Differentiation granules, a dynamic regulator of T. brucei development

Adaptation to a change of environment is an essential process for survival, in particular for parasitic organisms exposed to a wide range of hosts. Such adaptations include rapid control of gene expression through the formation of membraneless organelles composed of poly-A RNA and proteins. The African trypanosome Trypanosoma brucei is exquisitely sensitive to well-defined environmental stimuli that trigger cellular adaptations through differentiation events that characterise its complex life cycle. The parasite has been shown to form stress granules in vitro, and it has been proposed that such a stress response could have been repurposed to enable differentiation and facilitate parasite transmission. Therefore, we explored the composition and positional dynamics of membraneless granules formed in response to starvation stress and during differentiation in the mammalian host between the replicative slender and transmission-adapted stumpy forms. We find that T. brucei differentiation does not reflect the default response to environmental stress. Instead, the developmental response of the parasites involves a specific and programmed hierarchy of membraneless granule assembly, with distinct components and regulation by protein kinases such as TbDYRK, that are required for the parasite to successfully progress through its life cycle development and prepare for transmission.

Single-step phase identification and phase locking for coherent beam combination using deep learning

Coherent beam combination offers a solution to the challenges associated with the power handling capacity of individual fibres, however, the combined intensity profile strongly depends on the relative phase of each fibre. Optimal combination necessitates precise control over the phase of each fibre channel, however, determining the required phase compensations is challenging because phase information is typically not available. Additionally, the presence of continuously varying phase noise in fibre laser systems means that a single-step and high-speed correction process is required. In this work, we use a spatial light modulator to demonstrate coherent combination in a seven-beam system. Deep learning is used to identify the relative phase offsets for each beam directly from the combined intensity pattern, allowing real-time correction. Furthermore, we demonstrate that the deep learning agent can calculate the phase corrections needed to achieve user-specified target intensity profiles thus simultaneously achieving both beam combination and beam shaping.

Alzheimer's disease marker phospho-tau181 is not elevated in the first year after moderate-to-severe TBI

BACKGROUND

Traumatic brain injury (TBI) is associated with the tauopathies Alzheimer's disease and chronic traumatic encephalopathy. Advanced immunoassays show significant elevations in plasma total tau (t-tau) early post-TBI, but concentrations subsequently normalise rapidly. Tau phosphorylated at serine-181 (p-tau181) is a well-validated Alzheimer's disease marker that could potentially seed progressive neurodegeneration. We tested whether post-traumatic p-tau181 concentrations are elevated and relate to progressive brain atrophy.

METHODS

Plasma p-tau181 and other post-traumatic biomarkers, including total-tau (t-tau), neurofilament light (NfL), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) and glial fibrillary acidic protein (GFAP), were assessed after moderate-to-severe TBI in the BIO-AX-TBI cohort (first sample mean 2.7 days, second sample within 10 days, then 6 weeks, 6 months and 12 months, n=42). Brain atrophy rates were assessed in aligned serial MRI (n=40). Concentrations were compared patients with and without Alzheimer's disease, with healthy controls.

RESULTS

Plasma p-tau181 concentrations were significantly raised in patients with Alzheimer's disease but not after TBI, where concentrations were non-elevated, and remained stable over one year. P-tau181 after TBI was not predictive of brain atrophy rates in either grey or white matter. In contrast, substantial trauma-associated elevations in t-tau, NfL, GFAP and UCH-L1 were seen, with concentrations of NfL and t-tau predictive of brain atrophy rates.

CONCLUSIONS

Plasma p-tau181 is not significantly elevated during the first year after moderate-to-severe TBI and levels do not relate to neuroimaging measures of neurodegeneration.

Association of multimorbidity with mortality after stroke stratified by age, severity, etiology, and prior disability

BACKGROUND

Multimorbidity is common in patients with stroke and is associated with increased medium- to long-term mortality, but its value for clinical decision-making and case-mix adjustment will depend on other factors, such as age, stroke severity, etiological subtype, prior disability, and vascular risk factors.

AIMS

In the absence of previous studies, we related multimorbidity to long-term post-stroke mortality with stratification by these factors.

METHODS

In patients ascertained in a population-based stroke incidence study (Oxford Vascular Study; 2002-2017), we related pre-stroke multimorbidity (weighted/unweighted Charlson comorbidity index (CCI)) to all-cause/vascular/non-vascular mortality (1/5/10 years) using regression models adjusted/stratified by age, sex, predicted early outcome (THRIVE score), stroke severity (NIH stroke scale (NIHSS)), etiology (Trial of Org 10172 in Acute Stroke Treatment (TOAST)), premorbid disability (modified Rankin Scale (mRS)), and non-CCI risk factors (hypertension, hyperlipidemia, atrial fibrillation, smoking, deprivation, anxiety/depression).

RESULTS

Among 2454 stroke patients (M/SD age: 74.1/13.9 years; 48.9% male; M/SD NIHSS: 5.7/7.0), 1375/56.0% had ⩾ 1 CCI comorbidity and 685/27.9% had ⩾ 2. After age/sex adjustment, multimorbidity (unweighted CCI ⩾ 2 vs 0) predicted (all ps < 0.001) mortality at 1 year (aHR = 1.57, 95% CI = 1.38-1.78), 5 years (aHR = 1.73, 95% CI = 1.53-1.96), and 10 years (aHR = 1.79, 95% CI = 1.58-2.03). Although multimorbidity was independently associated with premorbid disability (mRS > 2: aOR = 2.76, 2.13-3.60) and non-CCI risk factors (hypertension: 1.56, 1.25-1.95; hyperlipidemia: 2.58, 2.03-3.28; atrial fibrillation: 2.31; 1.78-2.98; smoking: 1.37, 1.01-1.86), it predicted death after adjustment for all measured confounders (10-year-aHR = 1.56, 1.37-1.78, p < 0.001), driven mainly by non-vascular death (aHR = 1.89, 1.55-2.29). Predictive value for 10-year all-cause death was greatest in patients with lower expected early mortality: lower THRIVE score (pint < 0.001), age < 75 years (aHR = 2.27, 1.71-3.00), NIHSS < 5 (1.84, 1.53-2.21), and lacunar stroke (3.56, 2.14-5.91). Results were similar using the weighted CCI.

CONCLUSION

Pre-stroke multimorbidity is highly prevalent and is an independent predictor of death after stroke, supporting its inclusion in case-mix adjustment models and in informing decision-making by patients, families, and carers. Prediction in younger patients and after minor stroke, particularly for non-vascular death, suggests potential clinical utility in targeting interventions that require survival for 5-10 years to achieve a favorable risk/benefit ratio.

DATA ACCESS STATEMENT

Data requests will be considered by the Oxford Vascular Study (OXVASC) Study Director (P.M.R.-peter.rothwell@ndcn.ox.ac.uk).

Terahertz microscopy using laser feedback interferometry based on a generalised phase-stepping algorithm

In this paper we report an improved method of coherent sensing through the use of a generalized phase-stepping algorithm to extract magnitude and phase information from interferometric fringes acquired by laser feedback interferometry (LFI). Our approach allows for significantly reduced optical sampling and acquisition times whilst also avoiding the need for fitting to complex models of lasers under optical feedback in post-processing. We investigate theoretically the applicability of this method under different levels of optical feedback, different laser parameters, and for different sampling conditions. We furthermore validate its use experimentally for LFI-based sensing using a terahertz (THz)-frequency laser in both far-field and near-field sensing configurations. Finally we demonstrate our approach for two-dimensional nanoscale imaging of the out-of-plane field supported by individual micro-resonators at THz frequencies. Our results show that fully coherent sensing can be achieved reliably with as little as 4 sampling points per imaging pixel, opening up opportunities for fast coherent sensing not only at THz frequencies but across the visible and infra-red spectrum.

Real-time visualization of the laser-plasma wakefield dynamics

The exploration of new acceleration mechanisms for compactly delivering high-energy particle beams has gained great attention in recent years. One alternative that has attracted particular interest is the plasma-based wakefield accelerator, which is capable of sustaining accelerating fields that are more than three orders of magnitude larger than those of conventional radio-frequency accelerators. In this device, acceleration is generated by plasma waves that propagate at nearly light speed, driven by intense lasers or charged particle beams. Here, we report on the direct visualization of the entire plasma wake dynamics by probing it with a femtosecond relativistic electron bunch. This includes the excitation of the laser wakefield, the increase of its amplitude, the electron injection, and the transition to the beam-driven plasma wakefield. These experimental observations provide first-hand valuable insights into the complex physics of laser beam-plasma interaction and demonstrate a powerful tool that can largely advance the development of plasma accelerators for real-time operation.

Enhanced Transmission at the Zeroth-Order Mode of a Terahertz Fabry-Perot Cavity

A planar Fabry-Perot cavity with intermirror spacing of d ≪ λ is explored for its "zero-order mode" terahertz transmission. The enhanced transmission observed as d → 0 indicates that such cavities satisfy the resonance conditions across a broad terahertz bandwidth. The experimental signatures from this elusive, "technically challenging" regime are evidenced using time-domain terahertz spectroscopy and are complemented by numerical calculations. The results raise intriguing possibilities for terahertz field modulation and pave new paths for strong coupling of multiple transition frequencies simultaneously.

