Miracle-dz/UniFAR-FTUs huggingface dataset:
High-throughput microgel biofabrication via air-assisted co-axial jetting for cell encapsulation, 3D bioprinting, and scaffolding applications

Microgels have recently received widespread attention for their applications in a wide array of domains such as tissue engineering, regenerative medicine, and cell and tissue transplantation because of their properties like injectability, modularity, porosity, and the ability to be customized in terms of size, form, and mechanical properties. However, it is still challenging to mass (high-throughput) produce microgels with diverse sizes and tunable properties. Herein, we utilized an air-assisted co-axial device (ACAD) for continuous production of microgels in a high-throughput manner. To test its robustness, microgels of multiple hydrogels and their combination, including alginate (Alg), gelatin methacrylate (GelMA) and Alg–GelMA, were formed at a maximum production rate of ∼65 000 microgels s−1 while retaining circularity and a size range of 50–500 µm based on varying air pressure levels. The ACAD platform allowed single and multiple cell encapsulation with 74 ± 6% efficiency. These microgels illustrated appealing rheological properties such as yield stress, viscosity, and shear modulus for bioprinting applications. Specifically, Alg microgels have the potential to be used as a sacrificial support bath while GelMA microgels have potential for direct extrusion both on their own or when loaded in a bulk GelMA hydrogel. Generated microgels showed high cell viability (>90%) and proliferation of MDA-MB-231 and human dermal fibroblasts over seven days in both encapsulation and scaffolding applications, particularly for GelMA microgels. The developed strategy provides a facile and rapid approach without any complex or expensive consumables and accessories for scalable high-throughput microgel production for cell therapy, tissue regeneration and 3D bioprinting applications.
MRPS36 provides a missing link in the eukaryotic 2-oxoglutarate dehydrogenase complex for recruitment of E3 to the E2 core

The tricarboxylic acid (TCA) cycle, or Krebs cycle, is the central pathway of energy production in eukaryotic cells and plays a key part in aerobic respiration throughout all kingdoms of life. The enzymes involved in this cycle generate the reducing equivalents NADH and FADH2 by a series of enzymatic reactions, which are utilized by the electron transport chain to produce ATP. One of the pivotal enzymes in this cycle is 2-oxoglutarate dehydrogenase complex (OGDHC), which generates NADH by oxidative decarboxylation of 2-oxoglutarate to succinyl-CoA. OGDHC is a megadalton protein complex originally thought to be assembled just from three catalytically active subunits (E1o, E2o, E3). In fungi and animals, however, the protein MRPS36 has more recently been proposed as a putative additional component. Based on extensive XL-MS data obtained from measurements in mice and bovine heart mitochondria, supported by phylogenetic analyses, we provide evidence that MRPS36 is an essential member of OGDHC, albeit only in eukaryotes. Comparative sequence analysis and computational structure predictions reveal that in eukaryotic OGDHC, E2o does not contain the peripheral subunit-binding domain (PSBD), present in bacterial and archaeal E2o’s. We propose that in eukaryotes MRPS36 evolved as an E3 adaptor protein, functionally replacing the PSBD. We further provide a refined structural model of the complete eukaryotic OGDHC containing 16 E1o, 12 E3, and 6 subunits of MRPS36 accommodated around the OGDHC core composed of 24 E2o subunits (3.45 MDa). The model provides new insights into the OGDH complex topology and stipulates putative mechanistic implications.
Lack of accelerated ovarian aging in a follicle-stimulating hormone receptor haploinsufficiency model

