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Microsatellites are present in mitochondria, chloroplast, and nuclear DNA, but nuclear microsatellites are more useful genetic tools than those in plastids or mitochondria. Plastid and mitochondrial microsatellites have been identified in the model plant Marchantia polymorpha (liverwort), but no laboratory has published information on nuclear microsatellite loci. The aim of this study was to detect novel nuclear markers in the most commonly employed liverwort species, design PCR primers that would allow amplification, and characterize the subsequently generated loci. We detected 18 polymorphic nuclear loci in M. polymorpha, amplifiable by PCR across all chromosomes. Additionally, trans-specific amplification of the eighteen loci was characterized in the closely related taxa Marchantia emarginata and Marchantia paleacea. All loci were present in M. paleacea, whereas 17 of 18 primer pairs were amplified in M. emarginata.

Whilst cold therapies such as cold-water immersion are regularly used in practice, the practical application does not always align with best practices. In this commentary, we highlight the key components of the British Association of Sport and Exercise Sciences (BASES) Expert Statement on the use of cooling therapies for post-exercise recovery and provide additional discussion on the empirical evidence and rationale that informed our perspective. We developed a series of specific questions to ensure that cold therapy recovery protocols are context-specific and tailored to the needs of the individual athletes. These questions, which cover the WHEN, WHAT, and HOW of cold therapy, were central to the development of the Expert Statement. This was presented as a decision tree to ensure that key messages could be concisely disseminated across a range of sporting environments and populations (e.g., gyms, locker rooms, and treatment rooms), supporting and informing decision-making for those wanting to use cold therapy to assist their recovery in line with previously published peer-reviewed work. Discussion points included the suitability of cooling therapies in some contexts, how athletes’ choice of cooling mode should be largely driven by practicalities (e.g., budget and availability), and, lastly, future research directions.

Theories of student engagement for dropout and school completion are proposed to begin as early as age five. Student engagement in elementary-age students has been linked to school completion, post-secondary education, and achievement. However, there is little research examining patterns and profiles of student engagement in this population. In an effort to provide more individualized support and intervention, work in the field of student engagement has begun to examine profiles of student engagement and disengagement or disaffection. This study explored the identification of distinguishable groups based on student engagement in a sample of third-grade students and those groups' associations with demographic and outcome variables. Consistent with findings of research with older students, four distinct profiles of student engagement were found for males and females: Engaged, Cognitively/Affectively Disengaged, Behaviorally Disengaged, Disaffected. An additional class characterized by high absences was found for males. Demographic characteristics were associated with cluster attributes for males (Free or Reduced Lunch, special education, English Learner, and race-ethnicity) and female (El status). Cluster affiliation was significantly associated with seventh grade Math and Language Arts grades for both males and females and absences for males. Implications and future directions for research are discussed. The findings from the current study indicate there are discernible classes of student engagement and disengagement that can be identified as early as the third grade. These results may aid in the early identification of those at risk for dropping out of school and more effectively link students to targeted early interventions.

Americans with more education vote at higher rates. Some studies have found evidence of a causal relationship, while others have not. The available data also tell us little about why and how education increases voting. The authors looked the educational trajectories and adult voting records of students who attend charter schools in Boston. The authors looked at the voting records of charter and non-charter students and find substantial differences. Specifically, 41 percent of all charter-school students vote in their first presidential election compared to 35 percent of students who did not attend a charter, an increase of 17 percent. When the authors looked more closely at the data, the charter effect is a female phenomenon. Female high-school students are 11 percentage points more likely to vote in adulthood if they attended a charter school, while the impact for males is nil. These findings are in line with widening gender gaps in educational attainment and political participation. The authors used state education and voting records to compare academic outcomes and election turnout for students who are and are not offered a charter seat and adjust our estimates based on who actually attends a charter school. The authors then investigated whether these educational gains extend beyond the classroom to civic participation. They found no impact on voter registration -- about 78 percent of students in both groups are registered to vote by age 21, with about 45 percent of students registered by their 19th birthday. However, the authors did find differences in voter turnout. Charter school students are more likely to vote than non-charter students, with the biggest difference in the first presidential election in which they are eligible to vote.

