Miracle-dz/UniFAR-FTUs huggingface dataset:
Loss of NR5A1 in Sertoli cells after sex determination changes their cellular identity and induces their death by anoikis

NR5A1 is an orphan nuclear receptor crucial for gonadal development in mammals. In the mouse testis it is expressed both in Sertoli cells (SC) and Leydig cells (LC). To investigate its role posteriorly to sex determination, we have generated and analysed mice lacking NR5A1 in SC from embryonic day (E) 13.5 onwards (Nr5a1SC−/− mutants). Ablation of Nr5a1 impairs the expression of genes characteristic of SC identity (e.g., Sox9, Amh), makes SC to progressively die from E14.5 by a Trp53-independent mechanism, and induces disorganization of the testis cords, which, together, yields germ cells (GC) to prematurely enter meiosis and die, instead of becoming quiescent. Single-cell RNA-sequencing experiments revealed that Nr5a1-deficient SC acquire a pre-granulosa cell-like identity, and profoundly modify the landscape of the adhesion molecules and extracellular matrix they express. We propose therefore that SC lacking NR5A1 transdifferentiate and die by anoikis. Fetal LC do not display major changes in their transcriptome, indicating that SC are not required beyond E14.5 for their emergence or maintenance. In contrast, adult LC were missing in Nr5a1SC−/− postnatal testes. In addition, adult males display Müllerian duct derivatives (i.e., uterus, vagina), as well as a decreased anogenital distance and a shorter penis that can be explained by loss of AMH production and defective HSD17B1- and HSD17B3-mediated synthesis of testosterone in SC during fetal life. Together, our findings indicate that Nr5a1 expressed in SC after the period of sex determination safeguards SC identity, which maintains proper seminiferous cord organization and prevents GC to enter meiosis.
Programmable Drug Control of Receptor Valency Modulates the Potency of Cell Therapeutics

An increasing number of preclinical and clinical studies are exploring the use of receptor-engineered cells that can respond to disease states for the treatment of cancer, infectious disease, autoimmunity, and regeneration. However, receptor-based cell therapies, including chimeric antigen receptor (CAR), face many critical issues including target recognition escape, adverse side effects, and lack of in vivo control. Drug-controllable receptors offer a promising solution to overcome these issues through precise in vivo tuning of cells via enhanced sensing and therapeutic efficacy. Here we develop a novel class of modular and tunable receptors, termed valency-controlled receptors (VCRs), which can leverage customized small molecules to mediate cell signaling strength via controlled spatial clustering. We first develop DNA origami activated VCRs to demonstrate that receptor valency is a core mechanism that modulates immune cell activation. We design a series of customized valency-control ligands (VCLs) by transforming small molecule drugs into a multivalency format and modularly fusing VCR onto the CAR architecture. We demonstrate that VCL induction allows enhanced target sensitivity of engineered cells. Using medicinal chemistry, we develop programmable bioavailable VCL drugs to demonstrate that the VCR system enables drug-induced highly potent responses towards low antigen cancers in vitro and in vivo. Valency controlled receptors and customizable drug ligands provide a new synthetic biology platform to precisely tune engineered cell therapeutic potency, which can address existing safety and efficacy barriers in cell therapy.
Bioinformatics Approaches to Determine the Effect of SARS-CoV-2 Infection on Patients with Intrahepatic Cholangiocarcinoma

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of coronavirus disease 2019 (COVID-19), has infected millions of individuals throughout the world, which poses a serious threat to human health. COVID-19 is a systemic disease that affects tissues and organs, including the lung and liver. Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are the most common liver cancer, and cancer patients are particularly at high risk of SARS-CoV-2 infection. The relationship between HCC and COVID-19 has been reported in previous studies, but ICC has been rare. With the methods of systems biology and bioinformatics, this study explored the link between COVID-19 and ICC. Transcriptional profiling of COVID-19 and ICC were obtained from the GEO database. A total of 70 common differentially expressed gene (DEGs) of both diseases were identified to investigate shared pathways. Then top-ranked 10 key DEGs (SCD, ACSL5, ACAT2, HSD17B4, ALDOA, ACSS1, ACADSB, CYP51A1, PSAT1, and HKDC1) were identified as hub genes by protein-protein interaction (PPI) network analysis. In addition, transcriptional regulatory networks regulating hub genes were revealed by hub Gene-transcription factor (TF) interaction analysis and hub gene-microRNA (miRNAs) interaction analysis. This study is expected to provide new references for future research and treatment of COVID-19 and ICC.
The physical basis of osmosis

