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Abstract Volcano monitoring is constrained by the distribution of sensors that record activity. Here, we explore the role of crowdsourcing to broaden acoustic monitoring records by surveying people across Aotearoa New Zealand about the sounds they heard following the 2022 climactic eruption of Hunga volcano in Tonga. We compare the 1930 survey responses to geophysical records of the pressure waves and find that they align well, both recording ~5-7 audible signals of varying amplitude with a peak of 60-80 decibels, arriving in two 30-minute phases ~3 hours post-eruption, travelling North-to-South. The crowdsourced observations fill instrumental gaps regarding the wave’s audible frequencies and contribute insights into interactions between the far-field acoustic wave and the social and built environment. Descriptions of short-lived impacts reveal that pressure waves are capable of substantial disturbances thousands of kilometers from the vent. We demonstrate that crowdsourcing can support traditional monitoring as a reliable low-cost method to capture perishable data.

Abstract As the global prevalence of chronic liver disease continues to rise, the need to determine which patients will develop end-stage liver disease and require liver transplantation is increasingly important. However, current prognostic models perform sub-optimally. We aim to determine microRNA profiles associated with clinical decompensation and mortality/transplantation within 1 year. We examined microRNA expression profiles in plasma samples from patients across the spectrum of cirrhosis (n = 154), acute liver failure (ALF) (n = 22), sepsis (n = 20) and healthy controls (HC) (n = 20). We demonstrated that a microRNA-based model (miR-24 and -27a) associated with systemic inflammation differentiated decompensated cirrhosis states from compensated cirrhosis and HC (AUC 0.77 (95% CI 0.69–0.85)). 6 patients within the compensated cirrhosis group decompensated the subsequent year and their exclusion improved model performance (AUC 0.81 (95% CI 0.71–0.89)). miR-191 (associated with liver injury) predicted risk of mortality across the cohort when acutely decompensated and acute-on-chronic-liver failure patients were included. When they were excluded miR-24 (associated with systemic inflammation) predicted risk of mortality. Our findings demonstrate that microRNA associated with systemic inflammation and liver injury predict adverse outcomes in cirrhosis. miR-24 and -191 require further investigation as prognostic biomarkers and therapeutic targets for patients with liver disease.

Background Muscarinic receptor agonism is a promising mechanism of action for treating psychosis, not present in most D 2R-blocking antipsychotics. Xanomeline, an M1/M4-preferring agonist, has shown efficacy in late-stage clinical trials, with more compounds being investigated. Therefore, we aim to synthesize evidence on the preclinical efficacy of muscarinic receptor agonists in animal models of psychosis to provide unique insights and evidence-based information to guide drug development. Methods We plan a systematic review and meta-analysis of in vivo animal studies comparing muscarinic receptor agonists or positive allosteric modulators with control conditions and existing D2R-blocking antipsychotics in animals subjected to any method that induces behavioural changes of relevance for psychosis. We will identify eligible studies by searching multiple electronic databases. At least two independent reviewers will conduct the study selection and data extraction using prespecified forms and assess the risk of bias with the SYRCLE’s tool. Our primary outcomes include locomotor activity and prepulse inhibition measured with standardized mean differences. We will examine other behavioural readouts of relevance for psychosis as secondary outcomes, such as social interaction and cognitive function. We will synthesize the data using multi-level meta-analysis with a predefined random-effects structure, considering the non-independence of the data. In meta-regressions we will explore potential sources of heterogeneity from a predefined list of characteristics of the animal population, model, and intervention. We will assess the confidence in the evidence considering a self-developed instrument thatconsiders the internal and external validity of the evidence. Protocol registration PROSPERO-ID: CRD42024520914

Adeno-associated viral vectors (AAVs) are a leading delivery system for gene therapy in animal models and humans. With several Food and Drug Administration-approved AAV gene therapies on the market, issues related to vector manufacturing have become increasingly important. In this study, we focused on potentially toxic DNA contaminants that can arise from AAV proviral plasmids, the raw materials required for manufacturing recombinant AAV in eukaryotic cells. Typical AAV proviral plasmids are circular DNAs containing a therapeutic gene cassette flanked by natural AAV inverted terminal repeat (ITR) sequences, and a plasmid backbone carrying prokaryotic sequences required for plasmid replication and selection in bacteria. While the majority of AAV particles package the intended therapeutic payload, some capsids instead package the bacterial sequences located on the proviral plasmid backbone. Since ITR sequences also have promoter activity, potentially toxic bacterial open reading frames can be produced in vivo, thereby representing a safety risk. In this study, we describe a new AAV proviral plasmid for vector manufacturing that (1) significantly decreases cross-packaged bacterial sequences, (2) increases correctly packaged AAV payloads, and (3) blunts ITR-driven transcription of cross-packaged material to avoid expressing potentially toxic bacterial sequences. This system may help improve the safety of AAV vector products.

