Miracle-dz/UniFAR-FTUs huggingface dataset:
Cortical depth-dependent human fMRI of resting-state networks using EPIK

Recent laminar-fMRI studies have substantially improved understanding of the evoked cortical responses in multiple sub-systems; in contrast, the laminar component of resting-state networks spread over the whole brain has been less studied due to technical limitations. Animal research strongly suggests that the supragranular layers of the cortex play a critical role in maintaining communication within the default mode network (DMN); however, whether this is true in this and other human cortical networks remains unclear. Here, we used EPIK, which offers unprecedented coverage at sub-millimeter resolution, to investigate cortical broad resting-state dynamics with depth specificity in healthy volunteers. Our results suggest that human DMN connectivity is primarily supported by intermediate and superficial layers of the cortex, and furthermore, the preferred cortical depth used for communication can vary from one network to another. This has major implications for the characterization of network-related diseases and should occupy future high-resolution studies. In addition, the laminar connectivity profile of some networks showed a tendency to change upon engagement in a motor task. In line with these connectivity changes, we observed that the amplitude of the low-frequency-fluctuations (ALFF), as well as the regional homogeneity (ReHo), exhibited a different laminar slope when subjects were either performing a task or were in a resting state (less variation among laminae, i.e., lower slope, during task performance compared to rest). The varied laminar profiles concerning network connectivity, ALFF, and ReHo, observed across two brain states (task vs. rest) suggest the potential diagnostic value of laminar fMRI in psychiatric diseases, e.g., to differentiate the cortical dynamics associated with disease stages linked, or not linked, to behavioral changes. The evaluation of laminar-fMRI across the brain encompasses computational challenges; nonetheless, it enables the investigation of a new dimension of the human neocortex, which may be key to understanding neurological disorders from a novel perspective.
Hidden limbs in the “limbless skink” Brachymeles lukbani: developmental observations

Reduced limbs and limblessness have evolved independently in many lizard clades. Skinks exhibit a wide range of limb-reduced morphologies, but only some species have been used to study the embryology of limb reduction (i.g., digit reduction in Chalcides and limb reduction in Scelotes). The genus Brachymeles, a Southeast Asian clade of skinks, includes species with a range of limb morphologies, from pentadactyl to functionally as well as structurally limbless species. Adults of the small, snake-like species Brachymeles lukbani show no sign of external limbs in the adult except for small depressions where they might be expected to occur. Embryos of B. lukbani in early stages of development, on the other hand, show a truncated but well-developed limb with a stylopod and a zeugopod, but no signs of an autopod. As development proceeds, the limb’s small size persists even while the embryo elongates. These observations are made based on external morphology. We used florescent whole-mount immunofluorescence to visualize the morphology of skeletal elements and muscles within the embryonic limb of B. lukabni. Early stages have a humerus and separated ulna and radius cartilages; associated with these structures are dorsal and ventral muscle masses as those found in the embryos of other limbed species. While the limb remains small, the pectoral girdle grows in proportion to the rest of the body, with well-developed skeletal elements and their associated muscles. In later stages of development, the small limb is still present under the skin but there are few indications of its presence, save for the morphology of the scale covering it. The adult morphology consists of a well-developed pectoral girdle, small humerus, extremely reduced ulna and radius, and well-developed limb musculature connected to the pectoral girdle. These muscles form in association with a developing limb during embryonic stages, a hint that “limbless” lizards that possesses these muscles may have or have had at least transient developing limbs, as we find in B. lukbani. Overall, the observed pattern of ontogenetic reduction, leading to an externally limbless adult in which a limb rudiment is hidden and covered under the trunk skin, is a situation called cryptomelia. The results of this work add to our growing understanding of clade-specific patterns of limb reduction and the convergent evolution of limbless phenotypes through different developmental processes.
A Machine Learning approach for Sentiment Analysis for Italian Reviews in Healthcare

In this paper, we present our approach to the task of binary sentiment classification for Italian reviews in healthcare domain. We first collected a new dataset for such domain. Then, we compared the results obtained by two different systems, one including a Support Vector Machine and one with BERT. For the first one, we linguistic pre–processed the dataset to extract hand-crafted features exploited by the classifier. For the second one, we oversampled the dataset to achieve better results. Our results show that the SVMbased system, without the worry of having to oversample, has better performance than the BERT-based one, achieving an F1-score of 91.21%.
Combinatorial screen of dynamic mechanical stimuli for predictive control of MSC mechano-responsiveness

