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Tri(oxyethylene)-functionalised perylene diimide: a promising interlayer material for enhanced organic photovoltaic performance
No full textA new tri(oxyethylene)-functionalised perylene diimide-based electron transport layer material has been synthesised and used in organic photovoltaic devices for efficient charge extraction
Reprogramming of Androgen Receptor Activity in Castration-resistant Prostate Cancer is Shaped by Truncated Variants
No full textBACKGROUND AND OBJECTIVE: Under the selective pressure of treatment, prostate cancer cells express constitutively active androgen receptor (AR) variants. Whether AR variants mediate therapy resistance remains contested, because they are often coexpressed with abundant full-length AR. Therefore, we sought to determine how truncated variants shape AR chromatin occupancy and responses to treatments in both the presence and absence of full-length AR. METHODS: We used a cohort of patient-derived xenografts of metastatic prostate cancer with diverse AR alterations. Chromatin immunoprecipitation and RNA sequencing were used to compare the landscape of AR binding and transcriptomic features. We assessed responses to castration by castrating host mice and evaluated responses to bipolar androgen therapy by administering testosterone cypionate. KEY FINDINGS AND LIMITATIONS: By profiling the AR cistrome, we identified a distinct group of tumours defined by ARv567es expression, a variant arising due to structural rearrangements of the AR gene. ARv567es-positive tumours also had a distinct epigenomic profile and altered transcriptional features, including loss of canonical AR-regulated gene signatures and elevated expression of AR-repressed genes. ARv567es-positive tumours were resistant to castration and bipolar androgen therapy. In tumours that coexpress full-length AR, this involves dampened transcriptional responses and disruption of the autoregulatory loop that modulates AR levels. Study limitations include the need for additional models of AR-driven prostate cancer. CONCLUSIONS AND CLINICAL IMPLICATIONS: The emergence of ARv567es via gene rearrangements causes transcriptional reprogramming and therapy resistance. This highlights ARv567es as a potential as a marker to guide treatment decisions
Open-source quality assurance for multi-parametric MRI: a diffusion analysis update for the magnetic resonance biomarker assessment software (MR-BIAS)
No full textOBJECTIVE: To validate the automated analysis of magnetic resonance imaging (MRI) diffusion phantoms with an updated version of the magnetic resonance biomarker assessment software (MR-BIAS), an open-source tool initially developed for the analysis of MRI relaxometry phantoms. MATERIALS AND METHODS: The updated MR-BIAS was validated against two published diffusion weighted MRI datasets: (i) a single-site study (n = 48) was used for validation of apparent diffusion coefficients (ADC) and to identify optimal region of interest (ROI) selection, and (ii) a multi-centre multi-vendor study including diffusion imaging from a shared benchmark protocol (n = 49) and site-specific protocols (n = 43). ADC analysis compared both datasets with ROIs manually matched to the original studies, and with automatically detected optimal ROIs. RESULTS: MR-BIAS ADC values were statistically equivalent (p < 0.05) to original studies within tolerances (manual ROI, automatic ROI) for the single-site study (± 0.01, ± 6 μm2/s) and for the multi-vendor study for benchmark (± 4, ± 7 μm2/s) and site-specific (± 3, ± 6 μm2/s) protocols. The optimal ROI was a central cylinder (height = 10mm, diameter = 10mm). MR-BIAS ADC summary metrics were comparable to those of the original studies. DISCUSSION: MR-BIAS can automatically and accurately perform ADC analysis of diffusion phantoms, making the software suitable for the quality assurance of multi-centre studies of multi-parametric MRI
Plasma p-tau217, NfL, GFAP diagnostic performance and biomarker profiles in Alzheimer's disease, frontotemporal dementia, and psychiatric disorders, in a prospective unselected neuropsychiatry memory clinic
