Neurosurgical team acceptability of brain-computer interfaces: a two-stage international cross-sectional survey

OBJECTIVE: Invasive brain-computer interfaces (BCIs) require neurosurgical implantation, which confers a range of risks. Despite this, no studies have assessed the acceptability of invasive BCIs amongst the neurosurgical team. This study aims to establish baseline knowledge of BCIs within the neurosurgical team and identify attitudes towards different applications of invasive BCI. METHOD: A two-stage cross-sectional international survey of the neurosurgical team (neurosurgeons, anaesthetists, and operating room nurses) was conducted. Results from the first, qualitative, survey were used to guide the second stage quantitative survey, which assessed acceptability of invasive BCI applications. 5-part Likert Scales were used to collect quantitative data. Surveys were distributed internationally via social media and collaborators. RESULTS: 108 qualitative responses were collected. Themes included the promise of BCIs positively impacting disease targets, concerns regarding stability, and an overall positive emotional reaction to BCI technology. The quantitative survey generated 538 responses from 32 countries. Baseline knowledge of BCI technology was poor, with 9% claiming to have a ‘good’ or ‘expert’ knowledge of BCIs. Acceptability of invasive BCI for rehabilitative purposes was >80%. Invasive BCI for augmentation in healthy populations divided opinion. CONCLUSION: The neurosurgical team’s view of the acceptability of BCI was divided across a range of indications. Some applications (for example stroke rehabilitation) were viewed as more appropriate than other applications (such as augmentation for military use). This range in views highlights the need for stakeholder consultation on acceptable use cases along with regulation and guidance to govern initial BCI implantations if patients are to realise the potential benefits

Process analysis of the patient pathway for automated data collection: an exemplar using pituitary surgery

Introduction: Automation of routine clinical data shows promise in relieving health systems of the burden associated with manual data collection. Identifying consistent points of documentation in the electronic health record (EHR) provides salient targets to improve data entry quality. Using our pituitary surgery service as an exemplar, we aimed to demonstrate how process mapping can be used to identify reliable areas of documentation in the patient pathway to target structured data entry interventions. Materials and methods: This mixed methods study was conducted in the largest pituitary centre in the UK. Purposive snowball sampling identified frontline stakeholders for process mapping to produce a patient pathway. The final patient pathway was subsequently validated against a real-world dataset of 50 patients who underwent surgery for pituitary adenoma. Events were categorized by frequency and mapped to the patient pathway to determine critical data points. Results: Eighteen stakeholders encompassing all members of the multidisciplinary team (MDT) were consulted for process mapping. The commonest events recorded were neurosurgical ward round entries (N = 212, 14.7%), pituitary clinical nurse specialist (CNS) ward round entries (N = 88, 6.12%) and pituitary MDT treatment decisions (N = 88, 6.12%) representing critical data points. Operation notes and neurosurgical ward round entries were present for every patient. 43/44 (97.7%) had a pre-operative pituitary MDT entry, pre-operative clinic letter, a post-operative clinic letter, an admission clerking entry, a discharge summary, and a post-operative histopathology pituitary multidisciplinary (MDT) team entries. Conclusion: This is the first study to produce a validated patient pathway of patients undergoing pituitary surgery, serving as a comparison to optimise this patient pathway. We have identified salient targets for structured data entry interventions, including mandatory datapoints seen in every admission and have also identified areas to improve documentation adherence, both of which support movement towards automation

The Cynomolgus Macaque Intestinal Mycobiome Is Dominated by the Kazachstania Genus and K. pintolopesii Species

The cynomolgus macaque, Macaca fascicularis, is a non-human primate (NHP) widely used in biomedical research as its genetics, immunology and physiology are similar to those of humans. They may also be a useful model of the intestinal microbiome as their prokaryome resembles that of humans. However, beyond the prokaryome relatively little is known about other constituents of the macaque intestinal microbiome including the mycobiome. Here, we conducted a region-by-region taxonomic survey of the cynomolgus intestinal mycobiota, from duodenum to distal colon, of sixteen captive animals of differing age (from young to old). Using a high-throughput ITS1 amplicon sequencing-based approach, the cynomolgus gut mycobiome was dominated by fungi from the Ascomycota phylum. The budding yeast genus Kazachstania was most abundant, with the thermotolerant species K. pintolopesii highly prevalent, and the predominant species in both the small and large intestines. This is in marked contrast to humans, in which the intestinal mycobiota is characterised by other fungal genera including Candida and Saccharomyces, and Candida albicans. This study provides a comprehensive insight into the fungal communities present within the captive cynomolgus gut, and for the first time identifies K. pintolopesii as a candidate primate gut commensal

A synthetic model simulator for intracranial aneurysm clipping: validation of the UpSurgeOn AneurysmBox

