The Hunter-8 Scale Prehospital Triage Workflow for Identification of Large Vessel Occlusion and Brain Haemorrhage.

OBJECTIVE: The Hunter-8 prehospital stroke scale predicts large vessel occlusion in hyperacute ischemic stroke patients (LVO) at hospital admission. We wished to test its performance in the hands of paramedics as part of a prehospital triage algorithm. We aimed to determine (a) the proportion of patients identified by the Hunter-8 algorithm, receiving reperfusion therapies, (b) whether a call to stroke team improved this, and (c) performance for LVO detection using an expanded LVO definition. METHODS: A prehospital workflow combining pre-morbid functional status, time from symptom onset, and the Hunter-8 scale was implemented from July 2019. A telephone call to the stroke team was prompted for potential treatment candidates. Classic LVO was defined as a proximal middle cerebral artery (MCA-M1), terminal internal carotid artery, or tandem occlusion. Extended LVO added proximal MCA-M2 and basilar occlusions. RESULTS: From July 2019 to April 2021, there were 363 Hunter-8 activations, 320 analyzed: 181 (56.6%) had confirmed ischemic strokes, 13 (4.1%) transient ischemic attack, 91 (28.5%) stroke mimics, and 35 (10.9%) intracranial hemorrhage. Fifty-two patients (16.3%) received reperfusion therapies, 35 with Hunter-8 ≥ 8. The stroke doctor changed the final destination for 76 patients (23.7%), and five received reperfusion therapies. The AUCs for classic and extended LVO were 0.73 (95% CI 0.66-0.79) and 0.72 (95% CI 0.65-0.77), respectively. CONCLUSION: The Hunter-8 workflow resulted in 28.7% of confirmed ischemic stroke patients receiving reperfusion therapies, with no secondary transfers to the comprehensive stroke center. The role of communication with stroke team needs to be further explored.

Why copy others? Insights from the social learning strategies tournament.

Social learning (learning through observation or interaction with other individuals) is widespread in nature and is central to the remarkable success of humanity, yet it remains unclear why copying is profitable and how to copy most effectively. To address these questions, we organized a computer tournament in which entrants submitted strategies specifying how to use social learning and its asocial alternative (for example, trial-and-error learning) to acquire adaptive behavior in a complex environment. Most current theory predicts the emergence of mixed strategies that rely on some combination of the two types of learning. In the tournament, however, strategies that relied heavily on social learning were found to be remarkably successful, even when asocial information was no more costly than social information. Social learning proved advantageous because individuals frequently demonstrated the highest-payoff behavior in their repertoire, inadvertently filtering information for copiers. The winning strategy (discountmachine) relied nearly exclusively on social learning and weighted information according to the time since acquisition.

Sensitivity derivatives for flexible sensorimotor learning.

To learn effectively, an adaptive controller needs to know its sensitivity derivatives--the variables that quantify how system performance depends on the commands from the controller. In the case of biological sensorimotor control, no one has explained how those derivatives themselves might be learned, and some authors suggest they are not learned at all but are known innately. Here we show that this knowledge cannot be solely innate, given the adaptive flexibility of neural systems. And we show how it could be learned using forms of information transport that are available in the brain. The mechanism, which we call implicit supervision, helps explain the flexibility and speed of sensorimotor learning and our ability to cope with high-dimensional work spaces and tools.

Double-stranded RNA as a not-self alarm signal: to evade, most viruses purine-load their RNAs, but some (HTLV-1, Epstein-Barr) pyrimidine-load.

For double-stranded RNA (dsRNA) to signal the presence of foreign (non-self) nucleic acid, self-RNA-self-RNA interactions should be minimized. Indeed, self-RNAs appear to have been fine-tuned over evolutionary time by the introduction of purines in clusters in the loop regions of stem-loop structures. This adaptation should militate against the "kissing" interactions which initiate formation of dsRNA. Our analyses of virus base compositions suggest that, to avoid triggering the host cell's dsRNA surveillance mechanism, most viruses purine-load their RNAs to resemble host RNAs ("stealth" strategy). However, some GC-rich latent viruses (HTLV-1, EBV) pyrimidine-load their RNAs. It is suggested that when virus production begins, these RNAs suddenly increase in concentration and impair host mRNA function by virtue of an excess of complementary "kissing" interactions ("surprise" strategy). Remarkably, the only mRNA expressed in the most fundamental form of EBV latency (the "EBNA-1 program") is purine-loaded. This apparent stealth strategy is reinforced by a simple sequence repeat which prefers purine-rich codons. During latent infection the EBNA-1 protein may evade recognition by cytotoxic T-cells, not by virtue of containing a simple sequence amino acid repeat as has been proposed, but by virtue of the encoding mRNA being purine-loaded to prevent interactions with host RNAs of either genic or non-genic origin.