Miracle-dz/UniFAR-FTUs huggingface dataset:
Dopamine and ALK4 signaling synergize to induce PCBP1-mediated alternative splicing of FosB and sustained behavioral sensitization to cocaine

ΔFosB, an alternative spliced product of FosB, is an essential component of dopamine-induced reward pathways and a master switch for addiction. However, the molecular mechanisms of its generation and regulation by dopamine signaling are unknown. Here we report that dopamine D1 receptor signaling synergizes with the activin/ALK4/Smad3 pathway to potentiate the generation of ΔFosB mRNA in medium spiny neurons (MSNs) of the nucleus-accumbens (NAc) through activation of the RNA binding protein PCBP1, a regulator of mRNA splicing. Concurrent activation of PCBP1 and Smad3 by D1 and ALK4 signaling induced their interaction, nuclear translocation, and binding to sequences in exon-4 and intron-4 of FosB mRNA. Ablation of either ALK4 or PCBP1 in MSNs impaired ΔFosB mRNA induction and nuclear translocation of ΔFosB protein in response to repeated co-stimulation of D1 and ALK4 receptors. Importantly, ALK4 was required in NAc MSNs of adult mice for behavioral sensitization to cocaine. These findings uncover an unexpected mechanism for ΔFosB generation and drug-induced sensitization through convergent dopamine and ALK4 signaling.
On the Existence of Competitive Equilibrium with Chores

We study the chore division problem in the classic Arrow-Debreu exchange setting, where a set of agents want to divide their divisible chores (bads) to minimize their disutilities (costs). We assume that agents have linear disutility functions. Like the setting with goods, a division based on competitive equilibrium is regarded as one of the best mechanisms for bads. Equilibrium existence for goods has been extensively studied, resulting in a simple, polynomial-time veriﬁable, necessary and sufﬁcient condition. However, dividing bads has not received a similar extensive study even though it is as relevant as dividing goods in day-to-day life. In this paper, we show that the problem of checking whether an equilibrium exists in chore division is NP-complete, which is in sharp contrast to the case of goods. Further, we derive a simple, polynomial-time veriﬁable, sufﬁcient condition for existence. Our ﬁxed-point formulation to show existence makes novel use of both Kakutani and Brouwer ﬁxed-point theorems, the latter nested inside the former, to avoid the undeﬁned demand issue speciﬁc to bads.
Applying Peer Instruction to Computer Science Students Using Non-native Language: A Study with Undergraduate Students

Peer Instruction (PI) has been applied widely in several institutions due to its success in supporting students' engagement and improving learning outcomes. This study examined the application of PI to an Introductory Computer Science course for year-one students taught in English that is not their native language. We aimed to identify the effectiveness of PI to improve students' content learning and English skills. Throughout the analysis of a survey of students' perceptions, we found evidence of the success of PI in terms of engagement and learning of the students, as occurred in previous studies. We found also encouraging results regarding the opportunities provided by PI to improve students non-native language skills. However, we found alarming results regarding the lack of pre-class reading preparation. Instructors should handle this issue since it is a crucial component when implementing the PI methodology for content learning and knowledge acquisition.
Analysis Of Heavy Rain And Typhoons Effect On The Ground Surface Using DInSAR Technique

In this research, we carried out the analysis of long-term continuous ground deformation (subsidence or uplift) based on C-band Differential Interferometric Synthetic Aperture Radar (DInSAR). This technique is employed to investigate ground deformation of the Yokohama and Miura cities of Kanagawa prefecture, Japan. The observation was starting from October 2Sth, 2017 to May 3rd, 2019. The study data used Sentinel-1 C-band data provided by the European Space Agency (ESA). The results of the research show that the maximum subsidence velocity of ground deformation was 5.89 cm/year, and the maximum uplift velocity was 8.36 cm/year in Yokohama city. Also, in Miura city, the maximum subsidence velocity of the ground deformation was 4.5 cm/year, and the maximum uplift velocity was 11.4 cm/year. In both cities, satellite SAR analysis results have the same tendency with each GNSS control point, and the difference of the subsidence was within approximately 0.5 cm. This result shows the analysis data of DInSAR was almost equal compare to the global navigation satellite system (GNSS) data by Geographical Survey Institute (GSI). This research shows the capability of the DInSAR technique to investigate long-term continuous ground surface conditions over a wide area with high accuracy in association with the occurrence of heavy rains and typhoons.
Shared-memory implementation of the Karp-Sipser kernelization process

