Miracle-dz/UniFAR-FTUs huggingface dataset:
Precursors of self-reported subclinical hypomania in adolescence: A longitudinal general population study

Symptoms of subclinical hypomania (SHM) are common in the general population of adolescents and young adults. SHM are most often transient yet might be risk markers of later bipolar disorder. The current study aimed to assess the clinical correlates of SHM at age 11 in the general population, examine the continuity of SHM from age 11-age 16 and explore the clinical precursors of age 16 SHM. As part of the Copenhagen Child Cohort 2000, 1,632 preadolescents participated in the examination of SHM and various clinical correlates at age 11, 893 were re-assessed for SHM at age 16 years. At age 11, SHM, psychotic experiences and depressive symptoms were assessed by semi-structured psychopathological interviews. Furthermore, the participants were diagnostically assessed by the Development and Well-Being Assessment and interviewed about sleep length. At age 16, SHM was assessed by self-report, using the Hypomania Checklist-32. Cannabis use occurring at age 15 or earlier was assessed at age 16. At age 11, SHM was associated with depressive disorders (Relative Risk [RR] = 2.96 [95% CI 1.26–6.96]), interview-based depressive symptoms (RR = 9.22 [5.93–14.34]), neurodevelopmental disorders (RR = 2.94 [1.66–5.20]), psychotic experiences (RR = 4.51 [2.90–7.01]) and insufficient sleep (RR = 2.10 [1.28–3.43]. In the longitudinal analyses, age 16 SHM was preceded by age 11 SHM (RR = 1.89 [1.02–3.49]), psychotic experiences (RR = 2.06, [1.28–3.33]), emotional disorders (RR = 1.77, [1.02–3.09]) and cannabis use (RR = 3.14, [1.93–5.10]), after mutual adjustment and adjustment for sex, and sociodemographic factors. In conclusion, age 11 SHM was statistically significantly associated with other types of psychopathology in cross-sectional analyses and showed some continuity with later self-reported SHM at age 16. Particularly early psychotic experiences and cannabis use stood out as independent precursors of self-reported SHM and might constitute important risk markers for the development of future SHM and bipolar disorder. An important potential caveat of the current study includes the self-report assessment of SHM.
Social and non‐social sensory responsivity in toddlers at high‐risk for autism spectrum disorder

Empirical evidence concerning sensory responsivity in young children who later develop autism spectrum disorder (ASD) remains relatively limited. It is unclear whether specific patterns or aspects of sensory responsivity underlay the emergence of the disorder. The goals of this study were to (a) examine whether social versus non‐social context impacted the expression of sensory responsivity in infants at high risk for ASD, and (b) examine if sensory responsivity in social or non‐social contexts was associated with severity of ASD symptoms. The Sensory Experiences Questionnaire 2.1 was collected for 338 infants (131 females, 207 males) at high‐risk for ASD at 12 and/or 24 months of age. High‐risk toddlers meeting diagnostic criteria for ASD (n = 75) showed elevated sensory responsivity in both social and non‐social contexts at 12 months of age and differences widened over the second year of life. Individuals with ASD demonstrate higher responsivity in both contexts suggestive of generalized atypical sensory responsivity in ASD.
Basic human values during the COVID-19 outbreak, perceived threat and their relationships with compliance with movement restrictions and social distancing

This study examines the evolution of Schwartz’s Basic Human Values during the COVID-19 outbreak, and their relationships with perceived threat, compliance with movement restrictions and social distancing. An online questionnaire was administered to a heterogeneous sample of French citizens (N = 1025) during the first French lockdown related to the outbreak. Results revealed a significant evolution of values; the conservation value was higher during the outbreak than usual, and both self-enhancement and openness-to-change values were lower during the COVID-19 outbreak than usual. Conservation and perceived threat during the outbreak were robustly and positively related to both compliance with movement restrictions and social distancing. Conservation during the outbreak emerged as a significant partial mediator of the relationship between perceived threat and outcomes (i.e., compliance with movement restrictions and social distancing). Implications of these results for the malleability of values and the COVID-19 modelling are discussed.
The Distribution of Gases within the Combustion Coal of a Cigarette