Post-acute COVID-19 neuropsychiatric symptoms are not associated with ongoing nervous system injury

A proportion of patients infected with severe acute respiratory syndrome coronavirus 2 experience a range of neuropsychiatric symptoms months after infection, including cognitive deficits, depression and anxiety. The mechanisms underpinning such symptoms remain elusive. Recent research has demonstrated that nervous system injury can occur during COVID-19. Whether ongoing neural injury in the months after COVID-19 accounts for the ongoing or emergent neuropsychiatric symptoms is unclear. Within a large prospective cohort study of adult survivors who were hospitalized for severe acute respiratory syndrome coronavirus 2 infection, we analysed plasma markers of nervous system injury and astrocytic activation, measured 6 months post-infection: neurofilament light, glial fibrillary acidic protein and total tau protein. We assessed whether these markers were associated with the severity of the acute COVID-19 illness and with post-acute neuropsychiatric symptoms (as measured by the Patient Health Questionnaire for depression, the General Anxiety Disorder assessment for anxiety, the Montreal Cognitive Assessment for objective cognitive deficit and the cognitive items of the Patient Symptom Questionnaire for subjective cognitive deficit) at 6 months and 1 year post-hospital discharge from COVID-19. No robust associations were found between markers of nervous system injury and severity of acute COVID-19 (except for an association of small effect size between duration of admission and neurofilament light) nor with post-acute neuropsychiatric symptoms. These results suggest that ongoing neuropsychiatric symptoms are not due to ongoing neural injury.

Pupil responses to colorfulness are selectively reduced in healthy older adults

The alignment between visual pathway signaling and pupil dynamics offers a promising non-invasive method to further illuminate the mechanisms of human color perception. However, only limited research has been done in this area and the effects of healthy aging on pupil responses to the different color components have not been studied yet. Here we aim to address this by modelling the effects of color lightness and chroma (colorfulness) on pupil responses in young and older adults, in a closely controlled passive viewing experiment with 26 broad-spectrum digital color fields. We show that pupil responses to color lightness and chroma are independent from each other in both young and older adults. Pupil responses to color lightness levels are unaffected by healthy aging, when correcting for smaller baseline pupil sizes in older adults. Older adults exhibit weaker pupil responses to chroma increases, predominantly along the Green-Magenta axis, while relatively sparing the Blue-Yellow axis. Our findings complement behavioral studies in providing physiological evidence that colors fade with age, with implications for color-based applications and interventions both in healthy aging and later-life neurodegenerative disorders.

A mixed-method approach to determining contact matrices in the Cox's Bazar refugee settlement

Contact matrices are an important ingredient in age-structured epidemic models to inform the simulated spread of the disease between subgroups of the population. These matrices are generally derived using resource-intensive diary-based surveys and few exist in the Global South or tailored to vulnerable populations. In particular, no contact matrices exist for refugee settlements-locations under-served by epidemic models in general. In this paper, we present a novel, mixed-method approach for deriving contact matrices in populations, which combines a lightweight, rapidly deployable survey with an agent-based model of the population informed by census and behavioural data. We use this method to derive the first set of contact matrices for the Cox's Bazar refugee settlement in Bangladesh. To validate our approach, we apply it to the UK population and compare our derived matrices with well-known contact matrices collected using traditional methods. Our findings demonstrate that our mixed-method approach successfully addresses some of the challenges faced by traditional and agent-based approaches to deriving contact matrices. It also shows potential for implementation in resource-constrained environments. This work therefore contributes to a broader aim of developing new methods and mechanisms of data collection for modelling disease spread in refugee and internally displaced person (IDP) settlements and better serving these vulnerable communities.

Identifying the severity of diabetic retinopathy by visual function measures using both traditional statistical methods and interpretable machine learning: a cross-sectional study

AIMS/HYPOTHESIS

To determine the extent to which diabetic retinopathy severity stage may be classified using machine learning (ML) and commonly used clinical measures of visual function together with age and sex.

METHODS

We measured the visual function of 1901 eyes from 1032 participants in the Northern Ireland Sensory Ageing Study, deriving 12 variables from nine visual function tests. Missing values were imputed using chained equations. Participants were divided into four groups using clinical measures and grading of ophthalmic images: no diabetes mellitus (no DM), diabetes but no diabetic retinopathy (DM no DR), diabetic retinopathy without diabetic macular oedema (DR no DMO) and diabetic retinopathy with DMO (DR with DMO). Ensemble ML models were fitted to classify group membership for three tasks, distinguishing (A) the DM no DR group from the no DM group; (B) the DR no DMO group from the DM no DR group; and (C) the DR with DMO group from the DR no DMO group. More conventional multiple logistic regression models were also fitted for comparison. An interpretable ML technique was used to rank the contribution of visual function variables to predictions and to disentangle associations between diabetic eye disease and visual function from artefacts of the data collection process.

RESULTS

The performance of the ensemble ML models was good across all three classification tasks, with accuracies of 0.92, 1.00 and 0.84, respectively, for tasks A-C, substantially exceeding the accuracies for logistic regression (0.84, 0.61 and 0.80, respectively). Reading index was highly ranked for tasks A and B, whereas near visual acuity and Moorfields chart acuity were important for task C. Microperimetry variables ranked highly for all three tasks, but this was partly due to a data artefact (a large proportion of missing values).

CONCLUSIONS/INTERPRETATION

Ensemble ML models predicted status of diabetic eye disease with high accuracy using just age, sex and measures of visual function. Interpretable ML methods enabled us to identify profiles of visual function associated with different stages of diabetic eye disease, and to disentangle associations from artefacts of the data collection process. Together, these two techniques have great potential for developing prediction models using untidy real-world clinical data.

BRCA1-BARD1 combines multiple chromatin recognition modules to bridge nascent nucleosomes

Chromatin association of the BRCA1-BARD1 heterodimer is critical to promote homologous recombination repair of DNA double-strand breaks (DSBs) in S/G2. How the BRCA1-BARD1 complex interacts with chromatin that contains both damage induced histone H2A ubiquitin and inhibitory H4K20 methylation is not fully understood. We characterised BRCA1-BARD1 binding and enzymatic activity to an array of mono- and di-nucleosome substrates using biochemical, structural and single molecule imaging approaches. We found that the BRCA1-BARD1 complex preferentially interacts and modifies di-nucleosomes over mono-nucleosomes, allowing integration of H2A Lys-15 ubiquitylation signals with other chromatin modifications and features. Using high speed- atomic force microscopy (HS-AFM) to monitor how the BRCA1-BARD1 complex recognises chromatin in real time, we saw a highly dynamic complex that bridges two nucleosomes and associates with the DNA linker region. Bridging is aided by multivalent cross-nucleosome interactions that enhance BRCA1-BARD1 E3 ubiquitin ligase catalytic activity. Multivalent interactions across nucleosomes explain how BRCA1-BARD1 can recognise chromatin that retains partial di-methylation at H4 Lys-20 (H4K20me2), a parental histone mark that blocks BRCA1-BARD1 interaction with nucleosomes, to promote its enzymatic and DNA repair activities.

In vivo evidence of microstructural hypo-connectivity of brain white matter in 22q11.2 deletion syndrome

22q11.2 deletion syndrome, or 22q11.2DS, is a genetic syndrome associated with high rates of schizophrenia and autism spectrum disorders, in addition to widespread structural and functional abnormalities throughout the brain. Experimental animal models have identified neuronal connectivity deficits, e.g., decreased axonal length and complexity of axonal branching, as a primary mechanism underlying atypical brain development in 22q11.2DS. However, it is still unclear whether deficits in axonal morphology can also be observed in people with 22q11.2DS. Here, we provide an unparalleled in vivo characterization of white matter microstructure in participants with 22q11.2DS (12-15 years) and those undergoing typical development (8-18 years) using a customized magnetic resonance imaging scanner which is sensitive to axonal morphology. A rich array of diffusion MRI metrics are extracted to present microstructural profiles of typical and atypical white matter development, and provide new evidence of connectivity differences in individuals with 22q11.2DS. A recent, large-scale consortium study of 22q11.2DS identified higher diffusion anisotropy and reduced overall diffusion mobility of water as hallmark microstructural alterations of white matter in individuals across a wide age range (6-52 years). We observed similar findings across the white matter tracts included in this study, in addition to identifying deficits in axonal morphology. This, in combination with reduced tract volume measurements, supports the hypothesis that abnormal microstructural connectivity in 22q11.2DS may be mediated by densely packed axons with disproportionately small diameters. Our findings provide insight into the in vivo white matter phenotype of 22q11.2DS, and promote the continued investigation of shared features in neurodevelopmental and psychiatric disorders.

Acute blood biomarker profiles predict cognitive deficits 6 and 12 months after COVID-19 hospitalization

Post-COVID cognitive deficits, including 'brain fog', are clinically complex, with both objective and subjective components. They are common and debilitating, and can affect the ability to work, yet their biological underpinnings remain unknown. In this prospective cohort study of 1,837 adults hospitalized with COVID-19, we identified two distinct biomarker profiles measured during the acute admission, which predict cognitive outcomes 6 and 12 months after COVID-19. A first profile links elevated fibrinogen relative to C-reactive protein with both objective and subjective cognitive deficits. A second profile links elevated D-dimer relative to C-reactive protein with subjective cognitive deficits and occupational impact. This second profile was mediated by fatigue and shortness of breath. Neither profile was significantly mediated by depression or anxiety. Results were robust across secondary analyses. They were replicated, and their specificity to COVID-19 tested, in a large-scale electronic health records dataset. These findings provide insights into the heterogeneous biology of post-COVID cognitive deficits.