We investigate the parallelization of the Karp-Sipser kernelization technique, which consti-tutes the central part of the well-known Karp-Sipser heuristic for the maximum cardinality matching problem. The technique reduces a given problem instance to a smaller but equivalent one, by repeated applications of two operations: vertex removal, and merging two vertices. The operation of merging two vertices poses the principal challenge in parallelizing the technique. We describe an algorithm that min-imizes the need for synchronization and present an efficient shared-memory parallel implementation of the kernelization technique for bipartite graphs. Using extensive experiments on a variety of multicore CPUs, we show that our implementation scales well up to 32 cores on one socket.
Depression Screening Using Deep Learning on Follow-up Questions in Clinical Interviews

Depression is a very common mental health disorder with a devastating social and economic impact. It can be costly and difficult to detect, traditionally requiring a significant number of hours by a trained psychiatrist. Recently, machine learning models have been trained for depression screening using patient voice recordings from an interview driven by a virtual agent. To engage the patient in a conversation and increase the quantity of responses, the virtual interviewer asks a series of follow-up questions. For obvious reason, a subject would prefer to have to answer fewer questions. Unfortunately, it is unknown to date if these series of follow-on questions have a tangible impact on the performance of deep learning models for depression classification. Therefore, we study the effect of including one, two, or more follow-up questions on depression screening. We apply a pretrained-on-voice transfer learning model, namely, VGGish-based model, to classify different subsequences of audio clips. We find that follow-up questions can help to increase the F1 score for the majority of questions, with two questions resulting in the highest F1 scores. Our results can be leveraged for the design of future mental illness screening applications by informing us not only about the selection of the most effective questions but also the number of follow-up questions typically required for screening to produce reliable results.
The Sinorhizobium meliloti Nitrogen Stress Response Changes Radically in the Face of Concurrent Phosphate Stress

Expression of hundreds of S. meliloti genes changed more than two-fold in response to either nitrogen or phosphate limitation. When these two stresses were applied together, stress responsive gene expression shifted dramatically. In particular, the nitrogen stress response in the presence of phosphate stress had only 30 of about 350 genes in common with the 280 genes that responded to nitrogen stress with adequate phosphate. Expression of sRNAs was also altered in response to these stresses. 82% of genes that responded to nitrogen stress also responded to phosphate stress, including 20 sRNAs. A subset of these sRNAs is known to be chaperoned by the RNA binding protein, Hfq. Hfq had previously been shown to influence about a third of the genes that responded to both nitrogen and phosphate stresses. Phosphate limitation influenced changes in gene expression more than nitrogen limitation and, when both stresses were present, phosphate stress sometimes reversed the direction of some of the changes induced by nitrogen stress. These nutrient stress responses are therefore context dependent.
Individual Sensitivity to Change in the Lingua Franca Use of English

