Miracle-dz/UniFAR-FTUs huggingface dataset:
The chromatin landscape of bryophytes

transcriptional regulation of transposons and genes vary among different lineages of eukaryotes including the bryophytes that diverged from vascular plants 510-480 mya. The monophyletic bryophytes comprise mosses, liverworts and hornworts. The chromatin landscapes of mosses and liverworts are different, leaving open the question regarding the identity of the chromatin landscape of all bryophytes. Here we assembled the chromatin landscape of the model hornwort Anthoceros agrestis. By comparing chromatin landscapes between mosses, liverworts and hornworts we define the common chromatin landscape of the ancestor of extant bryophytes. The constitutive heterochromatin of bryophytes is characterized by the absence of gene body DNA methylation, low levels of non-CG DNA methylation and the absence of segregation of transposons in a few well defined chromosomal compartments. In addition, whereas histone modifications of euchromatin and facultative heterochromatin are primarily associated with genes in angiosperms and mosses, nearly half of the hornwort transposons are associated with facultative heterochromatin and euchromatin. Hence the ancestral genome of bryophytes was likely a patchwork of interspersed small units of euchromatin, facultative and constitutive heterochromatin. Each unit contained a few transposons and genes that share the same chromatin state. We propose that in bryophytes, this specific type of genome organization prevented the recruitment of transposons to form constitutive heterochromatin around point centromeres observed in the genomes of angiosperms.
Reduced oriens-lacunosum/moleculare cell model identifies biophysical current balances for in vivo theta frequency spiking resonance

Conductance-based models have played an important role in the development of modern neuroscience. These mathematical models are powerful “tools” that enable theoretical explorations in experimentally untenable situations, and can lead to the development of novel hypotheses and predictions. With advances in cell imaging and computational power, multi-compartment models with morphological accuracy are becoming common practice. However, as more biological details are added, they make extensive explorations and analyses more challenging largely due to their huge computational expense. Here, we focus on oriens-lacunosum/moleculare (OLM) cell models. OLM cells can contribute to functionally relevant theta rhythms in the hippocampus by virtue of their ability to express spiking resonance at theta frequencies, but what characteristics underlie this is far from clear. We converted a previously developed detailed multi-compartment OLM cell model into a reduced single compartment model that retained biophysical fidelity with its underlying ion currents. We showed that the reduced OLM cell model can capture complex output that includes spiking resonance in in vivo-like scenarios as previously obtained with the multi-compartment model. Using the reduced model, we were able to greatly expand our in vivo-like scenarios. Applying spike-triggered average analyses, we were thus able to to determine that it is a combination of hyperpolarization-activated cation and muscarinic type potassium currents that specifically allow OLM cells to exhibit spiking resonance at theta frequencies. Further, we developed a robust Kalman Filtering (KF) method to estimate parameters of the reduced model in real-time. We showed that it may be possible to directly estimate conductance parameters from experiments since this KF method can reliably extract parameter values from model voltage recordings. Overall, our work showcases how the contribution of cellular biophysical current details could be determined and assessed for spiking resonance. As well, our work shows that it may be possible to directly extract these parameters from current clamp voltage recordings.
Non-invasive muscle biopsy: estimation of muscle fibre size from a neuromuscular interface

Because of the biophysical relation between muscle fibre diameter and the propagation velocity of action potentials along the muscle fibres, motor unit conduction velocity (MUCV) could be a non-invasive index of muscle fibre size in humans. However, the relation between MUCV and fibre size has been only assessed indirectly in animal models and in human patients with invasive intramuscular EMG recordings, or it has been mathematically derived from computer simulations. By combining advanced non-invasive techniques to record motor unit activity in vivo, i.e., high-density surface EMG, with the gold standard technique for muscle tissue sampling, i.e., muscle biopsy, here we investigated the relation between the conduction velocity of populations of motor units identified from the biceps brachii muscle, and muscle fibre diameter. Moreover, we demonstrate the possibility to predict muscle fibre diameter (R2 = 0.66) and cross-sectional area (R2 = 0.65) from conduction velocity estimates with low systematic bias (~2% and ~4% respectively) and a relatively low margin of individual error (~8% and ~16%, respectively). The proposed neuromuscular interface opens new perspectives in the use of high-density EMG as a non-invasive tool to estimate muscle fibre size without the need of surgical biopsy sampling. The non-invasive nature of high-density surface EMG for the assessment of muscle fibre size may be useful in studies monitoring child development, aging, space and exercise physiology. SIGNIFICANCE STATEMENT Our study explored the relation between the conduction velocity of populations of motor units and muscle fibre size in healthy humans. Our results provide in vivo evidence that a high-density surface EMG-derived physiological parameter, i.e. motor unit conduction velocity, can be adopted to estimate muscle fibre size, without the need of surgical biopsy sampling. Here we propose a neuromuscular interface that opens new perspectives not only in the study of neuromuscular disorders, but also in other fields where the non-invasive and painless determination of muscle fibre and motor unit size becomes a priority, such as in aging, space and exercise physiology.
Diurnality shapes the visual opsin genes of colorful Neotropical frogs Opsin gene evolution in diurnal and colorful frogs

