Activation of mitochondrial TUFM ameliorates metabolic dysregulation through coordinating autophagy induction

Leveraging microtopography to pattern multi-oriented muscle actuators

Engineering skeletal muscle tissue with precisely defined alignment is of significant importance for applications ranging from drug screening to biohybrid robotics. Aligning 2D contractile muscle monolayers, which are compatible with high-content imaging and can be deployed in planar soft robots, typically requires micropatterned cues. However, current protocols for integrating microscale topographical features in extracellular matrix hydrogels require expensive microfabrication equipment and multi-step procedures involving error-prone manual handling steps. To address this challenge, we present STAMP (simple templating of actuators via micro-topographical patterning), an easily accessible and cost-effective one-step method to pattern microtopography of various sizes and configurations on the surface of hydrogels using reusable 3D printed stamps. We demonstrate that STAMP enables precisely controlling the alignment of mouse and human skeletal muscle fibers without negatively impacting their maturation or function. To showcase the versatility of our technique, we designed a planar soft robot inspired by the iris, which leverages spatially segregated regions of concentric and radial muscle fibers to control pupil dilation. Optogenetic skeletal muscle fibers grown on a STAMPed iris substrates formed a multi-oriented actuator, and selective light stimulation of the radial and concentric fibers was used to control the function of the iris, including pupil constriction. Computational modeling of the biohybrid robot as an active bilayer matched experimental outcomes, showcasing the robustness of our STAMP method for designing, fabricating, and testing planar biohybrid robots capable of complex multi-DOF motion.

Identification of key genes regulating brown adipose tissue thermogenesis in goat kids (Capra hircus) by using weighted gene co-expression network analysis

Brown adipose tissue (BAT) is crucial for the maintenance of body temperature in newborn animals through non-shivering thermogenesis (NST). However, which kind key genes involved in the regulation of BAT thermogenesis and the internal regulation mechanism of heat production in goat BAT were still unclear. In this study, we analyzed the perirenal adipose tissue transcriptome of Dazu black goats from 0, 7, 14, 21 and 28 days after birth using weighted gene co-expression network analysis (WGCNA) to identify key genes involved in the thermogenesis of BAT. Genes were classified into 22 co-expression modules by WGCNA. The turquoise module exhibited high gene expression in D0, with generally lower expression in the later dates. This pattern is consistent with the rapid color, morphological, and thermogenic changes observed in perirenal adipose tissue shortly after birth. GO functional annotation revealed that the genes in the turquoise module were significantly enriched in the mitochondrion, mitochondrial protein-containing complex, cytoplasm, and mitochondrial inner membrane. KEGG pathway enrichment analysis indicated that these genes were predominantly enriched in the signaling pathways of oxidative phosphorylation, thermogenesis, and TCA cycle. By combining the gene co-expression network analysis of the turquoise module genes and the differentially expression genes (DEG) analysis, we identified 5 candidate key genes (ACO2, MRPS27, IMMT, MRPL12, and TUFM) involved in regulation of perirenal adipose tissue thermogenesis. This finding offer candidate genes that in the regulation of BAT thermogenesis and body temperature maintenance in goat kids.

Shigella sonnei: epidemiology, evolution, pathogenesis, resistance and host interactions

Shigella sonnei is a major cause of diarrhoea globally and is increasing in prevalence relative to other Shigella because of multiple demographic and environmental influences. This single-serotype species has traditionally received less attention in comparison to Shigella flexneri and Shigella dysenteriae, which were more common in low-income countries and more tractable in the laboratory. In recent years, we have learned that Shigella are highly complex and highly susceptible to environmental change, as exemplified by epidemiological trends and increasing relevance of S. sonnei. Ultimately, methods, tools and data generated from decades of detailed research into S. flexneri have been used to gain new insights into the epidemiology, microbiology and pathogenesis of S. sonnei. In parallel, widespread adoption of genomic surveillance has yielded insights into antimicrobial resistance, evolution and organism transmission. In this Review, we provide an overview of current knowledge of S. sonnei, highlighting recent insights into this globally disseminated antimicrobial-resistant pathogen and assessing how novel data may impact future vaccine development and implementation.

Repetitive prefrontal tDCS activates VTA dopaminergic neurons, resulting in attenuation of Alzheimer's Disease-like deficits in Tg2576 mice

BACKGROUND

Emerging evidence implicates early dysfunction of dopaminergic neurons in the Ventral Tegmental Area (VTA) as a key contributor to Alzheimer's Disease (AD) pathophysiology. Specifically, the VTA dopaminergic neurodegeneration and the consequent reduction of dopamine (DA) in mesocorticolimbic targets are associated with the onset of cognitive impairments and neuropsychiatric-like manifestations in AD animal models. Moreover, decreased midbrain volume and functional VTA disconnection are identified as predictors of accelerated progression from Mild Cognitive Impairment to AD-dementia in clinical populations. Given these findings, interventions capable of directly modulating VTA activity and augmenting DA release, despite the ongoing neurodegeneration, may hold therapeutic potential for mitigating DA-related deficits in AD. This study aims at evaluating the therapeutic potential of prefrontal transcranial Direct Current Stimulation (tDCS) in the Tg2576 mouse model of AD, exhibiting early VTA dopaminergic neurodegeneration.

METHODS

Repeated tDCS was applied to assess its ability to activate VTA DA neurons. We also evaluated tDCS effects on synaptic plasticity, cognitive and non-cognitive behaviours and AD-related pathology. Hippocampal DA release and Nucleus Accumbens (NAc) DA transporter (DAT) expression were measured. With immunohistochemistry we examined microglial density and morphological complexity at different disease stages. Additionally, intracellular amyloid-β (Aβ) levels and plaque burden were evaluated to determine the impact of tDCS on AD pathology.

RESULTS

Prefrontal tDCS enhanced the activity of VTA dopaminergic neurons, leading to increased hippocampal DA release and higher DAT levels in the NAc. The enhanced DA outflow is associated with restored CA3-CA1 synaptic plasticity and improvements in recognition memory and motivational behaviours. tDCS reduced microglial numbers and morphological complexity in Tg2576 mice at both pre-plaque stage (7-months) and at an advanced stage characterized by plaque accumulation (12-months). Notably, tDCS also decreased Aβ plaque burden, although no changes in intracellular Aβ levels were observed in younger Tg2576 mice.

CONCLUSIONS

These findings highlight the multifaceted therapeutic potential of prefrontal tDCS in targeting key AD pathophysiological hallmarks, including dopaminergic dysfunction, synaptic impairments, neuroinflammation and plaque deposition. As a non-invasive neuromodulatory approach, prefrontal tDCS emerges as a promising early intervention strategy to complement existing AD treatments, with the potential to improve patient outcomes and quality of life.

In silico-based analysis and in vitro experiments identify SIGMAR1 as a potential marker of putative lung cancer stem cells

BACKGROUND

Lung cancer is the leading cause of cancer-related mortality worldwide; however, despite the development and clinical application of various drugs, the prognosis remains poor. One reason for this is the high rate of recurrence and metastasis. The cancer stem cell (CSC) theory has been proposed to explain their root cause, and removal of CSCs is necessary to cure cancer completely; however, detailed profiles of lung CSCs have not been clarified. Here, we used single-cell RNA sequencing (scRNA-seq) data to identify novel markers for lung CSCs and validated their expression and function in vitro.

METHODS

A549-derived tumorspheres were used as a model for lung CSCs. To identify genes upregulated in CSC-like cells, we reanalyzed two publicly available scRNA-seq datasets from human lung cancer tissues. Additionally, trajectory analysis was performed to examine changes in candidate gene expression during CSC differentiation. The role of these candidate genes in CSC regulation was further investigated through functional assays.

RESULTS

Tumorspheres exhibited increased expression of well-established CSC markers. scRNA-seq analysis suggested that SIGMAR1 expression was significantly upregulated in CSC-like cells and decreased with differentiation. Furthermore, siRNA-mediated SIGMAR1 knockdown suppressed tumorsphere self-renewal capacity and reduced CSC marker expression.