The study of ongoing change in English typically focuses on studying evidence from codified varieties of the language. Recent corpus studies show, however, that advanced non-native users of English may display heightened sensitivity to features undergoing frequency shifts similar to that experienced by native speakers. In addition, most studies aiming to detect patterns of linguistic regularity utilize large data sets that attempt to minimize the presence of the individual. In this study, we focus on change in ELF and place non-native individuals at the center of attention. Our empirical section examines how aggregated features that are currently undergoing change in codified varieties of English vary in the repertoires of ELF users of Twitter. To carry out this task, this study utilizes geo-tagged tweets retrieved from the Nordic Tweet Stream. The data obtained from this real-time monitor corpus are freely available for research and re-use at https://cs.uef. fi/nts/. For the analysis itself, we selected the idiolects of 150 individual users who actively tweet in English from geographically varying locations in Finland. As American English predominates with several patterns of linguistic change in codified varieties of English, a simplified dichotomy between American and British features is utilized as a conceptual tool for inspecting variation. The idiolects are analyzed from the perspective of spelling and lexico-grammatical and morphological variation, such as V + -ing |V + infinitive (e.g. start doing | start to do) and expanded predicates (e.g. take a look | have a look). The quantitative observations show that, particularly in the case of grammatical features, ELF speakers appear to have generally adhered to ongoing linguistic change.
Integrative Metabolomics, Proteomics and Transcriptomics Analysis Reveals Liver Toxicity of Mesoporous Silica Nanoparticles

As pharmaceutical excipients, mesoporous silica nanoparticles (MSNs) have attracted considerable concern based on potential risks to the public. The impact of MSNs on biochemical metabolism is poorly understood, and few studies have compared the effects of MSNs administered via different routes. To evaluate the hepatotoxicity of MSNs, metabolomics, proteomics and transcriptomic analyses were performed in mice after intravenous (20 mg/kg/d) or oral ad-ministration (200 mg/kg/d) of MSNs for 10 days. Intravenous injection induced significant hepatic injury based on pathological inspection and increased the levels of AST/ALT and the inflammatory factors IL-6, IL-1β and TNF-a. Omics data suggested intravenous administration of MSNs perturbed the following metabolites: succinate, hypoxanthine, GSSG, NADP+, NADPH and 6-phosphogluconic acid. In addition, increases in GPX, SOD3, G6PD, HK, and PFK at proteomic and transcriptomic levels suggested elevation of glycolysis and pentose phosphate pathway, synthesis of glutathione and nucleotides, and antioxidative pathway activity, whereas oxidative phosphorylation, TCA and mitochondrial energy metabolism were reduced. On the other hand, oral administration of MSNs disturbed inflammatory factors and metabolites of ribose-5-phosphate, 6-phosphogluconate, GSSG, and NADP+ associated with the pentose phosphate pathway, glutathione synthesis and oxidative stress albeit to a lesser extent than intravenous injection despite the administration of a ten-fold greater dose. Overall, systematic biological data suggested that intravenous injection of nanoparticles of pharmaceutical excipients substantially affected hepatic metabolism function and induced oxidative stress and inflammation, whereas oral administration exhibited milder effects compared with intravenous injection.
Current State and Future Directions of Multimodality Imaging in Cardiac Sarcoidosis

Cardiac sarcoidosis (CS) is an increasingly recognized cause of heart failure and arrhythmia. Historically challenging to identify, particularly in the absence of extracardiac sarcoidosis, diagnosis of CS has improved with advancements in cardiac imaging. Recognition as well as management may require interpretation of multiple imaging modalities. Echocardiography may serve as an initial screening study for cardiac involvement in patients with systemic sarcoidosis. Cardiac magnetic resonance imaging (CMR) provides information on diagnosis as well as risk stratification, particularly for ventricular arrhythmia in the setting of late gadolinium enhancement. More recently, 18F-fluorodeoxyglucose position emission tomography (FDG-PET) has assumed a valuable role in the diagnosis and longitudinal management of patients with CS, allowing for the assessment of response to treatment. Hybrid FDG-PET/CT may also be used in the evaluation of extracardiac inflammation, permitting the identification of biopsy sites for diagnostic confirmation. Herein we examine the approach to diagnosis and management of CS using multimodality imaging via a case-based review.
Life Habits and Mental Health: Behavioural Addiction, Health Benefits of Daily Habits, and the Reward System

