Miracle-dz/UniFAR-FTUs huggingface dataset:
Simple brane-world inflationary models in light of BICEP2

Motivated by the recent CMB $B$-mode observation announced by the BICEP2 collaboration, we study simple inflationary models in the Randall-Sundrum brane-world cosmology. Brane-world cosmological effects alter the inflationary predictions of the spectral index ($n_s$) and the tensor-to-scalar ratio ($r$) from those obtained in the standard cosmology. In particular, the tensor-to-scalar ratio is enhanced in the presence of the 5th dimension, and simple inflationary models which predict small $r$ values in the standard cosmology can yield $r$ values being compatible with the BICEP2 result, $r=0.2^{+0.07}_{-0.05}$. Confirmation of the BICEP2 result and more precise measurements of $n_s$ and $r$ in the near future allow us to constrain the 5-dimensional Planck mass ($M_5$) of the brane-world scenario. We also discuss the post inflationary scenario, namely, reheating of the universe through inflaton decay to the Standard Model particles. When we require the renormalizability of the inflationary models, the inflaton only couples with the Higgs doublet among the Standard Model fields, through which reheating process occurs. If $M_5$ is as low as $10^6$ GeV, the mass of inflaton becomes of ${\cal O}$(100 GeV), providing the inflationary predictions being consistent with the BICEP2 and Planck results. Such a light inflaton has some impacts on phenomenology at the electroweak scale through the coupling with the Higgs doublet.
Deregulations of miR‐1 and its target Multiplexin promote dilated cardiomyopathy associated with myotonic dystrophy type 1

Myotonic dystrophy type 1 (DM1) is the most common muscular dystrophy. It is caused by the excessive expansion of non-coding CTG repeat, which when transcribed affect functions of RNA-binding factors. Specifically, MBNL1 is sequestered in nuclear foci while CELF1 is stabilised, with adverse effects on alternative splicing, processing and stability of a large set of muscular and cardiac transcripts. Among these effects, inefficient processing and down-regulation of muscle- and heart-specific miRNA, miR-1, has been reported in DM1 patients, but the impact of reduced miR-1 on DM1 pathogenesis was unknown. Here, we used Drosophila DM1 models to explore miR-1 involvement in cardiac dysfunction in DM1. We found that miR-1 down-regulation in the heart led to dilated cardiomyopathy (DCM), a DM1-associated phenotype. We then combined in silico screening for miR-1 targets with transcriptional profiling of DM1 cardiac cells to identify miR-1 target genes with potential roles in DCM. We identified Multiplexin (Mp) as a new cardiac miR-1 target involved in DM1. Mp and its human ortholog Col15A1 were both highly enriched in cardiac cells of DCM-developing DM1 flies and in heart samples from DM1 patients with DCM, respectively. Importantly, when overexpressed in the heart, Mp induced DCM, whereas its attenuation ameliorated the DCM phenotype in aged DM1 flies. Reduced levels of miR-1 and consecutive up-regulation of its target Mp/Col15A1 are thus critical in DM1-associated DCM.
The Role of the Posterior Medial Network in Language Comprehension: Dissociating Construction of Episodic versus Semantic Representations

Language comprehension involves the construction of complex mental representations, i.e., “event representations”, reflecting current events or situation models. The construction of these representations requires manipulation of both semantic and episodic content and has been widely associated with the functioning of the posterior medial network, a subsystem of the default network. However, it is still unknown the extent to which activity in posterior medial network reflects construction of the variable episodic versus semantic content of event representations. In this fMRI study, we establish the unique neural correlates of (1) episodic richness and (2) semantic coherence measured during a narrative reading task. Interestingly, we observed a functional fractionation within the posterior medial network in terms of brain regions whose activity was modulated by semantic or episodic content. Specifically, the number of episodic details in the narratives modulated the activity in the left angular gyrus and the retrosplenial cortex/ventral posterior cingulate cortex. Semantic coherence, in contrast, modulated neural responses in the right anterior temporal lobe/middle temporal gyrus, but also in brain regions within the posterior medial network, such as the dorsal posterior cingulate cortex. These results provide the first demonstration of functional dissociations within the posterior medial network in terms of brain regions involved in the construction of semantic versus episodic representational content during a language comprehension task. Significance Statement The construction of “event representations”, which is crucial to understand the world around us, predict the future and make plans, requires manipulation of both semantic and episodic information. The functioning of the posterior medial network has been tightly linked to formation of event representations. However, it is unclear the extent to which activity in this network reflects construction of the variable episodic versus semantic content of event representations. The present study provides the first demonstration of functional dissociations within posterior medial network in terms of brain regions involved in construction of semantic versus episodic representational content during language comprehension. These findings represent a first step towards understanding how episodic and semantic memory systems operate during the construction of event representations.
Ultrafast (>400 Hz) network oscillations induced in thalamorecipient cortical layers by optogenetic activation of thalamocortical axons

