Miracle-dz/UniFAR-FTUs huggingface dataset:
MHC-matched allogeneic bone marrow transplants fail to eliminate SHIV-infected cells from ART-suppressed Mauritian cynomolgus macaques

Background Allogeneic hematopoietic stem cell transplants (allo-HSCTs) dramatically reduce HIV reservoirs in antiretroviral therapy (ART) suppressed individuals. However, the mechanism(s) responsible for these post-transplant viral reservoir declines are not fully understood but may include pre-transplant conditioning regimens, ART-mediated protection of donor cells, and graft-versus-host (GvH) responses. Therefore, we modeled allo-HSCT in ART-suppressed simian-human immunodeficiency virus (SHIV)-infected Mauritian cynomolgus macaques (MCMs) to illuminate factors contributing to transplant-induced viral reservoir decay. Results We infected four MCMs with CCR5-tropic SHIV162P3 and started ART 6-16 weeks post-infection (p.i.) to establish robust viral reservoirs. We maintained the MCMs on continuous ART during myeloablative conditioning with total body irradiation (TBI) and while transplanting allogeneic MHC-matched α/β T cell-depleted bone marrow cells. Post-transplant, we prophylactically treated the MCMs with cyclophosphamide and tacrolimus to prevent GvH disease (GvHD). The transplants produced ~85% whole blood donor chimerism without causing high-grade GvHD. Consequently, three MCMs had undetectable SHIV DNA in their peripheral blood mononuclear cells post-transplant. However, SHIV-harboring cells persisted in various tissues. We detected viral DNA in lymph node biopsies and terminal analyses of tissues between 38 and 62 days post-transplant. Further, we removed ART from one MCM at 63 days post-transplant, resulting in viral rebound within seven days and viral loads nearing 1×108 SHIV RNA copies/ml of plasma after treatment interruption. Conclusions Our results indicate that myeloablative conditioning and maintaining ART through the peri-transplant period alone are insufficient for eradicating latent viral reservoirs early after allo-HSCTs. Furthermore, our findings suggest that extended ART and GvH responses may be necessary to substantially deplete viral reservoirs after allo-HSCTs.
Phytophthora capsici sterol reductase PcDHCR7 has a role in mycelium development and pathogenicity

The de novo biosynthesis of sterols is critical for eukaryotes, however, some organisms lack this pathway including most oomycetes. Phytophthora spp. are sterol auxotroph but remarkably, have retained a few genes encoding enzymes in the sterol biosynthesis pathway. Here we investigated the function of PcDHCR7, a gene in Phytophthora capsici predicted to encode the △7-sterol reductase. When expressed in Saccharomyces cerevisiae, PcDHCR7 showed a △7-sterol reductase activity. Knocking out PcDHCR7 in P. capsici resulted in loss of the capacity to transform ergosterol into brassicasterol, which means PcDHCR7 has a △7-sterol reductase activity in P. capsici itself. This enables P. capsici to transform sterols recruited from the environment for better use. Biological characteristics were compared between wild-type isolate and PcDHCR7 knock-out transformants. The results indicated that PcDHCR7 plays a key role in mycelium development and pathogenicity of zoospores in P. capsici.
Interaction of the causal agent of apricot bud gall Acalitus phloeocoptes (Nalepa) with apricot: Implications in infested tissues

Apricot bud gall mite, Acalitus phloeocoptes (Nalepa), is a destructive arthropod pest that causes significant economic losses to apricot trees worldwide. Infested bud examination revealed that the starch granules in the bud axon were extended at the onset of the attack. During the later stages of the attack, the cytoplasm was distributed in apricot. The results also demonstrated that the accumulation of large amounts of cytokinin (zeatin, ZT) and auxin (indoleacetic acid, IAA) led to rapid bud proliferation during the rapid growth period. Abscisic acid (ABA) controls the development of gall buds and plays a vital role in gall bud maturity. The reduction of gibberellic acid (GA3) content led to rapid lignification at the later phase of bud development. Our results reveal the mechanism underlying the interaction of apricot bud gall with its parasite and provide reliable information for designing valuable breeding programs. This study will be quite useful for pest management and will provide a comprehensive evaluation of ecology-based cost-effective control, life history and demographic parameters of A. phloeocoptes.
Axonal CB1 Receptors Mediate Inhibitory Bouton Formation via cAMP Increase and PKA

