Miracle-dz/UniFAR-FTUs huggingface dataset:
Increased Functional Connectivity of the Intraparietal Sulcus Underlies the Attenuation of Numerosity Estimations for Self-Generated Words

Previous studies have shown that self-generated stimuli in auditory, visual, and somatosensory domains are attenuated, producing decreased behavioral and neural responses compared with the same stimuli that are externally generated. Yet, whether such attenuation also occurs for higher-level cognitive functions beyond sensorimotor processing remains unknown. In this study, we assessed whether cognitive functions such as numerosity estimations are subject to attenuation in 56 healthy participants (32 women). We designed a task allowing the controlled comparison of numerosity estimations for self-generated (active condition) and externally generated (passive condition) words. Our behavioral results showed a larger underestimation of self-generated compared with externally generated words, suggesting that numerosity estimations for self-generated words are attenuated. Moreover, the linear relationship between the reported and actual number of words was stronger for self-generated words, although the ability to track errors about numerosity estimations was similar across conditions. Neuroimaging results revealed that numerosity underestimation involved increased functional connectivity between the right intraparietal sulcus and an extended network (bilateral supplementary motor area, left inferior parietal lobule, and left superior temporal gyrus) when estimating the number of self-generated versus externally generated words. We interpret our results in light of two models of attenuation and discuss their perceptual versus cognitive origins. SIGNIFICANCE STATEMENT We perceive sensory events as less intense when they are self-generated compared with when they are externally generated. This phenomenon, called attenuation, enables us to distinguish sensory events from self and external origins. Here, we designed a novel fMRI paradigm to assess whether cognitive processes such as numerosity estimations are also subject to attenuation. When asking participants to estimate the number of words they had generated or passively heard, we found bigger underestimation in the former case, providing behavioral evidence of attenuation. Attenuation was associated with increased functional connectivity of the intraparietal sulcus, a region involved in numerosity processing. Together, our results indicate that the attenuation of self-generated stimuli is not limited to sensory consequences but is also impact cognitive processes such as numerosity estimations.
Detection of PD-L1–Expressing Myeloid Cell Clusters in the Hyaluronan-Enriched Stroma in Tumor Tissue and Tumor-Draining Lymph Nodes

Expression of the transmembrane protein PD-L1 is frequently upregulated in cancer. Because PD-L1–expressing cells can induce apoptosis or anergy of T lymphocytes through binding to the PD1 receptor, the PD-L1–mediated inhibition of activated PD1+ T cells is considered a major pathway for tumor immune escape. However, the mechanisms that regulate the expression of PD-L1 in the tumor microenvironment are not fully understood. Analysis of organotypic tumor tissue slice cultures, obtained from mice with implanted syngeneic tumors (MBT2 bladder tumors in C3H mice, Renca kidney, and CT26 colon tumors in BALB/c mice), as well as from patients with cancer, revealed that tumor-associated hyaluronan (HA) supports the development of immunosuppressive PD-L1+ macrophages. Using genetically modified tumor cells, we identified epithelial tumor cells and cancer-associated mesenchymal fibroblast-like cells as a major source of HA in the tumor microenvironment. These HA-producing tumor cells, and particularly the vimentin-positive fibroblast-like cells of bone marrow origin, directly interact with tumor-recruited myeloid cells to form large stromal congregates/clusters that are highly enriched for both HA and PD-L1. Furthermore, similar cell clusters composed of HA-producing fibroblast-like cells and PD-L1+ macrophages were detected in tumor-draining, but not in distant, lymph nodes. Collectively, our findings indicate that the formation of multiple large HA-enriched stromal clusters that support the development of PD-L1–expressing APCs in the tumor microenvironment and draining lymph nodes could contribute to the immune escape and resistance to immunotherapy in cancer. Key Points Hyaluronan-enriched tumor stroma supports the development of PD-L1+ cell clusters. Fibroblasts and epithelial tumor cells serve as the main source of hyaluronan. Hyal2-expressing myeloid cells contribute to the development of PD-L1+ macrophages.
Hydrogen implantation into ZnO for n+-layer formation

