Extracellular vesicles may provide an alternative detoxification pathway during skeletal muscle myoblast ageing.

Skeletal muscle (SM) acts as a secretory organ, capable of releasing myokines and extracellular vesicles (SM-EVs) that impact myogenesis and homeostasis. While age-related changes have been previously reported in murine SM-EVs, no study has comprehensively profiled SM-EV in human models. To this end, we provide the first comprehensive comparison of SM-EVs from young and old human primary skeletal muscle cells (HPMCs) to map changes associated with SM ageing. HPMCs, isolated from young (24 ± 1.7 years old) and older (69 ± 2.6 years old) participants, were immunomagnetically sorted based on the presence of the myogenic marker CD56 (N-CAM) and cultured as pure (100% CD56+) or mixed populations (MP: 90% CD56+). SM-EVs were isolated using an optimised protocol combining ultrafiltration and size exclusion chromatography (UF + SEC) and their biological content was extensively characterised using Raman spectroscopy (RS) and liquid chromatography mass spectrometry (LC-MS). Minimal variations in basic EV parameters (particle number, size, protein markers) were observed between young and old populations. However, biochemical fingerprinting by RS highlighted increased protein (amide I), lipid (phospholipids and phosphatidylcholine) and hypoxanthine signatures for older SM-EVs. Through LC-MS, we identified 84 shared proteins with functions principally related to cell homeostasis, muscle maintenance and transcriptional regulation. Significantly, SM-EVs from older participants were comparatively enriched in proteins involved in oxidative stress and DNA/RNA mutagenesis, such as E3 ubiquitin-protein ligase TTC3 (TTC3), little elongation complex subunit 1 (ICE1) and Acetyl-CoA carboxylase 1 (ACACA). These data suggest SM-EVs could provide an alternative pathway for homeostasis and detoxification during SM ageing.

Proteomic analysis reveals a PLK1-dependent G2/M degradation program and a role for AKAP2 in coordinating the mitotic cytoskeleton.

Ubiquitination is an essential regulator of cell division. The kinase Polo-like kinase 1 (PLK1) promotes protein degradation at G2/M phase through the E3 ubiquitin ligase Skp1-Cul1-F box (SCF)ßTrCP. However, the magnitude to which PLK1 shapes the mitotic proteome is uncharacterized. Combining quantitative proteomics with pharmacologic PLK1 inhibition revealed a widespread, PLK1-dependent program of protein breakdown at G2/M. We validated many PLK1-regulated proteins, including substrates of the cell-cycle E3 SCFCyclin F, demonstrating that PLK1 promotes proteolysis through at least two distinct E3 ligases. We show that the protein-kinase-A-anchoring protein A-kinase anchor protein 2 (AKAP2) is cell-cycle regulated and that its mitotic degradation is dependent on the PLK1/ßTrCP signaling axis. Expression of a non-degradable AKAP2 mutant resulted in actin defects and aberrant mitotic spindles, suggesting that AKAP2 degradation coordinates cytoskeletal organization during mitosis. These findings uncover PLK1's far-reaching role in shaping the mitotic proteome post-translationally and have potential implications in malignancies where PLK1 is upregulated.

A multimodal fMRI dataset unifying naturalistic processes with a rich array of experimental tasks.

Cognitive neuroscience has advanced significantly due to the availability of openly shared datasets. Large sample sizes, large amounts of data per person, and diversity in tasks and data types are all desirable, but are difficult to achieve in a single dataset. Here, we present an open dataset with N = 101 participants and 6 hours of scanning per participant, with 6 multifaceted cognitive tasks including 2 hours of naturalistic movie viewing. This datasets' combination of ample sample size, extensive data per participant, more than 600 hours worth of data, and a wide range of experimental conditions - including cognitive, affective, social, and somatic/interoceptive tasks - positions it uniquely for probing important questions in cognitive neuroscience.

Phylosymbiosis shapes skin bacterial communities and pathogen-protective function in Appalachian salamanders.