A previously unexplored mechanical loading strategy is found to promote efficient tissue synthesis by mesenchymal stem cells. Mechanobiological-based control of mesenchymal stromal cells (MSCs) to facilitate engineering and regeneration of load-bearing tissues requires systematic investigations of specific dynamic mechanical stimulation protocols. Using deformable membrane microdevice arrays paired with combinatorial experimental design and modeling, we probed the individual and integrative effects of mechanical stimulation parameters (strain magnitude, rate at which strain is changed, and duty period) on myofibrogenesis and matrix production of MSCs in three-dimensional hydrogels. These functions were found to be dominantly influenced by a previously unidentified, higher-order interactive effect between strain magnitude and duty period. Empirical models based on our combinatorial cue-response data predicted an optimal loading regime in which strain magnitude and duty period were increased synchronously over time, which was validated to most effectively promote MSC matrix production. These findings inform the design of loading regimes for MSC-based engineered tissues and validate a broadly applicable approach to probe multifactorial regulating effects of mechanobiological cues.
Cross Sections and Product Kinetic Energy Analysis of H2O+ -H2O collisions at Suprathermal Energies

The reaction of H2O+ with H2O is studied using a longitudinal geometry double mass spectrometer in the collision energy range Ec.m. =0.5–25 eV. Cross sections are reported for oxonium ion (H3O+) production and the symmetric charge exchange. Isotopic substitution is used to discern the product branches, including the separation of the two channels for oxonium ion production: (i) proton transfer to the target molecule; and (ii) atom pickup by the primary ion. The largest branching ratio is observed for the charge exchange channel, where no isotope effect is detected in the investigated energy range. Proton transfer exhibits the second largest branching ratio and accounts for more than 90% of the oxonium ion production throughout the measured energy range. The proton transfer cross section is dependent on isotopic substitution, while the atom pickup channel is too weak to make a distinct statement on its isotopic behavior. Product ion energies, determined by time‐of‐flight measurements, are also reported for .
Capturing and Selecting Senescence Variation in Wheat

Senescence is a highly quantitative trait, but in wheat the genetics underpinning senescence regulation remain relatively unknown. To select senescence variation, and ultimately identify novel genetic regulators, accurate characterisation of senescence phenotypes is essential. When investigating senescence, phenotyping efforts often focus on, or are limited to, visual assessment of the flag leaves. However, senescence is a whole plant process, involving remobilisation and translocation of resources into the developing grain. Furthermore, the temporal progression of senescence poses challenges regarding trait quantification and description, whereupon the different models and approaches applied result in varying definitions of apparently similar metrics. To gain a holistic understanding of senescence we phenotyped flag leaf and peduncle senescence progression, alongside grain maturation. Reviewing the literature, we identified techniques commonly applied in quantification of senescence variation and developed simple methods to calculate descriptive and discriminatory metrics. To capture senescence dynamism, we developed the idea of calculating thermal time to different flag leaf senescence scores, for which between year Spearman’s rank correlations of r ≥ 0.59, P < 4.7 × 10−5(TT70), identify as an accurate phenotyping method. Following our experience of senescence trait genetic mapping, we recognised the need for singular metrics capable of discriminating senescence variation, identifying Thermal Time to Flag Leaf Senescence score of 70 (TT70) and Mean Peduncle senescence (MeanPed) scores as most informative. Moreover, grain maturity assessments confirmed a previous association between our staygreen traits and grain fill extension, illustrating trait functionality. Here we review different senescence phenotyping approaches and share our experiences of phenotyping two independent RIL populations segregating for staygreen traits. Together, we direct readers towards senescence phenotyping methods we found most effective, encouraging their use when investigating and discriminating senescence variation of differing genetic bases, and to aid trait selection and weighting in breeding and research programs alike.
Effect of cerium dioxide nanoparticles on the expression of selected growth and transcription factors in human astrocytes

This study was undertaken to examine the effect of cerium dioxide nanoparticles on the expression levels of genes, encoded transcription and growth factors, which are important for control of cell proliferation and survival in human astrocytes. Exposure of astrocytes with cerium dioxide nanoparticles (0.17 and 0.34 mg/ml of medium) during 20 h significantly decreases the expression level of transcription factors TBX3, E2F8 and FOXF1 mRNAs, being stronger for higher doses of nanoparticles. Moreover, the expression levels of IGFBP1 and IGFBP2 as well as LIF mRNA also significantly decreased in astrocytes after treatment with cerium dioxide nanoparticles. It is possible that the observed changes in the expression profile of the studied genes in astrocytes treated with cerium dioxide nanoparticles are associated with its toxic effect mediated by endoplasmic reticulum stress sensor‐signaling systems in part through the bifunctional membrane enzyme ERN1. Thus, cerium dioxide nanoparticles have a significant effect on important regulatory mechanisms, which control cell proliferation and survival in human astrocytes.
Distinct Neural Representations of Content and Ordinal Structure in Auditory Sequence Memory