Bulk ZnO crystals were implanted using 100keV H+ ions with doses 5×1016 and 2×1017cm−2 and subsequently annealed at 200–600°C to study the evolution of the implanted H by employing secondary ion mass spectrometry and scanning spreading resistance microscopy. It is shown that the heat treatment results in a decrease of H concentration in the implanted region, while no significant broadening of the H profiles is observed. This suggests that the implanted H is trapped in immobile complexes which dissociate during annealing with subsequent outdiffusion of H from the implanted region. The formation of a highly conductive n+-layer is observed in the implanted region, and the n+-layer is found to be stable up to 600°C. A correlation between electrical activity of H and presence of radiation damage is discussed.
Iliski, a software for robust calculation of transfer functions

Understanding the relationships between biological events is paramount to unravel pathophysiological mechanisms. These relationships can be modeled with Transfer Functions (TFs), with no need of a priori hypotheses as to the shape of the transfer function. Here we present Iliski, a software dedicated to TFs computation between two signals. It includes different pre-treatment routines and TF computation processes: deconvolution, deterministic and non-deterministic optimization algorithms that are adapted to disparate datasets. We apply Iliski to data on neurovascular coupling, an ensemble of biological events that link neuronal activity to local changes of blood flow, highlighting the software benefits and caveats in the computation and evaluation of TFs. We also propose a workflow that will help users to choose the best computation according to the dataset. Iliski is available under the open-source license CC BY 4.0 on GitLab (https://gitlab.com/AliK_A/iliski) and can be used on the most common operating systems, either within the MATLAB environment, or as a standalone application.
Rapid SARS-CoV-2 Detection and Classification Using Phase Imaging with Computational Specificity

Efforts to mitigate the COVID-19 crisis revealed that fast, accurate, and scalable testing is crucial for curbing the current impact and that of future pandemics. We propose an optical method for directly imaging unlabeled viral particles and using deep learning for detection and classification. An ultrasensitive interferometric method was used to image four virus types with nanoscale optical pathlength sensitivity. Pairing these data with fluorescence images for ground truth, we trained semantic segmentation models based on U-Net, a particular type of convolutional neural network. The trained network was applied to classify the viruses from the interferometric images only, containing simultaneously SARS-CoV-2, H1N1 (influenza-A), HAdV (adenovirus), and ZIKV (Zika). Remarkably, due to the nanoscale sensitivity in the input data, the neural network was able to identify SARS-CoV-2 vs. the other viruses with 96% accuracy. The inference time for each image is 60 ms, on a common graphic processing unit. This approach of directly imaging unlabeled viral particles may provide an extremely fast test, of less than a minute per patient. As the imaging instrument operates on regular glass slides, we envision this method as potentially testing on patient breath condensates. The necessary high throughput can be achieved by translating concepts from digital pathology, where a microscope can scan hundreds of slides automatically. One Sentence Summary This work proposes a rapid (<1 min.), label-free testing method for SARS-CoV-2 detection, using quantitative phase imaging and deep learning.
Analysis methods for measuring fNIRS responses generated by a block-design paradigm

Significance fNIRS is an increasingly popular tool in auditory research, but the range of analysis procedures employed across studies complicates interpretation of data. Aim To assess the impact of different analysis procedures on the morphology, detection, and lateralization of auditory responses in fNIRS. Specifically, whether averaging or GLM-based analyses generate different experimental conclusions, when applied to a block-protocol design. The impact of parameter selection of GLMs on detecting auditory-evoked responses was also quantified. Approach 17 listeners were exposed to three commonly employed auditory stimuli: noise, speech, and silence. A block design was employed, comprising sounds of 5-s duration, and 10–20 s silent intervals. Results Both analysis procedures generated similar response morphologies and amplitude estimates, and both also indicated responses to speech to be significantly greater than to noise and silence. Neither approach indicated a significant effect of brain hemisphere on responses to speech. Methods to correct for systemic hemodynamic responses using short channels improved detection at the individual level. Conclusions Consistent with theoretical considerations, simulations, and other experimental domains, GLM and averaging analyses generate the same group-level experimental conclusions. We release this dataset publicly for use in future development and optimization of algorithms.
Master Transcription Factors Regulate the DNA Methylation Landscape During Hepatocyte Differentiation