Abstract Measurements have been made of the distribution of temperature and low molecular weight gases within a burning cigarette, using a sampling probe coupled directly to a mass spectrometer (or Bosch carbon monoxide meter). The interior of the combustion coal is effectively an oxygen-deficient pyrolytic region. The oxides of carbon are produced in two distinct regions: a high-temperature (about 400-800°C) combustion region and a low- temperature (about 150-400°C) pyrolysis region. In the high-temperature coal the carbonised tobacco acts very much as a classical oxidizing solid fuel bed of carbon to give the two carbon oxides (and water). In the low-temperature region behind the coaI tobacco decomposes to give a substantiaI proportion of the carbon oxides and a major proportion of the hydrocarbons found in mainstream smoke.
Extracting Semantic Representations of Sexual Biases from Word Vectors

Sexually biased cyberhate speech has become a fast-growing problem on PTT (a representative online forum in Taiwan). The applications of computational linguistics like word embeddings would also carry similar biases. This paper analyzed the distribution of word representations of netizens from mu zhu jiao (a cult that often produces misogynistic cyberhate speech). Word vector representations (word2vec) was utilized for scrutinizing semantic representations of texts found on PTT. The findings from the distributed semantic representation of mu zhu jiao implied a sexual bias against them. This paper serves as the first study which investigates the distribution of word representations of the abusive language on PTT forum with an NLP method by taking advantage of both quantitative and qualitative methods.
Sequence to Sequence Convolutional Neural Network for Automatic Spelling Correction

The paper proposes a system that compensates most of the noise in a text in natural language caused by technical imperfection of the input device such as keyboard or scanner with optical character recognition, quick typing, or writer incompetence. Correcting the spelling errors in the text improves the performance of the following natural language processing. The incorrect sequence of characters is transcribed into another sequence of correct characters by a neural network with encoder-decoder architecture. Our approach to automatic spelling correction considers characters in an erroneous sentence as words of the source languages. The neural network searches for the best sequence of output characters for the given input. The proposed approach for spelling correction does not require any or minimal amount of training data. Instead, the error model is expressed by a simple component that distorts unannotated data and creates any necessary quantity of training examples for a neural network. The experimental results show that the presented approach significantly improves the distorted data (from 50% WER to 0.09% WER) with distortion lower than 1.5% WER.
Bilingual Parallel Sentence Extraction from Comparable Corpora

This research aims to develop a parallel sentence extraction method for automatically extracting parallel sentence pairs from bilingual comparable corpora based on cross-lingual word embeddings. Our task is to effectively identify matched sentence pairs from a Chinese-English corpus with the goal of maximizing F1 score. Our method employs pre-trained, task-specific, and hybrid (a combination of pre-trained and task-specific) monolingual word embeddings to construct a cross-lingual transformation matrix respectively to transform the word embeddings between the two languages, and develops two search strategies (sequential and exhaustive) for parallel sentence extraction. Our empirical evaluation results suggest that task-specific word embeddings (directly trained from a task-relevant corpus, i.e., 25,695 Chinese and English abstracts of theses) outperforms their counterparts. With respect to the two search strategies, our evaluation results suggest that the exhaustive search strategy attains a higher recall rate; the sequential search strategy is more efficient in time. Both strategies achieve a promising performance, with an F1 score up to 60.18%.
A Real-World Human-Machine Interaction Platform in Insurance Industry

In the insurance industry, lots of effort is putting into helping the customer to solve their problems that occurred during and after purchasing cycle and helping telemarketers to practice selling skills. Chat bots and assistant bots are widely used in these business scenarios, but building a bot application from scratch is expensive. In this paper, a human-machine interaction platform specially designed for intelligent bot applications in insurance industry that combined the technologies of Question Answering (QA), task-oriented dialogue and chit-chat was proposed and we demonstrate the architecture design of this platform, key technologies and the scenario of applications in real-world insurance industry. It has been supporting many intelligent bot applications of insurance industry already, such as Intelligent Coach Bot (ICB) which helps telemarketers to practice their selling skills, Intelligent Customer Service Bot (ICSB) which provides after-sales services and Insurance Advisor Bot (IAB) which helps customer to purchase the most suitable insurance product. Currently, these bot applications serve millions of users per day and are able to solve 80% of the online problems.
Biocomposites Based on Agar and Cellulose Nanofibers Prepared from Carrot Slag