Two forms of information, frequency (content) and ordinal position (structure), have to be stored when retaining a sequence of auditory tones in working memory (WM). However, the neural representations and coding characteristics of content and structure, particularly during WM maintenance, remain elusive. Here, in two EEG studies in human participants (both sexes), by transiently perturbing the “activity-silent” WM retention state and decoding the reactivated WM information, we demonstrate that content and structure are stored in a dissociative manner with distinct characteristics throughout WM process. First, each tone in the sequence is associated with two codes in parallel, characterizing its frequency and ordinal position, respectively. Second, during retention, a structural retrocue successfully reactivates structure but not content, whereas a following white noise triggers content but not structure. Third, structure representation remains stable, whereas content code undergoes a dynamic transformation through memory progress. Finally, the noise-triggered content reactivations during retention correlate with subsequent WM behavior. Overall, our results support distinct content and structure representations in auditory WM and provide an efficient approach to access the silently stored WM information in the human brain. The dissociation of content and structure could facilitate efficient memory formation via generalizing stable structure to new auditory contents. SIGNIFICANCE STATEMENT In memory experiences, contents do not exist independently but are linked with each other via ordinal structure. For instance, recalling a piece of favorite music relies on correct ordering (sequence structure) of musical tones (content). How are the structure and content for an auditory temporally structured experience maintained in working memory? Here, by using impulse-response approach and time-resolved representational dissimilarity analysis on human EEG recordings in an auditory working memory task, we reveal that content and structure are stored in a dissociated way, which would facilitate efficient and rapid memory formation through generalizing stable structure knowledge to new auditory inputs.
Mouse embryonic stem cells switch migratory behaviour during early differentiation

Development relies on a series of precisely orchestrated cell fate changes. While studies of fate transitions often focus on changes in gene regulatory networks, most transitions are also associated with changes in cell shape and cell behaviour. Here, we investigate changes in migratory behaviour in mouse embryonic stem (ES) cells during their first developmental fate transition, exit from ES cell state. We show that naïve pluripotent ES cells cannot efficiently migrate on 2-dimensional substrates but are able to migrate in an amoeboid fashion when placed in confinement. Exit from ES cell state, typically characterised by enhanced cell spreading, is associated with decreased migration in confinement and acquisition of mesenchymal-like migration on 2D substrates. Interestingly, confined, amoeboid-like migration of ES cells strongly depends on Myosin IIA, but not Myosin IIB. In contrast mesenchymal-like migration of cells exiting the ES cell state does not depend on Myosin motor activity but relies on the activity of the Arp2/3 complex. Together, our data suggest that during early differentiation, cells undergo a switch in the regulation of the actin cytoskeleton, leading to a transition from amoeboid-to mesenchymal-like migration. Summary statement Naïve mouse embryonic stem cells display amoeboid-like migration in confinement, but switch to mesenchymal-like migration as they exit the ES cell state.
End Image Defect Detection of Float Glass Based on Faster Region-Based Convolutional Neural Network

The float glass contains various defects for reasons of raw materials and production process. These defects can be observed on the end images of the glass. Since the defects are correlated with specific links of the production process, it is possible to discover the process problems by identifying the location and type of defects in end images. Based on faster region-based convolutional neural network (Faster RCNN), this paper proposes a deep learning method that improves the feature extraction network, and adds a Laplacian convolutional layer to preprocess the end images. Considering the defect features in end images, the anchor box size was adjusted to speed up the training. Besides, the lack of generalizability induced by small dataset was solved through data enhancement. With improved VGG16 as the feature extraction layer, a glass defect detection model was established, whose generalizability was improved through transfer learning. The experimental results show that the proposed model achieved a mean detection accuracy of 94% on actual test set, meeting the requirements for actual use in factories.
Mandatory Corporate Carbon Disclosure: Evidence from a Natural Experiment

We study the introduction of a unique law in the United Kingdom that mandates publicly listed firms to disclose their greenhouse gas emissions in a standardized way. Using a difference-in-differences framework, we provide evidence that firms respond to the disclosure regulation by reducing their emissions. Examining why firms reduce their emissions, we show that a mix of institutional investor, general stakeholder, and competitive pressure is likely to explain the reduction. We also study the financial effects of the regulation and find that firms disclosing low (high) emissions relative to industry peers exhibit positive (negative) abnormal returns.
Misalignment of selection, plasticity, and among-individual variation: A test of theoretical predictions with Peromyscus maniculatus