Osmosis is an important force in all living organisms, yet the molecular basis of osmosis is widely misunderstood as arising from differences in water concentration in solutions of differing osmolarities. In 1923 Debye proposed a physical model for a semipermeable membrane that was hardly noticed at the time and slipped out of view. We show that Debye’s analysis of van’t Hoff’s law for osmotic equilibrium provides a consistent and plausible explanation for osmotic flow. A difference in osmolyte concentrations in solutions separated by a semipermeable membrane generates different pressures at the two water-membrane interfaces. Water is therefore driven through the membrane for exactly the same reason that pure water flows in response to an imposed hydrostatic pressure difference. In this paper we present the Debye model in both equilibrium and flow conditions. We point out its applicability regardless of the nature of the membrane with examples ranging from predominantly convective flow of water through synthetic membranes to purely diffusive flow of independent water molecules through a lipid bilayer and the flow of strongly interacting water molecules in single file across narrow protein channels.
Hybrid Epigenomes Reveal Extensive Local Genetic Changes to Chromatin Accessibility Contribute to Divergence in Embryonic Gene Expression Between Species

Chromatin accessibility plays an important role in shaping gene expression patterns across development and evolution; however, little is known about the genetic and molecular mechanisms that influence chromatin configuration itself. Because cis and trans influences can both theoretically influence the accessibility of the epigenome, we sought to better characterize the role that both of these mechanisms play in altering chromatin accessibility in two closely related sea urchin species. Using hybrids of the two species, and adapting a statistical framework previously developed for the analysis of cis and trans influences on the transcriptome, we examined how these mechanisms shape the regulatory landscape at three important developmental stages, and compared our results to similar patterns in the transcriptome. We found extensive cis- and trans-based influences on evolutionary changes in chromatin, with cis effects slightly more numerous and larger in effect. Genetic mechanisms influencing gene expression and chromatin configuration are correlated, but differ in several important ways. Maternal influences also appear to have more of an effect on chromatin accessibility than on gene expression, persisting well past the maternal-to-zygotic transition. Furthermore, chromatin accessibility near GRN genes appears to be regulated differently than the rest of the epigenome, and indicates that trans factors may play an outsized role in the configuration of chromatin near these genes. Together, our results represent the first attempt to quantify cis and trans influences on evolutionary divergence in chromatin configuration in an outbred natural study system, and suggest that the regulation of chromatin is more genetically complex than was previously appreciated.
Drosophila integrates visual evidence and counterevidence in self motion estimation

3 – Department of Statistics and Data Science, Yale University, New Haven, CT 06511, USA 4 – Department of Physics, Yale University, New Haven, CT 06511, USA 5 – School of Engineering and Applied Science, Yale University, New Haven, CT 06511, USA 6 – Department of Neuroscience, Yale University, New Haven, CT 06511, USA 7 – Wu Tsai Institute, Yale University, New Haven, CT 06511, USA 8 – Present Address: Institute of Neuroscience, Technical University of Munich, Munich 80802, Germany # Lead Contact: damon.clark@yale.edu
On the Estimation of Integrated Volatility With Jumps and Microstructure Noise

In this article, we propose a nonparametric procedure to estimate the integrated volatility of an Itô semimartingale in the presence of jumps and microstructure noise. The estimator is based on a combination of the preaveraging method and threshold technique, which serves to remove microstructure noise and jumps, respectively. The estimator is shown to work for both finite and infinite activity jumps. Furthermore, asymptotic properties of the proposed estimator, such as consistency and a central limit theorem, are established. Simulations results are given to evaluate the performance of the proposed method in comparison with other alternative methods.
Home-field advantage affects the local adaptive interaction between Andropogon gerardii ecotypes and rhizobiome