In this review, the underlying mechanisms of health benefits and the risk of habitual behaviours such as internet use and media multitasking were explored, considering their associations with the reward/motivation system. The review highlights that several routines that are beneficial when undertaken normally may evolve into excessive behaviour and have a negative impact, as represented by “the inverted U-curve model”. This is especially critical in the current era, where technology like the internet has become mainstream despite the enormous addictive risk. The understanding of underlying mechanisms of behavioural addiction and optimal level of habitual behaviours for mental health benefits are deepened by shedding light on some findings of neuroimaging studies to have hints to facilitate better management and prevention strategies of addictive problems. With the evolution of the world, and the inevitable use of some technologies that carry the risk of addiction, more effective strategies for preventing and managing addiction are in more demand than before, and the insights of this study are also valuable foundations for future research.
Review: Use of Electrophysiological Techniques to Study Visual Functions of Aquatic Organisms

The light environments of natural water sources have specific characteristics. For the majority of aquatic organisms, vision is crucial for predation, hiding from predators, communicating information, and reproduction. Electroretinography (ERG) is a diagnostic method used for assessing visual function. An electroretinogram records the comprehensive potential response of retinal cells under light stimuli and divides it into several components. Unique wave components are derived from different retinal cells, thus retinal function can be determined by analyzing these components. This review provides an overview of the milestones of ERG technology, describing how ERG is used to study visual sensitivity (e.g., spectral sensitivity, luminous sensitivity, and temporal resolution) of fish, crustaceans, mollusks, and other aquatic organisms (seals, sea lions, sea turtles, horseshoe crabs, and jellyfish). In addition, it describes the correlations between visual sensitivity and habitat, the variation of visual sensitivity as a function of individual growth, and the diel cycle changes of visual sensitivity. Efforts to identify the visual sensitivity of different aquatic organisms are vital to understanding the environmental plasticity of biological evolution and for directing aquaculture, marine fishery, and ecosystem management.
Prediction Models for Sepsis-Associated Thrombocytopenia Risk in Intensive Care Units Based on a Machine Learning Algorithm

Sepsis-associated thrombocytopenia (SAT) is a common complication in the intensive care unit (ICU), which significantly increases the mortality rate and leads to poor prognosis of diseases. Machine learning (ML) is widely used in disease prediction in critically ill patients. Here, we aimed to establish prediction models for platelet decrease and severe platelet decrease in ICU patients with sepsis based on four common ML algorithms and identify the best prediction model. The research subjects were 1,455 ICU sepsis patients admitted to Dongyang People's Hospital affiliated with Wenzhou Medical University from January 1, 2015, to October 31, 2019. Basic clinical demographic information, biochemical indicators, and clinical outcomes were recorded. The prediction models were based on four ML algorithms: random forest, neural network, gradient boosting machine, and Bayesian algorithms. Thrombocytopenia was found to occur in 732 patients (49.7%). The mechanical ventilation time and length of ICU stay were longer, and the mortality rate was higher for the thrombocytopenia group than for the non-thrombocytopenia group. The models were validated on an online international database (Medical Information Mart for Intensive Care III). The areas under the receiver operating characteristic curves (AUCs) of the four models for the prediction of thrombocytopenia were between 0.54 and 0.72. The AUCs of the models for the prediction of severe thrombocytopenia were between 0.70 and 0.77. The neural network and gradient boosting machine models effectively predicted the occurrence of SAT, and the Bayesian models had the best performance in predicting severe thrombocytopenia. Therefore, these models can be used to identify such high-risk patients at an early stage and guide individualized clinical treatment, to improve the prognosis of diseases.
Music Training, and the Ability of Musicians to Harmonize, Are Associated With Enhanced Planning and Problem-Solving