Genetic variation and phenotypic plasticity are predicted to align with selection surfaces, a prediction that has rarely been empirically tested. Understanding the relationship between sources of phenotypic variation, i.e. genetic variation and plasticity, with selection surfaces improves our ability to predict a population’s ability to adapt to a changing environment and our understanding of how selection has shaped phenotypes. Here, we estimated the (co)variances among three different behaviors (activity, aggression, and anti-predator response) in a natural population of deer mice (Peromyscus maniculatus). Using multi-response generalized mixed effects models, we divided the phenotypic covariance matrix into among- and within-individual matrices. The among-individual covariances includes genetic and permanent environmental covariances (e.g. developmental plasticity) and is predicted to align with selection. Simultaneously, we estimated the within-individual (co)variances, which include reversible phenotypic plasticity. To determine whether genetic variation, plasticity and selection align in multivariate space we calculated the dimensions containing the greatest among-individual variation and the dimension in which most plasticity was expressed (i.e. the dominant eigenvector for the among- and within-individual covariance matrices respectively). We estimated selection coefficients based on survival estimates from a mark-recapture model. Alignment between the dominant eigenvectors of behavioural variation and the selection gradient was estimated by calculating the angle between them, with an angle of 0 indicating perfect alignment. The angle between vectors ranged from 68° to 89°, indicating that genetic variation, phenotypic plasticity, and selection are misaligned in this population. This misalignment could be due to the behaviors being close to their fitness optima, which is supported by low evolvabilities, or because of low selection pressure on these behaviors.
Removal of KCNQ2 from parvalbumin-expressing interneurons improves anti-seizure efficacy of retigabine

Anti-seizure drug (ASD) targets are widely expressed in both excitatory and inhibitory neurons. It remains unknown if the action of an ASD upon inhibitory neurons could counteract its beneficial effects on excitatory neurons (or vice versa), thereby reducing the efficacy of the ASD. Here, we examine whether the efficacy of the ASD retigabine (RTG) is altered after removal of the Kv7 potassium channel subunit KCNQ2, one of its drug targets, from parvalbumin-expressing interneurons (PV-INs). Parvalbumin-Cre (PV-Cre) mice were crossed with Kcnq2-floxed (Kcnq2fl/fl) mice to conditionally delete Kcnq2 from PV-INs. In these conditional knockout mice (cKO, PV-Kcnq2fl/fl), RTG (10 mg/kg, i.p.) significantly delayed the onset of either picrotoxin (PTX, 10 mg/kg, i.p)- or kainic acid (KA, 30mg/kg, i.p.)-induced convulsive seizures compared to vehicle, while RTG was not effective in wild-type littermates (WT). Immunostaining for KCNQ2 and KCNQ3 revealed that both subunits were enriched at axon initial segments (AISs) of hippocampal CA1 PV-INs, and their specific expression was selectively abolished in cKO mice. Accordingly, the M-currents recorded from CA1 PV-INs and their sensitivity to RTG were significantly reduced in cKO mice. While the ability of RTG to suppress CA1 excitatory neurons in hippocampal slices was unchanged in cKO mice, its suppressive effect on the spike activity of CA1 PV-INs was significantly reduced compared with WT mice. In addition, the RTG-induced suppression on intrinsic membrane excitability of PV-INs in WT mice was significantly reduced in cKO mice. These findings suggest that preventing RTG from suppressing PV-INs improves its anticonvulsant effect. Significance Statement One out of three patients with epilepsy remain resistant to anti-seizure drugs (ASD). Therefore, strategies that can enhance the efficacy of current ASDs or aid in the development of novel ASDs are in high demand. Here we show that by sparing a subset of inhibitory neurons, the ASD retigabine becomes more efficacious. These findings indicate that developing the ASDs that have relatively greater effects on excitatory over inhibitory neurons may be an effective strategy to improve the efficacy of ASDs.
A cysteine-based redox switch regulates millisecond dynamics of protein disulfide isomerase and controls enzyme activity

Cysteine residues provide enzymes involved in signaling and metabolism with an allosteric mechanism to quickly respond to changes in the surrounding redox environment. Yet how thiol modifications impact enzyme structure and dynamics is poorly understood. Here, we apply single-molecule Förster resonance energy transfer (smFRET) to study redox-dependent conformational dynamics of a highly flexible oxidoreductase, protein disulfide isomerase (PDI), in solution. We demonstrate that PDI toggles in the millisecond timescale between two major conformational ensembles, “open” and “closed”, that differ ∼20Å in length due to relocation of the two catalytic domains, whose equilibrium distribution is modulated by the redox state. While reduced PDI predominantly populates the open ensemble, oxidized PDI visits both ensembles with similar probability. We provide evidence that i) transition from the open to the closed ensemble requires loss of free thiols, not disulfide bonding, as previously thought, and ii) exposure to small molecules that alkylate the catalytic cysteines and mutation of cysteines in the N-terminal active site shift PDI to the closed conformation. Finally, using mutational and kinetic analyses, we show that the fraction of open ensemble at equilibrium positively correlates with the reductase activity of PDI. This work forms the basis of a new dynamic mechanism of PDI regulation by a cysteine-based redox switch in which thiol-controlled equilibrium distribution of the open/closed ensembles dictates function.