Phylosymbiosis is an association between host-associated microbiome composition and host phylogeny. This pattern can arise via the evolution of host traits, habitat preferences, diets, and the co-diversification of hosts and microbes. Understanding the drivers of phylosymbiosis is vital for modelling disease-microbiome interactions and manipulating microbiomes in multi-host systems. This study quantifies phylosymbiosis in Appalachian salamander skin in the context of infection by the fungal pathogen Batrachochytrium dendrobatidis (Bd), while accounting for environmental microbiome exposure. We sampled ten salamander species representing >150M years of divergence, assessed their Bd infection status, and analysed their skin and environmental microbiomes. Our results reveal a significant signal of phylosymbiosis, whereas the local environmental pool of microbes, climate, geography, and Bd infection load had a smaller impact. Host-microbe co-speciation was not evident, indicating that the effect stems from the evolution of host traits influencing microbiome assembly. Bd infection is correlated with host phylogeny and the abundance of Bd-inhibitory bacterial strains, suggesting that the long-term evolutionary dynamics between salamander hosts and their skin microbiomes affect the present-day distribution of the pathogen, along with habitat-linked exposure risk. Five Bd-inhibitory bacterial strains showed unusual generalism: occurring in most host species and habitats. These generalist strains may enhance the likelihood of probiotic manipulations colonising and persisting on hosts. Our results underscore the substantial influence of host-microbiome eco-evolutionary dynamics on environmental health and disease outcomes.

Heart rate variability biofeedback to reduce anxiety in autism spectrum disorder - a mini review.

There is a reported high prevalence of anxiety in people with autism spectrum disorder. This mini review appraises existing research investigating heart rate variability biofeedback to help manage symptoms of anxiety in people with autism spectrum disorder. A thorough search of electronic databases was conducted to find relevant literature. Consultation with experts and a librarian helped develop search terms following the PICO framework. Five databases were searched, and screening was undertaken using Covidence software, with the process outlined in a PRISMA flowchart. The latest review showed positive short-term effects but there is a need for long-term follow-up. Future investigations should consider device type, training settings, and control interventions. Accurate heart rate variability assessment independent of biofeedback devices is crucial. Additional measures like cortisol assessment and user feedback are recommended for comprehensive evaluation. The findings highlight progress in the evidence base and offer insight to future directions.

Regulatory Considerations in the Approval of Rezafungin (Rezzayo) for the Treatment of Candidemia and Invasive Candidiasis in Adults.

On 22 March 2023, the FDA approved rezafungin (Rezzayo) for the treatment of candidemia and invasive candidiasis in adults with limited or no alternative treatment options. Rezafungin is an echinocandin that supports weekly dosing, enabling outpatient parenteral treatment that potentially avoids the need for a central venous catheter. Approval of rezafungin was based on a single adequate and well-controlled phase 3 study designed with a day 30 all-cause mortality primary end point and 20% noninferiority margin, which demonstrated that rezafungin is noninferior to the comparator echinocandin. Nonclinical studies of rezafungin in nonhuman primates identified a neurotoxicity safety signal; however, rezafungin's safety profile in the completed clinical studies was similar to other Food and Drug Administration-approved echinocandins. Here we describe the rationale for this approval and important considerations during the review process for a flexible development program intended to expedite the availability of antimicrobial therapies to treat serious infections in patients with limited treatment options. Clinical Trials Registration . NCT02734862 and NCT03667690.

Proteomic Analysis Reveals a PLK1-Dependent G2/M Degradation Program and Links PKA-AKAP2 to Cell Cycle Control.