Amphibians are an ideal model for studying visual system evolution because their biphasic (aquatic and terrestrial) life history and ecological diversity expose them to a broad range of visual conditions. Here we evaluate signatures of selection on visual opsin genes of five Neotropical diurnal frog groups, with a focus on three conspicuously colored and chemically defended (i.e., aposematic) clades: poison frogs (Dendrobatidae), Harlequin toads (Bufonidae: Atelopus ), and pumpkin toadlets (Brachycephalidae: Brachycephalus ). We found evidence of positive selection on 15 amino acid sites in LWS, SWS1, SWS2, and RH1 opsin genes, of which one in LWS has been previously identified as important for spectral tuning in other vertebrates. Patterns of selection reveal that the evolution of diurnality was important in shaping the vision of focal frog groups; whether conspicuous coloration has played a role remains unclear, as no support was found but inferences may have been statistically limited by sample size. Furthermore, we provide evidence that the SWS2 gene, normally expressed in rod cells in amphibians, has likely been lost in the ancestor of Dendrobatidae, suggesting that under low light levels, dendrobatids have inferior wavelength discrimination compared to other frogs. This might coincide with the diurnal activity of dendrobatids and could have implications for opsin evolution in this clade. Our analyses show that studies of opsin diversification could expand our understanding of how adaptations for diel habits evolve and how visual tuning alters the sensory landscape of animals. how anuran visual capabilities to intraspecific communication and signaling. Here, a taxonomically and ecologically comprehensive dataset of the four visual opsin genes ( LWS, SWS1, SWS2, RH1 ) for 116 anuran species spanning 20 families. Our analyses report 15 amino acid sites as under positive selection in diurnal species. We find no compelling evidence that conspicuous coloration is linked to the spectral tuning of visual pigments in our focal taxa. Moreover, our results provide evidence for the loss of the SWS2 gene in the ancestor of Dendrobatidae between 70–40 Mya, an event that coincides with the evolution of diurnal activity patterns in the clade.
Stasis in the adaptive landscape of two ecologically similar and sympatric damselfly species

Following the development of regression-based methods to estimate natural and sexual selection, evolutionary biologists have quantified the strength, mode and direction of selection in natural populations. Although this approach has been successful, its limitations include lack of replication across species, compromising the generality of the inferences beyond microevolutionary time scales. Here, we carried out a comparative selection study on wing shape and body size across multiple populations of two closely related and ecologically similar pond damselflies: Enallagma cyathigerum and Ischnura elegans (family Coenagrionidae). Our data revealed directional selection on body size in females and weak stabilizing selection on wing shape in both sexes, and these selection regimes were shared between the species. In contrast, sexual selection on male body size was curvilinear and divergent between species. By analyzing selection on the fine-grained spatial scale, we found that selection of male body size was shaped by the local social organization, and the relationship between socioecological indices and directional selection was consistent between the two species. Our study illustrates a case of stasis in the adaptive landscape caused by ecological similarity between taxa, supporting the idea that a shared ecological niche may result in a stable adaptive zone lasting millions of years.
Structural basis for the Rad6 activation by the Bre1 N-terminal domain

The mono-ubiquitination of the histone protein H2B (H2Bub1) is a highly conserved histone post-translational modification that plays critical roles in many fundamental processes. In yeast, this modification is catalyzed by the conserved Bre1-Rad6 complex. Bre1 contains a unique N-terminal Rad6 binding domain (RBD), how it interacts with Rad6 and contributes to the H2Bub1 catalysis is unclear. Here, we present crystal structure of the Bre1 RBD-Rad6 complex and structure-guided functional studies. Our structure provides a detailed picture of the interaction between the dimeric Bre1 RBD and a single Rad6 molecule. We further found that the interaction stimulates Rad6’s enzymatic activity by allosterically increasing its active site accessibility and likely contribute to the H2Bub1 catalysis through additional mechanisms. In line with these important functions, we found that the interaction is crucial for multiple H2Bub1-regulated processes. Our study provides molecular insights into the H2Bub1 catalysis.
Observing the products of stellar evolution in the old open cluster M67 with APOGEE

