Miracle-dz/UniFAR-FTUs huggingface dataset:
A subclass of evening cells promotes the switch from arousal to sleep at dusk

Animals exhibit rhythmic patterns of behavior that are shaped by an internal circadian clock and the external environment. While light intensity varies across the day, there are particularly robust differences at twilight (dawn/dusk). These periods are also associated with major changes in behavioral states, such as the transition from arousal to sleep. However, the neural mechanisms by which time and environmental conditions promote these behavioral transitions are poorly defined. Here, we show that the E1 subclass of Drosophila evening clock neurons promotes the transition from arousal to sleep at dusk. We first demonstrate that the cell-autonomous clocks of E2 neurons alone are required to drive and adjust the phase of evening anticipation, the canonical behavior associated with “evening” clock neurons. We next show that conditionally silencing E1 neurons causes a significant delay in sleep onset after dusk. However, rather than simply promoting sleep, activating E1 neurons produces time- and light- dependent effects on behavior. Activation of E1 neurons has no effect early in the day, but then triggers arousal before dusk and induces sleep after dusk. Strikingly, these phenotypes critically depend on the presence of light during the day. Despite their influence on behavior around dusk, in vivo voltage imaging of E1 neurons reveals that their spiking rate does not vary between dawn and dusk. Moreover, E1-specific clock ablation has no effect on arousal or sleep. Thus, we suggest that, rather than specifying “evening” time, E1 neurons act, in concert with other rhythmic neurons, to promote behavioral transitions at dusk.
Oxidative regulation of TDP-43 self-association by a β-to-α conformational switch

An evolutionarily conserved region of the TDP-43 low complexity domain twenty residues in length can adopt either an α-helical or β-strand conformation. When in the latter conformation, TDP-43 self-associates via the formation of a labile, cross-β structure. Self-association can be monitored via the formation of phase separated protein droplets. Exposure of droplets to hydrogen peroxide leads to oxidation of conserved methionine residues distributed throughout the low complexity domain. Oxidation disassembles the cross-β structure, thus eliminating both self-association and phase separation. Here we demonstrate that this process reciprocally enables formation of α-helical structure in precisely the same region formerly functioning to facilitate β-strand mediated self-association. We further observe that the α-helical conformation allows interaction with a lipid-like detergent, and that exposure to lipids enhances the β-to-α conformational switch. We hypothesize that regulation of this oxidative switch will prove to be important to the control of localized translation within vertebrate cells. The experimental observations reported herein were heavily reliant on studies of 1,6-hexanediol, a chemical agent that selectively dissolves labile structures formed via the self-association of protein domains of low sequence complexity. This aliphatic alcohol is shown to exert its dissociative activity primarily via hydrogen bonding interactions with carbonyl oxygen atoms of the polypeptide backbone. Such observations underscore the central importance of backbone-mediated protein:protein interactions that facilitate the self-association and phase separation of low complexity domains. Significance Statement The TDP-43 protein is a constituent of RNA granules involved in regulated translation. TDP-43 contains a C-terminal domain of 150 amino acids of low sequence complexity conspicuously decorated with ten methionine residues. An evolutionarily conserved region (ECR) of 20 residues within this domain can adopt either of two forms of labile secondary structure. Under normal conditions wherein methionine residues are reduced, the ECR forms a labile cross-β structure that enables RNA granule condensation. Upon methionine oxidation, the ECR undergoes a conformational switch to become an α-helix incompatible with self-association and granule integrity. Oxidation of the TDP-43 low complexity domain is hypothesized to occur proximal to mitochondria, thus facilitating dissolution of RNA granules and activation of localized translation.
Cis-regulatory polymorphism at fiz ecdysone oxidase contributes to polygenic adaptation to malnutrition in Drosophila

We investigate the contribution of a candidate gene, fiz (fezzik), to complex polygenic adaptation to juvenile malnutrition in Drosophila melanogaster. We show that experimental populations adapted during >250 generations of experimental evolution to a nutritionally poor larval diet (Selected populations) evolved several-fold lower fiz expression compared to unselected Control populations. This divergence in fiz expression is mediated by a cis-regulatory polymorphism. This polymorphism, which was originally present in a sample from a natural population in Switzerland, is distinct from a second cis-regulatory SNP previously identified in non-African D. melanogaster populations, implying that two independent cis-regulatory variants promoting high fiz expression segregate in non-African populations. Enzymatic analyses of Fiz protein expressed in E. coli demonstrate that it has ecdysone oxidase activity acting on both ecdysone and 20-hydroxyecdysone. Four of five fiz paralogs annotated to ecdysteroid metabolism also show reduced expression in Selected larvae, suggesting that malnutrition-driven selection favored general downregulation of ecdysone oxidases. Finally, as an independent test of the role of fiz in poor diet adaptation, we show that fiz knockdown by RNAi results in faster larval growth on the poor diet, but at the cost of greatly reduced survival. These results imply that downregulation of fiz in Selected populations was favored because of its role in suppressing growth in response to nutrient shortage. However, fiz downregulation is only adaptive in combination with other changes evolved by Selected populations, such as in nutrient acquisition and metabolism, which ensure that the organism can actually sustain the faster growth promoted by fiz downregulation.
Mutation in SLC45A2 leads to loss of melanin in parrot feathers