Targeted protein degradation by the ubiquitin-proteasome system is an essential mechanism regulating cellular division. The kinase PLK1 coordinates protein degradation at the G2/M phase of the cell cycle by promoting the binding of substrates to the E3 ubiquitin ligase SCFßTrCP. However, the magnitude to which PLK1 shapes the mitotic proteome has not been characterized. Combining deep, quantitative proteomics with pharmacologic PLK1 inhibition (PLK1i), we identified more than 200 proteins whose abundances were increased by PLK1i at G2/M. We validate many new PLK1-regulated proteins, including several substrates of the cell cycle E3 SCFCyclin F, demonstrating that PLK1 promotes proteolysis through at least two distinct SCF-family E3 ligases. Further, we found that the protein kinase A anchoring protein AKAP2 is cell cycle regulated and that its mitotic degradation is dependent on the PLK1/ßTrCP-signaling axis. Interactome analysis revealed that the strongest interactors of AKAP2 function in signaling networks regulating proliferation, including MAPK, AKT, and Hippo. Altogether, our data demonstrate that PLK1 coordinates a widespread program of protein breakdown at G2/M. We propose that dynamic proteolytic changes mediated by PLK1 integrate proliferative signals with the core cell cycle machinery during cell division. This has potential implications in malignancies where PLK1 is aberrantly regulated.

Single-dose effects of methylphenidate and atomoxetine on functional connectivity during an n-back task in boys with ADHD.

RATIONALE: Working memory deficits and associated neurofunctional abnormalities are frequently reported in attention-deficit/hyperactivity disorder (ADHD). Methylphenidate and atomoxetine improve working memory performance and increase activation of regions under-functioning in ADHD. Additionally, methylphenidate has been observed to modulate functional networks involved in working memory. No research, however, has examined the effects of atomoxetine or compared the two drugs. OBJECTIVES: This study aimed to test methylphenidate and atomoxetine effects on functional connectivity during working memory in boys with ADHD. METHODS: We tested comparative effects of methylphenidate and atomoxetine on functional connectivity during the n-back task in 19 medication-naïve boys with ADHD (10-15 years old) relative to placebo and assessed potential normalisation effects of brain dysfunctions under placebo relative to 20 age-matched neurotypical boys. Patients were scanned in a randomised, double-blind, cross-over design under single doses of methylphenidate, atomoxetine, and placebo. Controls were scanned once, unmedicated. RESULTS: Patients under placebo showed abnormally increased connectivity between right superior parietal gyrus (rSPG) and left central operculum/insula. This hyperconnectivity was not observed when patients were under methylphenidate or atomoxetine. Furthermore, under methylphenidate, patients showed increased connectivity relative to controls between right middle frontal gyrus (rMFG) and cingulo-temporo-parietal and striato-thalamic regions, and between rSPG and cingulo-parietal areas. Interrogating these networks within patients revealed increased connectivity between both rMFG and rSPG and right supramarginal gyrus under methylphenidate relative to placebo. Nonetheless, no differences across drug conditions were observed within patients at whole brain level. No drug effects on performance were observed. CONCLUSIONS: This study shows shared modulating effects of methylphenidate and atomoxetine on parieto-insular connectivity but exclusive effects of methylphenidate on connectivity increases in fronto-temporo-parietal and fronto-striato-thalamic networks in ADHD.

Comparison of extracellular vesicle isolation processes for therapeutic applications.

While extracellular vesicles (EVs) continue to gain interest for therapeutic applications, their clinical translation is limited by a lack of optimal isolation methods. We sought to determine how universally applied isolation methods impact EV purity and yield. EVs were isolated by ultracentrifugation (UC), polyethylene glycol precipitation, Total Exosome Isolation Reagent, an aqueous two-phase system with and without repeat washes or size exclusion chromatography (SEC). EV-like particles could be detected for all isolation methods but varied in their purity and relative expression of surface markers (Alix, Annexin A2, CD9, CD63 and CD81). Assessments of sample purity were dependent on the specificity of characterisation method applied, with total particle counts and particle to protein (PtP) ratios often not aligning with quantitative measures of tetraspanin surface markers obtained using high-resolution nano-flow cytometry. While SEC resulted in the isolation of fewer particles with a relatively low PtP ratio (1.12 × 107 ± 1.43 × 106 vs highest recorded; ATPS/R 2.01 × 108 ± 1.15 × 109, p ⩽ 0.05), EVs isolated using this method displayed a comparatively high level of tetraspanin positivity (e.g. ExoELISA CD63⁺ particles; 1.36 × 1011 ± 1.18 × 1010 vs ATPS/R 2.58 × 1010 ± 1.92 × 109, p ⩽ 0.001). Results originating from an accompanying survey designed to evaluate pragmatic considerations surrounding method implementation (e.g. scalability and cost) identified that SEC and UC were favoured for overall efficiency. However, reservations were highlighted in the scalability of these methods, which could potentially hinder downstream therapeutic applications. In conclusion, variations in sample purity and yield were evident between isolation methods, while standard non-specific assessments of sample purity did not align with advanced quantitative high-resolution analysis of EV surface markers. Reproducible and specific assessments of EV purity will be critical for informing therapeutic studies.