Can a nation-wide e-cohort of ADHD and ASD in childhood be established using Welsh routinely available datasets?

OBJECTIVES

We investigated the feasibility and validity of establishing a nationwide e-cohort of individuals with a diagnosis of attention deficit hyperactivity disorder (ADHD) and/or autism spectrum disorder (ASD) for future longitudinal research.

DESIGN

Individuals with a childhood diagnosis of ADHD/ASD as recorded on routinely available healthcare datasets were compared with matched controls and a sample of directly assessed individuals with ADHD.

SETTING

This study used data from the Welsh Secure Anonymised Information Linkage Databank in Wales, UK. Routinely collected data from primary care, emergency department and hospital admissions were linked at person level.

PARTICIPANTS

All individuals in Wales, UK born between 1 January 1991 and 31 December 2000. Individuals with a recorded diagnosis of ADHD and/or ASD by age 18 years were identified using International Classification of Diseases, 10th Revision and National Health Service (NHS) READ codes and matched to 3 controls each and 154 individuals with ADHD recruited from an established research study.

OUTCOME MEASURES

Recorded service use for anxiety and depression, alcohol and drug use and self-harm including emergency department use in young adulthood (age 16-25 years).

RESULTS

7726 individuals had a recorded diagnosis of ADHD (80% male) and 5001 of ASD (79% male); 1.4% and 0.9% of the population, respectively. Cox's regression analyses showed ADHD was associated with increased risks of anxiety/depression (HR: 2.36, 95% CI: 2.20 to 2.53), self-harm (HR: 5.70, 95% CI: 5.07 to 6.40), alcohol (HR: 3.95, 95% CI: 3.42 to 4.56), drug use (HR: 5.88, 95% CI: 5.08 to 6.80) and emergency department service use (HR: 1.36, 95% CI: 1.31 to 1.41). Those with ASD were at increased risk of anxiety/depression (HR: 2.11, 95% CI: 1.91 to 2.34), self-harm (HR: 2.93, 95% CI: 2.45 to 3.50) and drug use (HR: 2.21, 95% CI: 1.66 to 2.95) but not alcohol use. The ADHD e-cohort were similar to the directly assessed cohort.

CONCLUSIONS

Our identification strategy demonstrated the feasibility of establishing a large e-cohort of those with ADHD/ASD with expected patterns of poorer early adult outcomes, demonstrating a valid method of identifying large samples for future longitudinal studies without selective attrition.

Neuroimaging, clinical and life course correlates of normal-appearing white matter integrity in 70-year-olds

We investigate associations between normal-appearing white matter microstructural integrity in cognitively normal ∼70-year-olds and concurrently measured brain health and cognition, demographics, genetics and life course cardiovascular health. Participants born in the same week in March 1946 (British 1946 birth cohort) underwent PET-MRI around age 70. Mean standardized normal-appearing white matter integrity metrics (fractional anisotropy, mean diffusivity, neurite density index and orientation dispersion index) were derived from diffusion MRI. Linear regression was used to test associations between normal-appearing white matter metrics and (i) concurrent measures, including whole brain volume, white matter hyperintensity volume, PET amyloid and cognition; (ii) the influence of demographic and genetic predictors, including sex, childhood cognition, education, socio-economic position and genetic risk for Alzheimer's disease (APOE-ɛ4); (iii) systolic and diastolic blood pressure and cardiovascular health (Framingham Heart Study Cardiovascular Risk Score) across adulthood. Sex interactions were tested. Statistical significance included false discovery rate correction (5%). Three hundred and sixty-two participants met inclusion criteria (mean age 70, 49% female). Higher white matter hyperintensity volume was associated with lower fractional anisotropy [b = -0.09 (95% confidence interval: -0.11, -0.06), P < 0.01], neurite density index [b = -0.17 (-0.22, -0.12), P < 0.01] and higher mean diffusivity [b = 0.14 (-0.10, -0.17), P < 0.01]; amyloid (in men) was associated with lower fractional anisotropy [b = -0.04 (-0.08, -0.01), P = 0.03)] and higher mean diffusivity [b = 0.06 (0.01, 0.11), P = 0.02]. Framingham Heart Study Cardiovascular Risk Score in later-life (age 69) was associated with normal-appearing white matter {lower fractional anisotropy [b = -0.06 (-0.09, -0.02) P < 0.01], neurite density index [b = -0.10 (-0.17, -0.03), P < 0.01] and higher mean diffusivity [b = 0.09 (0.04, 0.14), P < 0.01]}. Significant sex interactions (P < 0.05) emerged for midlife cardiovascular health (age 53) and normal-appearing white matter at 70: marginal effect plots demonstrated, in women only, normal-appearing white matter was associated with higher midlife Framingham Heart Study Cardiovascular Risk Score (lower fractional anisotropy and neurite density index), midlife systolic (lower fractional anisotropy, neurite density index and higher mean diffusivity) and diastolic (lower fractional anisotropy and neurite density index) blood pressure and greater blood pressure change between 43 and 53 years (lower fractional anisotropy and neurite density index), independently of white matter hyperintensity volume. In summary, poorer normal-appearing white matter microstructural integrity in ∼70-year-olds was associated with measures of cerebral small vessel disease, amyloid (in males) and later-life cardiovascular health, demonstrating how normal-appearing white matter can provide additional information to overt white matter disease. Our findings further show that greater 'midlife' cardiovascular risk and higher blood pressure were associated with poorer normal-appearing white matter microstructural integrity in females only, suggesting that women's brains may be more susceptible to the effects of midlife blood pressure and cardiovascular health.

p-Type Conjugated Polymers Containing Electron-Deficient Pentacyclic Azepinedione

Bisthienoazepinedione (BTA) has been reported for constructing high-performing p-type conjugated polymers in organic electronics, but the ring extended version of BTA is not well explored. In this work, we report a new synthesis of a key building block to the ring expanded electron-deficient pentacyclic azepinedione (BTTA). Three copolymers of BTAA with benzodithiophene substituted by different side chains are prepared. These polymers exhibit similar energy levels and optical absorption in solution and solid state, while significant differences are revealed in their film morphologies and behavior in transistor and photovoltaic devices. The best-performing polymers in transistor devices contained alkylthienyl side chains on the BDT unit (pBDT-BTTA-2 and pBDT-BTTA-3) and demonstrated maximum saturation hole mobilities of 0.027 and 0.017 cm2 V-1 s-1. Blends of these polymers with PC71BM exhibited a best photovoltaic efficiency of 6.78% for pBDT-BTTA-3-based devices. Changing to a low band gap non-fullerene acceptor (BTP-eC9) resulted in improved efficiency of up to 13.5%. Our results are among the best device performances for BTA and BTTA-based p-type polymers and highlight the versatile applications of this electron-deficient BTTA unit.

Assessing the reporting quality of adult neuro-oncology protocols, abstracts, and trials: Adherence to the SPIRIT and CONSORT statements

Background

Comprehensive and transparent reporting of clinical trial activity is important. The Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) 2013 and Consolidated Standards of Reporting Trials (CONSORT) 2010 statements define the items to be reported in clinical trial protocols and randomized controlled trials, respectively. The aim of this methodological review was to assess the reporting quality of adult neuro-oncology trial protocols and trial result articles.

Methods

Adult primary and secondary brain tumor phase 3 trial protocols and result articles published after the introduction of the SPIRIT 2013 statement, were identified through searches of 4 electronic bibliographic databases. Following extraction of baseline demographic data, the reporting quality of independently included trial protocols and result articles was assessed against the SPIRIT and CONSORT statements respectively. The CONSORT-A checklist, an extension of the CONSORT 2010 statement, was used to specifically assess the abstract accompanying the trial results article. Percentage adherence (standard deviation [SD]) was calculated for each article.

Results

Seven trial protocols, and 36 trial result articles were included. Mean adherence of trial protocols to the SPIRIT statement was 79.4% (SD: 0.11). Mean adherence of trial abstracts to CONSORT-A was 75.3% (SD: 0.12) and trial result articles to CONSORT was 74.5% (SD: 0.10).

Conclusion

The reporting quality of adult neuro-oncology trial protocols and trial result articles requires improvement to ensure comprehensive and transparent communication of planned neuro-oncology clinical trials and results within the literature. Raising awareness by clinical triallists and implementing mandatory evidence of proof of adherence by journals should improve reporting quality.

Automated detection of cerebral microbleeds on MR images using knowledge distillation framework

Introduction

Cerebral microbleeds (CMBs) are associated with white matter damage, and various neurodegenerative and cerebrovascular diseases. CMBs occur as small, circular hypointense lesions on T2*-weighted gradient recalled echo (GRE) and susceptibility-weighted imaging (SWI) images, and hyperintense on quantitative susceptibility mapping (QSM) images due to their paramagnetic nature. Accurate automated detection of CMBs would help to determine quantitative imaging biomarkers (e.g., CMB count) on large datasets. In this work, we propose a fully automated, deep learning-based, 3-step algorithm, using structural and anatomical properties of CMBs from any single input image modality (e.g., GRE/SWI/QSM) for their accurate detections.