© 2016 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society Recent works have shown how the [C/N] ratio in stars after the first dredge-up (FDU) can be used as an age estimator in virtue of its dependence on stellar mass. For this purpose, precise predictions of the surface chemical composition before and after the mixing takes place in the convective envelope of subgiant stars are necessary. Stellar evolution models can provide us with such predictions, although a comparison with objects of known age is needed for calibration. Open clusters are excellent test cases, as they represent a single stellar population for which the age can be derived through, e.g. isochrone fitting. In this study, we present a detailed analysis of stars belonging to the well-known open cluster M67 observed by the Apache Point Observatory Galactic Evolution Experiment (APOGEE) survey in the twelfth data release of the Sloan Digital Sky Survey and whose chemical properties were derived with the APOGEE Stellar Parameters and Chemical Abundances Pipeline. We find that the [C/N] abundance of subgiant branch stars is overestimated by ∼0.2 dex due to an offset in the determination of the [N/Fe] abundance. Stars on the red giant branch and red clump are shown not to be affected by this offset. We derive [C/N]FDU = −0.46 ± 0.03 dex, which poses a strong constraint on calibrations of [C/N]FDU as age indicator. We also do not find any clear signature of additional chemical mixing processes that set in after the red giant branch bump. The results obtained for M67 indicate the importance of conducting high-resolution spectroscopic studies of open clusters of different ages in order to establish an accurate age-dating method for field stars.
Optical observations of the 2002cx-like supernova 2014ek and characterizations of SNe Iax

We present optical observations of supernova (SN) 2014ek discovered during the Tsinghua-NAOC Transient Survey (TNTS), which shows properties that are consistent with those of SN 2002cx-like events (dubbed as SNe Iax). The photometry indicates that it is underluminous compared to normal SNe Ia, with the absolute $V$-band peak magnitude being as $-17.66\pm0.20$ mag. The spectra are characterized by highly ionized Fe III and intermediate-mass elements (IMEs). The expansion velocity of the ejecta is found to be $\sim$5000 km s$^{-1}$ near the maximum light, only half of that measured for normal SNe Ia. The overall spectral evolution is quite similar to SN 2002cx and SN 2005hk, while the absorption features of the main IMEs seem to be relatively weaker. The ${}^{56}$Ni mass synthesized in the explosion is estimated to be about 0.08 M$_{\odot}$ from the pseudo bolometric light curve. Based on a large sample of SNe Iax, we examined the relations between peak luminosity, ejecta velocity, decline rate, and peak $V - R$ color but did not find noticeable correlations between these observables, in particular when a few extreme events like SN 2008ha are excluded in the analysis. For this sample, we also studied the birthplace environments and confirm that they still hold the trend of occurring preferentially in late-type spiral galaxies. Moreover, SNe Iax tend to occur in large star-forming regions of their host galaxies, more similar to SNe Ibc than SNe II, favoring that their progenitors should be associated with very young stellar populations.
Advanced Drug Delivery Platforms for the Treatment of Oral Pathogens

The oral cavity is a complex ecosystem accommodating various microorganisms (e.g., bacteria and fungi). Various factors, such as diet change and poor oral hygiene, can change the composition of oral microbiota, resulting in the dysbiosis of the oral micro-environment and the emergence of pathogenic microorganisms, and consequently, oral infectious diseases. Systemic administration is frequently used for drug delivery in the treatment of diseases and is associated with the problems, such as drug resistance and dysbiosis. To overcome these challenges, oral drug delivery systems (DDS) have received considerable attention. In this literature review, the related articles are identified, and their findings, in terms of current therapeutic challenges and the applications of DDSs, especially nanoscopic DDSs, for the treatment of oral infectious diseases are highlighted. DDSs are also discussed in terms of structures and therapeutic agents (e.g., antibiotics, antifungals, antiviral, and ions) that they deliver. In addition, strategies (e.g., theranostics, hydrogel, microparticle, strips/fibers, and pH-sensitive nanoparticles), which can improve the treatment outcome of these diseases, are highlighted.
Incremental case-based learning through introspective reasoning about knowledge goals

Simply stated and in the narrowest sense, a central focus addressed by this research is that of strategy selection in machine learning, particularly, in multistrategy failure-driven learning. That is, given some computational task (e.g., story understanding or problem solving) specified in terms of the system's goals, the context, and the input, if a failure occurs during the performance of the task, the problem is to (a) determine what to learn (e.g., how to repair the domain knowledge of the system), and (b) choose the appropriate learning algorithm(s) with which to carry out the necessary learning. The learning is considered successful (e.g., the domain knowledge is considered repaired) if given a similar future situation, the failure will not recur. In the broadest interpretation, this research presents the beginning of a computational theory of self-understanding and introspection, and its relation to human learning.
The Relationship of Trauma History, Substance Misuse, and Religious Coping to Trauma Symptoms among Homeless Men in Residential Treatment: A Preliminary Study