CONCLUSIONS

We propose that SIGMAR1 serves as a potential functional marker of CSCs and plays a crucial role in regulating self-renewal capacity. Targeting SIGMAR1 may provide a novel therapeutic strategy for preventing metastasis and recurrence-major clinical challenges in lung cancer treatment. Future studies should investigate the underlying mechanisms by which SIGMAR1 modulates CSC properties.

Autoantibody Profiling in Ulcerative Colitis: Identification of Early Immune Signatures and Disease-Associated Antigens for Improved Diagnosis and Monitoring

Ulcerative colitis (UC) is a major form of inflammatory bowel disease (IBD) characterised by chronic immune-mediated inflammation. While serological biomarkers for IBD diagnosis and differentiation have been explored, autoantibody-based profiling remains underdeveloped. This study aimed to elucidate antibody signatures in manifested and pre-diagnostic UC patients compared to controls using a high-content protein microarray. Serum and plasma samples from manifested and pre-diagnostic UC cohorts were analysed using AIT's 16k protein microarray, presenting 6369 human proteins. The pre-diagnostic cohort, consisting of 33 UC cases and 33 controls, included longitudinal samples collected before diagnosis, while the severe UC cohort, comprising 49 severe UC patients and 23 controls, included individuals undergoing treatment. Immunoglobulin G (IgG) autoantibody reactivity was assessed to identify differentially reactive antigens (DIRAGs) linked to UC onset, disease progression, and activity. In manifested UC, 691 DIRAGs showed higher reactivity in cases. In the pre-diagnostic cohort, 966 DIRAGs were identified, with 803 antigens exhibiting increased reactivity in cases. Longitudinal analysis revealed 1371 DIRAGs, with 1185 showing increased reactivity closer to diagnosis when comparing samples collected 4-11 months before UC diagnosis to earlier time points 9-24 months prior, highlighting potential early biomarkers. A significant overlap of 286 antigens, corresponding to 41 percent of identified DIRAGs, was observed between severe and pre-diagnostic UC datasets, with an odds ratio of 3.8 and a p-value below 2.2 × 10-16, confirming reliability and biological relevance. Additionally, 21 antigens correlated with simple clinical colitis activity index (SCCAI) scores. Reactome pathway analysis identified 49 pathways associated with DIRAGs in pre-diagnostic UC, distinct from 24 pathways in manifested UC, with an overlap of five key pathways related to protein folding, immune regulation, and viral infection, reflecting differences in disease onset and manifestation. Autoantibody profiling reveals early immune signatures in UC, offering novel biomarkers for preclinical diagnosis and disease monitoring. The overlap between pre-diagnostic and manifested UC antigenic profiles reinforces their biological relevance, linking them to molecular pathology. These findings highlight antibody profiling as an additional omics layer, paving the way for new diagnostic and therapeutic strategies in UC management.

Functional interrogation of neuronal connections by chemoptogenetic presynaptic ablation

Most neurons are embedded in multiple circuits, with signaling to distinct postsynaptic partners playing functionally different roles. The function of specific connections can be interrogated using synaptically localized optogenetic effectors, however these tools are often experimentally difficult to validate or produce paradoxical outcomes. We have developed a system for photoablation of synaptic connections originating from genetically defined neurons, based on presynaptic localization of the fluorogen activating protein dL5** that acts as a photosensitizer when bound to a cell-permeable dye. Using the well mapped zebrafish escape circuit as a readout, we first show that cytoplasmically expressed dL5** enables efficient spatially targeted neuronal ablation using near infra-red light. We then demonstrate that spatially patterned illumination of presynaptically localized dL5** can effectively disconnect neurons from selected downstream partners, producing precise behavioral deficits. This technique should be applicable to almost any genetically tractable neuronal circuit, enabling precise manipulation of functional connectivity within the nervous system.

Single-cell analysis of the epigenome and 3D chromatin architecture in the human retina

Most genetic risk variants linked to ocular diseases are non-protein coding and presumably contribute to disease through dysregulation of gene expression, however, deeper understanding of their mechanisms of action has been impeded by an incomplete annotation of the transcriptional regulatory elements across different retinal cell types. To address this knowledge gap, we carried out single-cell multiomics assays to investigate gene expression, chromatin accessibility, DNA methylome and 3D chromatin architecture in human retina, macula, and retinal pigment epithelium (RPE)/choroid. We identified 420,824 unique candidate regulatory elements and characterized their chromatin states in 23 sub-classes of retinal cells. Comparative analysis of chromatin landscapes between human and mouse retina cells further revealed both evolutionarily conserved and divergent retinal gene-regulatory programs. Leveraging the rapid advancements in deep-learning techniques, we developed sequence-based predictors to interpret non-coding risk variants of retina diseases. Our study establishes retina-wide, single-cell transcriptome, epigenome, and 3D genome atlases, and provides a resource for studying the gene regulatory programs of the human retina and relevant diseases.

Genome-centric metagenomics reveals uncharacterised microbiomes in Angus cattle

Understanding the intricate nexus between cattle health and microbiome dynamics holds profound implications for enhancing animal productivity and welfare. However, our understanding of the role of these microbial communities is limited in beef cattle, especially in understudied body sites such as the oral and nasal microbiome. Here, using a genome-centric metagenomics approach, we recovered substantial metagenome-assembled genomes (MAGs) from the faecal, oral and nasal microbiome of Australian Angus cattle from different herds and life stages. The MAGs recovered from faecal samples were dominated by Bacillota and Bacteroidota, while the MAGs from saliva and nasal mucus samples were mainly associated with Pseudomonadota, Actinomycetota and Bacteroidota. Functional annotation of the MAGs revealed enriched pathways involved in the production of some amino acids, nucleic acids and short chain fatty acids (SCFA). The metabolic capacities of the MAGs were correlated with their taxonomy, notably at the phylum level. Overall, this study provides a comprehensive catalogue of MAGs to further our understanding of their role in the health and fitness of beef cattle.

3D bio-printed proteinaceous bioactive scaffold loaded with dual growth factor enhanced chondrogenesis and in situ cartilage regeneration

Articular cartilage has a limited self-healing capacity, leading to joint degeneration and osteoarthritis over time. Therefore, bioactive scaffolds are gaining attention as a promising approach to regenerating and repairing damaged articular cartilage through tissue engineering. In this study, we reported on a novel 3D bio-printed proteinaceous bioactive scaffolds combined with natural porcine cancellous bone dECM, tempo-oxidized cellulose nanofiber (TOCN), and alginate carriers for TGF-β1, FGF-18, and ADSCs to repair cartilage defects. The characterization results demonstrate that the 3D scaffolds are physically stable and facilitate a controlled dual release of TGF-β1 and FGF-18. Moreover, the key biological proteins within the bioactive scaffold actively interact with the biological systems to create a favorable microenvironment for cartilage regeneration. Importantly, the in vitro, in vivo, and in silico simulation showed that the scaffolds promote stem cell recruitment, migration, proliferation, and ECM deposition, and synergistic effects of TGF-β1/FGF-18 with the bioactive scaffolds significantly regulate stem cell chondrogenesis by activating the PI3K/AKT and TGFβ1/Smad4 signaling pathways. After implantation, the proteinaceous bioactive scaffold led to the regeneration of mechanically robust, full-thickness cartilage tissue that closely resembles native cartilage. Thus, these findings may provide a promising approach for regulating stem cell chondrogenesis and treating in situ cartilage regeneration.

Autism spectrum disorder risk genes have convergent effects on transcription and neuronal firing patterns in primary neurons

Autism spectrum disorder (ASD) is a highly heterogenous neurodevelopmental disorder with numerous genetic risk factors. Notably, a disproportionate number of risk genes encode transcription regulators including transcription factors and proteins that regulate chromatin. Here, we tested the function of nine such ASD-linked transcription regulators by depleting them in primary cultured neurons. We then defined the resulting gene expression disruptions using RNA-sequencing and tested effects on neuronal firing using multielectrode array recordings. We identified shared gene expression signatures across many ASD risk genes that converged on disruption of critical synaptic genes. Fitting with this, we detected drastic disruptions to neuronal firing throughout neuronal maturation. Together, these findings provide evidence that multiple ASD-linked transcriptional regulators disrupt transcription of synaptic genes and have convergent effects on neuronal firing that may contribute to enhanced ASD risk.

