Variation in the fitted filtration efficiency of disposable face masks by sex.

BACKGROUND & OBJECTIVE: Disposable face masks are a primary protective measure against the adverse health effects of exposure to infectious and toxic aerosols such as airborne viruses and particulate air pollutants. While the fit of high efficiency respirators is regulated in occupational settings, relatively little is known about the fitted filtration efficiencies of ear loop style face masks worn by the public. METHODS: We measured the variation in fitted filtration efficiency (FFE) of four commonly worn disposable face masks, in a cohort of healthy adult participants (N = 100, 50% female, 50% male, average age = 32.3 ± 9.2 years, average BMI = 25.5 ± 3.4) using the U.S. Occupational Safety and Health Administration Quantitative Fit Test, for an N95 (respirator), KN95, surgical, and KF94 masks. The latter three ear loop style masks were additionally tested in a clip-modified condition, tightened using a plastic clip to centrally fasten loops in the back of the head. RESULTS: The findings show that sex is a major determinant of the FFE of KN95, surgical, and KF94 masks. On average, males had an 11% higher FFE relative to females, at baseline testing. We show that a simple modification using an ear loop clip, results in improvements in the average FFE for females but provides comparatively minor changes for males. On average, females had a 20% increased FFE when a clip was worn behind the head, relative to a 6% increase for males. IMPACT: The efficacy of a disposable face mask as protection against air contaminants depends on the efficiency of the mask materials and how well it fits the wearer. We report that the sex of the wearer is a major determinant of the baseline fitted filtration efficiency (FFE) of commonly available ear loop style face masks. In addition, we show that a simple fit modifier, an ear loop clip fastened behind the head, substantially improves baseline FFE for females but produces only minor changes for males. These findings have significant public health implications for the use of face masks as a protective intervention against inhalational exposure to airborne contaminants.

Three SARS-CoV-2 spike protein variants delivered intranasally by measles and mumps vaccines are broadly protective.

As the new SARS-CoV-2 Omicron variants and subvariants emerge, there is an urgency to develop intranasal, broadly protective vaccines. Here, we developed highly efficacious, intranasal trivalent SARS-CoV-2 vaccine candidates (TVC) based on three components of the MMR vaccine: measles virus (MeV), mumps virus (MuV) Jeryl Lynn (JL1) strain, and MuV JL2 strain. Specifically, MeV, MuV-JL1, and MuV-JL2 vaccine strains, each expressing prefusion spike (preS-6P) from a different variant of concern (VoC), were combined to generate TVCs. Intranasal immunization of IFNAR1-/- mice and female hamsters with TVCs generated high levels of S-specific serum IgG antibodies, broad neutralizing antibodies, and mucosal IgA antibodies as well as tissue-resident memory T cells in the lungs. The immunized female hamsters were protected from challenge with SARS-CoV-2 original WA1, B.1.617.2, and B.1.1.529 strains. The preexisting MeV and MuV immunity does not significantly interfere with the efficacy of TVC. Thus, the trivalent platform is a promising next-generation SARS-CoV-2 vaccine candidate.

IFN-λ uniquely promotes CD8 T cell immunity against SARS-CoV-2 relative to type I IFN.

Optimization of protective immune responses against SARS-CoV-2 remains an urgent worldwide priority. In this regard, type III IFN (IFN-λ) restricts SARS-CoV-2 infection in vitro, and treatment with IFN-λ limits infection, inflammation, and pathogenesis in murine models. Furthermore, IFN-λ has been developed for clinical use to limit COVID-19 severity. However, whether endogenous IFN-λ signaling has an effect on SARS-CoV-2 antiviral immunity and long-term immune protection in vivo is unknown. In this study, we identified a requirement for IFN-λ signaling in promoting viral clearance and protective immune programming in SARS-CoV-2 infection of mice. Expression of both IFN and IFN-stimulated gene (ISG) in the lungs were minimally affected by the absence of IFN-λ signaling and correlated with transient increases in viral titers. We found that IFN-λ supported the generation of protective CD8 T cell responses against SARS-CoV-2 by facilitating accumulation of CD103+ DC in lung draining lymph nodes (dLN). IFN-λ signaling specifically in DCs promoted the upregulation of costimulatory molecules and the proliferation of CD8 T cells. Intriguingly, antigen-specific CD8 T cell immunity to SARS-CoV-2 was independent of type I IFN signaling, revealing a nonredundant function of IFN-λ. Overall, these studies demonstrate a critical role for IFN-λ in protective innate and adaptive immunity upon infection with SARS-CoV-2 and suggest that IFN-λ serves as an immune adjuvant to support CD8 T cell immunity.