Homelessness is a global health and well-being crisis that impacts millions of people annually. Individuals without housing experience higher rates of alcohol and drug use problems than the general community. They also report more trauma exposure and are at increased risk for trauma-related symptoms. Faith-based organizations are among the institutions that provide treatment and recovery programs for homeless persons with substance use problems. The aim of this study was to explore the relationship of trauma history, substance use problems, and religious coping methods to trauma symptoms in a sample of homeless men in a faith-based residential treatment program. An ethnically diverse sample of 98 men participated; their mean age was 42.5 years. Measures included a brief trauma history screener, the Alcohol Use Disorders Identification Test (AUDIT), the Drug Abuse Screening Test (DAST-20), the Brief Religious Coping Scale (Brief RCOPE), and the Trauma Symptom Inventory (TSI). As predicted, trauma history, AUDIT scores, DAST-20 scores, and negative religious coping were positively associated with trauma symptoms. Racial identity also accounted for significant variance in TSI scores, especially regarding trauma-related anxious and depressive symptoms. Positive religious coping appeared essentially unrelated to trauma symptoms. These findings support the utility of the instruments used for assessment with homeless persons in residential treatment programs for substance abuse.
Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout

Asynchronous learning protocols have regained attention lately, especially in the Federated Learning (FL) setup, where slower clients can severely impede the learning process. Herein, we propose \texttt{AsyncDrop}, a novel asynchronous FL framework that utilizes dropout regularization to handle device heterogeneity in distributed settings. Overall, \texttt{AsyncDrop} achieves better performance compared to state of the art asynchronous methodologies, while resulting in less communication and training time overheads. The key idea revolves around creating ``submodels'' out of the global model, and distributing their training to workers, based on device heterogeneity. We rigorously justify that such an approach can be theoretically characterized. We implement our approach and compare it against other asynchronous baselines, both by design and by adapting existing synchronous FL algorithms to asynchronous scenarios. Empirically, \texttt{AsyncDrop} reduces the communication cost and training time, while matching or improving the final test accuracy in diverse non-i.i. d. FL scenarios.
Diagnostics of a nuclear starburst: water and methanol masers

We test models of starburst driven outflows using observations of the 22.2 GHz H2O and 36.2 GHz class I CH3OH maser lines. We have observed the starburst galaxy NGC 253 using the Karl G. Jansky Very Large Array. We present evidence for entrainment of star-forming dense-molecular gas in the outflow of NGC 253. We also show that H2O masers are associated with forming super star clusters and not with supernova remnants. We detect four new 36 GHz CH3OH masers in the central kpc and show possible evidence for a star-formation origin of two class I CH3OH masers. Such high resolution observations are essential for understanding the origin of these masers.
Modelling "Delegated Autonomy" in Cognitive Household Digital Twins

The concepts of Cognitive Household Digital Twin (CHDT) and Collaborative Virtual Power Plant Ecosystem (CVPP-E) was put forth to facilitate the effective management and organization of households within Renewable Energy Communities (RECs). A CVPP-E can be thought of as a complete digital representation of a REC. In the same vein, CHDTs can be perceived as digital twin depictions of each constituent household of a CVPP-E. Furthermore, CHDTs can be modelled as software agents that have intelligence or cognition, allowing them to perform complementary functions as independent decision-making entities that execute "delegated autonomy" instructions on behalf of their physical twin. Their decisions are expected to encourage collaborative behaviors that can help the energy ecosystem become more resilient and sustainable. In this study, we consider a CVPP-E with prosumer CHDTs who can choose to (a) consume energy directly from a locally installed photovoltaic system, (b) a locally installed energy storage system, (c) a community storage, or (d) from the grid. We also consider consumer CHDTs, whose consumption options are limited to (a) the grid and (b) community storage. All the considered CHDTs are "instructed," to consume energy from a specified source based on some "delegated autonomy" given to them by the corresponding Physical Twin (owner), which might reflect the owner’s contribution to a shared objective, enabling sustainable consumption in the ecosystem. The study's findings, which were obtained using a multi-method simulation technique, demonstrate the viability and potential utility of the hypothesis that these proposed CHDTs have complementing decision-making abilities.
Parameter estimation from realistic experiment scenario using artificial neural networks

One of the promising directions in future medicine is the optimization of therapies based on mathematical and engi-neering methods, with which the treatment can be personalized. In personalization, the key issue is the identification of the model parameters. We carry out the identification using artificial neural networks, which require training. We generate training data that is as realistic as possible, by generating sparse training datasets. We aim to simulate realistic experimental setups that also take the presence of holidays into account, when the drug injection and tumor volume measurement are not possible. We generate several smaller training datasets and their different versions, to determine how many times the parameters can change every week for the proper functioning of neural networks and to examine how the networks can give a proper estimate of the time-varying parameters from sparse measurements. In this research two different types of training datasets will be introduced to train artificial neural network. The training data are generated on known parameter intervals, taking into consideration the experimental setup we use to validate our results. The estimated parameters can be used to track the change of the parameters and personalize the model for optimization algorithms.