Electroencephalography Biomarkers of α5-GABA Positive Allosteric Modulators in Rodents

Background

Reduced cortical inhibition mediated by GABA (gamma-aminobutyric acid) is reported in depression, anxiety disorders, and aging. A novel positive allosteric modulator that specifically targets the α5-GABAA receptor subunit (α5-PAM), ligand GL-II-73 shows anxiolytic, antidepressant, and procognitive effects without the common side effects associated with nonspecific modulation by benzodiazepines such as diazepam, thus suggesting novel therapeutic potential. However, it is unknown whether α5-PAM has detectable signatures in clinically relevant brain electroencephalography (EEG).

Methods

We analyzed EEG in 10 freely moving rats at baseline and following injections of α5-PAM (GL-II-73) and diazepam.

Results

We showed that α5-PAM specifically decreased theta peak power, whereas diazepam shifted peak power from high to low theta while increasing beta and gamma power. EEG decomposition showed that these effects were periodic and corresponded to changes in theta oscillation event duration.

Conclusions

Thus, our study shows that α5-PAM has robust and distinct EEG biomarkers in rodents, indicating that EEG could enable noninvasive monitoring of α5-PAM treatment efficacy.

Smartphones as a platform for molecular analysis: concepts, methods, devices and future potential

Over the past 15 years, smartphones have had a transformative effect on everyday life. These devices also have the potential to transform molecular analysis over the next 15 years. The cameras of a smartphone, and its many additional onboard features, support optical detection and other aspects of engineering an analytical device. This article reviews the development of smartphones as platforms for portable chemical and biological analysis. It is equal parts conceptual overview, technical tutorial, critical summary of the state of the art, and outlook on how to advance smartphones as a tool for analysis. It further discusses the motivations for adopting smartphones as a portable platform, summarizes their enabling features and relevant optical detection methods, then highlights complementary technologies and materials such as 3D printing, microfluidics, optoelectronics, microelectronics, and nanoparticles. The broad scope of research and key advances from the past 7 years are reviewed as a prelude to a perspective on the challenges and opportunities for translating smartphone-based lab-on-a-chip devices from prototypes to authentic applications in health, food and water safety, environmental monitoring, and beyond. The convergence of smartphones with smart assays and smart apps powered by machine learning and artificial intelligence holds immense promise for realizing a future for molecular analysis that is powerful, versatile, democratized, and no longer just the stuff of science fiction.

Exploring the principles behind antibiotics with limited resistance

Antibiotics that target multiple cellular functions are anticipated to be less prone to bacterial resistance. Here we hypothesize that while dual targeting is crucial, it is not sufficient in preventing resistance. Only those antibiotics that simultaneously target membrane integrity and block another cellular pathway display reduced resistance development. To test the hypothesis, we focus on three antibiotic candidates, POL7306, Tridecaptin M152-P3 and SCH79797, all of which fulfill the above criteria. Here we show that resistance evolution against these antibiotics is limited in ESKAPE pathogens, including Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii and Pseudomonas aeruginosa, while dual-target topoisomerase antibiotics are prone to resistance. We discover several mechanisms restricting resistance. First, de novo mutations result in only a limited elevation in resistance, including those affecting the molecular targets and efflux pumps. Second, resistance is inaccessible through gene amplification. Third, functional metagenomics reveal that mobile resistance genes are rare in human gut, soil and clinical microbiomes. Finally, we detect rapid eradication of bacterial populations upon toxic exposure to membrane targeting antibiotics. We conclude that resistance mechanisms commonly found in natural bacterial pathogens provide only limited protection to these antibiotics. Our work provides guidelines for the future development of antibiotics.

Vulnerability of benthic trait diversity across the Mediterranean Sea following mass mortality events

Unraveling the functional future of marine ecosystems amid global change poses a pressing challenge. This is particularly critical in the Mediterranean Sea, which is highly impacted by global and local drivers. Utilizing extensive mass mortality events (MMEs) datasets spanning from 1986 to 2020 across the Mediterranean Sea, we investigated the trait vulnerability of benthic species that suffered from MMEs induced by nine distinct mortality drivers. By analyzing changes in ten ecological traits across 389 benthic species-constituting an extensive compendium of Mediterranean ecological traits to date-we identified 228 functional entities (FEs), defined as groups of species sharing the same trait values. Our findings indicate that of these 55 FEs were impacted by MMEs, accentuating a heightened vulnerability within specific trait categories. Notably, more than half of the mortality records showed severe impacts on calcifying and larger species with slower growth which mostly account for tree-like and massive forms. Altogether, we highlight that 29 FEs suffered extreme mortality, leading to a maximum increase of 19.1% of the global trait volume vulnerability over 35 years. We also reveal that 10.8% of the trait volume may have been temporarily lost over the last five years, emphasizing the risk of a rapid ecological transformation in the Mediterranean Sea.

Brain dynamics and spatiotemporal trajectories during threat processing

In the past decades, functional MRI research has investigated task processing in a largely static fashion based on evoked responses during blocked and event-related designs. Despite some progress in naturalistic designs, our understanding of threat processing remains largely limited to those obtained with standard paradigms with limited dynamics. In the present paper, we applied Switching Linear Dynamical Systems to uncover the dynamics of threat processing during a continuous threat-of-shock paradigm. First, we demonstrated that the SLDS model learned the regularities of the experimental paradigm, such that states and state transitions estimated from fMRI time series data from 85 regions of interest reflected threat proximity and threat approach vs. retreat. After establishing that the model captured key properties of threat-related processing, we characterized the dynamics of the states and their transitions. Importantly, we characterized both endogenous and exogenous contributions to dynamics. The results revealed how threat processing can be viewed in terms of dynamic multivariate patterns whose trajectories are a combination of intrinsic and extrinsic factors that jointly determine how the brain temporally evolves during dynamic threat. Furthermore, we developed a measure of region importance that quantifies the contributions of an individual brain region to system dynamics, which complements the system-level characterization that is obtained with the state-space SLDS formalism. Finally, we investigated the generalizability of the modelling approach. The successful application of the SLDS model trained on one paradigm to a separate experiment illustrates the potential of this approach to capture fMRI dynamics that generalize across related but distinct threat-processing tasks. We propose that viewing threat processing through the lens of dynamical systems offers important avenues to uncover properties of the dynamics of threat that are not unveiled with standard experimental designs and analyses.

SARS-CoV-2 ORF3a accessory protein is a water-permeable channel that induces lysosome swelling

ORF3a, the most abundantly expressed accessory protein of SARS-CoV-2, plays an essential role in virus egress by inactivating lysosomes through their deacidification. However, the mechanism underlying this process remains unclear. While seminal studies suggested ORF3a being a cation-selective channel (i.e., viroporin), recent works disproved this conclusion. To unravel the potential function of ORF3a, here we employed a multidisciplinary approach including patch-clamp electrophysiology, videoimaging, molecular dynamics (MD) simulations, and electron microscopy. Preliminary structural analyses and patch-clamp recordings in HEK293 cells rule out ORF3a functioning as either viroporin or proton (H+) channel. Conversely, videoimaging experiments demonstrate that ORF3a mediates the transmembrane transport of water. MD simulations identify the tetrameric assembly of ORF3a as the functional water transporter, with a putative selectivity filter for water permeation that includes two essential asparagines, N82 and N119. Consistent with this, N82L and N82W mutations abolish ORF3a-mediated water permeation. Finally, ORF3a expression in HEK293 cells leads to lysosomal volume increase, mitochondrial damage, and accumulation of intracellular membranes, all alterations reverted by the N82W mutation. We propose a novel function for ORF3a as a lysosomal water-permeable channel, essential for lysosome deacidification and inactivation, key steps to promote virus egress.