Preclinical Therapeutic Efficacy of RAF/MEK/ERK and IGF1R/AKT/mTOR Inhibition in Neuroblastoma.

Activating mutations in the RAS/MAPK pathway are observed in relapsed neuroblastoma. Preclinical studies indicate that these tumors have an increased sensitivity to inhibitors of the RAS/MAPK pathway, such as MEK inhibitors. MEK inhibitors do not induce durable responses as single agents, indicating a need to identify synergistic combinations of targeted agents to provide therapeutic benefit. We previously showed preclinical therapeutic synergy between a MEK inhibitor, trametinib, and a monoclonal antibody specific for IGF1R, ganitumab in RAS-mutated rhabdomyosarcoma. Neuroblastoma cells, like rhabdomyosarcoma cells, are sensitive to the inhibition of the RAS/MAPK and IGF1R/AKT/mTOR pathways. We hypothesized that the combination of trametinib and ganitumab would be effective in RAS-mutated neuroblastoma. In this study, trametinib and ganitumab synergistically suppressed neuroblastoma cell proliferation and induced apoptosis in cell culture. We also observed a delay in tumor initiation and prolongation of survival in heterotopic and orthotopic xenograft models treated with trametinib and ganitumab. However, the growth of both primary and metastatic tumors was observed in animals receiving the combination of trametinib and ganitumab. Therefore, more preclinical work is necessary before testing this combination in patients with relapsed or refractory RAS-mutated neuroblastoma.

Acute, dose-response effects of guayusa leaf extract on mood, cognitive and motor-cognitive performance, and blood pressure, heart rate, and ventricular repolarization.

PURPOSE: We conducted a randomized, double-blind, placebo-controlled crossover trial in young adults to examine the dose-dependent (600 mg versus 1200 mg), acute effects of consumption of an Ilex guayusa tea extract (GLE) on mood, cognitive and motor-cognitive performance, as well as its acute cardiovascular effects. METHODS: Twenty-five adults (mean ± SD, age = 28 ± 7 y; 9 M/16 F) completed familiarization and then three randomly ordered experimental visits where they consumed either 600 mg (GLE600) or 1200 mg (GLE1200) GLE or placebo (PLA). Following supplement consumption, participants completed a mood state survey, assessments of perceived jitteriness, energy, and focus, and neurocognitive and motor-cognitive testing. Blood pressure (BP), heart rate, and QT interval length were determined before and after supplementation. RESULTS: GLE600 significantly improved total mood disturbance (mean ± SE difference = -6.9 ± 2.6 au, p = 0.034), fatigue-inertia (-2.84 ± 0.89 au, p = 0.008), perceived energy (+13.00 ± 4.49 au; p = 0.02), motor speed (+4.52 ± 1.42 au, p = 0.008), and psychomotor speed (+7.20 ± 2.16 au, p = 0.005) relative to PLA. GLE1200 also improved psychomotor speed (+5.08 ± 2.16 ms, p = 0.045) and uniquely increased motor-cognitive performance as reflected by a decrease in reaction time (-0.106 ± 0.04 ms, p = 0.026) during a neurocognitive hop test. The effect of GLE on jitteriness was both dose- and sex-dependent. Jitteriness increased with increasing GLE dose in women only (p < 0.001). Both GLE600 and GLE1200 similarly increased systolic and diastolic BP by 4-5 mmHg (p ≤ 0.022). Neither GLE600 nor GLE1200 acutely influenced QTc length (p = 0.31). CONCLUSIONS: The goal of GLE supplementation should be considered when selecting a dosing strategy. Lower dosages of GLE (e.g. 600 mg) appear to optimize cognitive and mood-related outcomes while limiting side-effects such as jitteriness in women, and higher dosages may be necessary (e.g. 1200 mg) to promote improvements in motor-cognitive performance.