Experience-dependent formation and removal of inhibitory synapses are essential throughout life. For instance, GABAergic synapses are removed to facilitate learning, and strong excitatory activity is accompanied by the formation of inhibitory synapses to maintain coordination between excitation and inhibition. We recently discovered that active dendrites trigger the growth of inhibitory synapses via CB1 receptor-mediated endocannabinoid signaling, but the underlying mechanism remained unclear. Using two-photon microscopy to monitor the formation of individual inhibitory boutons in hippocampal organotypic slices from mice (both sexes), we found that CB1 receptor activation mediated the formation of inhibitory boutons and promoted their subsequent stabilization. Inhibitory bouton formation did not require neuronal activity and was independent of Gi/o-protein signaling, but was directly induced by elevating cAMP levels using forskolin and by activating Gs-proteins using DREADDs. Blocking PKA activity prevented CB1 receptor-mediated inhibitory bouton formation. Our findings reveal that axonal CB1 receptors signal via unconventional downstream pathways and that inhibitory bouton formation is triggered by an increase in axonal cAMP levels. Our results demonstrate an unexpected role for axonal CB1 receptors in axon-specific, and context-dependent, inhibitory synapse formation. SIGNIFICANCE STATEMENT Coordination between excitation and inhibition is required for proper brain function throughout life. It was previously shown that new inhibitory synapses can be formed in response to strong excitation to maintain this coordination, and this was mediated by endocannabinoid signaling via CB1 receptors. As activation of CB1 receptors generally results in the suppression of synaptic transmission, it remained unclear how CB1 receptors can mediate the formation of inhibitory synapses. Here we show that CB1 receptors on inhibitory axons signal via unconventional intracellular pathways and that inhibitory bouton formation is triggered by an increase in axonal cAMP levels and requires PKA activity. Our findings point to a central role for axonal cAMP signaling in activity-dependent inhibitory synapse formation.
Odor induces characteristic time courses of theta, beta and gamma oscillations in human olfactory cortex

Neuronal oscillations are fundamental to cognition, facilitating coordination and communication of information within and across brain regions. Studies on the spectral and temporal dynamics of oscillatory rhythms have contributed substantial insight to our understanding of mechanisms of human visual, auditory and somatosensory perception. However, these oscillations have been largely unexplored in the human olfactory system, where we lack basic understanding of fundamental spectrotemporal and functional properties. Determining if and how dynamic signatures of neural activity occur in human olfactory cortex is critical to understanding how we process odors. Here, we establish a characteristic oscillatory response to an odor in the human brain. Using direct electrical recordings from human piriform cortex, we identified three key odor-induced rhythms, in the theta (4-8Hz), beta (13-30Hz) and gamma (30-150Hz) frequency bands, each with distinct functional and temporal properties. While theta emerges and dissipates rapidly at the start of inhalation, beta and gamma emerge later, with beta persisting through exhalation, and gamma peaking around the transition between inhalation and exhalation. Beta and gamma amplitudes strongly predict odor identification ability, whereas theta does not. Theta phase modulates beta and gamma amplitudes during inhalation, only when odor is present. Our findings establish that smells elicit distinct neuronal rhythms in human olfactory cortex, which are dynamically interplayed over the course of a sniff. Our data further suggest a fundamental role for beta and gamma oscillations in human olfactory processing, and that their amplitudes—organized by theta phase—subserve odor identification in humans.
Visual thalamocortical mechanisms of waking state-dependent activity and alpha oscillations