Are You Safe or Should I Go? How Perceived Trustworthiness and Probability of a Sexual Transmittable Infection Impact Activation of the Salience Network

Functional imaging studies indicate that both the assessment of a person as untrustworthy and the assumption that a person has a sexually transmitted infection are associated with activation in regions of the salience network. However, studies are missing that combine these aspects and investigate the perceived trustworthiness of individuals previously assessed with high or low probability of a sexually transmitted infection. During fMRI measurements, 25 participants viewed photographs of people preclassified as having high or low HIV probability and judged their trustworthiness. In a postrating, stimuli were rated for trustworthiness, attractiveness, and HIV probability. Persons preclassified as HIV- in contrast to those preclassified as HIV+ were rated more trustworthy and with lower HIV probability. Activation in medial orbitofrontal cortex was higher for those rated and preclassified as HIV- than HIV+. Based on the individual ratings, but not the preclassification, there was significantly higher activation in the insula, amygdala, anterior cingulate cortex, and nucleus accumbens in response to untrustworthy than to trustworthy faces. Activation of the salience network occurred when a person was judged as untrustworthy, but not according to a preclassification. Activation in the medial orbitofrontal cortex, a structure associated with reward, was enhanced when a person was perceived as trustworthy and also when a person was preclassified with low HIV probability. Our findings suggest that trustworthiness and HIV- perception have consistency across samples, while the perception of risk and associated activation of the salience network has restricted cross-sample consistency.

Unraveling latent cognitive, metacognitive, strategic, and affective processes underlying children's problem-solving using Bayesian cognitive modeling

Children exhibit remarkable variability in their mathematical problem-solving abilities, yet the cognitive, metacognitive and affective mechanisms underlying these individual differences remain poorly understood. We developed a novel Bayesian model of arithmetic problem-solving (BMAPS) to uncover the latent processes governing children's arithmetic strategy choice and efficiency. BMAPS inferred cognitive parameters related to strategy execution and metacognitive parameters related to strategy selection, revealing key mechanisms of adaptive problem solving. BMAPS parameters collectively explained individual differences in problem-solving performance, predicted longitudinal gains in arithmetic fluency and mathematical reasoning, and mediated the effects of anxiety and attitudes on performance. Clustering analyses using BMAPS parameters revealed distinct profiles of strategy use, metacognitive efficiency, and developmental change. By quantifying the fine-grained dynamics of strategy selection and execution and their relation to affective factors and academic outcomes, BMAPS provides new insights into the cognitive and metacognitive underpinnings of children's mathematical learning. This work advances powerful computational methods for uncovering latent mechanisms of complex cognition in children.

Branched endosomal disruptor (BEND) lipids mediate delivery of mRNA and CRISPR-Cas9 ribonucleoprotein complex for hepatic gene editing and T cell engineering

Lipid nanoparticles (LNPs) are the preeminent non-viral drug delivery vehicle for mRNA-based therapies. Immense effort has been placed on optimizing the ionizable lipid (IL) structure, which contains an amine core conjugated to lipid tails, as small molecular adjustments can result in substantial changes in the overall efficacy of the resulting LNPs. However, despite some advancements, a major barrier for LNP delivery is endosomal escape. Here, we develop a platform for synthesizing a class of branched ILs that improve endosomal escape. These compounds incorporate terminally branched groups that increase hepatic mRNA and ribonucleoprotein complex delivery and gene editing efficiency as well as T cell transfection compared to non-branched lipids. Through an array of complementary experiments, we determine that our lipid architecture induces greater endosomal penetration and disruption. This work provides a scheme to generate a class of ILs for both mRNA and protein delivery.

Markers of mitochondrial function and oxidative metabolism in female skeletal muscle do not display intrinsic circadian regulation

Mitochondria are key regulators of metabolism and ATP supply in skeletal muscle, while circadian rhythms influence many physiological processes. However, whether mitochondrial function is intrinsically regulated in a circadian manner in mouse skeletal muscle is inadequately understood. Accordingly, we measured post-absorptive transcript abundance of markers of mitochondrial biogenesis, dynamics, and metabolism (extensor digitorum longus [EDL], soleus, gastrocnemius), protein abundance of electron transport chain complexes (EDL and soleus), enzymatic activity of SDH (tibialis anterior and plantaris), and maximum uncoupled respiration (tibialis anterior) in different skeletal muscles from female C57BL/6NJ mice at four zeitgeber times (ZT), ZT 1, 7, 13, and 19. Our findings demonstrate that markers of mitochondrial function and oxidative metabolism do not display intrinsic time-of-day regulation at the gene, protein, enzymatic, or functional level. The core-clock genes Bmal1 and Dbp exhibited intrinsic circadian rhythmicity in skeletal muscle (i.e., EDL, soleus, gastrocnemius) and circadian amplitude varied by muscle type. These findings demonstrate that female mouse skeletal muscle does not display circadian regulation of markers of mitochondrial function or oxidative metabolism over 24 hours.

Spontaneous base flipping helps drive Nsp15's preferences in double stranded RNA substrates

Coronaviruses evade detection by the host immune system with the help of the endoribonuclease Nsp15, which regulates levels of viral double stranded RNA by cleaving 3' of uridine (U). While prior structural data shows that to cleave double stranded RNA, Nsp15's target U must be flipped out of the helix, it is not yet understood whether Nsp15 initiates flipping or captures spontaneously flipped bases. We address this gap by designing fluorinated double stranded RNA substrates that allow us to directly relate a U's sequence context to both its tendency to spontaneously flip and its susceptibility to cleavage by Nsp15. Through a combination of nuclease assays, 19F NMR spectroscopy, mass spectrometry, and single particle cryo-EM, we determine that Nsp15 acts most efficiently on unpaired Us, particularly those that are already flipped. Across sequence contexts, we find Nsp15's cleavage efficiency to be directly related to that U's tendency to spontaneously flip. Overall, our findings unify previous characterizations of Nsp15's cleavage preferences, and suggest that activity of Nsp15 during infection is partially driven by bulged or otherwise relatively accessible Us that appear at strategic positions in the viral RNA.

Effects of Social Structure on Effective Population Size Change Estimates

Most methods currently used to infer the "demographic history of species" interpret this expression as a history of population size changes. The detection, quantification, and dating of demographic changes often rely on the assumption that population structure can be neglected. However, most vertebrates are typically organized in populations subdivided into social groups that are usually ignored in the interpretation of genetic data. This could be problematic since an increasing number of studies have shown that population structure can generate spurious signatures of population size change. Here, we simulate microsatellite data from a species subdivided into social groups where reproduction occurs according to different mating systems (monogamy, polygynandry, and polygyny). We estimate the effective population size (N e) and quantify the effect of social structure on estimates of changes in N e. We analyze the simulated data with two widely used methods for demographic inference. The first approach, BOTTLENECK, tests whether the samples are at mutation-drift equilibrium and thus whether a single N e can be estimated. The second approach, msvar, aims at quantifying and dating changes in N e. We find that social structure may lead to signals of departure from mutation-drift equilibrium including signals of expansion and bottlenecks. We also find that expansion signals may be observed under simple stationary Wright-Fisher models with low diversity. Since small populations tend to characterize many endangered species, we stress that methods trying to infer N e should be interpreted with care and validated with simulated data incorporating information about structure. Spurious expansion signals due to social structure can mask critical population size changes. These can obscure true bottleneck events and be particularly problematic in endangered species.

Engineered Cardiac Tissues as a Platform for CRISPR-Based Mitogen Discovery

Improved understanding of cardiomyocyte (CM) cell cycle regulation may allow researchers to stimulate pro-regenerative effects in injured hearts or promote maturation of human stem cell-derived CMs. Gene therapies, in particular, hold promise to induce controlled proliferation of endogenous or transplanted CMs via transient activation of mitogenic processes. Methods to identify and characterize candidate cardiac mitogens in vitro can accelerate translational efforts and contribute to the understanding of the complex regulatory landscape of CM proliferation and postnatal maturation. In this study, A CRISPR knockout-based screening strategy using in vitro neonatal rat ventricular myocyte (NRVM) monolayers is established, followed by candidate mitogen validation in mature 3-D engineered cardiac tissues (ECTs). This screen identified knockout of the purine metabolism enzyme adenosine deaminase (ADA-KO) as an effective pro-mitogenic stimulus. RNA-sequencing of ECTs further reveals increased pentose phosphate pathway (PPP) activity as the primary driver of ADA-KO-induced CM cycling. Inhibition of the pathway's rate limiting enzyme, glucose-6-phosphate dehydrogenase (G6PD), prevented ADA-KO induced CM cycling, while increasing PPP activity via G6PD overexpression increased CM cycling. Together, this study demonstrates the development and application of a genetic/tissue engineering platform for in vitro discovery and validation of new candidate mitogens affecting regenerative or maturation states of cardiomyocytes.