Oscillations of extracellular voltage, reflecting synchronous rhythmic activity in large populations of neurons, are a ubiquitous feature in the mammalian brain and are thought to subserve critical, if not fully understood cognitive functions. Oscillations at different frequency bands are hallmarks of specific brain or behavioral states. At the higher end of the scale, ultrafast (400-600 Hz) oscillations in the somatosensory cortex, in response to peripheral stimulation, were observed in human and a handful of animal studies; however, their synaptic basis and functional significance remain largely unexplored. Here we report that brief optogenetic activation of thalamocortical axons ex-vivo elicited precisely reproducible, ~410 Hz local field potential wavelets (“ripplets”) in middle layers of mouse somatosensory (barrel) cortex. Fast-spiking (FS) inhibitory interneurons were exquisitely synchronized with each other and fired spike bursts in anti-phase with ripplets, while excitatory neurons fired only 1-2 spikes per stimulus. Both subtypes received shared excitatory inputs at ripplet frequency, and bursts in layer 5 FS cells required intact connection with layer 4, suggesting that layer 4 excitatory cells were driving FS bursts in both layers. Ripplets may be a ubiquitous cortical response to exceptionally salient sensory stimuli, and could provide increased bandwidth for encoding and transmitting sensory information. Lastly, optogenetically-induced ripplets are a uniquely accessible model system for studying synaptic mechanisms of fast and ultrafast oscillations.
Predicting cell population-specific gene expression from genomic sequence

Most regulatory elements, especially enhancer sequences, are cell population-specific. One could even argue that a distinct set of regulatory elements is what defines a cell population. However, discovering which non-coding regions of the DNA are essential in which context, and as a result, which genes are expressed, is a difficult task. Some computational models tackle this problem by predicting gene expression directly from the genomic sequence. These models are currently limited to predicting bulk measurements and mainly make tissue-specific predictions. Here, we present a model that leverages single-cell RNA-sequencing data to predict gene expression. We show that cell population-specific models outperform tissue-specific models, especially when the expression profile of a cell population and the corresponding tissue are dissimilar. Further, we show that our model can prioritize GWAS variants and learn motifs of transcription factor binding sites. We envision that our model can be useful for delineating cell population-specific regulatory elements.
Bridging The Evolving Semantics: A Data Driven Approach to Knowledge Discovery In Biomedicine

Recent progress in biological, medical and health-care technologies, and innovations in wearable sensors provide us with unprecedented opportunities to accumulate massive data to understand disease prognosis and develop personalized treatments and interventions. These massive data supplemented with rapid growth in computing infrastructure has enabled bio-medical researchers to perform more comprehensive experiments and detailed case-studies. At the same time, performing these experiments are not only monetarily expensive but also time consuming. Thus, there is a growing need to provide tools to the researchers that will allow them to pose queries that will assist them in focusing on interesting “hypotheses”. However, such a tool would require capabilities to derive inferences based on existing known relationship between medical concepts. In this paper, we tackle this problem as one of non-factoid question answering wherein we try to answer the user-post questions by leveraging both authoritative as well as social media posts. While the former provides us with well knowledge on well researched topics, the latter provides us with real-time feedback on variety of topics like adverse drug effect (ADE), symptoms-drug relationship, etc. The challenge with leveraging the authoritative sources to infer answers for non-factoid question lies in: (a) The effective navigation of the answer search-space for timely response to the queries, (b) Ranking the candidate answers derived in step-(a) to enable non-trivial and novel discoveries, and (c) Being robust to perform confirmatory as well as discovery type of tasks.
A Principal Odor Map Unifies Diverse Tasks in Human Olfactory Perception

Mapping molecular structure to odor perception is a key challenge in olfaction. Here, we use graph neural networks (GNN) to generate a Principal Odor Map (POM) that preserves perceptual relationships and enables odor quality prediction for novel odorants. The model is as reliable as a human in describing odor quality: on a prospective validation set of 400 novel odorants, the model-generated odor profile more closely matched the trained panel mean (n=15) than did the median panelist. Applying simple, interpretable, theoretically-rooted transformations, the POM outperformed chemoinformatic models on several other odor prediction tasks, indicating that the POM successfully encoded a generalized map of structure-odor relationships. This approach broadly enables odor prediction and paves the way toward digitizing odors. One-Sentence Summary An odor map achieves human-level odor description performance and generalizes to diverse odor-prediction tasks.
Identifying the potential for sustainable human–wildlife coexistence by integrating willingness to coexist with habitat suitability models