The brain exhibits distinct patterns of recurrent activity closely related to the behavioral state of the animal. The neural mechanisms that underlie state-dependent activity in the awake animal are incompletely understood. Here, we demonstrate that two types of state-dependent activity - rapid arousal/movement related signals and a 3-5 Hz alpha-like rhythm - in the primary visual cortex (V1) of mice strongly correlate with activity in the visual thalamus. Inactivation of V1 does not interrupt arousal/movement related signals in most visual thalamic neurons, but it abolishes the 3-5 Hz oscillation. Silencing of the visual thalamus similarly eradicates the alpha-like rhythm and perturbs arousal/movement-related activation in V1. Finally, we observed that whisker movement or locomotion is not required for rapid increases in cortical activation. Our results indicate that thalamocortical interactions together with cell-intrinsic properties of thalamocortical cells play a crucial role in shaping state-dependent activity in V1 of the awake animal. Highlights Whisker movements correlate with rapid synaptic activation in V1 and visual thalamus Silencing of V1 does not abolish movement related activation in most dLGN or LP cells Silencing of visual thalamus strongly reduces movement related activation in V1 Thalamocortical interactions generate state-dependent alpha frequency oscillation Visual thalamic cells exhibit LTS firing during alpha oscillation in the awake mouse
The extracellular matrix controls stem cell specification and crypt morphology in the developing and adult mouse gut

The rapid renewal of the epithelial gut lining is fuelled by stem cells that reside at the base of intestinal crypts. In recent years, the signal transduction pathways and morphogens that regulate intestinal stem cell self-renewal and differentiation have been extensively characterised. In contrast, although extracellular matrix (ECM) components form an integral part of the intestinal stem cell niche, their direct influence on the cellular composition is less well understood. Here, we set out to systematically compare the effect of two major ECM classes, fibrillar collagen type I and the basement membrane, on the intestinal epithelium. We found that both collagen I and laminin-containing cultures allow growth of small intestinal epithelial cells with all differentiated and undifferentiated cell types present in both cultures, albeit at different ratios. Specific to the collagen culture was a subset of cells with a fetal-like gene expression program. In contrast, laminin, but not collagen IV, increased Lgr5+ stem cells and Paneth cells, and induced crypt-like morphology changes. The transition from a collagen culture to a laminin culture, resembles the gut development in vivo. Here, the ECM is dramatically remodelled by mesenchymal cells, which is accompanied by a specific and local expression of the laminin receptor ITGA6 in the crypt-forming epithelium. This laminin:ITGA6 signalling is essential for the stem cell induction and crypt formation in vitro. Importantly, deletion of laminin in the adult mouse results in a fetal-like epithelium with a marked reduction of adult intestinal stem cells. Overall, our data support the hypothesis that the formation of intestinal crypts is induced by an increased laminin concentration in the ECM.
Defective Satellite DNA Clustering into Chromocenters Underlies Hybrid Incompatibility in Drosophila

Although rapid evolution of pericentromeric satellite DNA repeats is theorized to promote hybrid incompatibility (HI)(1–4), how divergent repeats affect hybrid cells remains poorly understood. Recently, we demonstrated that sequence-specific DNA-binding proteins cluster satellite DNA from multiple chromosomes into ‘chromocenters’, thereby bundling chromosomes to maintain the entire genome in a single nucleus(5, 6). Here we show that ineffective clustering of divergent satellite DNA in the cells of Drosophila hybrids results in chromocenter disruption, associated micronuclei formation and tissue atrophy. We further demonstrate that previously identified HI factors trigger chromocenter disruption and micronuclei in hybrids, linking their function to a conserved cellular process. Together, we propose a unifying framework that explains how the widely observed satellite DNA divergence between closely related species can cause reproductive isolation.
Why is the expression of so many genes rhythmic? Energetic cost explains protein rhythmicity and expression noise control explains mRNA rhythmicity

Many genes have nycthemeral rhythms of expression, i.e. 24-hours periodic variation, at either mRNA or protein level or both, often in a tissue-specific manner. Here we investigate the evolutionary trade-offs which can explain rhythmic expression in different genes and tissues. We test two main advantages for rhythmicity: cost saving on protein production and the control of expression noise. We find that cost saving explains rhythmicity at the protein level, while control of noise explains rhythmicity at the mRNA level. Trends for costs are consistent in bacteria, plants and animals, and are also supported in tissue-specific patterns in mouse. Noise control had strongest support in mouse, with limited power in other species. Genes under stronger purifying selection are rhythmically expressed at the mRNA level, probably because they are noisesensitive genes. Moreover, we suggest that mRNA rhythmicity allows to switch between optimal precision and higher stochasticity. This higher stochasticity allows to maintain oscillations and to exhibit diverse molecular phenotypes, i.e. ”blind anticipation” of cells. The ability to alternate between these two states, enabled by rhythmicity at the mRNA level, might be adaptive in fluctuating environments. The adaptive role of rhythmic expression is also supported by rhythmic genes being highly expressed yet tissue-specific genes. This provides a good evolutionary explanation for the observation that nycthemeral rhythms are often tissue-specific.
Time-series trend of pandemic SARS-CoV-2 variants visualized using batch-learning self-organizing map for oligonucleotide compositions