Adapting cytoskeleton-mitochondria patterning with myocyte differentiation by promyogenic PRR33

Coordinated cytoskeleton-mitochondria organization during myogenesis is crucial for muscle development and function. Our understanding of the underlying regulatory mechanisms remains inadequate. Here, we identified a novel muscle-enriched protein, PRR33, which is upregulated during myogenesis and acts as a promyogenic factor. Depletion of Prr33 in C2C12 represses myoblast differentiation. Genetic deletion of Prr33 in mice reduces myofiber size and decreases muscle strength. The Prr33 mutant mice also exhibit impaired myogenesis and defects in muscle regeneration in response to injury. Interactome and transcriptome analyses reveal that PRR33 regulates cytoskeleton and mitochondrial function. Remarkably, PRR33 interacts with DESMIN, a key regulator of cytoskeleton-mitochondria organization in muscle cells. Abrogation of PRR33 in myocytes substantially abolishes the interaction of DESMIN filaments with mitochondria, leading to abnormal intracellular accumulation of DESMIN and mitochondrial disorganization/dysfunction in myofibers. Together, our findings demonstrate that PRR33 and DESMIN constitute an important regulatory module coordinating mitochondrial organization with muscle differentiation.

Empagliflozin in Acute Myocardial Infarction Reduces No-Reflow and Preserves Cardiac Function by Preventing Endothelial Damage

Empagliflozin treatment before acute myocardial infarction mainly targets the endothelial cell transcriptome. Empagliflozin treatment before and after myocardial infarction decreased no reflow and microvascular injury, leading to reduced infiltration of inflammatory cells, reduced infarct size, and improved cardiac function in mice. In diabetic patients receiving empagliflozin after myocardial infarction, perfused boundary region, flow-mediated dilation, and global longitudinal strain were improved.

Nanomaterials and methods for cancer therapy: 2D materials, biomolecules, and molecular dynamics simulations

This review explores the potential of biomolecule-based nanomaterials, i.e., protein, peptide, nucleic acid, and polysaccharide-based nanomaterials, in cancer nanomedicine. It highlights the wide range of design possibilities for creating multifunctional nanomedicines using these biomolecule-based nanomaterials. This review also analyzes the primary obstacles in cancer nanomedicine that can be resolved through the usage of nanomaterials based on biomolecules. It also examines the unique in vivo characteristics, programmability, and biological functionalities of these biomolecule-based nanomaterials. This summary outlines the most recent advancements in the development of two-dimensional semiconductor-based nanomaterials for cancer theranostic purposes. It focuses on the latest developments in molecular simulations and modelling to provide a clear understanding of important uses, techniques, and concepts of nanomaterials in drug delivery and synthesis processes. Finally, the review addresses the challenges in molecular simulations, and generating, analyzing, and developing biomolecule-based and two-dimensional semiconductor-based nanomaterials, and highlights the barriers that must be overcome to facilitate their application in clinical settings.

Mitochondria and Cancer

Mitochondria are semiautonomous organelles with diverse metabolic and cellular functions including anabolism and energy production through oxidative phosphorylation. Following the pioneering observations of Otto Warburg nearly a century ago, an immense body of work has examined the role of mitochondria in cancer pathogenesis and progression. Here, we summarize the current state of the field, which has coalesced around the position that functional mitochondria are required for cancer cell proliferation. In this review, we discuss how mitochondria influence tumorigenesis by impacting anabolism, intracellular signaling, and the tumor microenvironment. Consistent with their critical functions in tumor formation, mitochondria have become an attractive target for cancer therapy. We provide a comprehensive update on the numerous therapeutic modalities targeting the mitochondria of cancer cells making their way through clinical trials.

Meta-analysis of single-cell RNA sequencing co-expression in human neural organoids reveals their high variability in recapitulating primary tissue

Human neural organoids offer an exciting opportunity for studying inaccessible human-specific brain development; however, it remains unclear how precisely organoids recapitulate fetal/primary tissue biology. We characterize field-wide replicability and biological fidelity through a meta-analysis of single-cell RNA-sequencing data for first and second trimester human primary brain (2.95 million cells, 51 data sets) and neural organoids (1.59 million cells, 173 data sets). We quantify the degree primary tissue cell type marker expression and co-expression are recapitulated in organoids across 10 different protocol types. By quantifying gene-level preservation of primary tissue co-expression, we show neural organoids lie on a spectrum ranging from virtually no signal to co-expression indistinguishable from primary tissue, demonstrating a high degree of variability in biological fidelity among organoid systems. Our preserved co-expression framework provides cell type-specific measures of fidelity applicable to diverse neural organoids, offering a powerful tool for uncovering unifying axes of variation across heterogeneous neural organoid experiments.

Clinical use of tigecycline may contribute to the widespread dissemination of carbapenem-resistant hypervirulent Klebsiella pneumoniae strains

The emergence of carbapenem-resistant hypervirulent Klebsiella pneumoniae (CR-hvKP) poses grave threats to human health. These strains increased dramatically in clinical settings in China in the past few years but not in other parts of the world. Four isogenic K. pneumoniae strains, including classical K. pneumoniae, carbapenem-resistant K. pneumoniae (CRKP), hypervirulent K. pneumoniae (hvKP) and CR-hvKP, were created and subjected to phenotypic characterization, competition assays, mouse sepsis model and rat colonization tests to investigate the mechanisms underlying the widespread nature of CR-hvKP in China. Acquisition of virulence plasmid led to reduced fitness and abolishment of colonization in the gastrointestinal tract, which may explain why hvKP is not clinically prevalent after its emergence for a long time. However, tigecycline treatment facilitated the colonization of hvKP and CR-hvKP and reduced the population of Lactobacillus spp. in animal gut microbiome. Feeding with Lactobacillus spp. could significantly reduce the colonization of hvKP and CR-hvKP in the animal gastrointestinal tract. Our data implied that the clinical use of tigecycline to treat carbapenem-resistant K. pneumoniae infections facilitated the high spread of CR-hvKP in clinical settings in China and demonstrated that Lactobacillus spp. was a potential candidate for anticolonization strategy against CR-hvKP.

The anticancer effect of metformin targets VDAC1 via ER-mitochondria interactions-mediated autophagy in HCC

Metformin (MetF) is used worldwide as a first-line therapy for type 2 diabetes. Recently, interest in the pleiotropic effects of MetF, such as its anticancer and antiaging properties, has increased. However, the molecular target of MetF and the detailed mechanism underlying its ability to inhibit cell growth through autophagy induction remain incompletely understood. In this study, using an innovative label-free drug affinity responsive target stability (DARTS)-LC-MS/MS method, we discovered that mitochondrial voltage-dependent anion channel 1 (VDAC1) is a novel binding protein involved in the induction of autophagy-related cell death by high-dose MetF in hepatocellular carcinoma (HCC). Computational alanine scanning mutagenesis revealed that MetF and VDAC1 (D9, E203) interact electrostatically. MetF disrupts the IP3R-GRP75-VDAC1 complex, which plays a key role in stabilizing mitochondria-associated ER membranes (MAMs), by binding to VDAC1. This disruption leads to increased cytosolic calcium levels, thereby contributing to autophagy induction. MetF also decreased the AMP/ATP ratio and activated the AMPK pathway. Cells with genetic knockdown of VDAC1 mimicked the activity of MetF. In conclusion, this study provides new insights into the involvement of MetF in ionic interactions with VDAC1, contributing to its anticancer effects in HCC. These findings help elucidate the diverse biological and pharmacological effects of MetF, particularly its influence on autophagy, as well as the potential of MetF as a therapeutic agent for diseases characterized by VDAC1 overexpression.

Rhythm-Ready: Harnessing Smart Devices to Detect and Manage Arrhythmias

PURPOSE OF REVIEW

To survey recent progress in the application of implantable and wearable sensors to detection and management of cardiac arrhythmias.