Follicle-stimulation hormone (FSH) and FSH receptor (FSHR) signaling is essential for lifelong ovarian and endocrine functions in females. Previous studies have reported that Fshr haploinsufficiency in female mice led to accelerated ovarian aging, including anticipated progressive fertility decline, irregular estrus cycles, increased follicular atresia and premature ovarian failure at 7 to 9 months of age. Interestingly, these phenotypes resemble key characteristics of human menopause and thus Fshr haploinsufficiency was proposed as a promising research mouse model of menopause. However, the Fshr haploinsufficiency model had not been fully explored, especially at the molecular level. In this study, we characterized the ovarian and endocrine functions of a Fshr heterozygous knockout allele that was generated on the C57BL/6 genetic background as part of the Knockout Mouse Project (KOMP). Based on our analyses of these mice using a breeding assay, ovarian tissue histology and serum hormone quantifications (i.e. FSH, AMH, INHA) analyses, the KOMP Fshr heterozygous knockout female mice do not show the anticipated phenotypes of ovarian aging in terms of fertility and endocrine function. We further confirmed that the expression of Fshr is unaltered in the ovaries of the KOMP Fshr heterozygous knockout animals compared to wild-type. Together, our data suggests that the KOMP Fshr heterozygous knockout strain does not recapitulate the previously reported ovarian aging phenotypes associated to another model of Fshr haploinsufficiency.
Majority of the highly variable NLRs in maize share genomic location and contain additional target-binding domains

Nucleotide-binding Leucine Rich Repeat proteins (NLRs) are a major class of immune receptors in plants. NLRs include both conserved and rapidly evolving members, however their evolutionary trajectory in crops remains understudied. Availability of crop pan-genomes enables analysis of the recent events in the evolution of this highly complex gene family within domesticated species. Here, we investigated the NLR complement of 26 nested association mapping (NAM) founder lines of maize. We found that maize has just four main subfamilies containing rapidly evolving highly variable NLR (hvNLR) receptors. Curiously, three of these phylogenetically distinct hvNLR lineages are located in adjacent clusters on chromosome 10. By combining sequence diversity analysis and AlphaFold2 computational structure prediction we predicted ligand binding sites in the hvNLRs. We also observed novel insertion domains in the LRR regions of two hvNLR subfamilies that likely contribute to target recogniton. To make this analysis accessible, we created NLRCladeFinder, a Google Colaboratory notebook, that accepts any newly identified NLR sequence, places it in the evolutionary context of maize pan-NLRome, and provides an updated clade alignment, phylogenetic tree, and sequence diversity information for the gene of interest.
THERE ARE NO STARLESS MASSIVE PROTO-CLUSTERS IN THE FIRST QUADRANT OF THE GALAXY

We search the λ = 1.1 mm Bolocam Galactic Plane Survey for clumps containing sufficient mass to form ∼104 M☉ star clusters. Eighteen candidate massive proto-clusters are identified in the first Galactic quadrant outside of the central kiloparsec. This sample is complete to clumps with mass Mclump > 104 M☉ and radius r ≲ 2.5 pc. The overall Galactic massive cluster formation rate is CFR(Mcluster > 104) ≲ 5 Myr−1, which is in agreement with the rates inferred from Galactic open clusters and M31 massive clusters. We find that all massive proto-clusters in the first quadrant are actively forming massive stars and place an upper limit of τstarless < 0.5 Myr on the lifetime of the starless phase of massive cluster formation. If massive clusters go through a starless phase with all of their mass in a single clump, the lifetime of this phase is very short.
MHC class Ia molecules facilitate MCK2-dependent MCMV infection of macrophages and virus dissemination to the salivary gland

Murine cytomegalovirus (MCMV) infection of macrophages relies on MCMV-encoded chemokine 2 (MCK2) through one or more unknown cellular receptors while infection of fibroblast occurs independent of MCK2 and is mediated by cell-expressed neuropilin 1. Applying a CRISPR screen, we now identified that the MHC-Ia/Beta-2-microglobulin (B2m) complex serves as an entry port for MCK2-mediated infection of macrophages. Further analyses revealed that MCK2-dependent infection requires expression of the MHC-Ia haplotypes H-2b and H-2d but not H-2k. The importance of the MCK2-MHC-I-pathway for primary infection and viral dissemination was highlighted by experiments with B2m-deficient mice, which lack surface expression of MHC-I molecules. In those mice, intranasally administered MCK2-proficient MCMV could not infect alveolar macrophages and subsequently failed to disseminate into the salivary glands. The identified molecular pathway used by MCMV to infect lung resident macrophages provides essential knowledge for understanding cytomegalovirus-induced pathogenesis, tissue targeting, and virus dissemination.
Activity of tonically active neurons in the primate striatum reflects interaction between time processing and reward prediction

