GeNN: a code generation framework for accelerated brain simulations

Large-scale numerical simulations of detailed brain circuit models are important for identifying hypotheses on brain functions and testing their consistency and plausibility. An ongoing challenge for simulating realistic models is, however, computational speed. In this paper, we present the GeNN (GPU-enhanced Neuronal Networks) framework, which aims to facilitate the use of graphics accelerators for computational models of large-scale neuronal networks to address this challenge. GeNN is an open source library that generates code to accelerate the execution of network simulations on NVIDIA GPUs, through a flexible and extensible interface, which does not require in-depth technical knowledge from the users. We present performance benchmarks showing that 200-fold speedup compared to a single core of a CPU can be achieved for a network of one million conductance based Hodgkin-Huxley neurons but that for other models the speedup can differ. GeNN is available for Linux, Mac OS X and Windows platforms. The source code, user manual, tutorials, Wiki, in-depth example projects and all other related information can be found on the project website http://genn-team.github.io/genn/

HIGH CROSSOVER RATE1 encodes PROTEIN PHOSPHATASE X1 and restricts meiotic crossovers in Arabidopsis.

Meiotic crossovers are tightly restricted in most eukaryotes, despite an excess of initiating DNA double-strand breaks. The majority of plant crossovers are dependent on class I interfering repair, with a minority formed via the class II pathway. Class II repair is limited by anti-recombination pathways; however, similar pathways repressing class I crossovers have not been identified. Here, we performed a forward genetic screen in Arabidopsis using fluorescent crossover reporters to identify mutants with increased or decreased recombination frequency. We identified HIGH CROSSOVER RATE1 (HCR1) as repressing crossovers and encoding PROTEIN PHOSPHATASE X1. Genome-wide analysis showed that hcr1 crossovers are increased in the distal chromosome arms. MLH1 foci significantly increase in hcr1 and crossover interference decreases, demonstrating an effect on class I repair. Consistently, yeast two-hybrid and in planta assays show interaction between HCR1 and class I proteins, including HEI10, PTD, MSH5 and MLH1. We propose that HCR1 plays a major role in opposition to pro-recombination kinases to restrict crossovers in Arabidopsis.Marie Curie International Training Network COMREC European Research Council (ERC) National Research Foundation of Korea Suh Kyungbae Foundatio

Public attitudes towards automated external defibrillators: results of a survey in the Australian general population

BackgroundSwift defibrillation by lay responders using automated external defibrillators (AEDs) increases survival in out-of-hospital cardiac arrest (OHCA). This study evaluated newly designed yellow–red vs. commonly used green–white signage for AEDs and cabinets and assessed public attitudes to using AEDs during OHCA.MethodsNew yellow–red signage was designed to enable easy identification of AEDs and cabinets. A prospective, cross-sectional study of the Australian public was conducted using an electronic, anonymised questionnaire between November 2021 and June 2022. The validated net promoter score investigated public engagement with the signage. Likert scales and binary comparisons evaluated preference, comfort and likelihood of using AEDs for OHCA.ResultsThe yellow–red signage for AED and cabinet was preferred by 73.0% and 88%, respectively, over the green–white counterparts. Only 32% were uncomfortable with using AEDs, and only 19% indicated a low likelihood of using AEDs in OHCA.ConclusionThe majority of the Australian public surveyed preferred yellow–red over green–white signage for AED and cabinet and indicated comfort and likelihood of using AEDs in OHCA. Steps are necessary to standardise yellow–red signage of AED and cabinet and enable widespread availability of AEDs for public access defibrillation

Rapid synchronous type 1 IFN and virus-specific T cell responses characterize first wave non-severe SARS-CoV-2 infections

Effective control of SARS-CoV-2 infection on primary exposure may reveal correlates of protective immunity to future variants, but we lack insights into immune responses before or at the time virus is first detected. We use blood transcriptomics, multiparameter flow cytometry, and T cell receptor (TCR) sequencing spanning the time of incident non-severe infection in unvaccinated virus-naive individuals to identify rapid type 1 interferon (IFN) responses common to other acute respiratory viruses and cell proliferation responses that discriminate SARS-CoV-2 from other viruses. These peak by the time the virus is first detected and sometimes precede virus detection. Cell proliferation is most evident in CD8 T cells and associated with specific expansion of SARS-CoV-2-reactive TCRs, in contrast to virus-specific antibodies, which lag by 1–2 weeks. Our data support a protective role for early type 1 IFN and CD8 T cell responses, with implications for development of universal T cell vaccines

How do parents of children with juvenile idiopathic arthritis (JIA) perceive their therapies?