In this study, the effect of cellulose nanofibers (CNF) prepared from carrot slag on the properties of agar biocomposite films is investigated. The composite film was characterized by ultraviolet–visible spectroscopy (UV-Vis), tensile test, fourier transforms infrared (FT-IR) spectroscopy and Transmission electron microscopy (TEM). The transmittance, mechanical properties and chemical structure of the composite film containing different CNF content (0.1, 0.3 and 0.5 phr based on agar) were studied. The UV-Vis showed that the transmittance of the film was decreased with increasing content of CNF. The FT-IR spectrum showed that the generation of hydrogen bonds leads to good interface bonding between Agar and CNF. Moreover, the performance of the bionanocomposite was improved by the addition of CNF. The composite containing 0.3 phr CNF results in a maximum tensile strength of 25.97 MPa. However, the tensile strength of the 0.5 phr CNF containing one is reduced to 24.42 MPa due to the agglomeration of CNF. The TEM shows that the diameter of CNF is 2.5 nm and the length is 18.20 nm. The usage of CNF obtained from carrot slag can not only recycle the waste from food industry, but also can be used as a reinforcing agent for preparing biodegradable composite film. It has potential uses in the development of biodegradable food packaging materials and biomedical applications.
Clinical characteristics and treatment patterns with histrelin acetate subcutaneous implants vs. leuprolide injections in children with precocious puberty: a real-world study using a US claims database

Abstract Objectives Gonadotropin-releasing hormone analogs are the treatment of choice for central precocious puberty (CPP). This study characterizes patients treated with histrelin implant or leuprolide injection. Methods A US claims database was used to identify patients aged ≤20 years with ≥1 histrelin or leuprolide claim (index treatment) between April 2010 and November 2017 and continuous enrollment ≥3 months before and ≥12 months after the index treatment date. Results Overall, 4,217 patients (histrelin, n=1,001; leuprolide, n=3,216) were identified. The percentage of patients with CPP diagnosis was greater in the histrelin (96.5%) vs. leuprolide (68.8%; p<0.0001) cohort. In patients with CPP (histrelin, n=966; leuprolide, n=2,214), mean age at treatment initiation was similar for histrelin (9.0 ± 2.0 years) and leuprolide (9.1 ± 2.3 years), with >50% of patients aged 6–9 years. Mean treatment duration was significantly longer for histrelin (26.7 ± 14.8 months) vs. leuprolide (14.1 ± 12.1 months; p<0.0001), and was longer in younger patient groups. More patients switched from leuprolide to histrelin (12.3%) than vice versa (3.6%; p<0.0001). Median annual total treatment costs were slightly lower for the histrelin cohort ($23,071 [interquartile range, $16,833–$31,050]) than the leuprolide cohort ($27,021 [interquartile range, $18,314–$34,995]; p<0.0001). Conclusions Patients with CPP treated with histrelin had a longer duration of treatment, lower rates of index treatment discontinuation, and lower annual treatment costs vs. those treated with leuprolide.
European Stroke Organisation (ESO) guidelines on the management of space-occupying brain infarction