Background and objectives: In recent decades, the rise of endovascular management of aneurysms has led to a significant decline in operative training for surgical aneurysm clipping. Simulation has the potential to bridge this gap and benchtop synthetic simulators aim to combine the best of both anatomical realism and haptic feedback. The aim of this study was to validate a synthetic benchtop simulator for aneurysm clipping (AneurysmBox, UpSurgeOn). Methods: Expert and novice surgeons from multiple neurosurgical centres were asked to clip a terminal internal carotid artery aneurysm using the AneurysmBox. Face and content validity were evaluated using Likert scales by asking experts to complete a post-task questionnaire. Construct validity was evaluated by comparing expert and novice performance using the modified Objective Structured Assessment of Technical Skills (mOSATS), developing a curriculum-derived assessment of Specific Technical Skills (STS), and measuring the forces exerted using a force-sensitive glove. Results: Ten experts and eighteen novices completed the task. Most experts agreed that the brain looked realistic (8/10), but far fewer agreed that the brain felt realistic (2/10). Half the expert participants (5/10) agreed that the aneurysm clip application task was realistic. When compared to novices, experts had a significantly higher median mOSATS (27 vs. 14.5; p < 0.01) and STS score (18 vs. 9; p < 0.01); the STS score was strongly correlated with the previously validated mOSATS score (p < 0.01). Overall, there was a trend towards experts exerting a lower median force than novices, however, these differences were not statistically significant (3.8 N vs. 4.0 N; p = 0.77). Suggested improvements for the model included reduced stiffness and the addition of cerebrospinal fluid (CSF) and arachnoid mater. Conclusion: At present, the AneurysmBox has equivocal face and content validity, and future versions may benefit from materials that allow for improved haptic feedback. Nonetheless, it has good construct validity, suggesting it is a promising adjunct to training

Characterization of patients with idiopathic normal pressure hydrocephalus using natural language processing within an electronic healthcare record system

OBJECTIVE: Idiopathic normal pressure hydrocephalus (iNPH) is an underdiagnosed, progressive, and disabling condition. Early treatment is associated with better outcomes and improved quality of life. In this paper, the authors aimed to identify features associated with patients with iNPH using natural language processing (NLP) to characterize this cohort, with the intention to later target the development of artificial intelligence–driven tools for early detection. / METHODS: The electronic health records of patients with shunt-responsive iNPH were retrospectively reviewed using an NLP algorithm. Participants were selected from a prospectively maintained single-center database of patients undergoing CSF diversion for probable iNPH (March 2008–July 2020). Analysis was conducted on preoperative health records including clinic letters, referrals, and radiology reports accessed through CogStack. Clinical features were extracted from these records as SNOMED CT (Systematized Nomenclature of Medicine Clinical Terms) concepts using a named entity recognition machine learning model. In the first phase, a base model was generated using unsupervised training on 1 million electronic health records and supervised training with 500 double-annotated documents. The model was fine-tuned to improve accuracy using 300 records from patients with iNPH double annotated by two blinded assessors. Thematic analysis of the concepts identified by the machine learning algorithm was performed, and the frequency and timing of terms were analyzed to describe this patient group. / RESULTS: In total, 293 eligible patients responsive to CSF diversion were identified. The median age at CSF diversion was 75 years, with a male predominance (69% male). The algorithm performed with a high degree of precision and recall (F1 score 0.92). Thematic analysis revealed the most frequently documented symptoms related to mobility, cognitive impairment, and falls or balance. The most frequent comorbidities were related to cardiovascular and hematological problems. / CONCLUSIONS: This model demonstrates accurate, automated recognition of iNPH features from medical records. Opportunities for translation include detecting patients with undiagnosed iNPH from primary care records, with the aim to ultimately improve outcomes for these patients through artificial intelligence–driven early detection of iNPH and prompt treatment

Local structure correlations in plastic cyclohexane-a reverse Monte Carlo study

Two solid phases of cyclohexane have been investigated over a temperature range spanning 13-266 K on a powdered, perdeuterated sample using neutron total scattering. Phase II has an ordered structure (C2/c) that forms below 186 K. Between 186 and 280 K it exists as a plastic solid-phase I (Fm3m), where the molecules are rotationally disordered about the lattice points of the face-centred cubic cell. Data-dependent atomistic configurations that represent the 'instantaneous' crystal structure have been generated from the total scattering data using reverse Monte Carlo refinement. Analysis of the local structure reveals that instantaneous distortions in phase I resemble the average structure of phase II

Animal models for COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the aetiological agent of coronavirus disease 2019 (COVID-19), an emerging respiratory infection caused by the introduction of a novel coronavirus into humans late in 2019 (frst detected in Hubei province, China). As of 18 September 2020, SARS-CoV-2 has spread to 215 countries, has infected more than 30 million people and has caused more than 950,000 deaths. As humans do not have pre-existing immunity to SARS-CoV-2, there is an urgent need to develop therapeutic agents and vaccines to mitigate the current pandemic and to prevent the re-emergence of COVID-19. In February 2020, the World Health Organization (WHO) assembled an international panel to develop animal models for COVID-19 to accelerate the testing of vaccines and therapeutic agents. Here we summarize the fndings to date and provides relevant information for preclinical testing of vaccine candidates and therapeutic agents for COVID-19.info:eu-repo/semantics/acceptedVersio

PiuA and PiaA, iron uptake lipoproteins of Streptococcus pneumoniae, elicit serotype independent antibody responses following human pneumococcal septicaemia

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