Background Hepatocytes are the dominant cell type of the human liver, with functions in metabolism, detoxification, and in producing secreted proteins. During the process of hepatocyte differentiation, gene regulation and master transcription factors have been extensively investigated, whereas little is known about how the epigenome is regulated, particularly the dynamics of DNA methylation, and the upstream factors that have critical roles. Results By examining changes in the transcriptome and the methylome during in vitro hepatocyte differentiation, we identified putative DNA methylation-regulating transcription factors, which are likely involved in DNA demethylation and maintenance of hypo-methylation in a differentiation stage-specific manner. Of these factors, we further reveal that GATA6 induces DNA demethylation together with chromatin activation at a binding-site-specific manner during endoderm differentiation. Conclusions These results provide an insight into the spatiotemporal regulatory mechanisms exerted on the DNA methylation landscape by transcription factors, and uncover a new role for transcription factors in early liver development.
ScoreNet: A Neural network-based post-processing model for identifying epileptic seizure onset and offset in EEGs

We design an algorithm to automatically detect epileptic seizure onsets and offsets from scalp EEGs. The proposed scheme consists of two sequential steps: detecting seizure episodes from long EEG recordings, and determining seizure onsets and offsets of the detected episodes. We introduce a neural network-based model called ScoreNet to carry out the second step by better predicting the seizure probability of pre-detected seizure epochs to determine seizure onsets and offsets. A cost function called log-dice loss with a similar meaning to the F1 score is proposed to handle the natural data imbalance inherent in EEG signals signifying seizure events. ScoreNet is then verified on the CHB-MIT Scalp EEG database in combination with several classifiers including random forest, CNN, and logistic regression. As a result, ScoreNet improves seizure detection performance over lone epoch-based seizure classification methods; F1 scores increase significantly from 16–37% to 53–70%, and false positive rates per hour decrease from 0.53–5.24 to 0.05–0.61. This method provides clinically acceptable latencies of detecting seizure onset and offset of less than 10 seconds. In addition, an effective latency index is proposed as a metric for detection latency whose scoring considers undetected events to provide better insight into onset and offset detection than conventional time-based metrics.
Temporal Kinetics of RNAemia and Associated Systemic Cytokines in Hospitalized COVID-19 Patients

Severe COVID-19 can be considered a systemic disease as many extrarespiratory complications occur. However, the systemic pathogenesis is poorly understood. ABSTRACT COVID-19 is associated with a wide range of extrarespiratory complications, of which the pathogenesis is currently not fully understood. However, both systemic spread and systemic inflammatory responses are thought to contribute to the systemic pathogenesis. In this study, we determined the temporal kinetics of viral RNA in serum (RNAemia) and the associated inflammatory cytokines and chemokines during the course of COVID-19 in hospitalized patients. We show that RNAemia can be detected in 90% of the patients who develop critical disease, compared to 50% of the patients who develop moderate or severe disease. Furthermore, RNAemia lasts longer in patients who develop critical disease. Elevated levels of interleukin-10 (IL-10) and MCP-1—but not IL-6—are associated with viral load in serum, whereas higher levels of IL-6 in serum were associated with the development of critical disease. In conclusion, RNAemia is common in hospitalized patients, with the highest frequency and duration in patients who develop critical disease. The fact that several cytokines or chemokines are directly associated with the presence of viral RNA in the circulation suggests that the development of RNAemia is an important factor in the systemic pathogenesis of COVID-19. IMPORTANCE Severe COVID-19 can be considered a systemic disease as many extrarespiratory complications occur. However, the systemic pathogenesis is poorly understood. Here, we show that the presence of viral RNA in the blood (RNAemia) occurs more frequently in patients who develop critical disease, compared to patients with moderate or severe disease. In addition, RNAemia is associated with increased levels of inflammatory cytokines and chemokines, like MCP-1 and IL-10, in serum during the course of disease. This suggests that extrarespiratory spread of SARS-CoV-2 contributes to systemic inflammatory responses, which are an important factor in the systemic pathogenesis of COVID-19.
BLOCKADE OF M4 MUSCARINIC RECEPTORS ON STRIATAL CHOLINERGIC INTERNEURONS NORMALIZES STRIATAL DOPAMINE RELEASE IN A MOUSE MODEL OF DYT1-TOR1A DYSTONIA