Diagnostic uncertainty is prevalent throughout medicine and significantly impacts patient care, especially when it goes unrecognized. However, we lack a reliable clinical means of identifying uncertainty. This study evaluates the narrative discourse within clinical notes in the Electronic Health Record as a means of identifying diagnostic uncertainty. Recognizing that discourse producers use language "semi-automatically" (Partington et al. 2013), we hypothesized that clinicians include distinct indications of uncertainty in their written assessments, which could be elucidated by linguistic analysis. Using a cohort of patients prospectively identified as having an uncertain diagnosis (UD), we conducted a detailed corpus-assisted discourse analysis. The analysis revealed a set of linguistic indicators constitutive of diagnostic uncertainty including terms of modality, register-specific terms, and linguistically identifiable clinical behaviours. This dictionary of UD indicators was thoroughly tested, and its performance was compared with a matched-control dataset. Based on the findings, we built a machine learning classification algorithm with the ability to predict UD patient cohorts with 87.0% accuracy, effectively demonstrating the feasibility of using clinical discourse to classify patients and directly impact the clinical environment.

Introduction: Over the last decade, ADAR1p150 has been linked by our research team and others to malignant progenitor reprogramming and therapeutic resistance in a broad array of malignancies. However, ADAR1p150's role in accelerated hematopoietic stem and progenitor cell (HSPC) aging in response to inflammatory cytokines had not been clearly elucidated. Here, we investigate ADAR1 splice isoform switching and the ADAR1p150 inhibitory effects of Rebecsinib on human HSPC function in normal humanized aged normal bone marrow (aNBM) HSPC mouse models. Methods: Whole transcriptome RNA sequencing (RNA-seq) was utilized with splice isoform and editome analysis to detect ADAR1 splice isoform switching and adenosine to inosine RNA editing. Rebecsinib (17S-FD-895), a pre-IND drug candidate, has shown promising potential as an inhibitor of ADAR1p150-mediated RNA editing ( Crews, Ma...Jamieson. Cell Stem Cell 2023), which is an important therapeutic target in patients with myelofibrosis or acute myeloid leukemia that overexpress ADAR1p150 compared with ADAR1p110. Human CD34 + cells, isolated from aged normal bone marrow (aNBM) from patients undergoing elective hip replacement surgery, were transduced with a lentiviral ADAR1-nano-luciferase reporter and transplanted into NSG-SGM3 adult mice that secrete human SCF, IL-3, and GM-CSF cytokines that support normal hematopoiesis. After engraftment confirmation peripheral blood human CD45 flow cytometric assessment and IVIS 200 system imaging of ADAR1-nano-luc-GFP reporter expressing HSPC engraftment, the mice were randomly divided into vehicle-treated and Rebecsinib-treated groups (15mg/kg, twice a week for two weeks). Peripheral blood, bone marrow, and spleen were collected upon treatment completion for analysis. Results: By HSPC RNA-seq, we detected an imbalance between ADAR1p150 and ADAR1p110 expression together with increased RNA editing and splicing alterations using whole transcriptome RNA sequencing (RNA-seq) of aged compared with young bone marrow hematopoietic stem and progenitor cells (HSPCs). However, the functional relevance of ADAR1 splice isoform switching had not been evaluated in human-aged normal bone marrow HSPC xenograft (PDX) mouse models nor had this cytokine-induced HSPC aging been reversed. Flow cytometric analysis and immunohistochemistry staining revealed that Rebecsinib treatment at a dose of 10mg/kg, twice a week for two weeks, effectively spared normal human immune cells (CD3+, CD14+, and CD19+ cells). Remarkably, Rebecsinib treatment not only preserved Hematopoietic Stem (CD34+CD38-) cells and Progenitor (CD34+CD38+) cells in peripheral blood, bone marrow, and spleen but also promoted their expansion. These findings demonstrate the potential of Rebecsinib to enhance the retention of HSPC populations in the bone marrow niche. Conclusions: Our pre-clinical experiments utilizing RNA-seq, a novel ADAR1-nano-luciferase-GFP reporter, and aNBM PDX mouse models provide compelling evidence supporting the potential of Rebecsinib to restore the balance of ADAR1p150:p110 ratios and engraftment in humanized aNBM HSPC mouse models. These findings highlight Rebecsinib as a promising therapeutic candidate for targeting leukemia and myelofibrosis while preserving essential HSPC populations.