RECENT FINDINGS

Sensor-enabled strategies are critical for the detection, prediction and management of arrhythmias. In the last several years, great innovation has occurred in the types of devices (implanted and wearable) that are available and the data they collect. The integration of artificial intelligence solutions into sensor-enabled strategies has set the stage for a new generation of smart devices that augment the human clinician. Smart devices enhanced by new sensor technologies and Artificial Intelligence (AI) algorithms promise to reshape the care of cardiac arrhythmias.

Mutagenic impact and evolutionary influence of radiotherapy in hematologic malignancies

Ionizing radiotherapy (RT) is a widely used palliative and curative treatment strategy for malignancies. In solid tumors, RT-induced double strand breaks lead to the accumulation of indels, and their repair by non-homologous end-joining has been linked to the ID8 mutational signature in resistant cells. However, the extent of RT-induced DNA damage in hematologic malignancies and its impact on their evolution and interplay with commonly used chemotherapies has not yet been explored. Here, we interrogated 580 whole genome sequencing (WGS) from patients with large B-cell lymphoma, multiple myeloma, and myeloid neoplasms and identified ID8 only in relapsed disease. Yet, it was detected after exposure to both RT and mutagenic chemotherapy (i.e., platinum). Using WGS of single-cell colonies derived from treated lymphoma cells, we revealed a dose-response relationship between RT and platinum and ID8. Finally, using ID8 as a genomic barcode we demonstrate that a single RT-resistant cell may seed systemic relapse.

The Maximal Expected Benefit of SARS-CoV-2 Interventions Among University Students: A Simulation Study Using Latent Class Analysis

Non-pharmaceutical public health measures (PHMs) were central to pre-vaccination efforts to reduce Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) exposure risk; heterogeneity in adherence placed bounds on their potential effectiveness, and correlation in their adoption makes assessing the impact attributable to an individual PHM difficult. During the Fall 2020 semester, we used a longitudinal cohort design in a university student population to conduct a behavioral survey of intention to adhere to PHMs, paired with an IgG serosurvey to quantify SARS-CoV-2 exposure at the end of the semester. Using Latent Class Analysis on behavioral survey responses, we identified three distinct groups among the 673 students with IgG samples: 256 (38.04%) students were in the most adherent group, intending to follow all guidelines, 306 (46.21%) in the moderately-adherent group, and 111 (15.75%) in the least-adherent group, rarely intending to follow any measure, with adherence negatively correlated with seropositivity of 25.4%, 32.2% and 37.7%, respectively. Moving all individuals in an SIR model into the most adherent group resulted in a 76-93% reduction in seroprevalence, dependent on assumed assortativity. The potential impact of increasing PHM adherence was limited by the substantial exposure risk in the large proportion of students already following all PHMs.

Measuring Growth, Resistance, and Recovery after Artemisinin Treatment of Plasmodium falciparum in a single semi-high-throughput Assay

Background

Artemisinin partial resistance (ART-R) has spread throughout Southeast Asia and mutations in pfKelch13, the molecular marker of resistance, are widely reported in East Africa. Effective in vitro assays and robust phenotypes are crucial for monitoring populations for the emergence and spread of resistance. The recently developed extended Recovery Ring-stage Survival Assay used a qPCR-based readout to reduce the labor intensiveness for in vitro phenotyping of ART-R and improved correlation with the clinical phenotype of ART-R. Here, we extend and refine this assay to include measurements of parasite growth and recovery after drug exposure. Clinical isolates and progeny from two genetic crosses were used to optimize and validate the reliability of a straight-from-blood, SYBR Green-based qPCR protocol in a 96-well plate format to accurately measure phenotypes for Growth, Resistance, and Recovery.

Results

The assay determined growth between 6 h and 96 h, resistance at 120 h, and recovery from 120 h and 192 h. Growth can be accurately captured by qPCR and is shown by reproduction of previous growth phenotypes from HB3 × Dd2. Resistance measured at 120 h continually shows the most consistent phenotype for ring stage susceptibility. Recovery identifies an additional response to drug than parasites that are determined sensitive by Fold Change at 120 h. Comparison of progeny phenotypes for Growth vs Resistance showed a minor but significant correlation, whereas Growth vs Recovery and Resistance vs Recovery showed no significant correlation. Additionally, dried blood spot (DBS) samples matched Fold Change measured from liquid samples demonstrating Resistance can be easily quantified using either storage method.

Conclusions

The qPCR-based methodology provides the throughput needed to quickly measure large numbers of parasites for multiple relevant phenotypes. Growth can reveal fitness defects and illuminate relationships between proliferation rates and drug response. Recovery serves as a complementary phenotype to resistance that quantifies the ability of sensitive parasites to tolerate drug exposure. All three phenotypes offer a comprehensive assessment of parasite-drug interaction each with independent genetic determinants of main effect and overlapping secondary effects that should be further. By adapting our method to include DBS, readouts can be easily extended to ex vivo surveillance applications.

Evolutionary Dynamics of G-Quadruplexes in Human and Other Great Ape Telomere-to-Telomere Genomes

G-quadruplexes (G4s) are non-canonical DNA structures that can form at approximately 1% of the human genome. G4s contribute to point mutations and structural variation and thus facilitate genomic instability. They play important roles in regulating replication, transcription, and telomere maintenance, and some of them evolve under purifying selection. Nevertheless, the evolutionary dynamics of G4s has remained underexplored. Here we conducted a comprehensive analysis of predicted G4s (pG4s) in the recently released, telomere-to-telomere (T2T) genomes of human and other great apes-bonobo, chimpanzee, gorilla, Bornean orangutan, and Sumatran orangutan. We annotated tens of thousands of new pG4s in T2T compared to previous ape genome assemblies, including 41,236 in the human genome. Analyzing species alignments, we found approximately one-third of pG4s shared by all apes studied and identified thousands of species- and genus-specific pG4s. pG4s accumulated and diverged at rates consistent with divergence times between the studied species. We observed a significant enrichment and hypomethylation of pG4 shared across species at regulatory regions, including promoters, 5' and 3'UTRs, and origins of replication, strongly suggesting their formation and functional role in these regions. pG4s shared among great apes displayed lower methylation levels compared to species-specific pG4s, suggesting evolutionary conservation of functional roles of the former. Many species-specific pG4s were located in the repetitive and satellite regions deciphered in the T2T genomes. Our findings illuminate the evolutionary dynamics of G4s, their role in gene regulation, and their potential contribution to species-specific adaptations in great apes, emphasizing the utility of high-resolution T2T genomes in uncovering previously elusive genomic features.

Disease-specific alterations in central fear network engagement during acquisition and extinction of conditioned interoceptive fear in inflammatory bowel disease

Interoceptive fear, which is shaped by associative threat learning and memory processes, plays a central role in abnormal interoception and psychiatric comorbidity in conditions of the gut-brain axis. Although animal and human studies support that acute inflammation induces brain alterations in the central fear network, mechanistic knowledge in patients with chronic inflammatory conditions remains sparse. We implemented a translational fear conditioning paradigm to elucidate central fear network reactivity in patients with quiescent inflammatory bowel disease (IBD), compared to patients with irritable bowel syndrome (IBS) and healthy controls (HC). Using functional magnetic resonance imaging, conditioned differential neural responses within regions of the fear network were analyzed during acquisition and extinction learning. In contrast to HC and IBS, IBD patients demonstrated distinctly altered engagement of key regions of the central fear network, including amygdala and hippocampus, during differential interoceptive fear learning, with more pronounced responses to conditioned safety relative to pain-predictive cues. Aberrant hippocampal responses correlated with chronic stress exclusively in IBD. During extinction, differential engagement was observed in IBD compared to IBS patients within amygdala, ventral anterior insula, and thalamus. No group differences were found in changes of cue valence as a behavioral measure of fear acquisition and extinction. Together, the disease-specific alterations in neural responses during interoceptive fear conditioning in quiescent IBD suggest persisting effects of recurring intestinal inflammation on central fear network reactivity. Given the crucial role of interoceptive fear in abnormal interoception, these findings point towards inflammation-related brain alterations as one trajectory to bodily symptom chronicity and psychiatric comorbidity. Patients with inflammatory conditions of the gut-brain axis may benefit from tailored treatment approaches targeting maladaptive interoceptive fear.