Music training is associated with enhanced executive function but little is known about the extent to which harmonic aspects of musical training are associated with components of executive function. In the current study, an array of cognitive tests associated with one or more components of executive function, was administered to young adult musicians and non-musicians. To investigate how harmonic aspects of musical training relate to executive function, a test of the ability to compose a four-part harmony was developed and administered to musicians. We tested the working hypothesis that musicians would outperform non-musicians on measures of executive function, and that among musicians, the ability to harmonize would correlate positively with measures of executive function. Results indicate that musicians outperformed non-musicians on the Tower of London task, a measure of planning and problem-solving. Group differences were not detected on tasks more selective for inhibitory control, conflict resolution, or working memory. Among musicians, scores on the harmony assessment were positively correlated with performance of the Tower of London task. Taken together, the current results support a strong relationship between musicianship and planning and problem solving abilities, and indicate that the ability to harmonize is associated with components of executive function contributing to planning and problem solving.
Agro-Morphological Characterization of Lentil Germplasm of Indian National Genebank and Development of a Core Set for Efficient Utilization in Lentil Improvement Programs

Lentil (Lens culinaris Medik.) is one of the major cool-season pulse crops worldwide. Its increasing demand as a staple pulse has led to the unlocking of diverse germplasm collections conserved in the genebanks to develop its superior varieties. The Indian National Genebank, housed at the Indian Council of Agricultural Research (ICAR)-National Bureau of Plant Genetic Resources, New Delhi, India, currently has 2,324 accessions comprising 1,796 indigenous and 528 exotic collections. This study was conducted to unveil the potential of lentil germplasm by assessing its agro-morphological characteristics and diversity, identifying trait-specific germplasm, and developing a core set. The complete germplasm set was characterized for two years, i.e., 2017–2018 and 2018–2019, and data were recorded on 26 agro-morphological traits. High phenotypic variability was observed for nine quantitative and 17 qualitative traits. A core set comprising 170 accessions (137 Indian and 33 exotic) was derived based on the characterization data as well as geographical origin using a heuristic method and PowerCore software. This core set was found to be sufficiently diverse and representative of the entire collection based on the comparison made using Shannon–Weaver diversity indices and χ2 test. These results were further validated by summary statistics. The core set displayed high genetic diversity as evident from a higher coefficient of variance in comparison to the entire set for individual traits and overall Shannon–Weaver diversity indices (entire: 1.054; core: 1.361). In addition, the total variation explained by the first three principal components was higher in the core set (70.69%) than in the entire collection (68.03%). Further, the conservation of pairwise correlation values among descriptors in the entire and core set reflected the maintenance of the structure of the whole set. Based on the results, this core set is believed to represent the entire collection, completely. Therefore, it constitutes a potential set of germplasm that can be used in the genetic enhancement of lentils.
GBE1 Is an Independent Prognostic Marker and Associated With CD163+ Tumor-Associated Macrophage Infiltration in Lung Adenocarcinoma

Glycogen branching enzyme (GBE1) is a critical gene that participates in regulating glycogen metabolism. However, the correlations between GBE1 expression and the prognosis and tumor-associated macrophages in lung adenocarcinoma (LUAD) also remain unclear. Herein, we firstly analyzed the expression level of GBE1 in LUAD tissues and adjacent lung tissues via The Cancer Genome Atlas (TCGA) database. The effect of GBE1 on prognosis was estimated by utilizing TCGA database and the PrognoScan database. The relationships between the clinical characteristics and GBE1 expression were evaluated via TCGA database. We then investigated the relationships between GBE1 and infiltration of immune cells in LUAD by utilizing the CIBERSORT algorithm and Tumor Immune Estimation Resource (TIMER) database. In addition, we used a tissue microarray (TMA) containing 92 LUAD tissues and 88 adjacent lung tissues with immunohistochemistry staining to verify the association between GBE1 expression and clinical characteristics, as well as the immune cell infiltrations. We found the expression level of GBE1 was significantly higher in LUAD tissues. High expression of GBE1 was associated with poorer overall survival (OS) in LUAD. In addition, high expression of GBE1 was correlated with advanced T classification, N classification, M classification, TNM stage, and lower grade. Moreover, GBE1 was positively correlated with infiltrating levels of CD163+ tumor-associated macrophages in LUAD. In conclusion, the expression of GBE1 is associated with the prognosis and CD163+ tumor-associated macrophage infiltration in LUAD, suggesting that it has potential to be prognostic and immunological biomarkers in LUAD.