BackgroundRight ventricular mass indexed to body surface area (RVMI) decreases and left ventricular mass index (LVMI) increases rapidly and substantially during early infancy. The relationship between these sizeable mass transformations and simultaneous electrocardiographic changes have not been previously delineated.MethodsNormal term infants (#45 initially enrolled) were prospectively evaluated at 2 days and at 2-week, 2-month, and 4-month clinic visits. Ventricular masses were estimated with 2D echocardiographic methods. QRS voltages were measured in leads V1, V6, I and aVF.ResultsMean QRS axis shifted from 135 (95%CI 124, 146) to 65 degrees (95%CI 49, 81) and correlated with both RVMI decrease and LVMI increase (R = 0.46⁎ vs. 0.25†, respectively. *p

Protein-reactive natural products such as the fungal metabolite cerulenin are recognized for their value as therapeutic candidates, due to their ability to selectively react with catalytic residues within a protein active site or a complex of protein domains. Here, we explore the development of fatty-acid and polyketide-synthase probes by synthetically modulating cerulenin's functional moieties. Using a mechanism-based approach, we reveal unique reactivity within cerulenin and adapt it for fluorescent labeling and crosslinking of fatty-acid and iterative type-I polyketide synthases. We also describe two new classes of silylcyanohydrin and silylhemiaminal masked crosslinking probes that serve as new tools for activity and structure studies of these biosynthetic pathways.

Carrier-protein-dependent metabolic pathways biosynthesize fatty acids, polyketides, and non-ribosomal peptides, producing metabolites with important pharmaceutical, environmental, and industrial properties. Recent findings demonstrate that these pathways rely on selective communication mechanisms involving protein-protein interactions (PPIs) that guide enzyme reactivity and timing. While rational design of these PPIs could enable pathway design and modification, this goal remains a challenge due to the complex nature of protein interfaces. Computational methods offer an encouraging avenue, though many score functions fail to predict experimental observables, leading to low success rates. Here, we improve upon the Rosetta score function, leveraging experimental data through iterative rounds of computational prediction and mutagenesis, to design a hybrid fatty acid-non-ribosomal peptide initiation pathway. By increasing the weight of the electrostatic score term, the computational protocol proved to be more predictive, requiring fewer rounds of iteration to identify mutants with high in vitro activity. This allowed efficient design of new PPIs between a non-ribosomal peptide synthetase adenylation domain, PltF, and a fatty acid synthase acyl carrier protein, AcpP, as validated by activity and structural studies. This method provides a promising platform for customized pathway design, establishing a standard for carrier-protein-dependent pathway engineering through PPI optimization.