Persistence of large mammals in the Anthropocene depends on human willingness to coexist with them, but this is rarely incorporated into habitat suitability or conservation priority assessments. We propose a framework that integrates human willingness-to-coexist with habitat suitability assessments to identify areas of high potential for sustainable coexistence. We demonstrate its applicability for elephants and rhinos in the socio-ecological system of Maasai Mara, Kenya, by integrating spatial distributions of people’s willingness-to-coexist based on Bayesian hierarchical models using 556 household interviews, with socio-ecological habitat suitability mapping validated with long-term elephant observations from aerial surveys. Willingness-to-coexist was higher if people had little personal experience with a species, and strongly reduced by experiencing a species as a threat to humans. The sustainable coexistence potential framework highlights areas of low socio-ecological suitability, and areas that require more effort to increase positive stakeholder engagement to achieve long-term persistence of large herbivores in human-dominated landscapes.
Optimizing the social utility of judicial punishment: An evolutionary biology and neuroscience perspective

Punishment as a response to impairment of individual or group welfare may be found not only among humans but also among a wide range of social animals. In some cases, acts of punishment serve to increase social cooperation among conspecifics. Such phenomena motivate the search for the biological foundations of punishment among humans. Of special interest are cases of pro-social punishment of individuals harming others. Behavioral studies have shown that in economic games people punish exploiters even at a cost to their own welfare. Additionally, neuroimaging studies have reported activity during the planning of such punishment in brain areas involved in the anticipation of reward. Such findings hint that there is an evolutionarily honed basic drive to punish social offenders. I argue that the transfer of punishment authority from the individual to the group requires that social offenders be punished as a public good, even if such punishment is not effective as retribution or deterrent. Furthermore, the social need for punishment of offenders has implications for alternatives to incarceration, publicity of punishment, and judicial structure.
Robust Inference of Gene Regulatory Networks

To successfully infer the biochemical network that underly a given biological function, two problems must be resolved. First, sufficiently informative data that allow discrimination between alternative models corresponding to different network structures must be recorded. Second, the ''correct'' network model with a structure including only the active interactions must be selected based on the recorded data set. In this work we address both these problems within the framework of robust inference. We first address the problem in a deterministic framework and show that determination of the existence of a specific interaction, or directed network edge, can be reduced to a rank test on a matrix constructed from available perturbation and response data. To deal with uncertainty, we introduce a norm-bounded set around the nominal data points in the sample space and assume the true response of the system is within this set. A similar uncertainty description is employed to describe uncertainties in the applied perturbations. Determination of the existence of a specific interaction under uncertainty can then be formulated as a robust rank problem, which can be solved using results from robust control theory. The proposed method provides necessary and sufficient conditions for the existence of a directed network edge under the assumption that the true response is within the given uncertainty set. Similarly, network edges can be determined with a robustness margin, i.e., the size of the uncertainty set for which the edge can identified with confidentiality. An important outcome of the method is determination of interactions for which the available data set does not contain sufficient information to infer existence or non-existence with confidence. Furthermore, based on well known results from linear algebra, we show how specific perturbation experiments can be designed to generate data that enable inference of a specific edge at a given level of confidence.
A neuro-inspired computational model of life-long learning and catastrophic interference, mimicking hippocampus novelty-based dopamine modulation and lateral inhibitory plasticity

The human brain has a remarkable lifelong learning capability to acquire new experiences while retaining previously acquired information. Several hypotheses have been proposed to explain this capability, but the underlying mechanisms are still unclear. Here, we propose a neuro-inspired firing-rate computational model involving the hippocampus and surrounding areas, that encompasses two key mechanisms possibly underlying this capability. The first is based on signals encoded by the neuromodulator dopamine, which is released by novel stimuli and enhances plasticity only when needed. The second is based on a homeostatic plasticity mechanism that involves the lateral inhibitory connections of the pyramidal neurons of the hippocampus. These mechanisms tend to protect neurons that have already been heavily employed in encoding previous experiences. The model was tested with images from the MNIST machine learning dataset, and with more naturalistic images, for its ability to mitigate catastrophic interference in lifelong learning. The results show that the proposed biologically grounded mechanisms can effectively enhance the learning of new stimuli while protecting previously acquired knowledge. The proposed mechanisms could be investigated in future empirical animal experiments and inspire machine learning models.
Ameliorating effect of the biological Zinc nanoparticles in abamectin induced hepato-renal injury in a rat model: Implication of oxidative stress, biochemical markers and COX-2 signaling pathways