Methods

In our method, the first step consists of an initial candidate detection step that detects CMBs with high sensitivity. In the second step, candidate discrimination step is performed using a knowledge distillation framework, with a multi-tasking teacher network that guides the student network to classify CMB and non-CMB instances in an offline manner. Finally, a morphological clean-up step further reduces false positives using anatomical constraints. We used four datasets consisting of different modalities specified above, acquired using various protocols and with a variety of pathological and demographic characteristics.

Results

On cross-validation within datasets, our method achieved a cluster-wise true positive rate (TPR) of over 90% with an average of <2 false positives per subject. The knowledge distillation framework improves the cluster-wise TPR of the student model by 15%. Our method is flexible in terms of the input modality and provides comparable cluster-wise TPR and better cluster-wise precision compared to existing state-of-the-art methods. When evaluating across different datasets, our method showed good generalizability with a cluster-wise TPR >80 % with different modalities. The python implementation of the proposed method is openly available.

An Observation-Based Dataset of Global Sub-Daily Precipitation Indices (GSDR-I)

Precipitation indices based on daily gauge observations are well established, openly available and widely used to detect and understand climate change. However, in many areas of climate science and risk management, it has become increasingly important to understand precipitation characteristics, variability and extremes at shorter (sub-daily) durations. Yet, no unified dataset of sub-daily indices has previously been available, due in large part to the lesser availability of suitable observations. Following extensive efforts in data collection and quality control, this study presents a new global dataset of sub-daily precipitation indices calculated from a unique database of 18,591 gauge time series. Developed together with prospective users, the indices describe sub-daily precipitation variability and extremes in terms of intensity, duration and frequency properties. The indices are published for each gauge where possible, alongside a gridded data product based on all gauges. The dataset will be useful in many fields concerned with variability and extremes in the climate system, as well as in climate model evaluation and management of floods and other risks.

Local genetic correlations exist among neurodegenerative and neuropsychiatric diseases

Genetic correlation ([Formula: see text]) between traits can offer valuable insight into underlying shared biological mechanisms. Neurodegenerative diseases overlap neuropathologically and often manifest comorbid neuropsychiatric symptoms. However, global [Formula: see text] analyses show minimal [Formula: see text] among neurodegenerative and neuropsychiatric diseases. Importantly, local [Formula: see text] s can exist in the absence of global relationships. To investigate this possibility, we applied LAVA, a tool for local [Formula: see text] analysis, to genome-wide association studies of 3 neurodegenerative diseases (Alzheimer's disease, Lewy body dementia and Parkinson's disease) and 3 neuropsychiatric disorders (bipolar disorder, major depressive disorder and schizophrenia). We identified several local [Formula: see text] s missed in global analyses, including between (i) all 3 neurodegenerative diseases and schizophrenia and (ii) Alzheimer's and Parkinson's disease. For those local [Formula: see text] s identified in genomic regions containing disease-implicated genes, such as SNCA, CLU and APOE, incorporation of expression quantitative trait loci identified genes that may drive genetic overlaps between diseases. Collectively, we demonstrate that complex genetic relationships exist among neurodegenerative and neuropsychiatric diseases, highlighting putative pleiotropic genomic regions and genes. These findings imply sharing of pathogenic processes and the potential existence of common therapeutic targets.

Optical Monitoring of In Situ Iron Loading into Single, Native Ferritin Proteins

Ferritin is a protein that stores and releases iron to prevent diseases associated with iron dysregulation in plants, animals, and bacteria. The conversion between iron-loaded holo-ferritin and empty apo-ferritin is an important process for iron regulation. To date, studies of ferritin have used either ensemble measurements to quantify the characteristics of a large number of proteins or single-molecule approaches to interrogate labeled or modified proteins. Here we demonstrate the first real-time study of the dynamics of iron ion loading and biomineralization within a single, unlabeled ferritin protein. Using optical nanotweezers, we trapped single apo- and holo-ferritins indefinitely, distinguished one from the other, and monitored their structural dynamics in real time. The study presented here deepens the understanding of the iron uptake mechanism of ferritin proteins, which may lead to new therapeutics for iron-related diseases.

Enhanced Organic Electrochemical Transistor Performance of Donor-Acceptor Conjugated Polymers Modified with Hybrid Glycol/Ionic Side Chains by Postpolymerization Modification

Emergent bioelectronic technologies are underpinned by the organic electrochemical transistor (OECT), which employs an electrolyte medium to modulate the conductivity of its organic semiconductor channel. Here we utilize postpolymerization modification (PPM) on a conjugated polymer backbone to directly introduce glycolated or anionic side chains via fluoride displacement. The resulting polymers demonstrated increased volumetric capacitances, with subdued swelling, compared to their parent polymer in p-type enhancement mode OECTs. This increase in capacitance was attributed to their modified side chain configurations enabling cationic charge compensation for thin film electrochemical oxidation, as deduced from electrochemical quartz crystal microbalance measurements. An overall improvement in OECT performance was recorded for the hybrid glycol/ionic polymer compared to the parent, owing to its low swelling and bimodal crystalline orientation as imaged by grazing-incidence wide-angle X-ray scattering, enabling its high charge mobility at 1.02 cm²·V^-1·s^-1. Compromised device performance was recorded for the fully glycolated derivative compared to the parent, which was linked to its limited face-on stacking, which hindered OECT charge mobility at 0.26 cm²·V^-1·s^-1, despite its high capacitance. These results highlight the effectiveness of anionic side chain attachment by PPM as a means of increasing the volumetric capacitance of p-type conjugated polymers for OECTs, while retaining solid-state macromolecular properties that facilitate hole transport.

Preferred Mode of Atmospheric Water Vapor Condensation on Nanoengineered Surfaces: Dropwise or Filmwise?

Condensing atmospheric water vapor on surfaces is a sustainable approach to addressing the potable water crisis. However, despite extensive research, a key question remains: what is the optimal combination of the mode and mechanism of condensation as well as the surface wettability for the best possible water harvesting efficacy? Here, we show how various modes of condensation fare differently in a humid air environment. During condensation from humid air, it is important to note that the thermal resistance across the condensate is nondominant, and the energy transfer is controlled by vapor diffusion across the boundary layer and condensate drainage from the condenser surface. This implies that, unlike condensation from pure steam, filmwise condensation from humid air would exhibit the highest water collection efficiency on superhydrophilic surfaces. To demonstrate this, we measured the condensation rates on different sets of superhydrophilic and superhydrophobic surfaces that were cooled below the dew points using a Peltier cooler. Experiments were performed over a wide range of degrees of subcooling (10-26 °C) and humidity-ratio differences (5-45 g/kg of dry air). Depending upon the thermodynamic parameters, the condensation rate is found to be 57-333% higher on the superhydrophilic surfaces compared to the superhydrophobic ones. The findings of the study dispel ambiguity about the preferred mode of vapor condensation from humid air on wettability-engineered surfaces and lead to the design of efficient atmospheric water harvesting systems.

Opportunity cost determines free-operant action initiation latency and predicts apathy

BACKGROUND

Apathy, a disabling and poorly understood neuropsychiatric symptom, is characterised by impaired self-initiated behaviour. It has been hypothesised that the opportunity cost of time (OCT) may be a key computational variable linking self-initiated behaviour with motivational status. OCT represents the amount of reward which is foregone per second if no action is taken. Using a novel behavioural task and computational modelling, we investigated the relationship between OCT, self-initiation and apathy. We predicted that higher OCT would engender shorter action latencies, and that individuals with greater sensitivity to OCT would have higher behavioural apathy.

METHODS

We modulated the OCT in a novel task called the 'Fisherman Game', Participants freely chose when to self-initiate actions to either collect rewards, or on occasion, to complete non-rewarding actions. We measured the relationship between action latencies, OCT and apathy for each participant across two independent non-clinical studies, one under laboratory conditions (n = 21) and one online (n = 90). 'Average-reward' reinforcement learning was used to model our data. We replicated our findings across both studies.

RESULTS

We show that the latency of self-initiation is driven by changes in the OCT. Furthermore, we demonstrate, for the first time, that participants with higher apathy showed greater sensitivity to changes in OCT in younger adults. Our model shows that apathetic individuals experienced greatest change in subjective OCT during our task as a consequence of being more sensitive to rewards.

CONCLUSIONS

Our results suggest that OCT is an important variable for determining free-operant action initiation and understanding apathy.