Alzheimer's disease (AD) is a neurodegenerative disease with heterogenous pathophysiological changes that develop years before the onset of clinical symptoms. These preclinical changes have generated considerable interest in identifying markers for the pathophysiological mechanisms linked to AD and AD-related disorders (ADRD). On the basis of our prior work integrating cerebrospinal fluid (CSF) and brain proteome networks, we developed a reliable and high-throughput mass spectrometry-selected reaction monitoring assay that targets 48 key proteins altered in CSF. To test the diagnostic utility of these proteins and compare them with existing AD biomarkers, CSF collected at baseline visits was assayed from 706 participants recruited from the Alzheimer's Disease Neuroimaging Initiative. We found that the targeted CSF panel of 48 proteins (CSF 48 panel) performed at least as well as existing AD CSF biomarkers (Aβ42, tTau, and pTau181) for predicting clinical diagnosis, FDG PET, hippocampal volume, and measures of cognitive and dementia severity. In addition, for each of those outcomes, the CSF 48 panel plus the existing AD CSF biomarkers significantly improved diagnostic performance. Furthermore, the CSF 48 panel plus existing AD CSF biomarkers significantly improved predictions for changes in FDG PET, hippocampal volume, and measures of cognitive decline and dementia severity compared with either measure alone. A potential reason for these improvements is that the CSF 48 panel reflects a range of altered biology observed in AD/ADRD. In conclusion, we show that the CSF 48 panel complements existing AD CSF biomarkers to improve diagnosis and predict future cognitive decline and dementia severity.

Summary: Background: The selective serotonin reuptake inhibitors (SSRIs) fluoxetine and fluvoxamine were repurposed for the treatment of early COVID-19 based on their antiviral activity in vitro, and observational and clinical trial evidence suggesting they prevented progression to severe disease. However, these SSRIs have not been recommended in therapeutic guidelines and their antiviral activity in vivo has not been characterised. Methods: PLATCOV is an open-label, multicentre, phase 2, randomised, controlled, adaptive pharmacometric platform trial running in Thailand, Brazil, Pakistan, and Laos. We recruited low-risk adult outpatients aged 18–50 with early symptomatic COVID-19 (symptoms 2 days follow-up).The viral clearance rate was estimated under a Bayesian hierarchical linear model fitted to the log10 viral densities measured in standardised duplicate oropharyngeal swab eluates taken daily over one week (18 measurements per patient). Secondary endpoints were all-cause hospital admission at 28 days, and time to resolution of fever and symptoms. This ongoing trial is registered at ClinicalTrials.gov (NCT05041907). Findings: 271 patients were concurrently randomised to either fluoxetine (n = 120) or no study drug (n = 151). All patients had received at least one COVID-19 vaccine dose and 67% were female (182/271). In the primary analysis, viral clearance rates following fluoxetine were compatible with a small or no increase relative to the no study drug arm (15% increase; 95% credible interval (CrI): −2 to 34%). There were no deaths or hospitalisations in either arm. There were no significant differences in times to symptom resolution or fever clearance between the fluoxetine and the no study drug arms (although only a quarter of patients were febrile at baseline). Fluoxetine was well tolerated, there were no serious adverse events and only one grade 3 adverse event in the intervention arm. Interpretation: Overall, the evidence from this study is compatible with fluoxetine having a weak in vivo antiviral activity against SARS-CoV-2, although the primary endpoint is also compatible with no effect. This level of antiviral efficacy is substantially less than with other currently available antiviral drugs. Funding: Wellcome Trust Grant ref: 223195/Z/21/Z through the COVID-19 Therapeutics Accelerator.

ABSTRACT Clinical research studies are becoming increasingly complex resulting in compounded work burden and longer study cycle times, each fueling runaway costs. The impact of protocol complexity often results in inadequate recruitment and insufficient sample sizes, which challenges validity and generalizability. Understanding the need to provide an alternative model to engage researchers and sponsors and bringing clinical research opportunities to the broader community, clinical research networks (CRN) have been proposed and initiated in the United States and other parts of the world. We report on the Johns Hopkins Clinical Research Network (JHCRN), established in 2009 as a multi‐disease research collaboration between the academic medical centers and community hospitals/health systems. We have discussed vision, governance, infrastructure, participating hospitals' characteristics, and lessons learned in creating this partnership. Designed to leverage organized patient communities, community‐based investigators, and academic researchers, the JHCRN provides expedited research across nine health systems in the mid‐Atlantic region. With one IRB of record, a centralized contracting office, and a pool of dedicated network coordinators, it facilitates research partnerships to expand research collaborations among the differing sizes and types of hospitals/health systems in a region. As of August 2024, total 81 studies‐clinical trials, cohort studies, and comparative effectiveness research have been conducted, with funding from the NIH, private foundations, and industry. The JHCRN experience has enhanced understanding of the complexity of participating sites and associated ambulatory practices. In conclusion, the CRN, as an academic–community partnership, provides an infrastructure for multiple disease studies, shared risk, and increased investigator and volunteer engagement.