Bird plumage coloration is a complex and multi-factorial process that involves both genetic and environmental factors. Diverse pigment groups contribute to plumage variation in different birds. In parrots, the predominant green color results from the combination of two different primary colors-yellow and blue. Psittacofulvin, a pigment uniquely found in parrots, is responsible for the yellow coloration, while blue is suggested to be the result of light scattering by feather nanostructures and melanin granules. So far, genetic control of melanin-mediated blue coloration has been elusive. In this study, we demonstrated that feather from the yellow mutant rose-ringed parakeet displays loss of melanosome granules in spongy layer of feather barb. Using whole genome sequencing, we found that mutation in SLC45A2, an important solute carrier protein in melanin synthetic pathway, is responsible for the sex-linked yellow phenotype in rose-ringed parakeet. Intriguingly, one of the mutations, P53L found in yellow P. krameri is already reported as P58A/S in the human albinism database, known to be associated with human OCA4. We further showed that mutations in SLC45A2 gene affect melanin production also in other members of Psittaculidae family such as alexandrine, and plum-headed parakeets. Additionally, we demonstrate that the mutations associated with the sex-linked yellow phenotype, localized within the transmembrane domains of the SLC45A2 protein, affect the protein localization pattern. This is the first evidence of plumage color variation involving SLC45A2 in parrots and confirmation of associated mutations in the transmembrane domains of the protein that affect its localization. Article Summary The vibrant green tone of parrot plumage emerges from a blend of yellow and blue. While yellow comes from a unique pigment psittacofulvin, the genetics of blue structural color has puzzled scientists. Through novel genetic study, here we identified mutations in SLC45A2 gene, causing loss of melanin in feathers that contributes to the blue structural color. This insight opens a new chapter in understanding avian coloration and the complex interplay of feather microstructure and genetics in nature’s palette.
Main Manuscript for Developmental pyrethroid exposure disrupts molecular pathways for circadian rhythms and synaptic plasticity in mouse brain.

: Neurodevelopmental disorders (NDDs) are a category of pervasive disorders of the developing nervous system with few or no recognized biomarkers. A significant portion of the risk for NDDs, including attention deficit hyperactivity disorder (ADHD), is contributed by the environment, and exposure to pyrethroid pesticides during pregnancy has been identified as a potential risk factor for NDD in the unborn child. We recently showed that low-dose developmental exposure to the pyrethroid pesticide deltamethrin in mice causes male-biased changes to ADHD-and NDD-relevant behaviors as well as the striatal dopamine system. Here, we used a multiomics approach to determine the broadest possible set of pharmacologically relevant changes in the mouse brain caused by developmental pyrethroid exposure (DPE). Using a litter-based, split-sample design, we exposed mouse dams during pregnancy and lactation to deltamethrin (3 mg/kg or vehicle every 3 days) at a concentration well below the EPA-determined benchmark dose used for regulatory guidance. We raised male offspring to adulthood, euthanized them, and pulverized and divided whole brain samples for split-sample transcriptomics, kinomics and multiomics integration. Transcriptome analysis revealed alterations to multiple canonical clock genes, and kinome analysis revealed changes in the activity of multiple kinases involved in synaptic plasticity. Multiomics integration revealed a dysregulated protein-protein interaction network containing primary clusters for mitogen-activated protein (MAP) kinase cascades, synaptic function, and the regulation of apoptosis. These results demonstrate that DPE causes a multi-modal biophenotype in the brain relevant to ADHD and identifies new potential avenues for therapeutics.
Dopaminergic D2 receptor modulation of striatal cholinergic interneurons contributes to sequence learning