Aging at scale: Younger dogs and larger breeds from the Dog Aging Project show accelerated epigenetic aging

Dogs exhibit striking within-species variability in lifespan, with smaller breeds often living more than twice as long as larger breeds. This longevity discrepancy also extends to health and aging-larger dogs show higher rates of age-related diseases. Despite this well-established phenomenon, we still know little about the biomarkers and molecular mechanisms that might underlie breed differences in aging and survival. To address this gap, we generated an epigenetic clock using DNA methylation from over 3 million CpG sites in a deeply phenotyped cohort of 864 companion dogs from the Dog Aging Project, including some dogs sampled annually for 2-3 years. We found that the largest breed size tends to have epigenomes that are, on average, 0.37 years older per chronological year compared to the smallest breed size. We also found that higher residual epigenetic age was significantly associated with increased mortality risk, with dogs experiencing a 34% higher risk of death for each year increase in residual epigenetic age. These findings not only broaden our understanding of how aging manifests within a diverse species but also highlight the significant role that demographic factors play in modulating the biological mechanisms underlying aging. Additionally, they highlight the utility of DNA methylation as both a biomarker for healthspan-extending interventions, a mortality predictor, and a mechanism for understanding inter-individual variation in aging in dogs.

Global A-to-I RNA editing during myogenic differentiation of goat MuSCs

Background

RNA editing, especially A-to-I editing sites, is a common RNA modification critical for stem cell differentiation, muscle development, and disease occurrence. Unveiling comprehensive RNA A-to-I editing events associated with myogenesis of the skeletal muscle satellite cells (MuSCs) is essential for extending our knowledge of the mechanism underpinning muscle development.

Results

A total of 9,632 RNA editing sites (RESs) were screened in the myoblasts (GM), myocytes (DM1), and myotubes (DM5) samples. Among these sites, 4,559 A-to-I edits were classified and further analyzed. There were 3,266 A-to-I sites in the protein-coding region, out of which 113 missense sites recoded protein. Notably, five A-to-I sites in the 3' UTR of four genes (TRAF6, NALF1, SLC38A1, ENSCHIG00000019092) altered their targeted miRNAs. Furthermore, a total of 370 A-to-I sites with different editing levels were detected, including FBN1, MYH10, GSK3B, CSNK1D, and PRKACB genes. These genes were predominantly enriched in the cytoskeleton in muscle cells, the hippo signaling pathway, and the tight junction. Furthermore, we identified 14 hub genes (TUFM, GSK3B, JAK2, RPSA, YARS1, CDH2, PRKACB, RUNX1, NOTCH2, CDC23, VCP, FBN1, RARS1, MEF2C) that potentially related to muscle development. Additionally, 123 stage-specific A-to-I editing sites were identified, with 43 sites in GM, 25 in DM1, and 55 in DM5 samples. These stage-specific edited genes significantly enriched essential biological pathways, including the cell cycle, oocyte meiosis, motor proteins, and hedgehog signaling pathway.

Conclusion

We systematically identified the RNA editing events in proliferating and differentiating goat MuSCs, which was crucial for expanding our understanding of the regulatory mechanisms of muscle development.

3D nanoplasmonic structure for ultrahigh enhanced SERS with less variability, polarization independence, and multimodal sensing applied to picric acid detection

Surface-enhanced Raman scattering (SERS) is recognized as a powerful analytical method. However, its efficacy is hindered by considerable signal variability stemming from factors like surface irregularities, temporal instability of the substrate, interference with substrate signal, polarization sensitivity and uneven molecular distribution. To address these challenges, a new strategy is employed to enhance the reproducibility of SERS signals. Initially, a periodic 3D metallic structure is utilized to achieve polarization-independent ultrahigh enhancement. Additionally, signal averaging over multiple points and normalization are implemented. The integration of these techniques enables multimodal sensing (SERS, SEF, SPR) using a plasmonic chip, demonstrating ultrahigh enhancement through the interaction of extended and localized plasmons alongside nanoantenna-type resonances. The chip comprises a periodic silver 2D grating adorned with Au nanocubes, behaving as a 3D metasurface to amplify plasmonic local fields, thus facilitating SERS. Its uniformity and polarization independence together with signal averaging and normalization mitigate signal variability. Fabricated via electron beam lithography, the chip's performance is evaluated for surface-enhanced fluorescence (SEF) and SERS using Rhodamine 6G as the target molecule. Results exhibit two orders of magnitude enhancement factor for SEF and 2.5 × 107 for SERS. For chemical sensing, the chip is tested for picric acid detection across a concentration range from nanomolar to millimolar, demonstrating a detection limit of approximately 3 nM.

Light-triggered protease-mediated release of actin-bound cargo from synthetic cells

Synthetic cells offer a versatile platform for addressing biomedical and environmental challenges, due to their modular design and capability to mimic cellular processes such as biosensing, intercellular communication, and metabolism. Constructing synthetic cells capable of stimuli-responsive secretion is vital for applications in targeted drug delivery and biosensor development. Previous attempts at engineering secretion for synthetic cells have been confined to non-specific cargo release via membrane pores, limiting the spatiotemporal precision and specificity necessary for selective secretion. Here, we designed and constructed a protein-based platform termed TEV Protease-mediated Releasable Actin-binding protein (TRAP) for selective, rapid, and triggerable secretion in synthetic cells. TRAP is designed to bind tightly to reconstituted actin networks and is proteolytically released from bound actin, followed by secretion via cell-penetrating peptide membrane translocation. We demonstrated TRAP's efficacy in facilitating light-activated secretion of both fluorescent and luminescent proteins. By equipping synthetic cells with a controlled secretion mechanism, TRAP paves the way for the development of stimuli-responsive biomaterials, versatile synthetic cell-based biosensing systems, and therapeutic applications through the integration of synthetic cells with living cells for targeted delivery of protein therapeutics.

Sex-specific differences in brain activity dynamics of youth with a family history of substance use disorder

An individual's risk of substance use disorder (SUD) is shaped by a complex interplay of potent biosocial factors. Current neurodevelopmental models posit vulnerability to SUD in youth is due to an overreactive reward system and reduced inhibitory control. Having a family history of SUD is a particularly strong risk factor, yet few studies have explored its impact on brain function and structure prior to substance exposure. Herein, we utilized a network control theory approach to quantify sex-specific differences in brain activity dynamics in youth with and without a family history of SUD, drawn from a large cohort of substance-naïve youth from the Adolescent Brain Cognitive Development Study. We summarize brain dynamics by calculating transition energy, which probes the ease with which a whole brain, region or network drives the brain towards a specific spatial pattern of activation (i.e., brain state). Our findings reveal that a family history of SUD is associated with alterations in the brain's dynamics wherein: i) independent of sex, certain regions' transition energies are higher in those with a family history of SUD and ii) there exist sex-specific differences in SUD family history groups at multiple levels of transition energy (global, network, and regional). Family history-by-sex effects reveal that energetic demand is increased in females with a family history of SUD and decreased in males with a family history of SUD, compared to their same-sex counterparts with no SUD family history. Specifically, we localize these effects to higher energetic demands of the default mode network in females with a family history of SUD and lower energetic demands of attention networks in males with a family history of SUD. These results suggest a family history of SUD may increase reward saliency in males and decrease efficiency of top-down inhibitory control in females. This work could be used to inform personalized intervention strategies that may target differing cognitive mechanisms that predispose individuals to the development of SUD.