The architecture of abnormal reward behaviour in dementia: multimodal hedonic phenotypes and brain substrate

Abnormal reward processing is a hallmark of neurodegenerative diseases, most strikingly in frontotemporal dementia. However, the phenotypic repertoire and neuroanatomical substrates of abnormal reward behaviour in these diseases remain incompletely characterized and poorly understood. Here we addressed these issues in a large, intensively phenotyped patient cohort representing all major syndromes of sporadic frontotemporal dementia and Alzheimer's disease. We studied 27 patients with behavioural variant frontotemporal dementia, 58 with primary progressive aphasia (22 semantic variant, 24 non-fluent/agrammatic variant and 12 logopenic) and 34 with typical amnestic Alzheimer's disease, in relation to 42 healthy older individuals. Changes in behavioural responsiveness were assessed for canonical primary rewards (appetite, sweet tooth, sexual activity) and non-primary rewards (music, religion, art, colours), using a semi-structured survey completed by patients' primary caregivers. Changes in more general socio-emotional behaviours were also recorded. We applied multiple correspondence analysis and k-means clustering to map relationships between hedonic domains and extract core factors defining aberrant hedonic phenotypes. Neuroanatomical associations were assessed using voxel-based morphometry of brain MRI images across the combined patient cohort. Altered (increased and/or decreased) reward responsiveness was exhibited by most patients in the behavioural and semantic variants of frontotemporal dementia and around two-thirds of patients in other dementia groups, significantly (P < 0.05) more frequently than in healthy controls. While food-directed changes were most prevalent across the patient cohort, behavioural changes directed toward non-primary rewards occurred significantly more frequently (P < 0.05) in the behavioural and semantic variants of frontotemporal dementia than in other patient groups. Hedonic behavioural changes across the patient cohort were underpinned by two principal factors: a 'gating' factor determining the emergence of altered reward behaviour and a 'modulatory' factor determining how that behaviour is directed. These factors were expressed jointly in a set of four core, trans-diagnostic and multimodal hedonic phenotypes: 'reward-seeking', 'reward-restricted', 'eating-predominant' and 'control-like'-variably represented across the cohort and associated with more pervasive socio-emotional behavioural abnormalities. The principal gating factor was associated (P < 0.05 after correction for multiple voxel-wise comparisons over the whole brain) with a common profile of grey matter atrophy in anterior cingulate, bilateral temporal poles, right middle frontal and fusiform gyri: the cortical circuitry that mediates behavioural salience and semantic and affective appraisal of sensory stimuli. Our findings define a multi-domain phenotypic architecture for aberrant reward behaviours in major dementias, with novel implications for the neurobiological understanding and clinical management of these diseases.

Shared genetic architecture of hernias: A genome-wide association study with multivariable meta-analysis of multiple hernia phenotypes

Abdominal hernias are common and characterised by the abnormal protrusion of a viscus through the wall of the abdominal cavity. The global incidence is 18.5 million annually and there are limited non-surgical treatments. To improve understanding of common hernia aetiopathology, we performed a six-stage genome-wide association study (GWAS) of 62,637 UK Biobank participants with either single or multiple hernia phenotypes including inguinal, femoral, umbilical and hiatus hernia. Additionally, we performed multivariable meta-analysis with metaUSAT, to allow integration of summary data across traits to generate combined effect estimates. On individual hernia analysis, we identified 3404 variants across 38 genome-wide significant (p < 5×10-8) loci of which 11 are previously unreported. Robust evidence for five shared susceptibility loci was discovered: ZC3H11B, EFEMP1, MHC region, WT1 and CALD1. Combined hernia phenotype analyses with additional multivariable meta-analysis of summary statistics in metaUSAT revealed 28 independent (seven previously unreported) shared susceptibility loci. These clustered in functional categories related to connective tissue and elastic fibre homeostasis. Weighted genetic risk scores also correlated with disease severity suggesting a phenotypic-genotypic severity correlation, an important finding to inform future personalised therapeutic approaches to hernia.

Remote versus face-to-face neuropsychological testing for dementia research: a comparative study in people with Alzheimer's disease, frontotemporal dementia and healthy older individuals

OBJECTIVES

We explored whether adapting neuropsychological tests for online administration during the COVID-19 pandemic was feasible for dementia research.

DESIGN

We used a longitudinal design for healthy controls, who completed face-to-face assessments 3-4 years before remote assessments. For patients, we used a cross-sectional design, contrasting a prospective remote cohort with a retrospective face-to-face cohort matched for age/education/severity.

SETTING

Remote assessments were conducted using video-conferencing/online testing platforms, with participants using a personal computer/tablet at home. Face-to-face assessments were conducted in testing rooms at our research centre.

PARTICIPANTS

The remote cohort comprised 25 patients (n=8 Alzheimer's disease (AD); n=3 behavioural variant frontotemporal dementia (bvFTD); n=4 semantic dementia (SD); n=5 progressive non-fluent aphasia (PNFA); n=5 logopenic aphasia (LPA)). The face-to-face patient cohort comprised 64 patients (n=25 AD; n=12 bvFTD; n=9 SD; n=12 PNFA; n=6 LPA). Ten controls who previously participated in face-to-face research also took part remotely.

OUTCOME MEASURES

The outcome measures comprised the strength of evidence under a Bayesian framework for differences in performances between testing environments on general neuropsychological and neurolinguistic measures.

RESULTS

There was substantial evidence suggesting no difference across environments in both the healthy control and combined patient cohorts (including measures of working memory, single-word comprehension, arithmetic and naming; Bayes Factors (BF)01 >3), in the healthy control group alone (including measures of letter/category fluency, semantic knowledge and bisyllabic word repetition; all BF01 >3), and in the combined patient cohort alone (including measures of working memory, episodic memory, short-term verbal memory, visual perception, non-word reading, sentence comprehension and bisyllabic/trisyllabic word repetition; all BF01 >3). In the control cohort alone, there was substantial evidence in support of a difference across environments for tests of visual perception (BF01=0.0404) and monosyllabic word repetition (BF01=0.0487).

CONCLUSIONS

Our findings suggest that remote delivery of neuropsychological tests for dementia research is feasible.

Post-polymerisation approaches for the rapid modification of conjugated polymer properties

Post-polymerisation functionalisation provides a facile and efficient way for the introduction of functional groups on the backbone of conjugated polymers. Using post-polymerisation functionalisation approaches, the polymer chain length is usually not affected, meaning that the resulting polymers only differ in their attached functional groups or side chains, which makes them particularly interesting for investigating the influence of the different groups on the polymer properties. For such functionalisations, highly efficient and selective reactions are needed to avoid the formation of complex mixtures or permanent defects in the polymer backbone. A variety of suitable synthetic approaches and reactions that fulfil these criteria have been identified and reported. In this review, a thorough overview is given of the post-polymerisation functionalisations reported to date, with the methods grouped based on the type of reaction used: cycloaddition, oxidation/reduction, nucleophilic aromatic substitution, or halogenation and subsequent cross-coupling reaction. Instead of modifications on the aliphatic side chains of the conjugated polymers, we focus on modifications directly on the conjugated backbones, as these have the most pronounced effect on the optical and electronic properties. Some of the discussed materials have been used in applications, ranging from solar cells to bioelectronics. By providing an overview of this versatile and expanding field for the first time, we showcase post-polymerisation functionalisation as an exciting pathway for the creation of new conjugated materials for a range of applications.

Low Dark Current Organic Photodetectors Utilizing Highly Cyanated Non-fullerene Acceptors

Organic materials combining high electron affinity with strong absorption in the visible spectrum are of interest for photodetector applications. In this study, we report two such molecular semiconductors, based upon an acceptor-donor-acceptor (A-D-A) approach. Coupling of an acceptor end group, 2,1,3-benzothiadiazole-4,5,6-tricarbonitrile (TCNBT), with a donor cyclopentadithiophene core affords materials with a band gap of 1.5 eV and low-lying LUMO levels around -4.2 eV. Both materials were readily synthesized by a one-pot nucleophilic displacement of a fluorinated precursor by cyanide. The two acceptors only differ in the nature of the solubilizing alkyl chain, which is either branched 2-ethyl hexyl (EH-TCNBT) or linear octyl (O-TCNBT). Both acceptors were blended with polymer donor PTQ10 as an active layer in OPDs. Significant device differences were observed depending on the alkyl chain, with the branched acceptor giving the optimum performance. Both acceptors exhibited very low dark current densities, with values up to 10^-5 mA cm^-2 at -2 V, highlighting the potential of the highly cyanated cores (TCNBT) as acceptor materials.

Development of a sensitive trial-ready poly(GP) CSF biomarker assay for C9orf72-associated frontotemporal dementia and amyotrophic lateral sclerosis

OBJECTIVE

A GGGGCC repeat expansion in the C9orf72 gene is the most common cause of genetic frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS). As potential therapies targeting the repeat expansion are now entering clinical trials, sensitive biomarker assays of target engagement are urgently required. Our objective was to develop such an assay.

METHODS

We used the single molecule array (Simoa) platform to develop an immunoassay for measuring poly(GP) dipeptide repeat proteins (DPRs) generated by the C9orf72 repeat expansion in cerebrospinal fluid (CSF) of people with C9orf72-associated FTD/ALS.

RESULTS AND CONCLUSIONS

We show the assay to be highly sensitive and robust, passing extensive qualification criteria including low intraplate and interplate variability, a high precision and accuracy in measuring both calibrators and samples, dilutional parallelism, tolerance to sample and standard freeze-thaw and no haemoglobin interference. We used this assay to measure poly(GP) in CSF samples collected through the Genetic FTD Initiative (N=40 C9orf72 and 15 controls). We found it had 100% specificity and 100% sensitivity and a large window for detecting target engagement, as the C9orf72 CSF sample with the lowest poly(GP) signal had eightfold higher signal than controls and on average values from C9orf72 samples were 38-fold higher than controls, which all fell below the lower limit of quantification of the assay. These data indicate that a Simoa-based poly(GP) DPR assay is suitable for use in clinical trials to determine target engagement of therapeutics aimed at reducing C9orf72 repeat-containing transcripts.