IntroductionAvailable evidence is mixed concerning associations between smoking status and COVID-19 clinical outcomes. Effects of nicotine replacement therapy (NRT) and vaccination status on COVID-19 outcomes in smokers are unknown.MethodsElectronic health record data from 104 590 COVID-19 patients hospitalized February 1, 2020 to September 30, 2021 in 21 U.S. health systems were analyzed to assess associations of smoking status, in-hospital NRT prescription, and vaccination status with in-hospital death and ICU admission.ResultsCurrent (n = 7764) and never smokers (n = 57 454) did not differ on outcomes after adjustment for age, sex, race, ethnicity, insurance, body mass index, and comorbidities. Former (vs never) smokers (n = 33 101) had higher adjusted odds of death (aOR, 1.11; 95% CI, 1.06-1.17) and ICU admission (aOR, 1.07; 95% CI, 1.04-1.11). Among current smokers, NRT prescription was associated with reduced mortality (aOR, 0.64; 95% CI, 0.50-0.82). Vaccination effects were significantly moderated by smoking status; vaccination was more strongly associated with reduced mortality among current (aOR, 0.29; 95% CI, 0.16-0.66) and former smokers (aOR, 0.47; 95% CI, 0.39-0.57) than for never smokers (aOR, 0.67; 95% CI, 0.57, 0.79). Vaccination was associated with reduced ICU admission more strongly among former (aOR, 0.74; 95% CI, 0.66-0.83) than never smokers (aOR, 0.87; 95% CI, 0.79-0.97).ConclusionsFormer but not current smokers hospitalized with COVID-19 are at higher risk for severe outcomes. SARS-CoV-2 vaccination is associated with better hospital outcomes in COVID-19 patients, especially current and former smokers. NRT during COVID-19 hospitalization may reduce mortality for current smokers.ImplicationsPrior findings regarding associations between smoking and severe COVID-19 disease outcomes have been inconsistent. This large cohort study suggests potential beneficial effects of nicotine replacement therapy on COVID-19 outcomes in current smokers and outsized benefits of SARS-CoV-2 vaccination in current and former smokers. Such findings may influence clinical practice and prevention efforts and motivate additional research that explores mechanisms for these effects.

Abstract Impairment of autophagy leads to an accumulation of misfolded proteins and damaged organelles and has been implicated in plethora of human diseases. Loss of autophagy in actively respiring cells has also been shown to trigger metabolic collapse mediated by the depletion of nicotinamide adenine dinucleotide (NAD) pools, resulting in cell death. Here we found that the deficit in the autophagy-NAD axis underpins the loss of viability in cell models of a neurodegenerative lysosomal storage disorder, Niemann-Pick type C1 (NPC1) disease. Defective autophagic flux in NPC1 cells resulted in mitochondrial dysfunction due to impairment of mitophagy, leading to the depletion of both the reduced and oxidised forms of NAD as identified via metabolic profiling. Consequently, exhaustion of the NAD pools triggered mitochondrial depolarisation and apoptotic cell death. Our chemical screening identified two FDA-approved drugs, celecoxib and memantine, as autophagy activators which effectively restored autophagic flux, NAD levels, and cell viability of NPC1 cells. Of biomedical relevance, either pharmacological rescue of the autophagy deficiency or NAD precursor supplementation restored NAD levels and improved the viability of NPC1 patient fibroblasts and induced pluripotent stem cell (iPSC)-derived cortical neurons. Together, our findings identify the autophagy-NAD axis as a mechanism of cell death and a target for therapeutic interventions in NPC1 disease, with a potential relevance to other neurodegenerative disorders.

Abstract The polygenic architecture of schizophrenia implicates several molecular pathways involved in synaptic function. However, it is unclear how polygenic risk funnels through these pathways to translate into syndromic illness. Using tensor decomposition, we analyze gene co-expression in the caudate nucleus, hippocampus, and dorsolateral prefrontal cortex of post-mortem brain samples from 358 individuals. We identify a set of genes predominantly expressed in the caudate nucleus and associated with both clinical state and genetic risk for schizophrenia that shows dopaminergic selectivity. A higher polygenic risk score for schizophrenia parsed by this set of genes predicts greater dopamine synthesis in the striatum and greater striatal activation during reward anticipation. These results translate dopamine-linked genetic risk variation into in vivo neurochemical and hemodynamic phenotypes in the striatum that have long been implicated in the pathophysiology of schizophrenia.

