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L-Sort: On-chip Spike Sorting with Efficient Median-of-Median Detection and Localization-based Clustering
Get PDFSpike sorting is a critical process for decoding large-scale neural activity from extracellular recordings. The advancement of neural probes facilitates the recording of a high number of neurons with an increase in channel counts, arising a higher data volume and challenging the current on-chip spike sorters. This paper introduces L-Sort, a novel on-chip spike sorting solution featuring median-of-median spike detection and localization-based clustering. By combining the median-of-median approximation and the proposed incremental median calculation scheme, our detection module achieves a reduction in memory consumption. Moreover, the localization-based clustering utilizes geometric features instead of morphological features, thus eliminating the memory-consuming buffer for containing the spike waveform during feature extraction. Evaluation using Neuropixels datasets demonstrates that L-Sort achieves competitive sorting accuracy with reduced hardware resource consumption. Implementations on FPGA and ASIC (180 nm technology) demonstrate significant improvements in area and power efficiency compared to state-of-the-art designs while maintaining comparable accuracy. If normalized to 22 nm technology, our design can achieve roughly x 10 area and power efficiency with similar accuracy, compared with the state-of-the-art design evaluated with the same dataset. Therefore, L-Sort is a promising solution for real-time, high-channel-count neural processing in implantable devices.</p
The secret lives of children’s money:Exploring children’s financial interactions in transitions from cash to digital monies
Get PDFThe nature of money is undergoing significant transformation, becoming more diverse, digital, data-driven and at times, less visible. Nonetheless, there is limited research addressing how children experience, and learn about contemporary forms of digital money. This presents a challenge for the banking sector, and from a Child-Computer Interaction (CCI) research perspective, as it is important to explore how children engage with and learn about money in an increasingly digitised financial landscape. This study explores children’s (aged 7-12) experiences with money using a Cultural Probes approach, inviting children to play as detectives, while also engaging their parents in semi-structured interviews. Findings reveal the ongoing importance of cash in children’s lives, while recognising the need for increasing digital interactions, highlighting key thresholds in their transition from cash to digital financial interactions. Parents particularly express concerns about fostering financial autonomy in a digital landscape, while limiting or mediating independent use of digital devices
Lossy encoding of distributions in judgment under uncertainty
Get PDFPeople often make judgments about uncertain facts and events, for example ‘Germany will win the world cup’. Judgment under uncertainty is often studied with reference to a normative ideal according to which people should make guesses that have a high probability of being correct. According to this normative ideal, you should say that Germany will win the world cup if you think that Germany is in fact likely to win. We argue that in many cases, judgment under uncertainty is instead best conceived of as an act of lossy compression, where the goal is to efficiently encode a probability distribution, rather than express the probability of a single outcome. We test formal computational models derived from our theory, showing in four experiments that they accurately predict how people make and interpret guesses. Our account naturally explains why people dislike vacuously-correct guesses (like ‘Some country will win the world cup’), and sheds light on apparently sub-optimal patterns of judgment such as the conjunction fallacy
Investigating the contribution of socio-economic position to ethnic inequalities in severe COVID-19 outcomes:population-based mediation analyses of national linked Scottish data
Get PDFWe quantified the extent to which socio-economic position (SEP) contributed to ethnic inequalities in severe COVID-19 outcomes (hospitalization or death) in Scotland. We used linked 2011 Scottish Census and health records to assess whether ethnic inequalities were mediated by different SEP measures: area deprivation, educational status, household composition, and multigenerational household. We considered disaggregated ethnicities 'White Scottish', 'White British or Irish', 'Other White', 'South Asian', 'African, Caribbean, or Black', and 'Other'. We applied marginal structural models to estimate causal pathways. Of the 3 297 205 individuals analysed, 38 213 (1.2%) had severe COVID-19 outcomes. South Asians had elevated risk of severe COVID-19 compared to White Scottish (hazard ratio: 1.7; 95% confidence interval: 1.5-1.9), while White British or Irish (hazard ratio: 0.7; confidence interval: 0.6-08) and other White (hazard ratio: 0.8; confidence interval: 0.7-0.9) had reduced risk. When holding area deprivation constant, the risk of severe COVID-19 declined by 16.5% for South Asians and 49.2% for White British or Irish; but increased for other White (75.4%). When holding education constant, the risk of severe COVID-19 reduced by 24.8% for White British or Irish and 20.6% for other White; but increased by 74.6% for South Asians. Only a slight change in risk was observed for the South Asians after holding household size and multigenerational household constant. Risk estimates for African, Caribbean or Black, and other groups were underpowered. SEP measures differed substantially in the extent to which they mediated ethnic inequalities in severe COVID-19. This highlights the necessity of addressing multiple dimensions of SEP that drive ethnic inequalities.</p