Machine Learning Predictions of Oil Yields Obtained by Plastic Pyrolysis and Application to Thermodynamic Analysis.

Chemical recycling via thermal processes such as pyrolysis is a potentially viable way to convert mixed streams of waste plastics into usable fuels and chemicals. Unfortunately, experimentally measuring product yields for real waste streams can be time- and cost-prohibitive, and the yields are very sensitive to feed composition, especially for certain types of plastics like poly(ethylene terephthalate) (PET) and polyvinyl chloride (PVC). Models capable of predicting yields and conversion from feed composition and reaction conditions have potential as tools to prioritize resources to the most promising plastic streams and to evaluate potential preseparation strategies to improve yields. In this study, a data set consisting of 325 data points for pyrolysis of plastic feeds was collected from the open literature. The data set was divided into training and test sub data sets; the training data were used to optimize the seven different machine learning regression methods, and the testing data were used to evaluate the accuracy of the resulting models. Of the seven types of models, eXtreme Gradient Boosting (XGBoost) predicted the oil yield of the test set with the highest accuracy, corresponding to a mean absolute error (MAE) value of 9.1%. The optimized XGBoost model was then used to predict the oil yields from real waste compositions found in Municipal Recycling Facilities (MRFs) and the Rhine River. The dependence of oil yields on composition was evaluated, and strategies for removing PET and PVC were assessed as examples of how to use the model. Thermodynamic analysis of a pyrolysis system capable of achieving oil yields predicted using the machine-learned model showed that pyrolysis of Rhine River plastics should be net exergy producing under most reasonable conditions.

Cell-autonomous immune dysfunction driven by disrupted autophagy in C9orf72-ALS iPSC-derived microglia contributes to neurodegeneration.

Although microglial activation is widely found in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), the underlying mechanism(s) are poorly understood. Here, using human-induced pluripotent stem cell-derived microglia-like cells (hiPSC-MG) harboring the most common ALS/FTD mutation (C9orf72, mC9-MG), gene-corrected isogenic controls (isoC9-MG), and C9orf72 knockout hiPSC-MG (C9KO-MG), we show that reduced C9ORF72 protein is associated with impaired phagocytosis and an exaggerated immune response upon stimulation with lipopolysaccharide. Analysis of the C9ORF72 interactome revealed that C9ORF72 interacts with regulators of autophagy and functional studies showed impaired initiation of autophagy in mC9-MG and C9KO-MG. Coculture studies with motor neurons (MNs) demonstrated that the autophagy deficit in mC9-MG drives increased vulnerability of mC9-MNs to excitotoxic stimulus. Pharmacological activation of autophagy ameliorated both cell-autonomous functional deficits in hiPSC-MG and MN death in MG-MN coculture. Together, these findings reveal an important role for C9ORF72 in regulating immune homeostasis and identify dysregulation in myeloid cells as a contributor to neurodegeneration in ALS/FTD.

Reduced inferior fronto-insular-thalamic activation during failed inhibition in young adults with combined ASD and ADHD compared to typically developing and pure disorder groups.