Space-occupying brain oedema is a potentially life-threatening complication in the first days after large hemispheric or cerebellar infarction. Several treatment strategies for this complication are available, but the size and quality of the scientific evidence on which these strategies are based vary considerably. The aim of this Guideline document is to assist physicians in their management decisions when treating patients with space-occupying hemispheric or cerebellar infarction. These Guidelines were developed based on the European Stroke Organisation (ESO) standard operating procedure and followed the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach. A working group identified 13 relevant questions, performed systematic reviews and meta-analyses of the literature, assessed the quality of the available evidence, and wrote evidence-based recommendations. An expert consensus statement was provided if not enough evidence was available to provide recommendations based on the GRADE approach. We found high-quality evidence to recommend surgical decompression to reduce the risk of death and to increase the chance of a favourable outcome in adult patients aged up to and including 60 years with space-occupying hemispheric infarction who can be treated within 48 hours of stroke onset, and low-quality evidence to support this treatment in older patients. There is continued uncertainty about the benefit and risks of surgical decompression in patients with space-occupying hemispheric infarction if this is done after the first 48 hours. There is also continued uncertainty about the selection of patients with space-occupying cerebellar infarction for surgical decompression or drainage of cerebrospinal fluid. These Guidelines further provide details on the management of specific subgroups of patients with space-occupying hemispheric infarction, on the value of monitoring of intracranial pressure, and on the benefits and risks of medical treatment options. We encourage new high-quality studies assessing the risks and benefits of different treatment strategies for patients with space-occupying brain infarction.
splatPop: simulating population scale single-cell RNA sequencing data

Population-scale single-cell RNA sequencing (scRNA-seq) is now viable, enabling finer resolution functional genomics studies and leading to a rush to adapt bulk methods and develop new single-cell-specific methods to perform these studies. Simulations are useful for developing, testing, and benchmarking methods but current scRNA-seq simulation frameworks do not simulate population-scale data with genetic effects. Here, we present splatPop, a model for flexible, reproducible, and well-documented simulation of population-scale scRNA-seq data with known expression quantitative trait loci. splatPop can also simulate complex batch, cell group, and conditional effects between individuals from different cohorts as well as genetically-driven co-expression.
High-speed multifocus phase imaging in thick tissue

Phase microscopy is widely used to image unstained biological samples. However, most phase imaging techniques require transmission geometries, making them unsuited for thick sample applications. Moreover, when applied to volumetric imaging, phase imaging generally requires large numbers of measurements, often making it too slow to capture live biological processes with fast 3D index-of-refraction variations. By combining oblique back-illumination microscopy and a z-splitter prism, we perform phase imaging that is both epi-mode and multifocus, enabling high-speed 3D phase imaging in thick, scattering tissues with a single camera. We demonstrate here 3D qualitative phase imaging of blood flow in chick embryos over a field of view of 546 × 546 × 137 μm3 at speeds up to 47 Hz.
Peripheral CB1 receptor blockade acts as a memory enhancer through an adrenergic-dependent mechanism

Peripheral inputs to the brain continuously shape its function and can influence the formation of non-emotional memory, but the underlying mechanisms have not been fully understood. Cannabinoid type-1 receptors (CB1R), widely distributed in the organism, is a well-recognized player in memory performance, and its systemic modulation significantly influences memory function. By assessing non-emotional memory in mice, we have now found a relevant role of peripheral CB1R in the formation of persistent memory. Indeed, peripherally restricted CB1R antagonism by using AM6545 showed a mnemonic effect that was occluded in adrenalectomized mice, after peripheral adrenergic blockade, or when vagus nerve was chemogenetically inhibited. Genetic CB1R deletion in dopamine β-hydroxylase-expressing cells enhanced the formation of persistent memory, supporting a role of peripheral CB1R modulating the adrenergic tone. Notably, brain connectivity was affected by peripheral CB1R inhibition, and locus coeruleus activity and extracellular hippocampal norepinephrine, were increased. In agreement, intra-hippocampal β-adrenergic blockade prevented AM6545 mnemonic effects. Together, we disclose a novel peripheral mechanism relevant for the modulation of the formation of persistent non-emotional memory.
Presynaptic Mitochondrial Volume and Density Scale with Presynaptic Power Demand