Extreme functional specialization of fertile leaves in a widespread fern species and its implications on the evolution of reproductive dimorphism.

Resource allocation theory posits that organisms distribute limited resources across functions to maximize their overall fitness. In plants, the allocation of resources among maintenance, reproduction, and growth influences short-term economics and long-term evolutionary processes, especially during resource scarcity. The evolution of specialized structures to divide labor between reproduction and growth can create a feedback loop where selection can act on individual organs, further increasing specializaton and  resource allocation. Ferns exhibit diverse reproductive strategies, including dimorphism, where leaves can either be sterile (only for photosynthesis) or fertile (for spore dispersal). This dimorphism is similar to processes in seed plants (e.g., the production of fertile flowers and sterile leaves), and presents an opportunity to investigate divergent resource allocation between reproductive and vegetative functions in specialized organs. Here, we conducted anatomical and hydraulic analyses on Onoclea sensibilis L., a widespread dimorphic fern species, to reveal significant structural and hydraulic divergences between fertile and sterile leaves. Fertile fronds invest less in hydraulic architecture, with nearly 1.5 times fewer water-conducting cells and a nearly 0.5 times less drought-resistant xylem compared to sterile fronds. This comes at the increased relative investment in structural support, which may help facilitate spore dispersal. These findings suggest that specialization in ferns-in the form of reproductive dimorphism-can enable independent selection pressures on each leaf type, potentially optimizing spore dispersal in fertile fronds and photosynthetic efficiency in sterile fronds. Overall, our study sheds light on the evolutionary implications of functional specialization and highlights the importance of reproductive strategies in shaping plant fitness and evolution.

Nutrient Recovery from Algae Using Mild Oxidative Treatment and Ion Exchange.

Valorization of algal biomass to fuels and chemicals frequently requires pretreatment to lyse cells and extract lipids, leaving behind an extracted solid residue as an underutilized intermediate. Mild oxidative treatment (MOT) is a promising route to simultaneously convert nitrogen contained in these residues to easily recyclable ammonium and to convert carbon in the same fraction to biofuel precursor carboxylates. We show that for a Nannochloropsis algae under certain oxidation conditions, nearly all the nitrogen in the residues can be converted to ammonium and recovered by cation exchange, while up to ∼20% of the carbon can be converted to short chain carboxylates. At the same time, we also show that soluble phosphorus in the form of phosphate can be selectively recovered by anion exchange, leaving a clean aqueous carbon stream for further upgrading.

Targeting of nanoparticles to the cerebral vasculature after traumatic brain injury.

Traumatic brain injury has faced numerous challenges in drug development, primarily due to the difficulty of effectively delivering drugs to the brain. However, there is a potential solution in targeted drug delivery methods involving antibody-drug conjugates or nanocarriers conjugated with targeting antibodies. Following a TBI, the blood-brain barrier (BBB) becomes permeable, which can last for years and allow the leakage of harmful plasma proteins. Consequently, an appealing approach for TBI treatment involves using drug delivery systems that utilize targeting antibodies and nanocarriers to help restore BBB integrity. In our investigation of this strategy, we examined the efficacy of free antibodies and nanocarriers targeting a specific endothelial surface marker called vascular cell adhesion molecule-1 (VCAM-1), which is known to be upregulated during inflammation. In a mouse model of TBI utilizing central fluid percussion injury, free VCAM-1 antibody did not demonstrate superior targeting when comparing sham vs. TBI brain. However, the administration of VCAM-1-targeted nanocarriers (liposomes) exhibited a 10-fold higher targeting specificity in TBI brain than in sham control. Flow cytometry and confocal microscopy analysis confirmed that VCAM-1 liposomes were primarily taken up by brain endothelial cells post-TBI. Consequently, VCAM-1 liposomes represent a promising platform for the targeted delivery of therapeutics to the brain following traumatic brain injury.

Testing a hybrid risk assessment model: Predicting CSAM offender risk from digital forensic artifacts.