Learning action sequences is necessary for normal daily activities. Medium spiny neurons (MSNs) in the dorsal striatum (dStr) encode action sequences through changes in firing at the start and/or stop of action sequences or sustained changes in firing throughout the sequence. Acetylcholine (ACh), released from cholinergic interneurons (ChIs), regulates striatal function by modulating MSN and interneuron excitability, dopamine and glutamate release, and synaptic plasticity. Cholinergic neurons in dStr pause their tonic firing during the performance of learned action sequences. Activation of dopamine type-2 receptors (D2Rs) on ChIs is one mechanism of ChI pausing. In this study we show that deleting D2Rs from ChIs by crossing D2-floxed with ChAT-Cre mice (D2Flox-ChATCre), which inhibits dopamine-mediated ChI pausing and leads to deficits in an operant action sequence task and lower breakpoints in a progressive ratio task. These data suggest that D2Flox-ChATCre mice have reduced motivation to work for sucrose reward, but show no generalized motor skill deficits. D2Flox-ChATCre mice perform similarly to controls in a simple reversal learning task, indicating normal behavioral flexibility, a cognitive function associated with ChIs. In vivo electrophysiological recordings show that D2Flox-ChatCre mice have deficits in sequence encoding, with fewer dStr MSNs encoding entire action sequences compared to controls. Thus, ChI D2R deletion appears to impair a neural substrate of action chunking. Virally replacing D2Rs in dStr ChIs in adult mice improves action sequence learning, but not the lower breakpoints, further suggesting that D2Rs on ChIs in the dStr are critical for sequence learning, but not for driving the motivational aspects of the task. Significance statement The role of striatal projection neurons in encoding action sequences has been extensively studied, and cholinergic interneurons play a central role in striatal physiology, but we do not yet understand how cholinergic interneurons contribute to action sequencing. Using a combination of mouse genetics, behavior, and in vivo electrophysiology this work shows that genetic deletion of D2 receptors from striatal cholinergic interneurons disrupts the learning, performance, and encoding of action sequences, without changing general locomotion or motor skill learning. Virally replacing D2 receptors specifically in dorsal striatal cholinergic interneurons is sufficient to rescue the sequence behavior. Our observations may be useful in understanding and treating movement disorders in which dopamine and acetylcholine are imbalanced.
Solid phase extraction combined with energy dispersive X-ray fluorescence spectrometry for multielement determination

Abstract In this review, general aspects of the combination of the solid phase extraction (SPE) with energy dispersive X-ray fluorescence spectrometry (EDXRF) for multielement determination are presented. Derivations of SPE, such as dispersive solid phase extraction (DSPE), dispersive micro-solid phase extraction (DµSPE), and dispersive magnetic micro-solid phase extraction DM-µSPE are also presented, showing the possibility of direct analysis of the solid phase. The sorbents, advantages, disadvantages, and the analytical characteristics of the combination followed by direct determination of analytes retained on the solid phase are discussed. Furthermore, the perspectives of this analytical arrangement are presented.
Feasibility, comprehensibility and acceptability of the VISION-Cog, a novel tool to assess cognitive impairment in visually impaired older adults: a cross-sectional pilot study in Singapore

Objectives We pilot-tested the VISually Independent test battery Of NeuroCOGnition (VISION-Cog) to determine its feasibility, comprehensibility and acceptability in evaluating cognitive impairment (CI) in visually impaired older Asian adults. Design The VISION-Cog was iteratively fine-tuned through pilot studies and expert-panel discussion. In the first pilot study (Stage 1), we recruited 15 visually impaired and cognitively normal participants aged ≥60 years to examine the pilot VISION-Cog’s feasibility (length of time to administer), comprehensibility (clarity of instructions) and acceptability (participant burden). We then presented the pilot results to the expert panel (Stage 2) who decided via agreement on a revised version of the VISION-Cog. Subsequently, we conducted a second pilot study (Stage 3) on another four participants to ascertain improvement in feasibility, comprehensibility and acceptability of the revised version. Setting Singapore Eye Research Institute. Participants Nineteen Asian adults aged ≥60 years with visual impairment (defined as near visual acuity worse than N8) were recruited. Outcome measure Revised VISION-Cog. Result The VISION-Cog was deemed feasible, taking approximately 60 min to complete on average. All participants agreed that the test instructions were clear, and the battery did not cause undue discomfort or frustration. The data collector rated all tests as very user-friendly (score of 5/5). Minor modifications to the pilot VISION-Cog were suggested by the panel to improve its safety, clarity of instructions and content validity, which were incorporated and iteratively tested in the second pilot study until no further issues emerged. Conclusions Using an iterative mixed-methods process, we have developed a feasible, comprehensible and acceptable 5-domain and 9-item visually independent VISION-Cog test battery suitable to assist CI diagnosis in older adults with visual impairment. We will assess its diagnostic potential against clinician-based assessment of CI in subsequent phases.
Topic Sensitive Neural Headline Generation

Neural models have recently been used in text summarization including headline generation. The model can be trained using a set of document-headline pairs. However, the model does not explicitly consider topical similarities and differences of documents. We suggest to categorizing documents into various topics so that documents within the same topic are similar in content and share similar summarization patterns. Taking advantage of topic information of documents, we propose topic sensitive neural headline generation model. Our model can generate more accurate summaries guided by document topics. We test our model on LCSTS dataset, and experiments show that our method outperforms other baselines on each topic and achieves the state-of-art performance.
Full-Scale Information Diffusion Prediction With Reinforced Recurrent Networks