Due to climate change, drought frequencies and severities are predicted to increase across the United States. Plant responses and adaptation to stresses depend on plant genetic and environmental factors. Understanding the effect of those factors on plant performance is required to predict the species responses to environmental change. We used reciprocal gardens planted with distinct regional Andropogon gerardii ecotypes adapted to dry, mesic, and wet environments to characterize their rhizosphere communities using 16S rRNA metabarcode sequencing. Even though the local microbial pool was the main driver of these rhizosphere communities, the significant plant ecotype effect highlighted active microbial recruitment in the rhizosphere driven by ecotype or plant genetic background. Our data also suggest that ecotypes were more successful in recruiting rhizosphere community members unique to their local homesites, supporting the “home field advantage” hypothesis. These unique homesite microbes may represent microbial specialists that are linked to plant stress responses. Further, our data support ecotypic variation in the recruitment of congeneric but distinct bacterial variants, highlighting the nuanced effects of plant ecotypes on the rhizosphere microbiome recruitment. Our results should facilitate expanded studies on understanding the complexity of plant host interactions with local soil microbes and identification of functional potential of recruited microbes. Our study has the potential to aid in predicting ecosystem responses to climate change and the impact of management on restoration practices. Importance In this study, we used reciprocal gardens located across a sharp precipitation gradient to characterize rhizosphere communities of distinct dry, mesic, and wet regional Andropogon gerardii ecotypes. We used16S rRNA amplicon sequencing and focused oligotyping analysis and showed that even though the location was the main driver of the microbial communities, ecotypes could potentially recruit distinct bacterial populations. We showed that different A. gerardii ecotypes were more successful in overall community recruitment and recruitment of microbes unique to the “home” environment, when growing at their “home site”. We found evidence for “home field advantage” interactions between the host and associated rhizobiomes, and the capability of ecotypes to recruit specialized microbes that were potentially linked to plant stress responses. Our study provides insights into the understanding of factors effecting the plant adaptation, improving management strategies, and predicting of the future landscape under the changing climate.
Generation of eco-friendly channel catfish, Ictalurus punctatus, harboring alligator cathelicidin gene with robust disease resistance by harnessing different CRISPR/Cas9-mediated systems

The CRISPR/Cas9 platform holds promise for modifying fish traits of interest as a precise and versatile tool for genome manipulation. To reduce introgression of transgene and control reproduction, catfish species have been studied for upscaled disease resistance and intervening of reproduction to lower the potential environmental risks of introgression of escapees’ as transgenic animals. Taking advantage of the CRISPR/Cas9-mediated system, we succeeded in integrating the cathelicidin gene from an alligator (Alligator sinensis; As-Cath) into the target luteinizing hormone (LH) locus of channel catfish (Ictalurus punctatus) using two delivery systems assisted by double-stranded DNA (dsDNA) and single-stranded oligodeoxynucleotides (ssODNs), respectively. In this study, high knock-in (KI) efficiency (22.38%, 64/286) but low on-target was achieved using the ssODN strategy, whereas adopting a dsDNA as the donor template led to an efficient on-target KI (10.80%, 23/213). On-target KI of As-Cath was instrumental in establishing the LH knockout (LH−_As-Cath+) catfish line, which displayed heightened disease resistance and reduced fecundity compared to the wild-type sibling fish. Furthermore, implanting with HCG and LHRHa can restore the fecundity, spawnability and hatchability of the new transgenic fish line. Overall, we replaced the LH gene with an alligator cathelicidin transgene and then administered hormone therapy to gain complete reproductive control of disease-resistant transgenic catfish in an environmentally sound manner. This strategy not only effectively improves the consumer-valued traits, but also guards against genetic contamination. This is a breakthrough in aquaculture genetics to confine fish reproduction and prevent the establishment of transgenic or domestic genotypes in the natural environment.
Altered hierarchical auditory predictive processing after lesions to the orbitofrontal cortex