The striatum and its dopaminergic input participate in temporal processing and numerous studies provide evidence that interactions between dopamine and acetylcholine are critical for striatal functioning. However, the role of local cholinergic innervation of the striatum in behaviors requiring precise timing has not been specifically investigated. Here, we recorded from presumed striatal cholinergic interneurons, identified as tonically active neurons (TANs), in two male rhesus monkeys performing self-initiated movements after specified learned time intervals have elapsed since a visual cue. We found that 38% of all recorded TANs responded to the cue with a pause in firing and the strength of these responses could be modulated according to the duration of the interval being timed and the accuracy of time estimates. By examining the TAN response to the reward itself and by recording from TANs during a Pavlovian procedure in which no action was required, we found evidence that TAN activity modulation may potentially reflect differences in the animal’s prediction of reward. Thus, besides their well-known role in predicting and detecting rewarding events, TANs may generate signals related to the processing of time. Our findings suggest a role of the local cholinergic circuitry in the representation of time within the striatum.
Early Growth Assessment of Treculia africana Seedlings Influenced by Different Light Intensities and Mycorrhizal Inoculation

Light is essential for plant growth. The rate at which a plant grows depends on the light it receives. This study was carried out to observe the growth of Treculia africana seedlings under different light intensities (100%, 75%, 50%, and 25%) and mycorrhiza inoculation (Ectomycorrhiza, Endomycorrhiza, and topsoil {control}) with five replicates in each treatment. The experiment was laid out in a 3×4 factorial in CRD, and data were collected fortnightly for twelve (12) weeks. Data were subjected to analysis of variance in SAS, and the significant mean was separated using Fisher’s LSD. The result showed that the seedlings inoculated with ectomycorrhizal had the highest plant height (15.08), leaf area (26.90), number of leaves (5.75), collar diameter (2.61), fresh shoot weight (3.86), root weight (3.86), fresh weight (7.44), dry root weight (1.53), dry weight (2.87), absolute growth rate (0.34) and relative growth rate (0.39) which was significantly different from other treatment. Seedlings exposed to 75% and 25% light intensity had the highest performances compared to seedlings exposed to different light intensities. There was no significant difference (P>0.05) in the seedlings’ physiological variables assessed under the interaction of different light intensities and mycorrhiza inoculation. The seedlings inoculated with ectomycorrhizal and raised in 25% light intensity had the overall highest performance in all the growth variables assessed. Therefore, this study recommends raising Treculia africana seedlings with the inoculation of ectomycorrhizal and under shade to enhance early growth and massive nursery production.
Plant Breeding in the face of climate change

Climate change will have a net negative and inequitable impact on agriculture. Genetics for crop improvement ranks in the top set of technologies that can contribute to human adaptation to climate change. However, a framework for how to breed crops for climate change adaptation is lacking. Here we propose a framework to develop new genotype (G) x management (M) technologies (G x M) to adapt to climate change, and to transition from current to future G x M technologies in a way that future food security does not come at the expense of current food security. The framework integrate genomic, agronomic, and environmental (E) predictors to accomplish two critical goals: 1-predict emergent phenotypes that stems from the dynamic interplay between G, E and M, and thus enable the breeder to consider the behavior of new genetic and trait combinations in environments that plants have not been exposed or tested before, and 2-identify G x M technologies that could increase food and nutritional security while regenerating natural and production resources. We highlight the need to invest in artificial intelligence and information technologies for breeders to harness multiple sources of information to create G x M technologies to address the diverse cultural and geographically granular societal needs.
Using SuperClomeleon to Measure Changes in Intracellular Chloride during Development and after Early Life Stress