BACKGROUND: Recent research argues for a formalized hybrid risk assessment model that combines the current online child sex abuse risk measures with digital forensics artifacts. OBJECTIVE: We conducted a feasibility study as an initial step toward formalizing the hybrid risk assessment model by identifying high-level digital forensic artifacts that have the potential to be valid and reliable indicators of risk, with a focus on CPORT Items 5, 6, and 7. DATA: Law enforcement investigators from a High Tech Crime Unit (HTCU) randomly selected seven closed cases; selection criteria included: male offender over 18, mobile device, child sexual abuse material (CSAM) offense, and 2019-2023 index offense. Investigation details related to probable cause, final charges, conviction, and offender risk were not disclosed. Statistical information (f, %) for the following digital forensics artifacts was examined: 1) pornography collection (e.g., % of media, content type, gender ratio) and 2) evidence of networking/grooming and other problematic online activities (e.g., number of native messages vs. application messages; type of installed apps). METHOD: The analysis predicted whether the offender was a CSAM-only or dual offender and if our findings agreed with the level of risk for reoffending suggested by CPORT Items 5, 6, and 7. Results were shared with the HTCU and scored for accuracy. RESULTS: The hybrid model was accurate in 6 of 7 cases. CONCLUSION: We conclude a hybrid model is feasible, and the findings illustrate the importance of analyzing app artifacts for context. Study limitations and future research recommendations are discussed.

Lippia alba essential oil: A powerful and valuable antinociceptive and anti-inflammatory medicinal plant from Brazil.

ETHNOPHARMACOLOGICAL RELEVANCE: In Brazilian popular medicine, Lippia alba leaves are used in teas to treat pain and inflammatory diseases. AIM OF THE STUDY: to evaluate the chemical composition, antinociceptive, and anti-inflammatory activities of Lippia alba essential oil and its major compound geraniol. MATERIAL AND METHODS: Lippia alba leaves were collected in Pará state, Brazil. The leaf essential oil was obtained using a modified Clevenger-type extractor. Then, the oil was analyzed by GC and GC-MS analyses. To evaluate the toxicity of LaEO and geraniol, the doses of 50, 300, and 2000 mg/kg were used in a mouse model. For antinociception tests, abdominal contortion, hot plate, and formalin tests were used; all groups were treated with LaEO and geraniol at doses of 25, 50, and 100 mg/kg; and to evaluate inflammation using the ear edema model. RESULTS: The constituents identified in the highest content were oxygenated monoterpenes: geraniol (37.5%), geranial (6.7%) and neral (3.8%). The animals treated with LaEO and geraniol demonstrated atypical behaviors with aspects of lethargy and drowsiness, characteristics of animals in a state of sedation; the relative weights showed no significant difference compared to the controls. In the abdominal contortion test, LaEO at 25 mg/kg, 50 mg/kg doses, and 100 mg/kg reduced the number of contortions, representing a percentage reduction of 84.64%, 81.23%, and 66.21% respectively. In the hot plate test, LaEO and geraniol increased the latency time at doses of 25, 50, and 100 mg/kg in all test periods; there was no statistical difference between LaEO and geraniol. In the first phase of the formalin test, only doses of 25 mg/kg and 100 mg/kg of LaEO showed significant activity, reducing the latency time by 53.40% and 58.90%. LaEO at doses of 25 mg/kg and 100 mg/kg reduced the size of the edema, demonstrating an anti-inflammatory activity of 59.38% (25 mg/kg) and 50% (100 mg/kg). CONCLUSION: Lippia alba essential oil and geraniol showed central/peripheral analgesic and anti-inflammatory potential and can be used as an alternative or complementary treatment to conventional drugs. More studies are needed to evaluate its action mechanisms and its analgesic effects.

Enabling non-viral DNA delivery using lipid nanoparticles co-loaded with endogenous anti-inflammatory lipids.