To confront the global threat of coronavirus disease 2019, a massive number of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome sequences have been decoded, with the results promptly released through the GISAID database. Based on variant types, eight clades have already been defined in GISAID, but the diversity can be far greater. Owing to the explosive increase in available sequences, it is important to develop new technologies that can easily grasp the whole picture of the big-sequence data and support efficient knowledge discovery. An ability to efficiently clarify the detailed time-series changes in genome-wide mutation patterns will enable us to promptly identify and characterize dangerous variants that rapidly increase their population frequency. Here, we collectively analyzed over 150,000 SARS-CoV-2 genomes to understand their overall features and time-dependent changes using a batch-learning self-organizing map (BLSOM) for oligonucleotide composition, which is an unsupervised machine learning method. BLSOM can separate clades defined by GISAID with high precision, and each clade is subdivided into clusters, which shows a differential increase/decrease pattern based on geographic region and time. This allowed us to identify prevalent strains in each region and to show the commonality and diversity of the prevalent strains. Comprehensive characterization of the oligonucleotide composition of SARS-CoV-2 and elucidation of time-series trends of the population frequency of variants can clarify the viral adaptation processes after invasion into the human population and the time-dependent trend of prevalent epidemic strains across various regions, such as continents.
Polarization and Dielectric Study of Methylammonium Lead Iodide Thin Film to Reveal its Nonferroelectric Nature under Solar Cell Operating Conditions

Researchers have debated whether methylammonium lead iodide (MAPbI3), with a perovskite crystal structure, is ferroelectric and therefore contributes to the current–voltage hysteresis commonly observed in hybrid perovskite solar cells (PSCs). We thoroughly investigated temperature-dependent polarization, dielectric, and impedance spectroscopies, and we found no evidence of ferroelectric effect in a MAPbI3 thin film at normal operating conditions. Therefore, the effect does not contribute to the hysteresis in PSCs, whereas the large component of ionic migration observed may play a critical role. Our temperature-based polarization and dielectric studies find that MAPbI3 exhibits different electrical behaviors below and above ca. 45 °C, suggesting a phase transition around this temperature. In particular, we report the activation energies of ionic migration for the two phases and temperature-dependent permittivity of MAPbI3. This study contributes to the understanding of the material properties and device pe.
Learning interpretable cellular responses to complex perturbations in high-throughput screens

Recent advances in multiplexed single-cell transcriptomics experiments are facilitating the high-throughput study of drug and genetic perturbations. However, an exhaustive exploration of the combinatorial perturbation space is experimentally unfeasible, so computational methods are needed to predict, interpret, and prioritize perturbations. Here, we present the compositional perturbation autoencoder (CPA), which combines the interpretability of linear models with the flexibility of deep-learning approaches for single-cell response modeling. CPA encodes and learns transcriptional drug responses across different cell type, dose, and drug combinations. The model produces easy-to-interpret embeddings for drugs and cell types, which enables drug similarity analysis and predictions for unseen dosage and drug combinations. We show that CPA accurately models single-cell perturbations across compounds, doses, species, and time. We further demonstrate that CPA predicts combinatorial genetic interactions of several types, implying that it captures features that distinguish different interaction programs. Finally, we demonstrate that CPA can generate in-silico 5,329 missing genetic combination perturbations (97.6% of all possibilities) with diverse genetic interactions. We envision our model will facilitate efficient experimental design and hypothesis generation by enabling in-silico response prediction at the single-cell level, and thus accelerate therapeutic applications using single-cell technologies.
Structural brain connectivity in children with developmental dyscalculia