Trihexyphenidyl (THP), a non-selective muscarinic receptor (mAChR) antagonist, is the preferred oral pharmaceutical for the treatment of DYT1-TOR1A dystonia. A better understanding of the mechanism of action of THP is a critical step in the development of better therapeutics with fewer side effects. Using a mouse model of DYT1-TOR1A dystonia (Tor1a+/ΔE KI mice), we recently found that THP normalized striatal DA release, revealing a plausible mechanism of action for this compound. However, the exact mAChR subtypes that mediate this effect remain unclear. In this study we used a combination of a newly developed M4 subtype-selective mAChR antagonist and cell-type specific mAChR KO mice to determine which mAChR subtypes mediate the DA enhancing effects of THP. We determined that THP and the M4 subtype-selective mAChR antagonist enhance striatal DA release by blocking M4 mAChR on striatal cholinergic interneurons in Tor1a+/ΔE KI mice. However, in Tor1a+/+ mice THP increases striatal DA release through a combination of M1 and M4 mAChR, which reveals an alteration in M1 mAChR function in Tor1a+/ΔE KI mice. Taken together these data implicate a principal role for M4 mAChR located on striatal cholinergic interneurons in the mechanism of action of THP and suggest that M4-subtype selective mAChR antagonists may be more efficacious therapeutics for DYT1-TOR1A dystonia. SIGNIFICANCE STATEMENT Trihexyphenidyl, a non-selective muscarinic receptor antagonist, is the preferred oral therapeutic for DYT1-TOR1A dystonia, but it is poorly tolerated due to significant side effects. A better understanding of the mechanism of action of trihexyphenidyl is needed for the development of improved therapeutics. We recently found that trihexyphenidyl rescues the deficit in both striatal dopamine release and steady-state extracellular striatal dopamine concentrations in a mouse model of DYT1-TOR1A dystonia. However, the precise muscarinic receptor subtype(s) that mediate these effects are unknown. We used a newly developed M4 muscarinic receptor subtype-selective antagonist along with M1 and M4 muscarinic receptor knockout mice to determine the precise muscarinic receptor subtypes that mediate the dopamine-enhancing effects of trihexyphenidyl.
Evaluation of Postharvest Senescence in Broccoli Via Hyperspectral Imaging

Fresh fruits and vegetables are invaluable for human health, but their quality deteriorates before reaching consumers due to ongoing biochemical processes and compositional changes. The current lack of any objective indices for defining “freshness” of fruits or vegetables limits our capacity to control product quality leading to food loss and waste. It has been hypothesized that certain proteins and compounds such as glucosinolates can be used as an indicator to monitor the freshness of vegetables and fruits. However, it is challenging to “visualize” the proteins and bioactive compounds during the senescence processes. In this work, we propose machine learning hyperspectral image analysis approaches for estimating glucosinolates levels to detect postharvest senescence in broccoli. Therefore, we set out the research to quantify glucosinolates as “freshness-indicators” which aid in the development of an innovative and accessible tool to precisely estimate the freshness of produce. Such a tool would allow for significant advancement in postharvest logistics and supporting the availability for high-quality and nutritious fresh produce.
A standardized behavioral event equally impacts the activity of cortical visual areas and layers