Stable neural function requires an energy supply that can meet the intense episodic power demands of neuronal activity. The bioenergetic machinery of glycolysis and oxidative phosphorylation is highly responsive to such demands, but it must occupy a minimum volume if it is to accommodate these demands. We examined the trade-off between presynaptic power demands and the volume available to the bioenergetic machinery. We quantified the energy demands of six Drosophila motor nerve terminals through direct measurements of neurotransmitter release and Ca2+ entry, and via theoretical estimates of Na+ entry and power demands at rest. Electron microscopy revealed that terminals with the highest power demands contained the greatest volume of mitochondria, indicating that mitochondria are allocated according to presynaptic power demands. In addition, terminals with the greatest power demand-to-volume ratio (∼66 nmol·min-1·μL-1) harbor the largest mitochondria packed at the greatest density. If we assume sequential and complete oxidation of glucose by glycolysis and oxidative phosphorylation, then these mitochondria are required to produce ATP at a rate of 52 nmol·min-1·μL-1 at rest, rising to 963 during activity. Glycolysis would contribute ATP at 0.24 nmol·min-1·μL-1 of cytosol at rest, rising to 4.36. These data provide a quantitative framework for presynaptic bioenergetics in situ, and reveal that, beyond an immediate capacity to accelerate ATP output from glycolysis and oxidative phosphorylation, over longer time periods presynaptic terminals optimize mitochondrial volume and density to meet power demand. Significance Statement The remarkable energy demands of the brain are supported by the complete oxidation of its fuel but debate continues regarding a division of labor between glycolysis and oxidative phosphorylation across different cell types. Here we leverage the neuromuscular synapse, a model for studying neurophysiology, to elucidate fundamental aspects of neuronal energy metabolism that ultimately constrain rates of neural processing. We quantified energy production rates required to sustain activity at individual nerve terminals and compared these data with the volume capable of oxidative phosphorylation (mitochondria) and glycolysis (cytosol). We find strong support for oxidative phosphorylation playing a primary role in presynaptic terminals and provide the first in vivo estimates of energy production rates per unit volume of presynaptic mitochondria and cytosol.
Emergent Statistical Laws in Single-Cell Transcriptomic Data

Large scale data on single-cell gene expression have the potential to unravel the specific transcriptional programs of different cell types. The structure of these expression datasets suggests a similarity with several other complex systems that can be analogously described through the statistics of their basic building blocks. Transcriptomes of single cells are collections of messenger RNA abundances transcribed from a common set of genes just as books are different collections of words from a shared vocabulary, genomes of different species are specific compositions of genes belonging to evolutionary families, and ecological niches can be described by their species abundances. Following this analogy, we identify several emergent statistical laws in single-cell transcriptomic data closely similar to regularities found in linguistics, ecology or genomics. A simple mathematical framework can be used to analyze the relations between different laws and the possible mechanisms behind their ubiquity. Importantly, treatable statistical models can be useful tools in transcriptomics to disentangle the actual biological variability from general statistical effects present in most component systems and from the consequences of the sampling process inherent to the experimental technique. Author summary Gene expression profiles represent how different cells use their genetic information. Similarly, books are specific collections of words chosen from a shared vocabulary, and many complex systems can be ultimately described by the statistics of their basic components. Leveraging on this analogy, we identified several emergent statistical laws in single-cell transcriptomic data that are universally found in complex component systems. A simple mathematical description sets these laws in a treatable quantitative framework and represents a useful tool for dissecting the different sources of gene expression variability.
Whole Genome Sequence and CAZyme distribution of the cellulase hyper producing filamentous fungus Penicillium janthinellum NCIM 1366

Penicillium janthinellum NCIM 1366, capable of secreting cellulases that are highly efficient in the hydrolysis of lignocellulosic biomass, was sequenced to understand its cellulolytic machinery. De novo sequencing and assembly revealed a 37.6 Mb genome encoding 11,848 putative proteins, 93% of which had significant BLAST-P hits. The majority of the top hits (those with over 60% UniProt identity) belonged to P. brasilianum. Carbohydrate active enzymes (CAZymes) and other enzymes involved in lignocellulose degradation were also predicted from this strain and compared with those of the industrial workhorse of cellulase production-Trichoderma reesei RUT-C30. The comparison showed that the fungus encodes a far higher number of CAZYmes (422) as compared to T. reesei RUT-C30 (244), which gives a plausible explanation for its overall effectiveness in biomass hydrolysis. An analysis of the secreted CAZymes and annotated ligninases identified 216 predicted proteins which may be directly involved in the breakdown of lignocellulose.