Abstract Intraneuronal chloride concentrations ([Cl−]i) decrease during development resulting in a shift from depolarizing to hyperpolarizing GABA responses via chloride-permeable GABAA receptors. This GABA shift plays a pivotal role in postnatal brain development, and can be strongly influenced by early life experience. Here, we assessed the applicability of the recently developed fluorescent SuperClomeleon (SClm) sensor to examine changes in [Cl−]i using two-photon microscopy in brain slices. We used SClm mice of both sexes to monitor the developmental decrease in neuronal chloride levels in organotypic hippocampal cultures. We could discern a clear reduction in [Cl−]i between day in vitro (DIV)3 and DIV9 (equivalent to the second postnatal week in vivo) and a further decrease in some cells until DIV22. In addition, we assessed alterations in [Cl−]i in the medial prefrontal cortex (mPFC) of postnatal day (P)9 male SClm mouse pups after early life stress (ELS). ELS was induced by limiting nesting material between P2 and P9. ELS induced a shift toward higher (i.e., immature) chloride levels in layer 2/3 cells in the mPFC. Although conversion from SClm fluorescence to absolute chloride concentrations proved difficult, our study underscores that the SClm sensor is a powerful tool to measure physiological changes in [Cl−]i in brain slices.
Coinfection with Intestinal Parasite Expands Resident Macrophages and Impairs Control of Chronic Herpesvirus Infection

In addition to a range of homeostatic functions, resident macrophages are essential for immune surveillance in tissues. Therefore, anything that alters the phenotype or function of these cells potentially impacts their response to infectious challenges. Parasite infections cause proliferation of large peritoneal macrophages (LPMs), which are the resident macrophages of the peritoneal cavity. However, the functional consequences of LPM expansion on the control of secondary infectious challenge is unknown. Using a coinfection model with the intestinal parasite Heligmosomoides polygyrus (HP) and the virus, murine gammaherpesvirus-68 (MHV68), we investigated the impact of LPM expansion on viral infection. We determined that LPM expansion induced by HP required retinoic acid signaling. When we challenged HP-infected mice with MHV68, we observed increased herpesvirus infection and latency. Coinfection of mice with macrophage-specific deletion of GATA6, the retinoic acid-responsive transcription factor that drives LPM transcriptional programming, eradicated the increase in viral infection. In addition to increased MHV68 infection, parasite coinfected mice displayed increased herpesvirus reactivation from latency, indicating impaired control of chronic herpesvirus infection. Elimination of dietary vitamin A, which depletes retinoic acid and LPMs, abolished the increased MHV68 reactivation in parasite coinfected mice. These results indicate that parasite- and retinoic acid-mediated resident macrophage expansion drives increased herpesvirus infection, latency, and reactivation.
Welcome to the big leaves: Best practices for improving genome annotation in non‐model plant genomes

• Premise of the study Robust standards to evaluate quality and completeness are lacking for eukaryotic structural genome annotation. Genome annotation software is developed with model organisms and does not typically include benchmarking to comprehensively evaluate the quality and accuracy of the final predictions. Plant genomes are particularly challenging with their large genome sizes, abundant transposable elements (TEs), and variable ploidies. This study investigates the impact of genome quality, complexity, sequence read input, and approach on protein-coding gene prediction. • Methods The impact of repeat masking, long-read, and short-read inputs, de novo, and genome-guided protein evidence was examined in the context of the popular BRAKER and MAKER workflows for five plant genomes. Annotations were benchmarked for structural traits and sequence similarity. • Results Benchmarks that reflect gene structures, reciprocal similarity search alignments, and mono-exonic/multi-exonic gene counts provide a more complete view of annotation accuracy. Transcripts derived from RNA-read alignments alone are not sufficient for genome annotation. Gene prediction workflows that combine evidence-based and ab initio approaches are recommended, and a combination of short and long-reads can improve genome annotation. Adding protein evidence from de novo assemblies, genome-guided transcriptome assemblies, or full-length proteins from OrthoDB generates more putative false positives as implemented in the current workflows. Post-processing with functional and structural filters is highly recommended. • Discussion While annotation of non-model plant genomes remains complex, this study provides recommendations for inputs and methodological approaches. We discuss a set of best practices to generate an optimal plant genome annotation, and present a more robust set of metrics to evaluate the resulting predictions.
The neural correlates of continuous feedback processing