Information diffusion prediction is an important task, which studies how information items spread among users. With the success of deep learning techniques, recurrent neural networks (RNNs) have shown their powerful capability in modeling information diffusion as sequential data. However, previous works focused on either microscopic diffusion prediction, which aims at guessing who will be the next influenced user at what time, or macroscopic diffusion prediction, which estimates the total numbers of influenced users during the diffusion process. To the best of our knowledge, few attempts have been made to suggest a unified model for both microscopic and macroscopic scales. In this article, we propose a novel full-scale diffusion prediction model based on reinforcement learning (RL). RL incorporates the macroscopic diffusion size information into the RNN-based microscopic diffusion model by addressing the nondifferentiable problem. We also employ an effective structural context extraction strategy to utilize the underlying social graph information. Experimental results show that our proposed model outperforms state-of-the-art baseline models on both microscopic and macroscopic diffusion predictions on three real-world datasets.
Word Embeddings Position Embeddings Max Operation Vector Representation Convolution Layer Max Pooling Non-linear Activation Output Vector

Distantly supervised relation extraction has been widely used to find novel relational facts from plain text. To predict the relation between a pair of two target entities, existing methods solely rely on those direct sentences containing both entities. In fact, there are also many sentences containing only one of the target entities, which also provide rich useful information but not yet employed by relation extraction. To address this issue, we build inference chains between two target entities via intermediate entities, and propose a path-based neural relation extraction model to encode the relational semantics from both direct sentences and inference chains. Experimental results on realworld datasets show that, our model can make full use of those sentences containing only one target entity, and achieves significant and consistent improvements on relation extraction as compared with strong baselines. The source code of this paper can be obtained from https:// github.com/thunlp/PathNRE.
THUNLP at TAC KBP 2013 in Entity Linking

This paper describes the THUNLP system submitted to Entity Linking task of KBP Track in TAC 2013. This system achieves the third place with a B-cubed+ F1 score of 0.712 in mono-lingual entity linking task. In Chinese cross-lingual entity linking, this system achieved B-cubed+ F1 score of 0.647 with the help of Google Translate.
Orthogonal object proposal and its application

In this study, the authors propose an object proposal algorithm that can accurately propose object candidate regions at each frame, despite noise in a video. Accordingly, they define three orthogonal planes, namely vertical–horizontal, temporal–vertical, and temporal–horizontal planes. As these planes are orthogonal, they are the most compact planes that can span the spatiotemporal space of a video. Their algorithm selects good object proposals for the vertical–horizontal plane with the help of the object proposal results of the other planes. Experimental results demonstrate that the proposed algorithm produces better object proposals than the baseline algorithm and other state-of-the-art methods. In particular, their method provides more accurate object proposals in challenging environments with severe noise and background clutter. In addition, the object proposal results are utilised for visual tracking problems, and the experimental results show that their visual tracker outperforms recent deep-learning-based trackers.
Correlation between structure-specific intensity measures of site-dependent motions and frame response

The assessment of the seismic performance of a structure depends on the optimal choice of an earthquake Intensity Measure (IM). Given the fact that conventional IMs based only on ground motion information might not be able to successfully predict the seismic response of structures, several advanced structural-specific IMs have been proposed during the past years, taking into account not only earthquake characteristics but also structural information. Moreover, local site conditions may generate large amplifications as well as spatial variations in the ground motions, which influence the intensity measures and in most cases lead to important structural damage. Along these lines the objective of this paper is to study the correlation between well-known structure-specific intensity measures and the inelastic response of multi-story reinforced concrete planar frames taking into account site effects. First, site dependent ground motions are produced considering 2D analysis of the soil profile via Boundary Element Method (BEM) numerical technique. Three different geological configurations are considered that account for (i) uniform excitation, ii) canyon topography and iii) complex hills topography. Next, we focus on the dynamic behavior of two reinforced concrete frames (a symmetric and an asymmetric one) modeled and analyzed by the Finite Element Method (FEM). The buildings are subjected to a set of site-dependent strong motions and the expected structural damage state of each building is determined in terms of the Maximum Interstory Drift Ratio (MIDR). Then, a number of structure-specific seismic intensity measures is computed from the aforementioned site-dependent ground motions. The examined intensity measures take into account special characteristics of both the earthquake record and the building under consideration. The values of the MIDRs are correlated with the structure-specific ground motion intensity measures. In sum, the numerical results of this study show that certain intensity measures exhibit strong correlation with the seismic damage of the two buildings. However, their adequacy for estimation of structural response depends strongly on the local site conditions under investigation.