<p>Abstract</p> <p>Background</p> <p>Complementary and alternative medical (CAM) therapies are commonly used by pediatric patients with chronic medical conditions. Little is known about parents' perceptions of these therapies. This study describes the views of parents of patients with juvenile idiopathic arthritis (JIA) regarding conventional and CAM therapies.</p> <p>Methods</p> <p>Parents of children with JIA seen at a pediatric rheumatology clinic were surveyed between June 1 and July 31, 2007. Questionnaires asked about patients' use of over 75 therapies in the past 30 days, their perceived helpfulness (0 = not helpful; 3 = very helpful), perceived side effects (0 = none; 3 = severe), and whether each therapy would be recommended to other patients with JIA (Yes, No, Not sure).</p> <p>Results</p> <p>Questionnaires were returned by 52/76 (68%) parents; patients' average age was 10.9 years and 87% were Caucasian. Medications were used by 45 (88%) patients; heat (67%) and extra rest (54%) were also commonly used. CAM therapies were used by 48 (92%), e.g., massage (54%), vitamins and other supplements (54%), avoiding foods that worsened pain (35%) and stress management techniques (33%). Among the therapies rated by 3 or more parents, those that scored 2.5 or higher on helpfulness were: biologic medications, methotrexate, naproxen, wheelchairs, orthotics, heat, vitamins C and D, music, support groups and prayer. CAM therapies had 0 median side effects and parents would recommend many of them to other families.</p> <p>Conclusion</p> <p>JIA patients use diverse therapies. Parents report that many CAM therapies are helpful and would recommend them to other parents. These data can be used in counseling patients and guiding future research.</p

Large clones of pre-existing T cells drive early immunity against SARS-COV-2 and LCMV infection

T cell responses precede antibody and may provide early control of infection. We analyzed the clonal basis of this rapid response following SARS-COV-2 infection. We applied T cell receptor (TCR) sequencing to define the trajectories of individual T cell clones immediately. In SARS-COV-2 PCR+ individuals, a wave of TCRs strongly but transiently expand, frequently peaking the same week as the first positive PCR test. These expanding TCR CDR3s were enriched for sequences functionally annotated as SARS-COV-2 specific. Epitopes recognized by the expanding TCRs were highly conserved between SARS-COV-2 strains but not with circulating human coronaviruses. Many expanding CDR3s were present at high frequency in pre-pandemic repertoires. Early response TCRs specific for lymphocytic choriomeningitis virus epitopes were also found at high frequency in the preinfection naive repertoire. High-frequency naive precursors may allow the T cell response to respond rapidly during the crucial early phases of acute viral infection

Rapid synchronous type 1 IFN and virus-specific T cell responses characterize first wave non-severe SARS-CoV-2 infections

Effective control of SARS-CoV-2 infection on primary exposure may reveal correlates of protective immunity to future variants, but we lack insights into immune responses before or at the time virus is first detected. We use blood transcriptomics, multiparameter flow cytometry, and T cell receptor (TCR) sequencing spanning the time of incident non-severe infection in unvaccinated virus-naive individuals to identify rapid type 1 interferon (IFN) responses common to other acute respiratory viruses and cell proliferation responses that discriminate SARS-CoV-2 from other viruses. These peak by the time the virus is first detected and sometimes precede virus detection. Cell proliferation is most evident in CD8 T cells and associated with specific expansion of SARS-CoV-2-reactive TCRs, in contrast to virus-specific antibodies, which lag by 1–2 weeks. Our data support a protective role for early type 1 IFN and CD8 T cell responses, with implications for development of universal T cell vaccines

Large clones of pre-existing T cells drive early immunity against SARS-COV-2 and LCMV infection