Orbitofrontal cortex (OFC) is classically linked to inhibitory control, emotion regulation and reward processing. Recent perspectives propose that the OFC also generates predictions about perceptual events, actions, and their outcomes. We tested the role of the OFC in detecting violations of prediction at two levels of abstraction (i.e., hierarchical predictive processing) by studying the event-related potentials (ERPs) of patients with focal OFC lesions (n = 12) and healthy controls (n = 14) while they detected deviant sequences of tones in a Local-Global paradigm. The structural regularities of the tones were controlled at two hierarchical levels by rules defined at a local (i.e., between tones within sequences) and at a global (i.e., between sequences) level. In OFC patients, ERPs elicited by standard tones were unaffected at both local and global levels compared to controls. However, patients showed an attenuated mismatch negativity (MMN) and P3a to local prediction violation, as well as a diminished MMN followed by a delayed P3a to the combined local and global level prediction violation. The subsequent P3b component to conditions involving violations of prediction at the level of global rules was preserved in the OFC group. Comparable effects were absent in patients with lesions restricted to the lateral PFC, which lends a degree of anatomical specificity to the altered predictive processing resulting from OFC lesion. Overall, the altered magnitudes and time courses of MMN/P3a responses after lesions to the OFC indicate that the neural correlates of detection of auditory regularity violation is impacted at two hierarchical levels of rule abstraction. Highlights Orbitofrontal lesions reduce auditory MMN to unpredicted tones at the local level (between tones within sequences) of the rule hierarchy in the Local-Global paradigm. Orbitofrontal lesions also impact combined local and global (between sequences) level auditory deviance response, as manifested by diminished and delayed MMN and delayed P3a.
Scale coupling in Richtmyer-Meshkov flows induced by strong shocks

We perform the first systematic study of the nonlinear evolution and scale coupling in Richtmyer-Meshkov (RM) flows induced by strong shocks. The smoothed particle hydrodynamics code (SPHC) is employed to ensure accurate shock capturing, interface tracking and accounting for the dissipation processes. We find that in strong-shock-driven RMI the background motion is supersonic. The amplitude of the initial perturbation strongly influences the flow evolution and the interfacial mixing that can be sub-sonic or supersonic. At late times the flow remains laminar rather than turbulent, and RM bubbles flatten and decelerate. In the fluid bulk, reverse cumulative jets appear and “hot spots” are formed—local heterogeneous microstructures with temperature substantially higher than that in the ambient. Our numerical simulations agree with the zero-order, linear, weakly nonlinear, and highly nonlinear theoretical analyses as well as with the experiments and suggest that the evolution of RMI is a multi-scale and heter.
Machine Learning Applied to Battery Prognostics based on Advanced State of Health Estimation

Lithium Ion batteries are very attractive technology in the field of electric energy-storage devices with high energy and power densities. Knowledge of lithium-ion lifetime and aging acceleration factors is a crucial aspect for fruitful market introduction, including automotive and embedded applications. The degradation of batteries through various mechanisms over time is due to several factors, such as: temperature, voltage, time for calendar aging, Depth Of Discharge (DOD), State Of Charge (SOC), range and current rate. That’s why it is extremely important to get an accurate prediction of the factors that cause battery degradation. This paper analyzes the extent to which these factors cause battery degradation. Our approach has been tested on the Massachusetts Institute of Technology (MIT) datasets, and the experimental results show the effectiveness of the proposed approach.
A Representation-Based Query Strategy to Derive Qualitative Features for Improved Churn Prediction