Combination of immune checkpoint inhibitors with multi-targeted tyrosine kinase inhibitors for second- or later-line therapy of non-small cell lung cancer:a systematic review and meta-analysis
Get PDFBACKGROUND: Second- or later-line therapy for patients with advanced non-small cell lung cancer (NSCLC) is highly individualized. Combining immune checkpoint inhibitors (ICIs) with multi-targeted tyrosine kinase inhibitors (multi-TKIs) has emerged as a chemotherapy-free option for these patients. We aim to provide a comprehensive overview of the efficacy and safety of the treatment.METHODS: We systematically searched four databases for studies evaluating ICIs combined with multi-TKIs in second- or later-line therapy for NSCLC. Data were extracted and study quality was assessed using the Canadian Institute of Health Economics tool for case series. A systematic review and meta-analysis were conducted for efficacy outcomes.RESULTS: Twenty studies (10 prospective and 10 retrospective) were included from 155 retrieved articles. Nineteen studies were conducted in China, with programmed death receptor 1 (PD-1) antibodies and anlotinib as the most frequently used combination. The single-arm meta-analysis showed that the pooled median progression-free survival (mPFS) was 5.74 months [95% confidence interval (CI): 4.65-6.84], and the median overall survival was 15.41 months (95% CI: 13.40-17.41). The objective response rate was 26.35% (95% CI: 19.52-33.18%), and the disease control rate was about 80.73% (95% CI: 75.59-85.86%). For patients with EGFR/ALK/ROS1 mutations, the mPFS was 3.17 months (95% CI: 2.54-3.79). The most commonly reported severe adverse events across the included studies were hypertension, fatigue, hepatic dysfunction, urinary abnormalities, and hand-foot syndrome.CONCLUSIONS: The combination of ICIs and multi-TKIs offers an alternative chemotherapy-free treatment option for patients with advanced NSCLC in the second- or later-line setting.</p
Atomistic calculation of the τ0 inverse attempt frequency in Fe 3O 4 magnetite nanoparticles
Get PDFThe Arrhenius law predicts the transition time between equilibrium states in physical systems due to thermal activation, with broad applications in material science, magnetic hyperthermia and paleomagnetism where it is used to estimate the transition time and thermal stability of assemblies of magnetic nanoparticles. Magnetite is a material of great importance in paleomagnetic studies and magnetic hyperthermia but existing estimates of the attempt frequency 0 vary by several orders of magnitude in the range 107−1013 Hz, leading to significant uncertainty in their relaxation rate. Here we present a dynamical method enabling full parameterization of the Arrhenius-N'eel law using atomistic spin dynamics. We determine the temperature and volume dependence of the attempt frequency of magnetite nanoparticles with cubic anisotropy and find a value of 0=0.562±0.059 GHz at room temperature. For particles with enhanced anisotropy we find a significant increase in the attempt frequency and a strong temperature dependence suggesting an important role of anisotropy. The method is applicable to a wide range of dynamical systems where different states can be clearly identified and enables robust estimates of domain state stabilities, with particular importance in the rapidly developing field of micromagnetic analysis of paleomagnetic recordings where samples can be numerically reconstructed to provide a better understanding of geomagnetic recording fidelity over geological time scales
Interaction does not lead to spontaneous category-based conditioning in an artificial language
Get PDFVariation is present in every language at every structural level. Though extremely complex, linguistic variation is not fully unpredictable. Previous research suggests that cognitive biases in learning favour conditioned variation: learners often make languages more predictable by eliminating variation or by conditioning it on context, pointing to the presence of biases against random variation. Learning biases favour lexical conditioning over more general category-based conditioning, though both occur in natural languages. Interaction may also contribute to shaping conditioned variation by providing a mechanism for interlocutors to develop a shared system through the coordination of individual preferences. In the present study, we investigated the role of dyadic interaction in the emergence of conditioned variation. We trained participants on an artificial language with unpredictable variation in plural marking and objects representing one or two semantic categories and had them play a communication game using the newly learned language. We hypothesised that interaction would introduce category-based conditioning, this being the simplest conditioned system in the language. Contrary to our expectations, we found no evidence of spontaneous category-based conditioning: participants either removed variation or conditioned marker use on lexical items. Further experiments are needed to explain the emergence of this common linguistic pattern.</p
