene regulatory and protein–protein interaction networks. We have queried these networks using disease-associated SNPs for COPD, unipolar depression and coronary artery disease. COPD-associated SNPs can control genes involved in the regulation of lung or pulmonary function, asthma, brain region volumes, cortical surface area, depressed affect, neuroticism, Parkinson’s disease, white matter microstructure and smoking behaviour. We describe the regulatory connections, genes and biochemical pathways that underlay these co-occurring trait-SNP-gene associations. Collectively, our findings provide new avenues for the investigation of the underlying biology and diverse clinical presentations of COPD. In so doing, we identify a collection of genetic variants and genes that may aid COPD patient stratification and treatment.
Can single-neuron frequency tuning in human auditory cortex be quantified through fMRI adaptation?

Measuring neuronal frequency selectivity in human auditory cortex may be crucial for understanding common auditory deficits such as speech-in-noise difficulty. Non-invasive methods measure aggregate responses of large populations of neurons and therefore overestimate single-neuron tuning selectivity. Here we explore whether cortical frequency selectivity can be estimated through fMRI adaptation. Using ultra-high-field (7T) BOLD-fMRI and individualized functional parcellation of auditory cortex, we measured the suppression (or adaptation) of primary and non-primary cortical responses to a high-frequency (3.8 kHz) probe sound as a function of the frequency of a preceding adaptor sound (ranging from 0.5 to 3.8 kHz). The degree of frequency tuning of the adaptation effect strongly depended on the temporal structure of the adaptor. Suppression by a single 200-ms adaptor showed little or no tuning, despite clear frequency tuning of the responses to the different adaptors. In contrast, suppression by multiple (four) 50-ms adaptor bursts was clearly tuned, with greater frequency selectivity than the adaptor response tuning, suggesting that fMRI adaption to multiple adaptors may reflect the frequency tuning of the underlying neuronal response. Importantly, adaptation tuning differed between primary and non-primary regions, suggesting a local suppression effect, rather than inheritance from upstream subcortical structures. Using a computational model of fMRI adaptation in a tonotopically-organized neuronal array, we identify key factors determining the relationship between observed fMRI adaptation tuning and the frequency selectivity of the underlying neuronal response. Using this model, we derive a plausible range for the frequency selectivity of individual neurons in each region of auditory cortex.
Deep Multimodal Graph-Based Network for Survival Prediction from Highly Multiplexed Images and Patient Variables

The spatial architecture of the tumour microenvironment and phenotypic heterogeneity of tumour cells have been shown to be associated with cancer prognosis and clinical outcomes, including survival. Recent advances in highly multiplexed imaging, including imaging mass cytometry (IMC), capture spatially resolved, high-dimensional maps that quantify dozens of disease-relevant biomarkers at single-cell resolution, that contain potential to inform patient-specific prognosis. However, existing automated methods for predicting survival typically do not leverage spatial phenotype information captured at the single-cell level, and current methods tend to focus on a single modality, such as patient variables (PVs). There is no end-to-end method designed to leverage the rich information in whole IMC images and all marker channels, and aggregate this information with PVs in a complementary manner to predict survival with enhanced accuracy. We introduce a deep multimodal graph-based network (DMGN) that integrates entire IMC images and multiple PVs for end-to-end survival prediction of breast cancer. We propose a multimodal graph-based module that considers relationships between spatial phenotype information in all image regions and all PVs, and scales each region–PV pair based on its relevance to survival. We propose another module to automatically generate embeddings specialised for each PV to enhance multimodal aggregation. We show that our modules are consistently effective at improving survival prediction performance using two public datasets, and that DMGN can be applied to an independent validation dataset across the same antigens but different antibody clones. Our DMGN outperformed state-of-the-art methods at survival prediction.
A Drop-on-Demand Bioprinting Approach to Spatially Arrange Multiple Cell Types and Monitor Their Cell-Cell Interactions towards Vascularization Based on Endothelial Cells and Mesenchymal Stem Cells

Spheroids, organoids, or highly-dense cell-laden droplets are often used as building blocks for bioprinting, but so far little is known about the spatio-temporal cellular interactions post printing. We present a drop-on-demand approach to study the biological interactions of such building blocks in micrometer dimensions. Droplets (containing approximately 700 cells in 10 nl) of multiple cell types are patterned in a 3D hydrogel matrix with a precision of less than 70 μm. It is applied to investigate interactions of cell types relevant for vascularization approaches. We show that a gap of 200 μm between droplets containing endothelial cells (HUVECs) and adipose-derived mesenchymal stem cells (ASCs) leads to decreased sprouting of HUVECs towards ASCs and increased growth from ASCs towards HUVECs. For mixed aggregates containing both cell types, cellular interconnections of ASCs with up to approximately 0.8 millimeter length and inhibition of HUVEC sprouting are observed. When ASCs are differentiated into smooth muscle cells (SMCs), HUVECs display decreased sprouting towards SMCs in separate aggregates, whereas no cellular interconnections or inhibition of HUVEC sprouting are detected for mixed aggregates. These findings demonstrate that this approach acts as a new tool to investigate cell-cell interactions of different cell types in 3D bioprinted constructs.