Abstract Background Mitochondrial function plays a key role in regulating neurotransmission and may contribute to general intelligence. Mitochondrial complex I (MC-I) is the largest enzyme of the respiratory chain. Recently, it has become possible to measure MC-I distribution in vivo, using a novel positron emission tomography tracer [18F]BCPP-EF, thus, we set out to investigate the association between MC-I distribution and measures of cognitive function in the living healthy brain. Results Analyses were performed in a voxel-wise manner and identified significant associations between [18F]BCPP-EF DVRCS−1 in the precentral gyrus and parietal lobes and WAIS-IV predicted IQ, WAIS-IV arithmetic and WAIS-IV symbol-digit substitution scores (voxel-wise Pearson’s correlation coefficients transformed to Z-scores, thresholded at Z = 2.3 family-wise cluster correction at p

BackgroundThere is mixed evidence about the relations of current versus past cancer with severe COVID-19 outcomes and how they vary by patient and cancer characteristics.MethodsElectronic health record data of 104,590 adult hospitalized patients with COVID-19 were obtained from 21 United States health systems from February 2020 through September 2021. In-hospital mortality and ICU admission were predicted from current and past cancer diagnoses. Moderation by patient characteristics, vaccination status, cancer type, and year of the pandemic was examined.Results6.8% of the patients had current (n = 7,141) and 6.5% had past (n = 6,749) cancer diagnoses. Current cancer predicted both severe outcomes but past cancer did not; adjusted odds ratios (aOR) for mortality were 1.58 [95% confidence interval (CI), 1.46-1.70] and 1.04 (95% CI, 0.96-1.13), respectively. Mortality rates decreased over the pandemic but the incremental risk of current cancer persisted, with the increment being larger among younger vs. older patients. Prior COVID-19 vaccination reduced mortality generally and among those with current cancer (aOR, 0.69; 95% CI, 0.53-0.90).ConclusionsCurrent cancer, especially among younger patients, posed a substantially increased risk for death and ICU admission among patients with COVID-19; prior COVID-19 vaccination mitigated the risk associated with current cancer. Past history of cancer was not associated with higher risks for severe COVID-19 outcomes for most cancer types.ImpactThis study clarifies the characteristics that modify the risk associated with cancer on severe COVID-19 outcomes across the first 20 months of the COVID-19 pandemic. See related commentary by Egan et al., p. 3.

Background Degenerative cervical myelopathy (DCM) is a progressive chronic spinal cord injury estimated to affect 1 in 50 adults. Without standardised guidance, clinical research studies have selected outcomes at their discretion, often underrepresenting the disease and limiting comparability between studies. Utilising a standard minimum data set formed via multi-stakeholder consensus can address these issues. This combines processes to define a core outcome set (COS)-a list of key outcomes-and core data elements (CDEs), a list of key sampling characteristics required to interpret the outcomes. Further 'how' these outcomes should be measured and/or reported is then defined in a core measurement set (CMS). This can include a recommendation of a standardised time point at which outcome data should be reported. This study defines a COS, CDE, and CMS for DCM research. Methods and findings A minimum data set was developed using a series of modified Delphi processes. Phase 1 involved the setup of an international DCM stakeholder group. Phase 2 involved the development of a longlist of outcomes, data elements, and formation into domains. Phase 3 prioritised the outcomes and CDEs using a two-stage Delphi process. Phase 4 determined the final DCM minimal data set using a consensus meeting. Using the COS, Phase 5 finalised definitions of the measurement construct for each outcome. In Phase 6, a systematic review of the literature was performed, to scope and define the psychometric properties of measurement tools. Phase 7 used a modified Delphi process to inform the short-listing of candidate measurement tools. The final measurement set was then formed through a consensus meeting (Phase 8). To support implementation, the data set was then integrated into template clinical research forms (CRFs) for use in future clinical trials (Phase 9). In total, 28 outcomes and 6 domains (Pain, Neurological Function, Life Impact, Radiology, Economic Impact, and Adverse Events) were entered into the final COS. Thirty two outcomes and 4 domains (Individual, Disease, Investigation, and Intervention) were entered into the final CDE. Finally, 4 outcome instruments (mJOA, NDI, SF-36v2, and SAVES2) were identified for the CMS, with a recommendation for trials evaluating outcomes after surgery, to include baseline measurement and at 6 months from surgery. Conclusions The AO Spine RECODE-DCM has produced a minimum data set for use in DCM clinical trials today. These are available at https://myelopathy.org/minimum-dataset/. While it is anticipated the CDE and COS have strong and durable relevance, it is acknowledged that new measurement tools, alongside an increasing transition to study patients not undergoing surgery, may necessitate updates and adaptation, particularly with respect to the CMS., Author(s): Benjamin M. Davies 1,2,*, Xiaoyu Yang 1, Danyal Z. Khan 3,4, Oliver D. Mowforth 1,2, Alvaro Y. Touzet 5, Aria Nouri 1,6, James S. Harrop 7, Bizhan Aarabi 8, [...]