Mechanosensitive PIEZO2 channels shape coronary artery development
Get PDFCoronary arteries develop under constant mechanical stress. However, the role of mechanosensitive ion channels in this process remains poorly understood. Here we show that the ion channel PIEZO2, which responds to mechanical stimuli, is expressed in specific coronary endothelial cell populations during a critical phase of coronary vasculature remodeling. These Piezo2+ coronary endothelial cells show distinct transcriptional profiles and have mechanically activated ionic currents. Strikingly, PIEZO2 loss-of-function mouse embryos and mice with human pathogenic variants of PIEZO2 show abnormal coronary vessel development and cardiac left ventricular hyperplasia. We conclude that an optimal balance of PIEZO2 channel function contributes to proper coronary vessel formation, structural integrity and remodeling, and is likely to support normal cardiac function. Our study highlights the importance of mechanical cues in cardiovascular development and suggests that defects in this mechanosensing pathway may contribute to congenital heart conditions
Gene therapy in cardiac and vascular diseases: A review of approaches to treat genetic and common cardiovascular diseases with novel gene-based therapeutics
Get PDFIn the past decade, there has been substantive progress in gene therapy across disease indications. However, despite multiple gene therapies being approved for clinical use, none have a cardiovascular indication. Several reasons for this have inhibited or delayed progress in the cardiovascular field. First, developing cardiovascular gene therapeutics represents a substantial technical challenge, particularly relating to identifying and building effective delivery systems for therapeutic cargo that will be sufficient to gain meaningful efficacy with acceptable safety for the patient. Second, for genetic disease, gene editing therapy of pathogenic variants is at a relatively early stage of development. Third, since this is a field in development, the optimal design of clinical trials of cardiovascular gene therapies is also evolving and requires expert attention. Despite this, recent and current clinical trials are charting new ground, gaining valuable new patient-focused information that provides critical new learning and bench-to-bedside iterative development that has been so successful in other disease areas. While most clinical trials currently focus on cardiac gene therapy, vascular approaches are being developed, both genetic and common. We herein review the state-of-the-art in this rapidly progressing field of study. We consider gene therapy vector design, including transcriptional control, an area of incredible opportunity through engineering biology approaches to design, build, and test bespoke transcriptional units for expression of therapeutic cargo. Achieving progress in this exciting field will require close working between all stakeholders, including academic, clinical, industry, regulatory, and patient communities. Based on current progress, there is a 10-year horizon for bringing several cardiovascular gene therapies to licensing
Genetic adaptations shaping survival, pregnancy, and life at high altitude and sea level
Get PDFAdvancements in genetic research have greatly enhanced our understanding of human adaptation to high-altitude environments through the identification of genetic markers linked to hypoxia tolerance. Our recent studies identify key genes associated with haematological and ventilatory traits in Andeans. Adaptive variation at EPAS1, encoding endothelial PAS domain protein 1, a key regulator in the hypoxia-inducible factor (HIF) pathway (the alpha subunit of HIF2), has been associated with relatively low haematocrit at high altitude, which may be linked directly or indirectly to improvements in oxygen transport and/or delivery, while PRKAA1, encoding the AMP-activated protein kinase (AMPK) alpha-1 subunit, has been linked to ventilatory responses during wakefulness that are further associated with sleep phenotypes with metabolic implications. The relevance of these genetic adaptations extends beyond adult physiology; e.g. other studies have associated an adaptive genetic signature at PRKAA1 with pregnancy outcomes in Andean populations. Understanding how adaptive genetic variations in EPAS1 and PRKAA1 contribute to hypoxia tolerance offers a foundation for investigating broader evolutionary mechanisms of high-altitude adaptation, particularly in the contexts of pregnancy and fetal development, where oxygen availability is crucial. Integrative studies that combine molecular, physiological, and evolutionary perspectives offer promise in revealing the complexities of high-altitude adaptation and its relevance to hypoxia-related health challenges in both highland and lowland populations.This article is part of the discussion meeting issue ‘Pregnancy at high altitude: the challenge of hypoxia’
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