Lipid nanoparticles (LNPs) have transformed genetic medicine, recently shown by their use in COVID-19 mRNA vaccines. While loading LNPs with mRNA has many uses, loading DNA would provide additional advantages such as long-term expression and availability of promoter sequences. However, here we show that plasmid DNA (pDNA) delivery via LNPs (pDNA-LNPs) induces acute inflammation in naïve mice which we find is primarily driven by the cGAS-STING pathway. Inspired by DNA viruses that inhibit this pathway for replication, we co-loaded endogenous lipids that inhibit STING into pDNA-LNPs. Specifically, loading nitro-oleic acid (NOA) into pDNA-LNPs (NOA-pDNA-LNPs) ameliorates serious inflammatory responses in vivo enabling prolonged transgene expression (at least 1 month). Additionally, we demonstrate the ability to iteratively optimize NOA-pDNA-LNPs' expression by performing a small LNP formulation screen, driving up expression 50-fold in vitro. Thus, NOA-pDNA-LNPs, and pDNA-LNPs co-loaded with other bioactive molecules, will provide a major new tool in the genetic medicine toolbox, leveraging the power of DNA's long-term and promoter-controlled expression.

Characterization of Mass, Diameter, Density, and Surface Properties of Colloidal Nanoparticles Enabled by Charge Detection Mass Spectrometry.

A variety of scattering-based, microscopy-based, and mobility-based methods are frequently used to probe the size distributions of colloidal nanoparticles with transmission electron microscopy (TEM) often considered to be the "gold standard". Charge detection mass spectrometry (CDMS) is an alternative method for nanoparticle characterization that can rapidly measure the mass and charge of individual nanoparticle ions with high accuracy. Two low polydispersity, ∼100 nm diameter nanoparticle size standards with different compositions (polymethyl methacrylate/polystyrene copolymer and 100% polystyrene) were characterized using both TEM and CDMS to explore the merits and complementary aspects of both methods. Mass and diameter distributions are rapidly obtained from CDMS measurements of thousands of individual ions of known spherical shape, requiring less time than TEM sample preparation and image analysis. TEM image-to-image variations resulted in a ∼1-2 nm range in the determined mean diameters whereas the CDMS mass precision of ∼1% in these experiments leads to a diameter uncertainty of just 0.3 nm. For the 100% polystyrene nanoparticles with known density, the CDMS and TEM particle diameter distributions were in excellent agreement. For the copolymer nanoparticles with unknown density, the diameter from TEM measurements combined with the mass from CDMS measurements enabled an accurate measurement of nanoparticle density. Differing extents of charging for the two nanoparticle standards measured by CDMS show that charging is sensitive to nanoparticle surface properties. A mixture of the two samples was separated based on their different extents of charging despite having overlapping mass distributions centered at 341.5 and 331.0 MDa.

The multifaceted role of c-di-AMP signaling in the regulation of Porphyromonas gingivalis lipopolysaccharide structure and function.

Background: This study unveils the intricate functional association between cyclic di-3',5'-adenylic acid (c-di-AMP) signaling, cellular bioenergetics, and the regulation of lipopolysaccharide (LPS) profile in Porphyromonas gingivalis, a Gram-negative obligate anaerobe considered as a keystone pathogen involved in the pathogenesis of chronic periodontitis. Previous research has identified variations in P. gingivalis LPS profile as a major virulence factor, yet the underlying mechanism of its modulation has remained elusive. Methods: We employed a comprehensive methodological approach, combining two mutants exhibiting varying levels of c-di-AMP compared to the wild type, alongside an optimized analytical methodology that combines conventional mass spectrometry techniques with a novel approach known as FLATn. Results: We demonstrate that c-di-AMP acts as a metabolic nexus, connecting bioenergetic status to nuanced shifts in fatty acid and glycosyl profiles within P. gingivalis LPS. Notably, the predicted regulator gene cdaR, serving as a potent regulator of c-di-AMP synthesis, was found essential for producing N-acetylgalactosamine and an unidentified glycolipid class associated with the LPS profile. Conclusion: The multifaceted roles of c-di-AMP in bacterial physiology are underscored, emphasizing its significance in orchestrating adaptive responses to stimuli. Furthermore, our findings illuminate the significance of LPS variations and c-di-AMP signaling in determining the biological activities and immunostimulatory potential of P. gingivalis LPS, promoting a pathoadaptive strategy. The study expands the understanding of c-di-AMP pathways in Gram-negative species, laying a foundation for future investigations into the mechanisms governing variations in LPS structure at the molecular level and their implications for host-pathogen interactions.