The association between late replication timing and low transcription rates in eukaryotic heterochromatin is well known, yet the specific mechanisms underlying this link remain uncertain. In Saccharomyces cerevisiae, the histone deacetylase Sir2 is required for both transcriptional silencing and late replication at the repetitive ribosomal DNA (rDNA) arrays. We have previously reported that in the absence of SIR2, a de-repressed RNA PolII repositions MCM replicative helicases from their loading site at the ribosomal origin, where they abut well-positioned, high-occupancy nucleosomes, to an adjacent region with lower nucleosome occupancy. By developing a method that can distinguish activation of closely spaced MCM complexes, here we show that the displaced MCMs at rDNA origins have increased firing propensity compared to the nondisplaced MCMs. Furthermore, we found that both activation of the repositioned MCMs and low occupancy of the adjacent nucleosomes critically depend on the chromatin remodeling activity of FUN30. Our study elucidates the mechanism by which Sir2 delays replication timing, and it demonstrates, for the first time, that activation of a specific replication origin in vivo relies on the nucleosome context shaped by a single chromatin remodeler.

Background Obsessive-compulsive disorder (OCD) is associated with an increased risk of morbidity and mortality due to cardiometabolic disorders. Whether this association is driven by familial factors is unknown. This population-based family study explored the familial co-aggregation of OCD and cardiometabolic disorders.Methods We identified 6 049 717 individuals born in Sweden between 1950 and 2008, including 50 212 individuals with OCD, and followed them up to 2020. These individuals were linked to their mothers, fathers, full siblings, maternal and paternal half siblings, aunts, uncles and cousins. We estimated the risk of cardiovascular diseases (CVD) and metabolic disorders (including obesity, type 2 diabetes and hyperlipidaemia), comparing the relatives of probands with and without OCD. Cox proportional hazards regression models, incorporating time-varying exposures, estimated HRs.Results OCD was associated with an increased risk of CVD (HR 1.47; 95% CI 1.43 to 1.51), obesity (HR 1.69; 95% CI 1.63 to 1.74), type 2 diabetes (HR 2.01; 95% CI 1.90 to 2.12) and hyperlipidaemia (HR 1.42; 95% CI 1.33 to 1.52). The relatives of probands with OCD exhibited small increased risks of CVD (HRs from 1.01 to 1.11) and obesity (HRs from 1.03 to 1.20). Slightly increased risks for type 2 diabetes were observed in mothers (HR 1.11; 95% CI 1.07 to 1.15) and full siblings (HR 1.12; 95% CI 1.05 to 1.20), while for hyperlipidaemia it was only observed in mothers (HR 1.06; 95% CI 1.02 to 1.10).Conclusions Our results do not support a major contribution of familial factors to the association between OCD and cardiometabolic disorders, suggesting a more prominent role of unique environmental factors.