Transcriptomic and small RNA response to Mayaro virus infection in Anopheles stephensi mosquitoes

Mayaro virus (MAYV) is an arboviral pathogen in the genus Alphavirus that is circulating in South America with potential to spread to naïve regions. MAYV is also one of the few viruses with the ability to be transmitted by mosquitoes in the genus Anopheles, as well as the typical arboviral transmitting mosquitoes in the genus Aedes. Few studies have investigated the infection response of Anopheles mosquitoes. In this study we detail the transcriptomic and small RNA responses of An. stephensi to infection with MAYV via infectious bloodmeal at 2, 7, and 14 days post infection (dpi). 487 unique transcripts were significantly regulated, 78 putative novel miRNAs were identified, and an siRNA response is observed targeting the MAYV genome. Gene ontology analysis of transcripts regulated at each timepoint shows a number of proteases regulated at 2 and 7 dpi, potentially representative of Toll or melanization pathway activation, and repression of pathways related to autophagy and apoptosis at 14 dpi. These findings provide a basic understanding of the infection response of An. stephensi to MAYV and help to identify host factors which might be useful to target to inhibit viral replication in Anopheles mosquitoes.

Mayaro virus (MAYV) is a mosquito-borne Alphavirus responsible for outbreaks in South America and the Caribbean. In this study we infected Anopheles stephensi with MAYV and sequenced mRNA and small RNA to understand how MAYV infection impacts gene transcription and the expression of small RNAs in the mosquito vector. Genes involved with innate immunity and signaling pathways related to cell death are regulated in response to MAYV infection of An. stephensi, we also discovered novel miRNAs and describe the expression patterns of miRNAs, siRNAs, and piRNAs following bloodmeal ingestion. These results suggest that MAYV does induce a molecular response to infection in its mosquito vector species.

High-Resolution Ion-Flux Imaging of Proton Transport through Graphene|Nafion Membranes

In 2014, it was reported that protons can traverse between aqueous phases separated by nominally pristine monolayer graphene and hexagonal boron nitride (h-BN) films (membranes) under ambient conditions. This intrinsic proton conductivity of the one-atom-thick crystals, with proposed through-plane conduction, challenged the notion that graphene is impermeable to atoms, ions, and molecules. More recent evidence points to a defect-facilitated transport mechanism, analogous to transport through conventional ion-selective membranes based on graphene and h-BN. Herein, local ion-flux imaging is performed on chemical vapor deposition (CVD) graphene|Nafion membranes using an "electrochemical ion (proton) pump cell" mode of scanning electrochemical cell microscopy (SECCM). Targeting regions that are free from visible macroscopic defects (e.g., cracks, holes, etc.) and assessing hundreds to thousands of different sites across the graphene surfaces in a typical experiment, we find that most of the CVD graphene|Nafion membrane is impermeable to proton transport, with transmission typically occurring at ≈20-60 localized sites across a ≈0.003 mm² area of the membrane (>5000 measurements total). When localized proton transport occurs, it can be a highly dynamic process, with additional transmission sites "opening" and a small number of sites "closing" under an applied electric field on the seconds time scale. Applying a simple equivalent circuit model of ion transport through a cylindrical nanopore, the local transmission sites are estimated to possess dimensions (radii) on the (sub)nanometer scale, implying that rare atomic defects are responsible for proton conductance. Overall, this work reinforces SECCM as a premier tool for the structure-property mapping of microscopically complex (electro)materials, with the local ion-flux mapping configuration introduced herein being widely applicable for functional membrane characterization and beyond, for example in diagnosing the failure mechanisms of protective surface coatings.

Heteroplasmic mitochondrial DNA variants in cardiovascular diseases

Mitochondria are implicated in the pathogenesis of cardiovascular diseases (CVDs) but the reasons for this are not well understood. Maternally-inherited population variants of mitochondrial DNA (mtDNA) which affect all mtDNA molecules (homoplasmic) are associated with cardiometabolic traits and the risk of developing cardiovascular disease. However, it is not known whether mtDNA mutations only affecting a proportion of mtDNA molecules (heteroplasmic) also play a role. To address this question, we performed a high-depth (~1000-fold) mtDNA sequencing of blood DNA in 1,399 individuals with hypertension (HTN), 1,946 with ischemic heart disease (IHD), 2,146 with ischemic stroke (IS), and 723 healthy controls. We show that the per individual burden of heteroplasmic single nucleotide variants (mtSNVs) increases with age. The age-effect was stronger for low-level heteroplasmies (heteroplasmic fraction, HF, 5-10%), likely reflecting acquired somatic events based on trinucleotide mutational signatures. After correcting for age and other confounders, intermediate heteroplasmies (HF 10-95%) were more common in hypertension, particularly involving non-synonymous variants altering the amino acid sequence of essential respiratory chain proteins. These findings raise the possibility that heteroplasmic mtSNVs play a role in the pathophysiology of hypertension.

What can general practice learn from primary care nurses' and healthcare assistants' experiences of the COVID-19 pandemic? A qualitative study

OBJECTIVES

UK general practice has radically altered in response to COVID-19. The general practice nursing team has been central to these changes. To help learn from COVID-19 and maintain a sustainable nursing workforce, general practice should reflect on their support needs and perceptions of organisational strategies. This study aimed to explore primary care nurses' and healthcare assistants' experiences and perceptions of general practice, and the changes made to it, during the pandemic.

DESIGN

Exploratory qualitative study using semistructured interviews. Interview data were analysed using Braun and Clarke's 'codebook' thematic analysis.

SETTING

General practices in the Midlands, South East and South West England. Interviews were conducted in February and March 2021, as England began to unlock from its third national lockdown.

PARTICIPANTS

Practice nurses (n=12), healthcare assistants (n=7), advanced nurse practitioners (n=4) and nursing associates (n=1) recruited using convenience and snowball sampling.

RESULTS

Three themes were identified. Difficult changes describes dramatic changes made to general practice at the onset of the pandemic, creating confusion and anxiety. Dealing with change characterises how negative emotions were intensified by fear of infection, problematic government guidance, personal protective equipment (PPE) shortages and friction with doctors; but could be mitigated through effective practice communication, peer support and individual coping strategies. An opportunity for improvement highlights certain changes (eg, the increased use of telehealth) that participants believed could be adopted long term to improve efficiency.

CONCLUSION

General practice should learn from the COVID-19 pandemic to nurture the clinical role and resilience of nurses and healthcare assistants in the postpandemic 'new normal'. Robust PPE provision could enable them to undertake their patient-facing duties safely and confidently. Judicious implementation of telehealth could help preserve the practical and caring nature of nursing. Improving channels of communication and interprofessional collaboration could help realise their potential within the primary care team.

Automated Detection of Candidate Subjects With Cerebral Microbleeds Using Machine Learning

Cerebral microbleeds (CMBs) appear as small, circular, well defined hypointense lesions of a few mm in size on T2^*-weighted gradient recalled echo (T2^*-GRE) images and appear enhanced on susceptibility weighted images (SWI). Due to their small size, contrast variations and other mimics (e.g., blood vessels), CMBs are highly challenging to detect automatically. In large datasets (e.g., the UK Biobank dataset), exhaustively labelling CMBs manually is difficult and time consuming. Hence it would be useful to preselect candidate CMB subjects in order to focus on those for manual labelling, which is essential for training and testing automated CMB detection tools on these datasets. In this work, we aim to detect CMB candidate subjects from a larger dataset, UK Biobank, using a machine learning-based, computationally light pipeline. For our evaluation, we used 3 different datasets, with different intensity characteristics, acquired with different scanners. They include the UK Biobank dataset and two clinical datasets with different pathological conditions. We developed and evaluated our pipelines on different types of images, consisting of SWI or GRE images. We also used the UK Biobank dataset to compare our approach with alternative CMB preselection methods using non-imaging factors and/or imaging data. Finally, we evaluated the pipeline's generalisability across datasets. Our method provided subject-level detection accuracy > 80% on all the datasets (within-dataset results), and showed good generalisability across datasets, providing a consistent accuracy of over 80%, even when evaluated across different modalities.

Thalamic white matter macrostructure and subnuclei volumes in Parkinson's disease depression

Depression is a common non-motor feature of Parkinson's disease (PD) which confers significant morbidity and is challenging to treat. The thalamus is a key component in the basal ganglia-thalamocortical network critical to the pathogenesis of PD and depression but the precise thalamic subnuclei involved in PD depression have not been identified. We performed structural and diffusion-weighted imaging (DWI) on 76 participants with PD to evaluate the relationship between PD depression and grey and white matter thalamic subnuclear changes. We used a thalamic segmentation method to divide the thalamus into its 50 constituent subnuclei (25 each hemisphere). Fixel-based analysis was used to calculate mean fibre cross-section (FC) for white matter tracts connected to each subnucleus. We assessed volume and FC at baseline and 14-20 months follow-up. A generalised linear mixed model was used to evaluate the relationship between depression, subnuclei volume and mean FC for each thalamic subnucleus. We found that depression scores in PD were associated with lower right pulvinar anterior (PuA) subnucleus volume. Antidepressant use was associated with higher right PuA volume suggesting a possible protective effect of treatment. After follow-up, depression scores were associated with reduced white matter tract macrostructure across almost all tracts connected to thalamic subnuclei. In conclusion, our work implicates the right PuA as a relevant neural structure in PD depression and future work should evaluate its potential as a therapeutic target for PD depression.