Autism spectrum disorder (ASD) often co-occurs with attention-deficit/hyperactivity disorder (ADHD) and people with these conditions have frontostriatal functional atypicality during motor inhibition. We compared the neural and neurocognitive correlates of motor inhibition and performance monitoring in young adult males with "pure" and combined presentations with age-and sex-matched typically developing controls, to explore shared or disorder-specific atypicality. Males aged 20-27 years with typical development (TD; n = 22), ASD (n = 21), combined diagnoses ASD + ADHD (n = 23), and ADHD (n = 25) were compared using a modified tracking fMRI stop-signal task that measures motor inhibition and performance monitoring while controlling for selective attention. In addition, they performed a behavioural go/no-go task outside the scanner. While groups did not differ behaviourally during successful stop trials, the ASD + ADHD group relative to other groups had underactivation in typical performance monitoring regions of bilateral anterior insula/inferior frontal gyrus, right posterior thalamus, and right middle temporal gyrus/hippocampus during failed inhibition, which was associated with increased stop-signal reaction time. In the behavioural go/no-go task, both ADHD groups, with and without ASD, had significantly lower motor inhibition performance compared to TD controls. In conclusion, only young adult males with ASD + ADHD had neurofunctional atypicality in brain regions associated with performance monitoring, while inhibition difficulties on go/no-go task performance was shared with ADHD. The suggests that young people with ASD + ADHD are most severely impaired during motor inhibition tasks compared to ASD and ADHD but do not reflect a combination of the difficulties associated with the pure disorders.

A survey to evaluate parameters governing the selection and application of extracellular vesicle isolation methods.

Extracellular vesicles (EVs) continue to gain interest across the scientific community for diagnostic and therapeutic applications. As EV applications diversify, it is essential that researchers are aware of challenges, in particular the compatibility of EV isolation methods with downstream applications and their clinical translation. We report outcomes of the first cross-comparison study looking to determine parameters (EV source, starting volume, operator experience, application and implementation parameters such as cost and scalability) governing the selection of popular EV isolation methods across disciplines. Our findings highlighted an increased clinical focus, with 36% of respondents applying EVs in therapeutics and diagnostics. Data indicated preferential selection of ultracentrifugation for therapeutic applications, precipitation reagents in clinical settings and size exclusion chromatography for diagnostic applications utilising biofluids. Method selection was influenced by operator experience, with increased method diversity when EV research was not the respondents primary focus. Application and implementation criteria were indicated to be major influencers in method selection, with UC and SEC chosen for their abilities to process large and small volumes, respectively. Overall, we identified parameters influencing method selection across the breadth of EV science, providing a valuable overview of practical considerations for the effective translation of research outcomes.

Permeable Cornified Envelope Layer Regulates the Solute Transport in Human Stratum Corneum.

To unravel the diffusion mechanisms of percutaneous drug delivery, suitable numerical analysis of stratum corneum structure is essential. In this research paper, we accounted for the permeable envelope layer in the brick-and-mortar finite element models of human stratum corneum. Both penetration and desorption experiments for tritiated water were simulated by transient finite element analysis. Rivet-shaped corneodesmosomes were included in the brick and mortar model. Results showed that cornified lipid permeability (Penv) is a determinant in desorption of the solute, while lipid transverse diffusion coefficient (Dlip-trans) is prominent during penetration. These two major unknowns (Penv and Dlip-trans) were obtained by extensive fitting of the finite element model to the experimental water data. Penv and Dlip-trans were determined to be 1×10-2 cm/s and 5.7×10-10 cm2/s, respectively.

Extracellular vesicles: From bone development to regenerative orthopedics.

Regenerative medicine aims to promote the replacement of tissues lost to damage or disease. While positive outcomes have been observed experimentally, challenges remain in their clinical translation. This has led to growing interest in applying extracellular vesicles (EVs) to augment or even replace existing approaches. Through the engineering of culture environments or direct/indirect manipulation of EVs themselves, multiple avenues have emerged to modulate EV production, targeting, and therapeutic potency. Drives to modulate release using material systems or functionalize implants for improved osseointegration have also led to outcomes that could have real-world impact. The purpose of this review is to highlight advantages in applying EVs for the treatment of skeletal defects, outlining the current state of the art in the field and emphasizing avenues for further investigation. Notably, the review identifies inconsistencies in EV nomenclature and outstanding challenges in defining a reproducible therapeutic dose. Challenges also remain in the scalable manufacture of a therapeutically potent and pure EV product, with a need to address scalable cell sources and optimal culture environments. Addressing these issues will be critical if we are to develop regenerative EV therapies that meet the demands of regulators and can be translated from bench to bedside.