Grief and bereavement beliefs and their associations with death anxiety and complicated grief in a U.S. college student sample.

This study examined beliefs about grief and bereavement, and how the endorsement of myths is related to death anxiety and complicated grief. Results from a sample of college students in the United States (N = 391) suggested that myths about grief and bereavement are prevalent in this group. Additionally, the endorsement of certain myths significantly explained both death anxiety and complicated grief. Findings from this study provide additional support for death education in college and university settings to promote grief literacy. Implications for education, advocacy, research, and practice are discussed.

Accuracy, readability, and understandability of large language models for prostate cancer information to the public.

BACKGROUND: Generative Pretrained Model (GPT) chatbots have gained popularity since the public release of ChatGPT. Studies have evaluated the ability of different GPT models to provide information about medical conditions. To date, no study has assessed the quality of ChatGPT outputs to prostate cancer related questions from both the physician and public perspective while optimizing outputs for patient consumption. METHODS: Nine prostate cancer-related questions, identified through Google Trends (Global), were categorized into diagnosis, treatment, and postoperative follow-up. These questions were processed using ChatGPT 3.5, and the responses were recorded. Subsequently, these responses were re-inputted into ChatGPT to create simplified summaries understandable at a sixth-grade level. Readability of both the original ChatGPT responses and the layperson summaries was evaluated using validated readability tools. A survey was conducted among urology providers (urologists and urologists in training) to rate the original ChatGPT responses for accuracy, completeness, and clarity using a 5-point Likert scale. Furthermore, two independent reviewers evaluated the layperson summaries on correctness trifecta: accuracy, completeness, and decision-making sufficiency. Public assessment of the simplified summaries' clarity and understandability was carried out through Amazon Mechanical Turk (MTurk). Participants rated the clarity and demonstrated their understanding through a multiple-choice question. RESULTS: GPT-generated output was deemed correct by 71.7% to 94.3% of raters (36 urologists, 17 urology residents) across 9 scenarios. GPT-generated simplified layperson summaries of this output was rated as accurate in 8 of 9 (88.9%) scenarios and sufficient for a patient to make a decision in 8 of 9 (88.9%) scenarios. Mean readability of layperson summaries was higher than original GPT outputs ([original ChatGPT v. simplified ChatGPT, mean (SD), p-value] Flesch Reading Ease: 36.5(9.1) v. 70.2(11.2), <0.0001; Gunning Fog: 15.8(1.7) v. 9.5(2.0), p < 0.0001; Flesch Grade Level: 12.8(1.2) v. 7.4(1.7), p < 0.0001; Coleman Liau: 13.7(2.1) v. 8.6(2.4), 0.0002; Smog index: 11.8(1.2) v. 6.7(1.8), <0.0001; Automated Readability Index: 13.1(1.4) v. 7.5(2.1), p < 0.0001). MTurk workers (n = 514) rated the layperson summaries as correct (89.5-95.7%) and correctly understood the content (63.0-87.4%). CONCLUSION: GPT shows promise for correct patient education for prostate cancer-related contents, but the technology is not designed for delivering patients information. Prompting the model to respond with accuracy, completeness, clarity and readability may enhance its utility when used for GPT-powered medical chatbots.

Convergent evolution of fern nectaries facilitated independent recruitment of ant-bodyguards from flowering plants.

Plant-herbivore interactions reciprocally influence species' evolutionary trajectories. These interactions have led to many physical and chemical defenses across the plant kingdom. Some plants have even evolved indirect defense strategies to outsource their protection to ant bodyguards by bribing them with a sugary reward (nectar). Identifying the evolutionary processes underpinning these indirect defenses provide insight into the evolution of plant-animal interactions. Using a cross-kingdom, phylogenetic approach, we examined the convergent evolution of ant-guarding nectaries across ferns and flowering plants. Here, we discover that nectaries originated in ferns and flowering plants concurrently during the Cretaceous, coinciding with the rise of plant associations in ants. While nectaries in flowering plants evolved steadily through time, ferns showed a pronounced lag of nearly 100 My between their origin and subsequent diversification in the Cenozoic. Importantly, we find that as ferns transitioned from the forest floor into the canopy, they secondarily recruited ant bodyguards from existing ant-angiosperm relationships.