Developmental dyscalculia (DD) is a neurodevelopmental disorder specific to arithmetic learning even with normal intelligence and age-appropriate education. Difficulties often persist from childhood through adulthood. Underlying neurobiological mechanisms of DD, however, are poorly understood. This study aimed to identify possible structural connectivity alterations in DD. We evaluated 10 children with pure DD (11.3 ± 0.7 years) and 16 typically developing (TD) peers (11.2 ± 0.6 years) using diffusion tensor imaging. We first assessed white matter microstructure with tract-based spatial statistics. Then we used probabilistic tractography to evaluate tract lengths and probabilistic connectivity maps in specific regions. At whole brain level, we found no significant microstructural differences in white matter between children with DD and TD peers. Also, seed-based connectivity probabilities did not differ between groups. However, we did find significant differences in regions-of-interest tracts which had previously been related to math ability in children. The major findings of our study were reduced white matter coherence and shorter tract lengths of the left superior longitudinal/arcuate fasciculus and left anterior thalamic radiation in the DD group. Furthermore, lower white matter coherence and shorter pathways corresponded with the lower math performance as a result of the correlation analyses. These results from regional analyses indicate that learning, memory and language-related pathways in the left hemisphere might underlie DD.
A Coastal Experiment for GNSS-R Code-Level Altimetry Using BDS-3 New Civil Signals

High temporal and spatial resolutions are the key advantages of the global navigation satellites system-reflectometry (GNSS-R) technique, while low precision and instabilities constrain its development. Compared with conventional Ku/C band nadir-looking radar altimetry, the precision of GNSS-R code-level altimetry is restricted by the smaller bandwidth and the lower transmitted power of the signals. Fortunately, modernized GNSS broadcast new open-available ranging codes with wider bandwidth. The Chinese BDS-3 system was built on 31 July 2020; its inclined geostationary orbit and medium circular orbit satellites provide B1C and B2a public navigation service signals in the two frequency bands of B1 and B2. In order to investigate their performance on GNSS-R code-level altimetry, a coastal experiment was conducted on 5 November 2020 at a trestle of Weihai in the Shandong province of China. The raw intermediate frequency data with a 62 MHz sampling rate were collected and post-processed to solve the sea surface height every second continuously for over eight hours. The precisions were evaluated using the measurements from a 26 GHz radar altimeter mounted on the same trestle near our GNSS-R setup. The results show that a centimeter-level accuracy of GNSS-R altimetry—based on B1C code after the application of the moving average—can be achieved, while for B2a code, the accuracy is about 10 to 20 cm.
High-Precision GNSS PWV and Its Variation Characteristics in China Based on Individual Station Meteorological Data

The Global Navigation Satellite System (GNSS) plays an important role in retrieving high temporal–spatial resolution precipitable water vapor (PWV) and its applications. The weighted mean temperature (Tm) is a key parameter for the GNSS PWV estimation, which acts as the conversion factor from the zenith wet delay (ZWD) to the PWV. The Tm is determined by the air pressure and water vapor pressure, while it is not available nearby most GNSS stations. The empirical formular is often applied for the GNSS station surface temperature (Ts) but has a lower accuracy. In this paper, the temporal and spatial distribution characteristics of the coefficients of the linear Tm-Ts model are analyzed, and then a piecewise-linear Tm-Ts relationship is established for each GPS station using radiosonde data collected from 2011 to 2019. The Tm accuracy was increased by more than 10% and 20% for 86 and 52 radiosonde stations, respectively. The PWV time series at 377 GNSS stations from the infrastructure construction of national geodetic datum modernization and Crustal Movement Observation Network of China (CMONC) were further obtained from the GPS observations and meteorological data from 2011 to 2019. The PWV accuracy was improved when compared with the Bevis model. Furthermore, the daily and monthly average values, long-term trend, and its change characteristics of the PWV were analyzed using the high-precision inversion model. The results showed that the averaged PWV was higher in Central-Eastern China and Southern China and lower in Northwest China, Northeast China, and North China. The PWV is increasing in most parts of China, while the some PWVs in North China show a downward trend.