Microbubbles in Food Technology.

Microbubbles are largely unused in the food industry yet have promising capabilities as environmentally friendly cleaning and supporting agents within products and production lines due to their unique physical behaviors. Their small diameters increase their dispersion throughout liquid materials, promote reactivity because of their high specific surface area, enhance dissolution of gases into the surrounding liquid phase, and promote the generation of reactive chemical species. This article reviews techniques to generate microbubbles, their modes of action to enhance cleaning and disinfection, their contributions to functional and mechanical properties of food materials, and their use in supporting the growth of living organisms in hydroponics or bioreactors. The utility and diverse applications of microbubbles, combined with their low intrinsic ingredient cost, strongly encourage their increased adoption within the food industry in coming years.

Impact of Phylogenetic Tree Completeness and Mis-specification of Sampling Fractions on Trait Dependent Diversification Models.

Understanding the origins of diversity and the factors that drive some clades to be more diverse than others are important issues in evolutionary biology. Sophisticated SSE (state-dependent speciation and extinction) models provide insights into the association between diversification rates and the evolution of a trait. The empirical data used in SSE models and other methods is normally imperfect, yet little is known about how this can affect these models. Here, we evaluate the impact of common phylogenetic issues on inferences drawn from SSE models. Using simulated phylogenetic trees and trait information, we fitted SSE models to determine the effects of sampling fraction (phylogenetic tree completeness) and sampling fraction mis-specification on model selection and parameter estimation (speciation, extinction, and transition rates) under two sampling regimes (random and taxonomically biased). As expected, we found that both model selection and parameter estimate accuracies are reduced at lower sampling fractions (i.e., low tree completeness). Furthermore, when sampling of the tree is imbalanced across sub-clades and tree completeness is ≤ 60%, rates of false positives increase and parameter estimates are less accurate, compared to when sampling is random. Thus, when applying SSE methods to empirical datasets, there are increased risks of false inferences of trait dependent diversification when some sub-clades are heavily under-sampled. Mis-specifying the sampling fraction severely affected the accuracy of parameter estimates: parameter values were over-estimated when the sampling fraction was specified as lower than its true value, and under-estimated when the sampling fraction was specified as higher than its true value. Our results suggest that it is better to cautiously under-estimate sampling efforts, as false positives increased when the sampling fraction was over-estimated. We encourage SSE studies where the sampling fraction can be reasonably estimated and provide recommended best practices for SSE modeling. [Trait dependent diversification; SSE models; phylogenetic tree completeness; sampling fraction.].

Genetic assimilation of ancestral plasticity during parallel adaptation to zinc contamination in Silene uniflora.

Phenotypic plasticity in ancestral populations is hypothesized to facilitate adaptation, but evidence is piecemeal and often contradictory. Further, whether ancestral plasticity increases the probability of parallel adaptive changes has not been explored. The most general finding is that ancestral responses to a new environment are reversed following adaptation (known as reversion). We investigated the contribution of ancestral plasticity to adaptive evolution of gene expression in two independently evolved lineages of zinc-tolerant Silene uniflora. We found that the general pattern of reversion is driven by the absence of a widespread stress response in zinc-adapted plants compared with zinc-sensitive plants. We show that ancestral plasticity that moves expression closer to the optimum value in the new environment influences the evolution of gene expression among genes that are likely to be involved in adaptation and increases the chance that genes are recruited repeatedly during adaptation. However, despite convergence in gene expression levels between independently adapted lineages, ancestral plasticity does not influence how similar expression values of adaptive genes become. Surprisingly, we also observed that ancestral plasticity that increases fitness often becomes genetically determined and fixed, that is, genetically assimilated. These results emphasize the important role of ancestral plasticity in parallel adaptation.