A data-driven model of brain volume changes in progressive supranuclear palsy

The most common clinical phenotype of progressive supranuclear palsy is Richardson syndrome, characterized by levodopa unresponsive symmetric parkinsonism, with a vertical supranuclear gaze palsy, early falls and cognitive impairment. There is currently no detailed understanding of the full sequence of disease pathophysiology in progressive supranuclear palsy. Determining the sequence of brain atrophy in progressive supranuclear palsy could provide important insights into the mechanisms of disease progression, as well as guide patient stratification and monitoring for clinical trials. We used a probabilistic event-based model applied to cross-sectional structural MRI scans in a large international cohort, to determine the sequence of brain atrophy in clinically diagnosed progressive supranuclear palsy Richardson syndrome. A total of 341 people with Richardson syndrome (of whom 255 had 12-month follow-up imaging) and 260 controls were included in the study. We used a combination of 12-month follow-up MRI scans, and a validated clinical rating score (progressive supranuclear palsy rating scale) to demonstrate the longitudinal consistency and utility of the event-based model's staging system. The event-based model estimated that the earliest atrophy occurs in the brainstem and subcortical regions followed by progression caudally into the superior cerebellar peduncle and deep cerebellar nuclei, and rostrally to the cortex. The sequence of cortical atrophy progresses in an anterior to posterior direction, beginning in the insula and then the frontal lobe before spreading to the temporal, parietal and finally the occipital lobe. This in vivo ordering accords with the post-mortem neuropathological staging of progressive supranuclear palsy and was robust under cross-validation. Using longitudinal information from 12-month follow-up scans, we demonstrate that subjects consistently move to later stages over this time interval, supporting the validity of the model. In addition, both clinical severity (progressive supranuclear palsy rating scale) and disease duration were significantly correlated with the predicted subject event-based model stage (P < 0.01). Our results provide new insights into the sequence of atrophy progression in progressive supranuclear palsy and offer potential utility to stratify people with this disease on entry into clinical trials based on disease stage, as well as track disease progression.

Steering ecological-evolutionary dynamics to improve artificial selection of microbial communities

Microbial communities often perform important functions that depend on inter-species interactions. To improve community function via artificial selection, one can repeatedly grow many communities to allow mutations to arise, and "reproduce" the highest-functioning communities by partitioning each into multiple offspring communities for the next cycle. Since improvement is often unimpressive in experiments, we study how to design effective selection strategies in silico. Specifically, we simulate community selection to improve a function that requires two species. With a "community function landscape", we visualize how community function depends on species and genotype compositions. Due to ecological interactions that promote species coexistence, the evolutionary trajectory of communities is restricted to a path on the landscape. This restriction can generate counter-intuitive evolutionary dynamics, prevent the attainment of maximal function, and importantly, hinder selection by trapping communities in locations of low community function heritability. We devise experimentally-implementable manipulations to shift the path to higher heritability, which speeds up community function improvement even when landscapes are high dimensional or unknown. Video walkthroughs: https://go.nature.com/3GWwS6j ; https://online.kitp.ucsb.edu/online/ecoevo21/shou2/ .

Loss and dispersion of superficial white matter in Alzheimer's disease: a diffusion MRI study

Pathological cerebral white matter changes in Alzheimer's disease have been shown using diffusion tensor imaging. Superficial white matter changes are relatively understudied despite their importance in cortico-cortical connections. Measuring superficial white matter degeneration using diffusion tensor imaging is challenging due to its complex organizational structure and proximity to the cortex. To overcome this, we investigated diffusion MRI changes in young-onset Alzheimer's disease using standard diffusion tensor imaging and Neurite Orientation Dispersion and Density Imaging to distinguish between disease-related changes that are degenerative (e.g. loss of myelinated fibres) and organizational (e.g. increased fibre dispersion). Twenty-nine young-onset Alzheimer's disease patients and 22 healthy controls had both single-shell and multi-shell diffusion MRI. We calculated fractional anisotropy, mean diffusivity, neurite density index, orientation dispersion index and tissue fraction (1-free water fraction). Diffusion metrics were sampled in 15 a priori regions of interest at four points along the cortical profile: cortical grey matter, grey/white boundary, superficial white matter (1 mm below grey/white boundary) and superficial/deeper white matter (2 mm below grey/white boundary). To estimate cross-sectional group differences, we used average marginal effects from linear mixed effect models of participants' diffusion metrics along the cortical profile. The superficial white matter of young-onset Alzheimer's disease individuals had lower neurite density index compared to controls in five regions (superior and inferior parietal, precuneus, entorhinal and parahippocampus) (all P < 0.05), and higher orientation dispersion index in three regions (fusiform, entorhinal and parahippocampus) (all P < 0.05). Young-onset Alzheimer's disease individuals had lower fractional anisotropy in the entorhinal and parahippocampus regions (both P < 0.05) and higher fractional anisotropy within the postcentral region (P < 0.05). Mean diffusivity was higher in the young-onset Alzheimer's disease group in the parahippocampal region (P < 0.05) and lower in the postcentral, precentral and superior temporal regions (all P < 0.05). In the overlying grey matter, disease-related changes were largely consistent with superficial white matter findings when using neurite density index and fractional anisotropy, but appeared at odds with orientation dispersion and mean diffusivity. Tissue fraction was significantly lower across all grey matter regions in young-onset Alzheimer's disease individuals (all P < 0.001) but group differences reduced in magnitude and coverage when moving towards the superficial white matter. These results show that microstructural changes occur within superficial white matter and along the cortical profile in individuals with young-onset Alzheimer's disease. Lower neurite density and higher orientation dispersion suggests underlying fibres undergo neurodegeneration and organizational changes, two effects previously indiscernible using standard diffusion tensor metrics in superficial white matter.

Subjective cognitive complaints at age 70: associations with amyloid and mental health

OBJECTIVE

To investigate subjective cognitive decline (SCD) in relation to β-amyloid pathology and to test for associations with anxiety, depression, objective cognition and family history of dementia in the Insight 46 study.

METHODS

Cognitively unimpaired ~70-year-old participants, all born in the same week in 1946 (n=460, 49% female, 18% amyloid-positive), underwent assessments including the SCD-Questionnaire (MyCog). MyCog scores were evaluated with respect to 18F-Florbetapir-PET amyloid status (positive/negative). Associations with anxiety, depression, objective cognition (measured by the Preclinical Alzheimer Cognitive Composite, PACC) and family history of dementia were also investigated. The informant's perspective on SCD was evaluated in relation to MyCog score.

RESULTS

Anxiety (mean (SD) trait anxiety score: 4.4 (3.9)) was associated with higher MyCog scores, especially in women. MyCog scores were higher in amyloid-positive compared with amyloid-negative individuals (adjusted means (95% CIs): 5.3 (4.4 to 6.1) vs 4.3 (3.9 to 4.7), p=0.044), after accounting for differences in anxiety. PACC (mean (SD) -0.05 (0.68)) and family history of dementia (prevalence: 23.9%) were not independently associated with MyCog scores. The informant's perception of SCD was generally in accordance with that of the participant.

CONCLUSIONS

This cross-sectional study demonstrates that symptoms of SCD are associated with both β-amyloid pathology, and more consistently, trait anxiety in a population-based cohort of older adults, at an age when those who are destined to develop dementia are still likely to be some years away from symptoms. This highlights the necessity of considering anxiety symptoms when assessing Alzheimer's disease pathology and SCD.

Age-specific cerebral haemodynamic effects of early blood pressure lowering after transient ischaemic attack and non-disabling stroke

INTRODUCTION

There is limited knowledge of the effects of blood pressure (BP) lowering on cerebral haemodynamics after transient ischaemic attack (TIA) and non-disabling stroke, particularly at older ages. We aimed to evaluate changes in transcranial Doppler (TCD) haemodynamic indices in patients undergoing early blood pressure lowering after TIA/non-disabling stroke, irrespective of age.

PATIENTS AND METHODS

Among consecutive eligible patients attending a rapid-access clinic with suspected TIA/non-disabling stroke and no evidence of extra/intracranial stenosis, hypertensive ones underwent intensive BP-lowering guided by daily home telemetric blood pressure monitoring (HBPM). Clinic-based BP, HBPM, End-tidal CO2 and bilateral middle cerebral artery (MCA) velocity on TCD were compared in the acute setting versus one-month follow-up; changes were stratified by baseline hypertension (clinic-BP≥140/90) and by age (<65, 65-79 and ≥80).

RESULTS

In 697 patients with repeated TCD measures, mean/SD baseline systolic-BP (145.0/21.3 mmHg) was reduced by an average of 11.3/19.9 mmHg (p < 0.0001) at one-month (133.7/17.4 mmHg), driven by patients hypertensive at baseline (systolic-BP change = -19.0/19.2 mmHg, p < 0.001; vs -0.5/15.4, p = 0.62 in normotensives). Compared with baseline, a significant change was observed at one-month only in mean/SD MCA end diastolic velocity (EDV) (0.77/7.26 cm/s, p = 0.005) and in resistance index (RI) (-0.005/0.051, p = 0.016), driven by hypertensive patients (mean/SD EDV change: 1.145/6.96 cm/s p = 0.001, RI change -0.007/0.06, p = 0.014). Findings were similar at all ages (EDV change - ptrend=0.357; RI change - ptrend=0.225), including 117 patients aged ≥80. EDV and RI changes were largest in 100 patients with clinic systolic-BP decrease ≥30 mmHg (mean/SD EDV change = 2.49/7.47 cm/s, p = 0.001; RI change -0.024/0.063, p < 0.0001).