No full textINTRODUCTION: Plasma biomarkers offer promise for improving the diagnosis of Alzheimer's disease (AD) and differentiating AD and other neurodegenerative disorders (NDs) like frontotemporal dementia (FTD) from primary psychiatric disorders (PPDs), particularly in younger patients. METHODS: In this prospective study, we investigated plasma phosphorylated tau 217 (p-tau217), neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) in 341 unselected participants from a neuropsychiatry memory clinic, including AD (n = 40), behavioral variant FTD (bvFTD) (n = 15), PPD (n = 69), other NDs, and controls. RESULTS: Plasma p-tau217 showed strong diagnostic performance for distinguishing AD from bvFTD (96% accuracy) and PPD (93% accuracy). NfL best distinguished all NDs from PPD, while GFAP did not bring additional value. Biomarker profiles using predefined cut-offs and age-adjusted z-scores further clarified group differences. DISCUSSION: Plasma p-tau217 and NfL have strong diagnostic utility in real-world, diagnostically complex cohorts. These findings support implementation of scalable blood-based biomarkers to improve early and accurate diagnosis in memory clinical settings. Highlights: Plasma p-tau217 was significantly elevated in AD compared to other disorders. P-tau217 distinguished AD from bvFTD with high accuracy. P-tau217 distinguished AD from PPDs with high accuracy. NfL/p-tau217 ratio and GFAP added limited diagnostic value compared to p-tau217 and NfL. Findings support blood biomarkers in younger, real-world clinical cohorts
Measuring resilience in national food systems using "food systems resilience score"
No full textAchieving Zero Hunger by 2030, a United Nations Sustainable Development Goal, requires resilient food systems capable of securely feeding billions. This article introduces the Food Systems Resilience Score (FSRS), a novel framework that adapts a proven resilience measurement approach to the context of food systems. The FSRS builds on the success of the Community Flood Resilience Measurement Tool, which has been used in over 110 communities, by applying its five capitals (natural, human, social, financial, and manufactured) and four qualities (robustness, redundancy, resourcefulness, and rapidity) framework to food systems. We define food system resilience as the capacity to ensure adequate, appropriate, and accessible food supply to all, despite various disturbances and unforeseen disruptions. The FSRS measures resilience across multiple dimensions using carefully selected existing indicators, ensuring broad applicability and comparability. Our methodology includes rigorous technical validation to ensure reliability, including optimal coverage analysis, stability checks, and sensitivity testing. By providing standardized metrics and a comprehensive assessment of food system resilience, this framework not only advances research but also equips policymakers with valuable tools for effective interventions. The FSRS enables comparative analysis between countries and temporal tracking of resilience changes, facilitating targeted strategies to build and maintain resilient national food systems. This work contributes to the global effort toward long-term food security and sustainability
The Search for Disease Modification in Parkinson’s Disease—A Review of the Literature
No full textSporadic Parkinson's Disease (PD) affects 3% of people over 65 years of age. People are living longer, thanks in large part to improvements in global health technology and health access for non-neurological diseases. Consequently, neurological diseases of senescence, such as PD, are representing an ever-increasing share of global disease burden. There is an intensifying research focus on the processes that underlie these conditions in the hope that neurological decay may be arrested at the earliest time point. The concept of neuronal death linked to ageing- neural senescence- first emerged in the 1800s. By the late 20th century, it was recognized that neurodegeneration was common to all ageing human brains, but in most cases, this process did not lead to clinical disease during life. Conditions such as PD are the result of accelerated neurodegeneration in particular brain foci. In the case of PD, degeneration of the substantia nigra pars compacta (SNpc) is especially implicated. Why neural degeneration accelerates in these particular regions remains a point of contention, though current evidence implicates a complex interplay between a vast array of neuronal cell functions, bioenergetic failure, and a dysfunctional brain immunological response. Their complexity is a considerable barrier to disease modification trials, which seek to intercept these maladaptive cell processes. This paper reviews current evidence in the domain of neurodegeneration in Parkinson's disease, focusing on alpha-synuclein accumulation and deposition and the role of oxidative stress and inflammation in progressive brain changes. Recent approaches to disease modification are discussed, including the prevention or reversal of alpha-synuclein accumulation and deposition, modification of oxidative stress, alteration of maladaptive innate immune processes and reactive cascades, and regeneration of lost neurons using stem cells and growth factors. The limitations of past research methodologies are interrogated, including the difficulty of recruiting patients in the clinically quiescent prodromal phase of sporadic Parkinson's disease. Recommendations are provided for future studies seeking to identify novel therapeutics with disease-modifying properties
