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Feasibility and acceptability of a contextualized brief psychological intervention for people with bipolar disorder in rural Ethiopia
Get PDF“They treat us like rabid dogs”: Stigma and discrimination as experienced by people living with psychosis and their caregivers in Malawi—A photovoice study
Get PDFProgrammes for people who are homeless and have severe mental illness in low-income and middle-income countries: a systematic review
Get PDFPre-training, personalization, and self-calibration:all a neural network-based myoelectric decoder needs
Get PDFMyoelectric control systems translate electromyographic signals (EMG) from muscles into movement intentions, allowing control over various interfaces, such as prosthetics, wearable devices, and robotics. However, a major challenge lies in enhancing the system's ability to generalize, personalize, and adapt to the high variability of EMG signals. Artificial intelligence, particularly neural networks, has shown promising decoding performance when applied to large datasets. However, highly parameterized deep neural networks usually require extensive user-specific data with ground truth labels to learn individual unique EMG patterns. However, the characteristics of the EMG signal can change significantly over time, even for the same user, leading to performance degradation during extended use. In this work, we propose an innovative three-stage neural network training scheme designed to progressively develop an adaptive workflow, improving and maintaining the network performance on 28 subjects over 2 days. Experiments demonstrate the importance and necessity of each stage in the proposed framework.</p
Light-Mediated Tandem Giese/C–H Functionalizations Toward Cyclopenta[b]indoles
Get PDFAn efficient method for forming cyclopenta[b]indoles directly from 3-indole-α-ketoacids via tandem Giese/C–H functionalization has been developed. The use of photoactive 3-indole-α-ketoacids as radical precursors allows for the mild tandem radical reaction to be enabled by visible light without the need for any metals, photocatalysts, or base.</p
Modular and Interoperable Workflows for Benchmarking Alchemical Binding Free Energy Calculation Methodologies
Get PDFAlchemical free energy methods are gaining traction in computer-aided drug discovery. An expanding array of methodologies is available for the setup, execution, and analysis of relative binding free energy (RBFE) calculations. However, the sharing of algorithms and protocols developed by different organizations is often impeded by incompatible software and outdated file formats. In this work, we leveraged the BioSimSpace framework to build modular and interoperable RBFE workflows. We assessed the performance of various setup, simulation, and analysis tools developed by the community on a benchmark set of six protein–ligand congeneric series, providing recommendations on best practices for the reliable application of RBFE methods in drug discovery
Universally composable SNARKs with transparent setup without programmable random oracle
Get PDFNon-interactive zero-knowledge (NIZK) proofs enable a prover to convince a verifier of an NP statement’s validity using a single message, without disclosing any additional information. These proofs are widely studied and deployed, especially in their succinct form, where proof length is sublinear in the size of the NP relation. However, efficient succinct NIZKs typically require an idealized setup, such as a common reference string, which complicates real-world deployment. A key challenge is developing NIZKs with simpler, more transparent setups. A promising approach is the random-oracle (RO) methodology, which idealizes hash functions as public random functions. It is commonly believed that UC NIZKs cannot be realized using a non-programmable global RO—the simplest incarnation of the RO as a form of setup—since existing techniques depend on the ability to program the oracle. We challenge this belief and present a methodology to build UC-secure NIZKs based solely on a global, non-programmable RO. By applying our framework we are able to construct a NIZK that achieves witness-succinct proofs of logarithmic size, breaking both the programmability barrier and polylogarithmic proof size limitations for UC-secure NIZKs with transparent setups. We further observe that among existing global RO formalizations put forth by Camenisch et al. (Eurocrypt 2018), our choice of setup is necessary to achieve this result. From the technical standpoint, our contributions span both modeling and construction. We leverage the shielded (super-poly) oracle model introduced by Broadnax et al. (Eurocrypt 2017) to define a UC NIZK functionality that can serve as a drop-in replacement for its standard variant—it preserves the usual soundness and zero-knowledge properties while ensuring its compositional guarantees remain intact. To instantiate this functionality under a non-programmable RO setup, we follow the framework of Ganesh et al. (Eurocrypt 2023) and provide new building blocks for it, around which are some of our core technical contributions: a novel polynomial encoding technique and the leakage analysis of its companion polynomial commitment, based on Bulletproofs-style folding. We also provide a second construction, based on a recent work by Chiesa and Fenzi (TCC 2024), and show that it achieves a slightly weaker version of the NIZK functionality.</p