T cell responses precede antibody and may provide early control of infection. We analyzed the clonal basis of this rapid response following SARS-COV-2 infection. We applied T cell receptor (TCR) sequencing to define the trajectories of individual T cell clones immediately. In SARS-COV-2 PCR+ individuals, a wave of TCRs strongly but transiently expand, frequently peaking the same week as the first positive PCR test. These expanding TCR CDR3s were enriched for sequences functionally annotated as SARS-COV-2 specific. Epitopes recognized by the expanding TCRs were highly conserved between SARS-COV-2 strains but not with circulating human coronaviruses. Many expanding CDR3s were present at high frequency in pre-pandemic repertoires. Early response TCRs specific for lymphocytic choriomeningitis virus epitopes were also found at high frequency in the preinfection naive repertoire. High-frequency naive precursors may allow the T cell response to respond rapidly during the crucial early phases of acute viral infection

Democratic population decisions result in robust policy-gradient learning: A parametric study with GPU simulations

High performance computing on the Graphics Processing Unit (GPU) is an emerging field driven by the promise of high computational power at a low cost. However, GPU programming is a non-trivial task and moreover architectural limitations raise the question of whether investing effort in this direction may be worthwhile. In this work, we use GPU programming to simulate a two-layer network of Integrate-and-Fire neurons with varying degrees of recurrent connectivity and investigate its ability to learn a simplified navigation task using a policy-gradient learning rule stemming from Reinforcement Learning. The purpose of this paper is twofold. First, we want to support the use of GPUs in the field of Computational Neuroscience. Second, using GPU computing power, we investigate the conditions under which the said architecture and learning rule demonstrate best performance. Our work indicates that networks featuring strong Mexican-Hat-shaped recurrent connections in the top layer, where decision making is governed by the formation of a stable activity bump in the neural population (a "non-democratic" mechanism), achieve mediocre learning results at best. In absence of recurrent connections, where all neurons "vote" independently ("democratic") for a decision via population vector readout, the task is generally learned better and more robustly. Our study would have been extremely difficult on a desktop computer without the use of GPU programming. We present the routines developed for this purpose and show that a speed improvement of 5x up to 42x is provided versus optimised Python code. The higher speed is achieved when we exploit the parallelism of the GPU in the search of learning parameters. This suggests that efficient GPU programming can significantly reduce the time needed for simulating networks of spiking neurons, particularly when multiple parameter configurations are investigated. © 2011 Richmond et al

Incisional hernia following colorectal cancer surgery according to suture technique: Hughes Abdominal Repair Randomized Trial (HART).

BACKGROUND: Incisional hernias cause morbidity and may require further surgery. HART (Hughes Abdominal Repair Trial) assessed the effect of an alternative suture method on the incidence of incisional hernia following colorectal cancer surgery. METHODS: A pragmatic multicentre single-blind RCT allocated patients undergoing midline incision for colorectal cancer to either Hughes closure (double far-near-near-far sutures of 1 nylon suture at 2-cm intervals along the fascia combined with conventional mass closure) or the surgeon's standard closure. The primary outcome was the incidence of incisional hernia at 1 year assessed by clinical examination. An intention-to-treat analysis was performed. RESULTS: Between August 2014 and February 2018, 802 patients were randomized to either Hughes closure (401) or the standard mass closure group (401). At 1 year after surgery, 672 patients (83.7 per cent) were included in the primary outcome analysis; 50 of 339 patients (14.8 per cent) in the Hughes group and 57 of 333 (17.1 per cent) in the standard closure group had incisional hernia (OR 0.84, 95 per cent c.i. 0.55 to 1.27; P = 0.402). At 2 years, 78 patients (28.7 per cent) in the Hughes repair group and 84 (31.8 per cent) in the standard closure group had incisional hernia (OR 0.86, 0.59 to 1.25; P = 0.429). Adverse events were similar in the two groups, apart from the rate of surgical-site infection, which was higher in the Hughes group (13.2 versus 7.7 per cent; OR 1.82, 1.14 to 2.91; P = 0.011). CONCLUSION: The incidence of incisional hernia after colorectal cancer surgery is high. There was no statistical difference in incidence between Hughes closure and mass closure at 1 or 2 years. REGISTRATION NUMBER: ISRCTN25616490 (http://www.controlled-trials.com)