BackgroundDegenerative cervical myelopathy (DCM) is a progressive chronic spinal cord injury estimated to affect 1 in 50 adults. Without standardised guidance, clinical research studies have selected outcomes at their discretion, often underrepresenting the disease and limiting comparability between studies. Utilising a standard minimum data set formed via multi-stakeholder consensus can address these issues. This combines processes to define a core outcome set (COS)-a list of key outcomes-and core data elements (CDEs), a list of key sampling characteristics required to interpret the outcomes. Further "how" these outcomes should be measured and/or reported is then defined in a core measurement set (CMS). This can include a recommendation of a standardised time point at which outcome data should be reported. This study defines a COS, CDE, and CMS for DCM research.Methods and findingsA minimum data set was developed using a series of modified Delphi processes. Phase 1 involved the setup of an international DCM stakeholder group. Phase 2 involved the development of a longlist of outcomes, data elements, and formation into domains. Phase 3 prioritised the outcomes and CDEs using a two-stage Delphi process. Phase 4 determined the final DCM minimal data set using a consensus meeting. Using the COS, Phase 5 finalised definitions of the measurement construct for each outcome. In Phase 6, a systematic review of the literature was performed, to scope and define the psychometric properties of measurement tools. Phase 7 used a modified Delphi process to inform the short-listing of candidate measurement tools. The final measurement set was then formed through a consensus meeting (Phase 8). To support implementation, the data set was then integrated into template clinical research forms (CRFs) for use in future clinical trials (Phase 9). In total, 28 outcomes and 6 domains (Pain, Neurological Function, Life Impact, Radiology, Economic Impact, and Adverse Events) were entered into the final COS. Thirty two outcomes and 4 domains (Individual, Disease, Investigation, and Intervention) were entered into the final CDE. Finally, 4 outcome instruments (mJOA, NDI, SF-36v2, and SAVES2) were identified for the CMS, with a recommendation for trials evaluating outcomes after surgery, to include baseline measurement and at 6 months from surgery.ConclusionsThe AO Spine RECODE-DCM has produced a minimum data set for use in DCM clinical trials today. These are available at https://myelopathy.org/minimum-dataset/. While it is anticipated the CDE and COS have strong and durable relevance, it is acknowledged that new measurement tools, alongside an increasing transition to study patients not undergoing surgery, may necessitate updates and adaptation, particularly with respect to the CMS.

BackgroundDegenerative cervical myelopathy (DCM) is a progressive neurological condition, characterized by spinal cord injury secondary to degenerative changes in the spine. Misdiagnosis in primary care forms part of a complex picture leading to an average diagnostic delay of 2 years. This leads to potentially preventable and permanent disability. A lack of awareness secondary to deficits in postgraduate education may contribute to these delays. ObjectiveThis study aims to assess the awareness of DCM in the setting of general practice. MethodsGeneral practitioners completed a quantitative web-based cross-sectional questionnaire. The 17-item questionnaire captured data regarding demographics, subjective awareness, and objective knowledge. The questionnaire was disseminated via professional networks, including via practice managers and senior practice partners. Incentivization was provided via a bespoke DCM fact sheet for those that completed the survey. ResultsA total of 54 general practitioners representing all 4 UK nations responded to the survey. General practitioners most commonly self-assessed that they had “limited awareness” of DCM (n=24, 51%). General practitioners felt most commonly “moderately able” to recognize a case of DCM (n=21, 46%). In total, 13% (n=6) of respondents reported that they would not be at all able to recognize a patient with DCM. Respondents most commonly reported that they were “moderately confident” in their ability to triage a patient with DCM (n=19, 41%). A quarter of respondents reported no prior introduction to DCM throughout their medical training (n=13, 25%). The mean score for knowledge-based questions was 42.6% (SD 3.96%) with the lowest performance observed in patient demographic and clinical recognition items. ConclusionsGeneral practitioners lack confidence in the recognition and management of DCM. These findings are consistent with the diagnostic delays previously described in the literature at the primary care level. Further work to develop and implement educational interventions to general practitioner practices is a crucial step to improving patient outcomes in DCM.