Feedback processing is commonly studied by analyzing the brain’s response to discrete rather than continuous events. Such studies have led to the hypothesis that rapid phasic midbrain dopaminergic activity tracks reward prediction errors (RPEs), the effects of which are measurable at the scalp via electroencephalography (EEG). Although studies using continuous feedback are sparse, recent animal work suggests that moment-to-moment changes in reward are tracked by slowly ramping midbrain dopaminergic activity. Some have argued that these ramping signals index state values rather than RPEs. Our goal here was to develop an EEG measure of continuous feedback processing in humans, then test whether its behaviour could be accounted for by the RPE hypothesis. Participants completed a stimulus-response learning task in which a continuous reward cue gradually increased or decreased over time. A regression-based unmixing approach revealed EEG activity with a topography and timecourse consistent with the stimulus-preceding negativity (SPN), a scalp potential previously linked to reward anticipation and tonic dopamine release. Importantly, this reward-related activity depended on outcome expectancy: as predicted by the RPE hypothesis, activity for expected reward cues was reduced compared to unexpected reward cues. These results demonstrate the possibility of using human scalp-recorded potentials to track continuous feedback processing, and test candidate hypotheses of this activity.
Kinetics of blood cell differentiation during hematopoiesis revealed by quantitative long-term live imaging

Stem cells typically reside in a specialized physical and biochemical environment that facilitates regulation of their behavior. For this reason, stem cells are ideally studied in contexts that maintain this precisely constructed microenvironment while still allowing for live imaging. Here, we describe a long-term organ culture and imaging strategy for hematopoiesis in flies that takes advantage of powerful genetic and transgenic tools available in this system. We find that fly blood progenitors undergo symmetric cell divisions and that their division is both linked to cell size and is spatially oriented. Using quantitative imaging to simultaneously track markers for stemness and differentiation in progenitors, we identify two types of differentiation that exhibit distinct kinetics. Moreover, we find that infection-induced activation of hematopoiesis occurs through modulation of the kinetics of cell differentiation. Overall, our results show that even subtle shifts in proliferation and differentiation kinetics can have large and aggregate effects to transform blood progenitors from a quiescent to an activated state.
Noninvasive, automated and reliable detection of spreading depolarizations in severe traumatic brain injury using scalp EEG

Background Noninvasive detection of spreading depolarizations (SD), as a potentially treatable mechanism of worsening brain injuries after traumatic brain injuries (TBI), has remained elusive. Current methods to detect SDs are based on intracranial recording, an invasive method with limited spatial coverage. Less invasive methods to diagnose SD are needed to improve generalizability and application of this emerging science and to guide worsening brain injury treatments. Here, we demonstrate, for the first time, a signal processing paradigm that can enable automated detection of SDs using noninvasive electroencephalography (EEG). Methods Building on our previously developed WAVEFRONT algorithm, we have designed a novel automated SD detection method. This algorithm, with learnable parameters and improved velocity estimation, extracts and tracks propagating power depressions, as well as near-DC shifts using low-density EEG. This modified WAVEFRONT is robust to the amplitude outliers and non-propagating depressions on the scalp. We show the feasibility of detecting SD events (700 total SDs) in continuous, low-density scalp EEG recording (95±42.2 hours with 19 electrodes) acquired from 12 severe TBI patients who underwent decompressive hemicraniectomy (DHC) and intracranial EEG that could be used as a ground truth for event detection. We quantify the performance of WAVEFRONT in terms of SD detection accuracy, including true positive rate (TPR) and false positive rate (FPR), as well as the accuracy of estimating the frequency of SDs. Results WAVEFRONT achieves the best average validation accuracy of 74% TPR (with 95% confidence interval of 70.8%-76.7%), with less than 1.5% FPR using Delta band EEG. Preliminary evidence suggests that WAVEFRONT can achieve a very good performance (regression with R2 ≃0.71) in the estimation of SD frequencies. Conclusions We demonstrate feasibility and quantify the performance of noninvasive SD detection after severe TBI using an automated algorithm. WAVEFRONT can potentially be used for diagnosis and monitoring of worsening brain injuries to guide treatments by providing a measure of SD frequency. Extension of these results to patients with intact skulls requires further study.