CONCLUSION

There was no evidence of worsening of TCD haemodynamic indices associated with BP-lowering soon after TIA/non-disabling stroke, irrespective of age and degree of BP reduction. In fact, EDV increase and RI decrease observed after treatment of hypertensive patients suggest a decrease in distal vascular resistance.

Exploring Perceptions of Female Genital Mutilation/Cutting Abandonment (FGM/C) in Kenyan Health Care Professionals

Female genital mutilation/cutting (FGM/C) remains a global problem. We aimed to explore Kenyan health care professionals' (HCPs) perceptions of FGM/C abandonment and, in particular, those focused on those serving Maasai communities who continue to practice FGM/C. Using a grounded theory Straussian approach, 18 interviews were conducted with HCPs in Kajiado County, Kenya, to understand perceptions of FGM/C as a cultural practice, identify barriers and facilitators to abandonment, and explore attitudes to medicalization (FGM/C conducted by HCPs) and alternatives of FGM/C. Within a substantive theory, one core category ("FGM/C persists but can be abandoned") comprised two subcategories: "exploring the influencers of persistence" and the "roadmap to abandonment." HCPs believed collaborative multilateral efforts were necessary to support successful abandonment and that "enlightening" the community needed to focus on changing the perception of FGM/C as a social norm alongside a health risk educational approach. Future effective intervention is needed to support the abandonment of FGM/C in Kenya.

SARS-CoV-2 Tests: Bridging the Gap between Laboratory Sensors and Clinical Applications

This review covers emerging biosensors for SARS-CoV-2 detection together with a review of the biochemical and clinical assays that are in use in hospitals and clinical laboratories. We discuss the gap in bridging the current practice of testing laboratories with nucleic acid amplification methods, and the robustness of assays the laboratories seek, and what emerging SARS-CoV-2 sensors have currently addressed in the literature. Together with the established nucleic acid and biochemical tests, we review emerging technology and antibody tests to determine the effectiveness of vaccines on individuals.

Bias in Zipf's law estimators

The prevailing maximum likelihood estimators for inferring power law models from rank-frequency data are biased. The source of this bias is an inappropriate likelihood function. The correct likelihood function is derived and shown to be computationally intractable. A more computationally efficient method of approximate Bayesian computation (ABC) is explored. This method is shown to have less bias for data generated from idealised rank-frequency Zipfian distributions. However, the existing estimators and the ABC estimator described here assume that words are drawn from a simple probability distribution, while language is a much more complex process. We show that this false assumption leads to continued biases when applying any of these methods to natural language to estimate Zipf exponents. We recommend that researchers be aware of the bias when investigating power laws in rank-frequency data.

Silent cold-sensing neurons contribute to cold allodynia in neuropathic pain

Patients with neuropathic pain often experience innocuous cooling as excruciating pain. The cell and molecular basis of this cold allodynia is little understood. We used in vivo calcium imaging of sensory ganglia to investigate how the activity of peripheral cold-sensing neurons was altered in three mouse models of neuropathic pain: oxaliplatin-induced neuropathy, partial sciatic nerve ligation, and ciguatera poisoning. In control mice, cold-sensing neurons were few in number and small in size. In neuropathic animals with cold allodynia, a set of normally silent large diameter neurons became sensitive to cooling. Many of these silent cold-sensing neurons responded to noxious mechanical stimuli and expressed the nociceptor markers Nav1.8 and CGRPα. Ablating neurons expressing Nav1.8 resulted in diminished cold allodynia. The silent cold-sensing neurons could also be activated by cooling in control mice through blockade of Kv1 voltage-gated potassium channels. Thus, silent cold-sensing neurons are unmasked in diverse neuropathic pain states and cold allodynia results from peripheral sensitization caused by altered nociceptor excitability.

Nonameric structures of the cytoplasmic domain of FlhA and SctV in the context of the full-length protein

Type three secretion is the mechanism of protein secretion found in bacterial flagella and injectisomes. At its centre is the export apparatus (EA), a complex of five membrane proteins through which secretion substrates pass the inner membrane. While the complex formed by four of the EA proteins has been well characterised structurally, little is known about the structure of the membrane domain of the largest subunit, FlhA in flagella, SctV in injectisomes. Furthermore, the biologically relevant nonameric assembly of FlhA/SctV has been infrequently observed and differences in conformation of the cytoplasmic portion of FlhA/SctV between open and closed states have been suggested to reflect secretion system specific differences. FlhA has been shown to bind to chaperone-substrate complexes in an open state, but in previous assembled ring structures, SctV is in a closed state. Here, we identify FlhA and SctV homologues that can be recombinantly produced in the oligomeric state and study them using cryo-electron microscopy. The structures of the cytoplasmic domains from both FlhA and SctV are in the open state and we observe a conserved interaction between a short stretch of residues at the N-terminus of the cytoplasmic domain, known as FlhA_L/SctV_L, with a groove on the adjacent protomer’s cytoplasmic domain, which stabilises the nonameric ring assembly.

Investigating the Relationship Between IGF-I, IGF-II, and IGFBP-3 Concentrations and Later-Life Cognition and Brain Volume

BACKGROUND

The insulin/insulin-like signaling (IIS) pathways, including insulin-like growth factors (IGFs), vary with age. However, their association with late-life cognition and neuroimaging parameters is not well characterized.

METHODS

Using data from the British 1946 birth cohort, we investigated associations of IGF-I, IGF-II and IGF binding protein 3 (IGFBP-3; measured at 53 and 60-64 years of age) with cognitive performance [word-learning test (WLT) and visual letter search (VLS) at 60-64 years and 69 years of age] and cognitive state [Addenbrooke's Cognitive Exam III (ACE-III) at 69-71 years of age], and in a proportion, quantified neuroimaging measures [whole brain volume (WBV), white matter hyperintensity volume (WMHV), hippocampal volume (HV)]. Regression models included adjustments for demographic, lifestyle, and health factors.

RESULTS

Higher IGF-I and IGF-II at 53 years of age was associated with higher ACE-III scores [ß 0.07 95% confidence interval (CI) (0.02, 0.12); scoreACE-III 89.48 (88.86, 90.1), respectively). IGF-II at 53 years of age was additionally associated with higher WLT scores [scoreWLT 20 (19.35, 20.65)]. IGFBP-3 at 60 to 64 years of age was associated with favorable VLS score at 60 to 64 and 69 years of age [ß 0.07 (0.01, 0.12); ß 0.07 (0.02, 0.12), respectively], higher memory and cognitive state at 69 years of age [ß 0.07 (0.01, 0.12); ß 0.07 (0.01, 0.13), respectively], and reduced WMHV [ß -0.1 (-0.21, -0.00)]. IGF-I/IGFBP-3 at 60 to 64 years of was associated with lower VLS scores at 69 years of age [ß -0.08 (-0.15, -0.02)].

CONCLUSIONS

Increased measure in IIS parameters (IGF-I, IGF-II, and IGFBP-3) relate to better cognitive state in later life. There were apparent associations with specific cognitive domains (IGF-II relating to memory; IGFBP-3 relating to memory, processing speed, and WMHV; and IGF-I/IGFBP-3 molar ratio related to slower processing speed). IGFs and IGFBP-3 are associated with favorable cognitive function outcomes.

Prevalence, predictors and prognosis of incidental intracranial aneurysms in patients with suspected TIA and minor stroke: a population-based study and systematic review

INTRODUCTION

Unruptured intracranial aneurysms (UIAs) are common incidental imaging findings, but there are few data in patients with transient ischaemic attack (TIA)/stroke. The frequency of UIA might be higher due to shared risk factors, but rupture risk might be reduced by intensive secondary prevention. We determined the prevalence and prognosis of UIA in patients with suspected TIA/minor stroke.

METHODS

All patients referred to the population-based Oxford Vascular Study (2011-2020) with suspected TIA/minor stroke and non-invasive angiography were included. We determined the prevalence of incidental asymptomatic UIA and the risk of subsequent subarachnoid haemorrhage (SAH) by follow-up on intensive medical treatment, with guideline-based monitoring/management. We also did a systematic review of UIA prevalence/prognosis in cohorts with TIA/stroke.

FINDINGS

Among 2013 eligible patients, 95 (4.7%) had 103 previously unknown asymptomatic UIA. Female sex (OR 2.3, 95% CI 1.5 to 3.7), smoking (2.1, 1.2 to 3.6) and hypertension (1.6, 1.0 to 2.5) were independently predictive of UIA, with a prevalence of 11.1% in those with all three risk factors. During mean follow-up of 4.5 years, only one SAH occurred: 2.3 (95% CI 0.3 to 16.6) per 1000 person-years. We identified 19 studies of UIA in TIA/stroke cohorts (n=12 781), all with either symptomatic carotid stenosis or major acute stroke. The pooled mean UIA prevalence in patients with TIA/stroke was 5.1% (95% CI 4.8 to 5.5) and the incidence of SAH was 4.6 (95% CI 1.9 to 11.0) per 1000 person-years.

INTERPRETATION

The 5% prevalence of UIA in patients with confirmed TIA/minor stroke is likely higher than that in the general population. However, the risk of SAH on intensive medical treatment and guideline-based management/monitoring is low.