The effectiveness of any Machine Learning process depends on the accuracy of annotated data that is used to train a learner. However, manual annotation is expensive. Hence, researchers adopt a semi-supervised approach called active learning that aims to achieve state-of-the-art performance using minimal number of samples. Although it boosts classifier performance, the underlying query strategies are unable to eliminate redundancy in selected samples. Redundant samples lead to increased cost and sub-optimal performance of learner. Inspired by this challenge, the study proposes a new representation-based query strategy that selects highly informative and representative subsets of samples for manual annotation. Data comprises messages of a set of customers sent to a service provider. Series of experiments are conducted to analyze the effectiveness of the proposed query strategy, called “Entropy-based Min Max Similarity” (E-MMSIM), in the context of topic classification for churn prediction. The foundation of E-MMSIM is an algorithm that is popularly used to sequence proteins in protein databases. The algorithm is modified and utilized to select the most representative and informative samples. The performance is evaluated using F1-score, AUC and accuracy. It is observed that “E-MMSIM” outperforms popular query strategies, and improves performance of topic classifiers for each of the 4 topics of churn prediction. The trained topic classifiers are used to derive qualitative features. These features are further integrated with structured variables for the same group of customers to predict churn. Experiments provide evidence that inclusion of qualitative features derived using E-MMSIM, enhance the performance of churn classifiers by 5%.
An LSTM Based Strategy for Data and Model Calibration in Subsurface Electromagnetic Imaging

Mismatch between measurements and model used inside the inversion scheme represent a critical point in subsurface electromagnetic imaging. In this paper, a time-domain strategy based on the use of long short-term memory cells is proposed. The approach is assessed through a set of simulations where a couple of antennas are used to acquire scattered-field data in quasi-monostatic mode. A half-space numerical environment is considered. The processed data are then provided in input to a nonlinear multi-frequency inversion algorithm operating in the context of nonconstant-exponent Lebesgue spaces. Initial tests show promising outcomes.
Development of Amphibious Humanoid Platform for Sensor-based Behavior Acquisition of Whole-body Manipulation Tasks

To build a software platform for research on control and simulation methods for robots that can operate in multiple environments, we need a robot platform that we can use to verify behavior in real diverse surroundings such as land and water. Even though robots need much freedom and perception to work and move around in diverse environments, the more challenging the environment to adapt to, such as underwater or outer space, the more limited the resources we can bring to the environment. In this study, we propose a humanoid robot system that we can use to study the acquisition of whole-body manipulation tasks based on sensor information in water as well as on land by constructing the humanoid with force, vision, and posture perception and multiple degrees of freedom that can use its limbs in various ways such as walking, swimming, and working depending on the condition. As examples of sensor-based whole-body manipulation tasks, we conducted walking experiments, box carrying experiments, remote-control-based wiping experiments in the water, and swimming experiments with object tracking on the water's surface. We discussed the effects of the underwater environment, compared the experimental results between the land and underwater environments, and showed that we could use the proposed robot system to study the acquisition of whole-body manipulation movements in multiple conditions.
Planar Ultra-Wideband Power Dividers for 5G Applications

Power divider is one of the most important devices in microwave and millimeter wave communication systems, which is widely used in antenna array feed systems and power amplifier. Two different planar power dividers that are easy to integrate are proposed in this paper: an 8-way equal power ratio planar power divider with ring circuit and an 8-way planar Gysel power divider with sector layout. The simulation results show that in the range of 5.6GHz~7.4GHz, the insertion loss is less than 0.85 dB, the return loss is greater than 16.16dB, the isolation is greater than 21.41dB and the relative bandwidth is 27.7%.
Design and Rectangular Waveguide Validation of 2-Bit Wideband Reconfigurable Reflective Metasurface Element in X-Band

This letter presents a new design and rectangular waveguide validation of a wideband 2-bit reconfigurable reflective metasurface (RRM) element in the X-band. The element consists of a U-slot microstrip patch, a ground plane, and a 2-bit reflection-type phase shifter (RTPS) controlled by four p-i-n diodes. The direct circuit (DC) biases are elaborated for the 2-bit RTPS so that only two DC bias lines are required to regulate the four p-i-n diodes. The proposed RRM element has a wideband 2-bit phase resolution from 9.1 to 10.85 GHz and can be recognized with great angle stability. The rectangular waveguide experiment was conducted to prove the effectiveness of the proposed element further. The experimental results show that the 17.5% relative bandwidth is achieved under a total phase difference of 270° ± 20° with reflection losses less than 3 dB.