Extensive use of abamectin (ABM) as an anthelmintic in veterinary systems adversely affects the health and welfare of animals and humans. Zinc nanoparticles (ZnNPs) have therapeutic benefits and ameliorate the effect of environmental pollutants. In this study, we assessed the ameliorative effect of ZnNPs against the sub-lethal toxicity of ABM in rats. Forty healthy rats were randomly selected into four groups (n = 10); the control received normal saline and test rats were treated orally twice weekly with ABM (1 mg/kg bwt), ZnNPs (10 mg/kg bwt) and ABM + ZnNPs for 28 days. Upon completion of the study period, blood and tissue samples were collected and prepared for hematological, biochemical, pathological, and immunohistochemical analysis. Our results showed that ABM treatment significantly decreased body weight gain (BWG), red blood cells (RBCs), hemoglobin (Hb), hematocrit (HC), and platelet (PLT); while it significantly increased white blood cells (WBCs) and lymphocytes. ABM also significantly decreased antioxidant enzyme activities: superoxide dismuthase (SOD), glutathione peroxidase (GPx), and catalase (CAT) and increased hydrogen peroxide and malondialdehyde levels compared with other groups. ABM significantly raised alanine aminotransferase (ALT), aspartate amino transaminase (AST), and alkaline phosphatase (ALP) levels, which was restored by co-administration of ZnNPs. Moreover, ZnNPs ameliorated ABM-mediated negative histopathological changes in the liver and kidney tissues, exhibiting a significant protective effect. Cyclooxygenase 2 (COX-2) + immuno-expression were reduced after pretreatment with ZnNPs. These findings suggested that co-administration of ZnNPs with ABM mitigated its toxicity by combating oxidative stress and boosting antioxidant capacity, indicating the efficacy of ZnNPs in attenuating ABM toxicity. Graphical Abstract
Topical nerve growth factor prevents neurodegenerative and vascular stages of diabetic retinopathy

Specific and effective preventive treatment for diabetic retinopathy (DR) is presently unavailable, mostly because the early stages of the complication have been, until recently, poorly understood. The recent demonstration that the vascular phase of DR is preceded and possibly caused by the neurodegeneration of retinal ganglion cells suggests that DR could, at least theoretically, be prevented through an early neuroprotective approach. The aims of our study were to clarify the natural history of diabetes-driven retinal neurodegeneration and to verify the possibility to prevent DR using topical nerve growth factor (NGF). The results of the study show that retinal neurodegeneration, characterized by the loss of retinal ganglion cells represents a relatively early phenomenon of diabetes (between 5 and 16 weeks of age), which tends to be self-limiting in the long run. Neurodegeneration is followed by the development of DR-related vascular dysfunctions, as confirmed by the development of acellular capillaries and the loss of retinal pericytes. Both retinal neurodegeneration and subsequent vascular dysfunction can be successfully prevented by topical NGF administration. These findings suggest that: 1) The first stage of DR consists in a self-limiting retinal neurodegeneration 2) The demonstrated effectiveness of topical NGF in the prevention of DR could be rapidly translated into clinical practice.
Systemic glucocorticoid prescriptions pattern and factors of inappropriate use in primary care institutions of Southwest China

Background Inappropriate use of glucocorticoids in primary care institutions is serious. It not only causes economic burden, but leads to many adverse reactions. The purpose of this study is to explore systemic glucocorticoid prescription pattern and factors of inappropriate use in primary care institutions. Methods This is a retrospective study. Systemic glucocorticoids prescribed in 58 primary care institutions in Guizhou province of Southwest China in 2020 were selected from the Health Information System. All prescriptions were classified as appropriate or inappropriate use. Inappropriate use was classified into the following two categories: (a) Inappropriate indications; (b) Inappropriate selection of glucocorticoids. Multivariate analysis was used to explore the factors associated with inappropriate use of systemic glucocorticoids. Results A total of 63,315 glucocorticoid prescriptions were included in the analysis. Diseases of the respiratory system (60.8%) and diseases of the skin and subcutaneous tissue (23.1%) were the most common indications for use. Injections (89.8%) predominated and dexamethasone (86.5%) was the most prescribed glucocorticoid. 68.2% of all prescriptions were inappropriate. Compared to physicians with a college degree, physicians with a junior college (OR: 1.12, 95% CI: 1.08–1.17) and technical secondary education (OR: 1.12, 95% CI:1.05–1.19) were more likely to prescribe glucocorticoids inappropriately as were attending physicians (OR: 1.12, 95% CI: 1.01–1.25) and resident physicians (OR: 1.31, 95% CI: 1.15–1.48) compared to associate chief physicians. The risk of inappropriate glucocorticoid use was highest in patients 65 years of age and older (OR: 6.00, 95% CI: 5.62–6.40). In contrast, prescriptions given by injection were more likely to be used inappropriately than those given orally (OR: 0.44, 95% CI: 0.41–0.46). Conclusion Inappropriate use of systemic glucocorticoids without appropriate indications was extremely prominent in primary care institutions of Guizhou Province, especially in diseases of the respiratory system and among the elderly. The risk of inappropriate glucocorticoid use was highest in patients 65 years of age and older. It is important to note that physicians younger than 33, with more than 40 years of service, and attending or residents were more likely to inappropriately prescribe glucocorticoids.