Electroanalysis and electrophysiological recording of bio-doped conducting polymer-modified neural electrodes
No full textElectroanalytical methods are used to understand, modify, and control bionic devices. Bionic devices can record or stimulate cells to understand and/or control normal or abnormal biological processes. These devices contain electrodes that transduce electrical current within the electrical circuit into ionic current within a tissue. Despite the similarity between electroanalysis and electrophysiology, there remains a poor understanding of the relationship between the two techniques, including their methodology and theory. This paper investigates the electrochemical and acute electrophysiological recording performance of neural electrodes. A range of behaviors is achieved by modifying electrodes with the conducting polymer poly(3,4-ethylenedioxythiophene) (PEDOT) doped with chondroitin sulfate, dextran sulfate, or para-toluene sulfonate. The results support previous studies showing that increased electrode area reduced total impedance below the Maxwell-Wagner relaxation frequency and thermal noise while increasing the signal-to-noise ratio and neural spike count. The results allowed novel investigation of relative contributions of biological and electrode properties to electrophysiological performance, with increased electrode area having a larger impact on neural population within recording range rather than reducing thermal noise. The utility of measuring electrode impedance for predicting electrophysiological performance is mainly for an indirect measure of electrode area. The results provide insight into noise sources from electrophysiological recordings and limitations in cable theory in neuroscience
Generation smoke-free: Protective factors for never smoking among young First Nations peoples aged 10–15 years in the Next Generation Youth Wellbeing Study
No full textPurpose In Australia, smoking accounts for half of all Aboriginal and Torres Strait Islander (First Nations) deaths aged ≥45 years. Regular smoking is more common among First Nations than non-Indigenous peoples in Australia. Smoking primarily commences during adolescence and young adulthood. Preventing uptake is important for long-term health outcomes. This study aimed to identify the protective factors that support young people to be smoke-free, to inform prevention programs and strategies. Methods The ‘Next Generation Youth Wellbeing Study’ is a mixed-methods cohort study. It includes First Nations adolescents aged 10–24 years and living in urban, rural and remote communities in central Australia, Western Australia and New South Wales. This study analysed self-reported data on smoking from young people aged 10–15 years, collected during 2018–20, using Poisson regression to investigate the relation of various factors to never-smoking. Main findings Among 682 participants, 54% were female, 90% had never smoked tobacco and 79% lived in smoke-free homes. Factors independently associated with never smoking were: having friends who did not smoke (prevalence ratio [PR] 1.22, 95% confidence interval [CI] 1.15–1.30); daily school attendance (PR 1.14, 1.06–1.22), never drinking (PR 1.84, 1.38–2.46), self-reported good/excellent health (PR 1.12, 1.00–1.26), good mental health (PR 1.12, 1.04–1.20), never been questioned by police (PR 1.24, 1.14–1.34) and never interacting with the justice system (PR 1.23, 1.13–1.33), compared with participants without these exposures. There was no association between never smoking and sex, available money or physical activity. Principal conclusions Most First Nations young people had never smoked; this was related to multiple smoke-free influences, good health and wellbeing and positive social engagement and experiences. Alongside opportunities in home, school and community settings to support smoke-free behaviours, broader system-wide changes are required