Summary: Background: Perivascular spaces (PVS) on brain MRI are surrogates for small parenchymal blood vessels and their perivascular compartment, and may relate to brain health. However, it is unknown whether PVS can predict dementia risk and brain atrophy trajectories in participants without dementia, as longitudinal studies on PVS are scarce and current methods for PVS assessment lack robustness and inter-scanner reproducibility. Methods: We developed a robust algorithm to automatically assess PVS count and size on clinical MRI, and investigated 1) their relationship with dementia risk and brain atrophy in participants without dementia, 2) their longitudinal evolution, and 3) their potential use as a screening tool in simulated clinical trials. We analysed 46,478 clinical measurements of cognitive functioning and 20,845 brain MRI scans from 10,004 participants (71.1 ± 9.7 years-old, 56.6% women) from three publicly available observational studies on ageing and dementia (the Alzheimer’s Disease Neuroimaging Initiative, the National Alzheimer’s Coordinating Centre database, and the Open Access Series of Imaging Studies). Clinical and MRI data collected between 2004 and 2022 were analysed with consistent methods, controlling for confounding factors, and combined using mixed-effects models. Findings: Our fully-automated method for PVS assessment showed excellent inter-scanner reproducibility (intraclass correlation coefficients >0.8). Fewer PVS and larger PVS diameter at baseline predicted higher dementia risk and accelerated brain atrophy. Longitudinal trajectories of PVS markers differed significantly in participants without dementia who converted to dementia compared with non-converters. In simulated placebo-controlled trials for treatments targeting cognitive decline, screening out participants at low risk of dementia based on our PVS markers enhanced the power of the trial independently of Alzheimer’s disease biomarkers. Interpretation: These robust cerebrovascular markers predict dementia risk and brain atrophy and may improve risk-stratification of patients, potentially reducing cost and increasing throughput of clinical trials to combat dementia. Funding: US National Institutes of Health.

Opioids have been the primary method used to manage pain for hundreds of years, however the increasing prescription rate of these drugs in the modern world has led to a public health crisis of overdose related deaths. Naloxone is the current standard treatment for opioid overdose rescue, but it has not been fully investigated for potential off-target toxicity effects. The current methods for pharmaceutical development do not correlate well with pre-clinical animal studies compared to clinical results, creating a need for improved methods for therapeutic evaluation. Microphysiological systems (MPS) are a rapidly growing field, and the FDA has accepted this area of research to address this concern, offering a promising alternative to traditional animal models. This study establishes a novel multi-organ MPS model of acute opioid overdose and rescue to investigate the efficacy and off-target toxicity of naloxone in combination with opioids. By integrating primary human and human induced pluripotent stem cell (hiPSC)-derived cells, including preBötzinger complex neurons, liver, cardiac, and skeletal muscle components, this study establishes a novel functional multi-organ MPS model of acute opioid overdose and rescue to investigate the efficacy and off-target toxicity of naloxone in combination with opioids, with clinically relevant functional readouts of organ function. The system was able to successfully exhibit opioid overdose using methadone, as well as rescue using naloxone evidenced by the neuronal component activity. In addition to efficacy, the multi-organ platform was able to characterize potential off-target toxicity effects of naloxone, specifically in the cardiac component.

IntroductionVegetation fires lead to the formation of charred materials, often referred to as pyrogenic carbon (PyC), which are recalcitrant and have a high carbon densitymeaning they have the potential to act as a long-term carbon store. In the United Kingdom, peatlands are periodically subject to fire, both management burns and wildfires, which generate PyC. However, in the United Kingdom context, the characterisation of physical and chemical properties of PyC is limited.MethodsIn this study, samples of peatland vegetation (Calluna vulgaris, Polytrichum juniperinum, Vaccinium myrtillus and Eriophorum vaginatum) were burnt in laboratory conditions across typical ranges of characteristics from United Kingdom peatland vegetation fires (250°C–800°C and 2–10 min burn duration). Four broad severity groupings were established (low, moderate, high, very high) corresponding to 60, 70, 80% and 90% mass loss respectively. The PyC samples were then analysed using Brunauer-Emmett-Teller (BET) surface area analysis, CHNO elemental analysis, and Fouriertransform infrared spectroscopy (FTIR) to gain a greater understanding of their physiochemical characteristics.ResultsWhile there was a good degree of similarity between samples within each severity group, there were significant differences between severity groups. Low to high severity samples had relatively low surface areas compared to the very high severity samples, which exhibited the greatest surface areas and a high degree of variability. O/C and H/C ratios decreased with increasing severity. FTIR showed that distinct spectra were produced between severity groups, reflecting increased sample aromaticity with burn severity.DiscussionThe findings of this study suggest that burn severity is a good predictor of PyC physiochemical characteristics.