Active forgetting and neuropsychiatric diseases

Recent and pioneering animal research has revealed the brain utilizes a variety of molecular, cellular, and network-level mechanisms used to forget memories in a process referred to as "active forgetting". Active forgetting increases behavioral flexibility and removes irrelevant information. Individuals with impaired active forgetting mechanisms can experience intrusive memories, distressing thoughts, and unwanted impulses that occur in neuropsychiatric diseases. The current evidence indicates that active forgetting mechanisms degrade, or mask, molecular and cellular memory traces created in synaptic connections of "engram cells" that are specific for a given memory. Combined molecular genetic/behavioral studies using Drosophila have uncovered a complex system of cellular active-forgetting pathways within engram cells that is regulated by dopamine neurons and involves dopamine-nitric oxide co-transmission and reception, endoplasmic reticulum Ca2+ signaling, and cytoskeletal remodeling machinery regulated by small GTPases. Some of these molecular cellular mechanisms have already been found to be conserved in mammals. Interestingly, some pathways independently regulate forgetting of distinct memory types and temporal phases, suggesting a multi-layering organization of forgetting systems. In mammals, active forgetting also involves modulation of memory trace synaptic strength by altering AMPA receptor trafficking. Furthermore, active-forgetting employs network level mechanisms wherein non-engram neurons, newly born-engram neurons, and glial cells regulate engram synapses in a state and experience dependent manner. Remarkably, there is evidence for potential coordination between the network and cellular level forgetting mechanisms. Finally, subjects with several neuropsychiatric diseases have been tested and shown to be impaired in active forgetting. Insights obtained from research on active forgetting in animal models will continue to enrich our understanding of the brain dysfunctions that occur in neuropsychiatric diseases.

Design and construction of a low-cost compressive loading and perfusion flow bioreactor

This article reports the design and construction of an open-source compressive loading and perfusion flow bioreactor for under $4000, as well as validation of the device and an example use-application. The bioreactor is capable of recording applied force and displacement as well as regulating media flow rate. This bioreactor was built to be user friendly, widely adaptable for modular changes, and made of readily available materials.

A zebrafish tufm mutant model for the COXPD4 syndrome of aberrant mitochondrial function

Mitochondrial dysfunction is a critical factor leading to a wide range of clinically heterogeneous and often severe disorders due to its central role in generating cellular energy. Mutations in the TUFM gene are known to cause combined oxidative phosphorylation deficiency 4 (COXPD4), a rare mitochondrial disorder characterized by a comprehensive quantitative deficiency in mitochondrial respiratory chain (MRC) complexes. The development of a reliable animal model for COXPD4 is crucial for elucidating the roles and mechanisms of TUFM in disease pathogenesis and benefiting its medical management. In this study, we construct a zebrafish tufm-/- mutant that closely resembles the COXPD4 syndrome, exhibiting compromised mitochondrial protein translation, dysfunctional mitochondria with oxidative phosphorylation defects, and significant metabolic suppression of the tricarboxylic acid cycle. Leveraging this COXPD4 zebrafish model, we comprehensively validate the clinical relevance of TUFM mutations and identify probucol as a promising therapeutic approach for managing COXPD4. Our data offer valuable insights for understanding mitochondrial diseases and developing effective treatments.

An approach for developing a blood-based screening panel for lung cancer based on clonal hematopoietic mutations

Early detection can significantly reduce mortality due to lung cancer. Presented here is an approach for developing a blood-based screening panel based on clonal hematopoietic mutations. Animal model studies suggest that clonal hematopoietic mutations in tumor infiltrating immune cells can modulate cancer progression, representing potential predictive biomarkers. The goal of this study was to determine if the clonal expansion of these mutations in blood samples could predict the occurrence of lung cancer. A set of 98 potentially pathogenic clonal hematopoietic mutations in tumor infiltrating immune cells were identified using sequencing data from lung cancer samples. These mutations were used as predictors to develop a logistic regression machine learning model. The model was tested on sequencing data from a separate set of 578 lung cancer and 545 non-cancer samples from 18 different cohorts. The logistic regression model correctly classified lung cancer and non-cancer blood samples with 94.12% sensitivity (95% Confidence Interval: 92.20-96.04%) and 85.96% specificity (95% Confidence Interval: 82.98-88.95%). Our results suggest that it may be possible to develop an accurate blood-based lung cancer screening panel using this approach. Unlike most other "liquid biopsies" currently under development, the approach presented here is based on standard sequencing protocols and uses a relatively small number of rationally selected mutations as predictors.

State-of-the-art sleep arousal detection evaluated on a comprehensive clinical dataset

Aiming to apply automatic arousal detection to support sleep laboratories, we evaluated an optimized, state-of-the-art approach using data from daily work in our university hospital sleep laboratory. Therefore, a machine learning algorithm was trained and evaluated on 3423 polysomnograms of people with various sleep disorders. The model architecture is a U-net that accepts 50 Hz signals as input. We compared this algorithm with models trained on publicly available datasets, and evaluated these models using our clinical dataset, particularly with regard to the effects of different sleep disorders. In an effort to evaluate clinical relevance, we designed a metric based on the error of the predicted arousal index. Our models achieve an area under the precision recall curve (AUPRC) of up to 0.83 and F1 scores of up to 0.81. The model trained on our data showed no age or gender bias and no significant negative effect regarding sleep disorders on model performance compared to healthy sleep. In contrast, models trained on public datasets showed a small to moderate negative effect (calculated using Cohen's d) of sleep disorders on model performance. Therefore, we conclude that state-of-the-art arousal detection on our clinical data is possible with our model architecture. Thus, our results support the general recommendation to use a clinical dataset for training if the model is to be applied to clinical data.

Oxidized mRNA Lipid Nanoparticles for In Situ Chimeric Antigen Receptor Monocyte Engineering

Chimeric antigen receptor (CAR) monocyte and macrophage therapies are promising solid tumor immunotherapies that can overcome the challenges facing conventional CAR T cell therapy. mRNA lipid nanoparticles (mRNA-LNPs) offer a viable platform for in situ engineering of CAR monocytes with transient and tunable CAR expression to reduce off-tumor toxicity and streamline cell manufacturing. However, identifying LNPs with monocyte tropism and intracellular delivery potency is difficult using traditional screening techniques. Here, ionizable lipid design and high-throughput in vivo screening are utilized to identify a new class of oxidized LNPs with innate tropism and mRNA delivery to monocytes. A library of oxidized (oLNPs) and unoxidized LNPs (uLNPs) is synthesized to evaluate mRNA delivery to immune cells. oLNPs demonstrate notable differences in morphology, ionization energy, and pKa, therefore enhancing delivery to human macrophages, but not T cells. Subsequently, in vivo library screening with DNA barcodes identifies an oLNP formulation, C14-O2, with innate tropism to monocytes. In a proof-of-concept study, the C14-O2 LNP is used to engineer functional CD19-CAR monocytes in situ for robust B cell aplasia (45%) in healthy mice. This work highlights the utility of oxidized LNPs as a promising platform for engineering CAR macrophages/monocytes for solid tumor CAR monocyte therapy.

TUFM in health and disease: exploring its multifaceted roles

The nuclear-encoded mitochondrial protein Tu translation elongation factor, mitochondrial (TUFM) is well-known for its role in mitochondrial protein translation. Originally discovered in yeast, TUFM demonstrates significant evolutionary conservation from prokaryotes to eukaryotes. Dysregulation of TUFM has been associated with mitochondrial disorders. Although early hypothesis suggests that TUFM is localized within mitochondria, recent studies identify its presence in the cytoplasm, with this subcellular distribution being linked to distinct functions of TUFM. Significantly, in addition to its established function in mitochondrial protein quality control, recent research indicates a broader involvement of TUFM in the regulation of programmed cell death processes (e.g., autophagy, apoptosis, necroptosis, and pyroptosis) and its diverse roles in viral infection, cancer, and other disease conditions. This review seeks to offer a current summary of TUFM's biological functions and its complex regulatory mechanisms in human health and disease. Insight into these intricate pathways controlled by TUFM may lead to the potential development of targeted therapies for a range of human diseases.

Revealing the mechanism and function underlying pairwise temporal coupling in collective motion

Coordinated motion in animal groups has predominantly been studied with a focus on spatial interactions, such as how individuals position and orient themselves relative to one another. Temporal aspects have, by contrast, received much less attention. Here, by studying pairwise interactions in juvenile zebrafish (Danio rerio)-including using immersive volumetric virtual reality (VR) with which we can directly test models of social interactions in situ-we reveal that there exists a rhythmic out-of-phase (i.e., an alternating) temporal coordination dynamic. We find that reciprocal (bi-directional) feedback is both necessary and sufficient to explain this emergent coupling. Beyond a mechanistic understanding, we find, both from VR experiments and analysis of freely swimming pairs, that temporal coordination considerably improves spatial responsiveness, such as to changes in the direction of motion of a partner. Our findings highlight the synergistic role of spatial and temporal coupling in facilitating effective communication between individuals on the move.