COVID-19 Vaccine Boosters in People With Multiple Sclerosis Improved SARS-CoV-2 Cross-Variant Antibody Response and Prediction of Protection
No full textBACKGROUND AND OBJECTIVES: Although disease-modifying therapies (DMTs) may suppress coronavirus disease 2019 (COVID-19) vaccine responses in people with multiple sclerosis (pwMS), limited data are available on the cumulative effect of additional boosters. Maturation of Spike immunoglobulin G (IgG) to target a greater diversity of SARS-CoV-2 variants, especially past the BA.1 variant, has not been reported. In addition, the prediction of variant-specific protection, given that Spike antibody testing is not performed routinely, remains a challenge. We, therefore, evaluated whether additional vaccine doses improved the breadth of cross-variant recognition to target emerging SARS-CoV-2 variants. Machine learning-based models were designed to predict variant-specific protection status. METHODS: In a prospective observational cohort (n = 442), Spike IgG titers and live virus neutralization against D614, BA.1, BA.2, BA.5, XBB.1.1, XBB.1.5, and EG.5.1 variants were determined in 1,011 serum samples (0-12 months after 2-4 doses). Predictive protection models were developed by K-fold cross-validation on training and test data sets (random split 70:30). RESULTS: After primary vaccination, pwMS on immunosuppressive disease-modifying therapy (IMM-DMT) had 10-fold and 7.2-fold lower D614 Spike IgG titers than pwMS on low-efficacy (LE)-DMT and cladribine (p < 0.01). After 4 doses, pwMS on IMM-DMT had significantly lower Spike IgG titers, compared with pwMS on low-efficacy disease-modifying therapy, for D614 (p < 0.05), as well as BA.1, BA.2, BA.5, XBB.1, XBB.1.5, and EG.5.1(p < 0.01). The breadth of Spike IgG to recognize variants other than the cognate antigen increased after 4 doses of all DMTs. Although pwMS on IMM-DMT displayed reduced cross-variant recognition, a fourth dose resulted in a 2-4-fold increase in protection against newer variants and a reduction in two-thirds of pwMS without protective Spike IgG (p < 0.0001). Tixagevimab and cilgavimab did not induce additional cross-variant protection. Variant-specific predictive models of vaccine protection were influenced by treatment, time since primary vaccination, and age, with high sensitivity (99.4%, 95% CI 96.8-99.99) and specificity (72.0%, 95% CI 50.6-87.9) for XBB.1.5/EG.5.1 variants. DISCUSSION: Despite not eliciting adequate antibody response in pwMS on IMM-DMT, COVID-19 boosters improve the breadth of the humoral response against SARS-CoV-2 emerging variants. Vaccine protection can be predicted by statistical modeling
Global Applicability of the Kappa Distribution for Rainfall Frequency Analysis
No full textExtreme rainfall events have profound implications across various sectors, necessitating accurate modeling to assess risks and devise effective adaptation strategies. The common practice of employing three-parameter probability distributions, such as the Generalized Extreme Value (GEV) and Pearson Type III distributions, in rainfall frequency analysis often encounters limitations in capturing rare, heavy-tailed events with a lack of consensus as to which distribution is the most applicable. In this study, we explore the applicability of the four-parameter Kappa distribution (K4D) for modeling extreme daily rainfalls using annual maxima from the Global Historical Climatology Network-Daily database. Quality checks and thresholds were used to remove erroneous and poor-quality data, retaining 20,500 stations with 50 or more years of data. The variation in the second shape parameter ((Formula presented.)) was examined across regime characteristics, geospatial regions, and climate regional groupings to identify where the K4D is best able to model extreme rainfalls. Consistent with theoretical expectations, (Formula presented.) converges toward zero (i.e., toward the limiting GEV distribution) as the average number of rainfall events per year increases (here approximated by rain days). However, in arid regions with a limited number of annual storm events, we observe average values of (Formula presented.) greater than zero, with a strong regional and climatic coherence in (Formula presented.). Our results suggest that there is merit in using the K4D for modeling heavy tail behavior, particularly in regions with a small number of events per year. These findings will contribute to advancing statistical modeling techniques for extreme rainfall, benefiting hydrological modeling and risk assessments