A methylome-wide association study of major depression with out-of-sample case-control classification and trans-ancestry comparison
Get PDFMajor depression (MD) is a leading cause of global disease burden, and both experimental and population-based studies suggest that differences in DNA methylation may be associated with the condition. However, previous DNA methylation studies have, so far, not been widely replicated, suggesting a need for larger meta-analysis studies. Here we conducted a meta-analysis of methylome-wide association analysis for lifetime MD across 18 studies of 24,754 European-ancestry participants (5,443 MD cases) and an East Asian sample (243 cases, 1,846 controls). We identified 15 CpG sites associated with lifetime MD with methylome-wide significance. The methylation score created using the methylome-wide association analysis summary statistics was significantly associated with MD status in an out-of-sample classification analysis (area under the curve 0.53). Methylation score was also associated with five inflammatory markers, with the strongest association found with tumor necrosis factor beta. Mendelian randomization analysis revealed 23 CpG sites potentially causally linked to MD, with 7 replicated in an independent dataset. Our study provides evidence that variations in DNA methylation are associated with MD, and further evidence supporting involvement of the immune system.</p
Le$bean or lesbian? A survey of marginalised users' motivations for obfuscation on TikTok
Get PDFMany TikTok users report the censorship of ‘sensitive’ content by ‘the algorithm’; this is particularly true of marginalised users. In order to evade perceived censorship, users employ a range of linguistic techniques to obfuscate – hide – their intended meaning. This has received significant media attention, and we complement this by conducting a survey to establish users' motivations for employing these techniques. Our work is informed by linguistic scholarship on self-censorship, anti-languages and platform vernaculars. We conducted a novel survey of 627 UK TikTok users across 2023–2024 (female = 377, male = 224, other = 26) and found that use of obfuscation was relatively low in our sample, and primarily related to the types of content users were posting (historically censored content), rather than acting as a way to establish social identity as we had predicted – though our sample was far from homogeneous on this point. Through a structural equation modelling (SEM) analysis we show that men and people of colour (POC) were significantly more likely to use obfuscation. For POC this is driven partly by positive associations with obfuscation use, suggesting it is seen as a way to be playful with language, as well as evade ‘the algorithm’
Identifying the optimal time point for adaptive re-planning in prostate cancer radiotherapy to minimise rectal toxicity using normal tissue imaging biomarkers
Get PDFBackground and Purpose Adaptive radiotherapy (ART) in prostate cancer (PCa), although not yet standard practice, is typically triggered by inter-fractional anatomical changes that emerge progressively during treatment. This study investigates whether radiomics extracted before and during treatment can identify the optimal time point for re-planning, with the goal of reducing late rectal bleeding. Materials and Methods This study included 187 PCa patients from the single-centre, prospectively collected VoxTox dataset (UK-CRN-ID-13716), treated with image-guided radiotherapy using TomoTherapy and daily MVCT. Patients received either 74 Gy in 37 fractions (N = 110) or 60 Gy in 20 fractions (N = 77). Radiomic features were extracted from pre-treatment planning CTs and daily MVCTs. Grade ≥ 1 rectal bleeding was assessed at 2 years post-treatment using CTCAE v4.03. Two analysis strategies were employed: a separate analysis, where weekly features were evaluated independently; and a cumulative analysis, which progressively incorporated features from previous weeks. Logistic regression models with elastic net penalty were trained and evaluated using AUC.In both groups, week 1 provided the highest standalone predictive performance (test AUC = 0.766 for 74 Gy; 0.734 for 60 Gy). In the cumulative analysis, week 3 was optimal for the 74 Gy group (test AUC = 0.767), balancing performance and timing. For the 60 Gy group, week 1 remained optimal but suffered from reduced generalisability (test AUC = 0.643).Conclusions Radiomic analysis of daily imaging can support early, proactive ART in PCa, offering a personalised strategy to reduce late rectal bleeding beyond conventional anatomy-based approaches
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