Unwinding of a eukaryotic origin of replication visualized by cryo-EM.

To prevent detrimental chromosome re-replication, DNA loading of a double hexamer of the minichromosome maintenance (MCM) replicative helicase is temporally separated from DNA unwinding. Upon S-phase transition in yeast, DNA unwinding is achieved in two steps: limited opening of the double helix and topological separation of the two DNA strands. First, Cdc45, GINS and Polε engage MCM to assemble a double CMGE with two partially separated hexamers that nucleate DNA melting. In the second step, triggered by Mcm10, two CMGEs separate completely, eject the lagging-strand template and cross paths. To understand Mcm10 during helicase activation, we used biochemical reconstitution with cryogenic electron microscopy. We found that Mcm10 splits the double CMGE by engaging the N-terminal homo-dimerization face of MCM. To eject the lagging strand, DNA unwinding is started from the N-terminal side of MCM while the hexamer channel becomes too narrow to harbor duplex DNA.

Specific exercise patterns generate an epigenetic molecular memory window that drives long-term memory formation and identifies ACVR1C as a bidirectional regulator of memory in mice.

Exercise has beneficial effects on cognition throughout the lifespan. Here, we demonstrate that specific exercise patterns transform insufficient, subthreshold training into long-term memory in mice. Our findings reveal a potential molecular memory window such that subthreshold training within this window enables long-term memory formation. We performed RNA-seq on dorsal hippocampus and identify genes whose expression correlate with conditions in which exercise enables long-term memory formation. Among these genes we found Acvr1c, a member of the TGF ß family. We find that exercise, in any amount, alleviates epigenetic repression at the Acvr1c promoter during consolidation. Additionally, we find that ACVR1C can bidirectionally regulate synaptic plasticity and long-term memory in mice. Furthermore, Acvr1c expression is impaired in the aging human and mouse brain, as well as in the 5xFAD mouse model, and over-expression of Acvr1c enables learning and facilitates plasticity in mice. These data suggest that promoting ACVR1C may protect against cognitive impairment.

Deep learning imaging phenotype can classify metabolic syndrome and is predictive of cardiometabolic disorders.

BACKGROUND: Cardiometabolic disorders pose significant health risks globally. Metabolic syndrome, characterized by a cluster of potentially reversible metabolic abnormalities, is a known risk factor for these disorders. Early detection and intervention for individuals with metabolic abnormalities can help mitigate the risk of developing more serious cardiometabolic conditions. This study aimed to develop an image-derived phenotype (IDP) for metabolic abnormality from unenhanced abdominal computed tomography (CT) scans using deep learning. We used this IDP to classify individuals with metabolic syndrome and predict future occurrence of cardiometabolic disorders. METHODS: A multi-stage deep learning approach was used to extract the IDP from the liver region of unenhanced abdominal CT scans. In a cohort of over 2,000 individuals the IDP was used to classify individuals with metabolic syndrome. In a subset of over 1,300 individuals, the IDP was used to predict future occurrence of hypertension, type II diabetes, and fatty liver disease. RESULTS: For metabolic syndrome (MetS) classification, we compared the performance of the proposed IDP to liver attenuation and visceral adipose tissue area (VAT). The proposed IDP showed the strongest performance (AUC 0.82) compared to attenuation (AUC 0.70) and VAT (AUC 0.80). For disease prediction, we compared the performance of the IDP to baseline MetS diagnosis. The models including the IDP outperformed MetS for type II diabetes (AUCs 0.91 and 0.90) and fatty liver disease (AUCs 0.67 and 0.62) prediction and performed comparably for hypertension prediction (AUCs of 0.77). CONCLUSIONS: This study demonstrated the superior performance of a deep learning IDP compared to traditional radiomic features to classify individuals with metabolic syndrome. Additionally, the IDP outperformed the clinical definition of metabolic syndrome in predicting future morbidities. Our findings underscore the utility of data-driven imaging phenotypes as valuable tools in the assessment and management of metabolic syndrome and cardiometabolic disorders.