Multiple recent studies have shown that motor activity greatly impacts the activity of primary sensory areas like V1. Yet, the role of this motor related activity in sensory processing is still unclear. Here we further dissect how these behavior relevant signals are broadcast to different layers and areas of visual cortex. To do so, we leveraged a standardized motor behavior fidget event in behavioral videos of passively viewing mice. A large two-photon Ca2+ imaging database of neuronal responses uncovered four neural response types during fidgets that are surprisingly consistent in their proportion and response patterns across all visual areas and layers of the visual cortex. Indeed, the layer and area identity could not be decoded above chance level based only on neuronal recordings. The broad availability of standardized behavior signals could be a key component in how the cortex selects, learns and binds local sensory information with relevant motor outputs.
Mutation Landscape of SARS COV2 in Africa

COVID-19 disease has had a relatively less severe impact in Africa. To understand the role of SARS CoV2 mutations on COVID-19 disease in Africa, we analysed 282 complete nucleotide sequences from African isolates deposited in the NCBI Virus Database. Sequences were aligned against the prototype Wuhan sequence (GenBank accession: NC_045512.2) in BWA v. 0.7. 17. SAM and BAM files were created, sorted and indexed in SAMtools v. 1.10 and marked for duplicates using Picard v. 2.23. 4. Variants were called with mpileup in BCFtools v. 1.11. Phylograms were created using Mr. Bayes v 3.2. 6. A total of 2,349 single nucleotide polymorphism (SNP) profiles across 294 sites were identified. Clades associated with severe disease in the United States, France, Italy, and Brazil had low frequencies in Africa (L84S=2.5%, L3606F=1.4%, L3606F/V378I/=0.35, G251V=2%). Sub Saharan Africa (SSA) accounted for only 3% of P323L and 4% of Q57H mutations in Africa. Comparatively low infections in SSA were attributed to the low frequency of the D614G clade in earlier samples (25% vs 67% global). Higher disease burden occurred in countries with higher D614G frequencies (Egypt=98%, Morocco=90%, Tunisia=52%, South Africa) with D614G as the first confirmed case. V367F, D364Y, V483A and G476S mutations associated with efficient ACE2 receptor binding and severe disease were not observed in Africa. 95% of all RdRp mutations were deaminations leading to CpG depletion and possible attenuation of virulence. More genomic and experimental studies are needed to increase our understanding of the temporal evolution of the virus in Africa, clarify our findings, and reveal hot spots that may undermine successful therapeutic and vaccine interventions.
Increased Connectivity among Sensory and Motor Regions during Visual and Audiovisual Speech Perception

In everyday conversation, we usually process the talker's face as well as the sound of the talker's voice. Access to visual speech information is particularly useful when the auditory signal is degraded. Here, we used fMRI to monitor brain activity while adult humans (n = 60) were presented with visual-only, auditory-only, and audiovisual words. The audiovisual words were presented in quiet and in several signal-to-noise ratios. As expected, audiovisual speech perception recruited both auditory and visual cortex, with some evidence for increased recruitment of premotor cortex in some conditions (including in substantial background noise). We then investigated neural connectivity using psychophysiological interaction analysis with seed regions in both primary auditory cortex and primary visual cortex. Connectivity between auditory and visual cortices was stronger in audiovisual conditions than in unimodal conditions, including a wide network of regions in posterior temporal cortex and prefrontal cortex. In addition to whole-brain analyses, we also conducted a region-of-interest analysis on the left posterior superior temporal sulcus (pSTS), implicated in many previous studies of audiovisual speech perception. We found evidence for both activity and effective connectivity in pSTS for visual-only and audiovisual speech, although these were not significant in whole-brain analyses. Together, our results suggest a prominent role for cross-region synchronization in understanding both visual-only and audiovisual speech that complements activity in integrative brain regions like pSTS. SIGNIFICANCE STATEMENT In everyday conversation, we usually process the talker's face as well as the sound of the talker's voice. Access to visual speech information is particularly useful when the auditory signal is hard to understand (e.g., background noise). Prior work has suggested that specialized regions of the brain may play a critical role in integrating information from visual and auditory speech. Here, we show a complementary mechanism relying on synchronized brain activity among sensory and motor regions may also play a critical role. These findings encourage reconceptualizing audiovisual integration in the context of coordinated network activity.