Can you trust clinical practice guidelines for laparoscopic surgery? A systematic review of clinical practice guidelines for laparoscopic surgery.

BACKGROUND: Clinical practice guidelines aim to support clinicians in providing clinical care and should be supported by evidence. There is currently no information on whether clinical practice guidelines in laparoscopic surgery are supported by evidence. METHODS: We performed a systematic review and identified clinical practice guidelines of laparoscopic surgery published in PubMed and Embase between March 2016 and February 2019. We performed an independent assessment of the strength of recommendation based on the evidence provided by the guideline authors. We used the 'Appraisal of Guidelines for Research & Evaluation II' (AGREE-II) Tool's 'rigour of development', 'clarity of presentation', and 'editorial independence' domains to assess the quality of the guidelines. We performed a mixed-effects generalised linear regression modelling. RESULTS: We retrieved 63 guidelines containing 1905 guideline statements. The median proportion of 'difference in rating' of strength of recommendation between the guideline authors and independent assessment was 33.3% (quartiles: 18.3%, 55.8%). The 'rigour of development' domain score (odds ratio 0.06; 95% confidence intervals 0.01-0.48 per unit increase in rigour score; P value = 0.0071) and whether the strength of recommendation was 'strong' by independent evaluation (odds ratio 0.09 (95% confidence intervals 0.06-0.13; P value < 0.001) were the only determinants of difference in rating between the guideline authors and independent evaluation. CONCLUSION: A considerable proportion of guideline statements in clinical practice guidelines in laparoscopic surgery are not supported by evidence. Guideline authors systematically overrated the strength of the recommendation (i.e., even when the evidence points to weak recommendation, guideline authors made strong recommendations).

Linear Summation Underlies Direction Selectivity in Drosophila.

While linear mechanisms lay the foundations of feature selectivity in many brain areas, direction selectivity in the elementary motion detector (EMD) of the fly has become a paradigm of nonlinear neuronal computation. We have bridged this divide by demonstrating that linear spatial summation can generate direction selectivity in the fruit fly Drosophila. Using linear systems analysis and two-photon imaging of a genetically encoded voltage indicator, we measure the emergence of direction-selective (DS) voltage signals in the Drosophila OFF pathway. Our study is a direct, quantitative investigation of the algorithm underlying directional signals, with the striking finding that linear spatial summation is sufficient for the emergence of direction selectivity. A linear stage of the fly EMD strongly resembles similar computations in vertebrate visual cortex, demands a reappraisal of the role of upstream nonlinearities, and implicates the voltage-to-calcium transformation in the refinement of feature selectivity in this system. VIDEO ABSTRACT.

High power and ultra-low-noise photodetector for squeezed-light enhanced gravitational wave detectors.

Current laser-interferometric gravitational wave detectors employ a self-homodyne readout scheme where a comparatively large light power (5-50 mW) is detected per photosensitive element. For best sensitivity to gravitational waves, signal levels as low as the quantum shot noise have to be measured as accurately as possible. The electronic noise of the detection circuit can produce a relevant limit to this accuracy, in particular when squeezed states of light are used to reduce the quantum noise. We present a new electronic circuit design reducing the electronic noise of the photodetection circuit in the audio band. In the application of this circuit at the gravitational-wave detector GEO 600 the shot-noise to electronic noise ratio was permanently improved by a factor of more than 4 above 1 kHz, while the dynamic range was improved by a factor of 7. The noise equivalent photocurrent of the implemented photodetector and circuit is about 5µA/Hz above 1 kHz with a maximum detectable photocurrent of 20 mA. With the new circuit, the observed squeezing level in GEO 600 increased by 0.2 dB. The new circuit also creates headroom for higher laser power and more squeezing to be observed in the future in GEO 600 and is applicable to other optics experiments.

Direction Selectivity in Drosophila Emerges from Preferred-Direction Enhancement and Null-Direction Suppression.

UNLABELLED: Across animal phyla, motion vision relies on neurons that respond preferentially to stimuli moving in one, preferred direction over the opposite, null direction. In the elementary motion detector of Drosophila, direction selectivity emerges in two neuron types, T4 and T5, but the computational algorithm underlying this selectivity remains unknown. We find that the receptive fields of both T4 and T5 exhibit spatiotemporally offset light-preferring and dark-preferring subfields, each obliquely oriented in spacetime. In a linear-nonlinear modeling framework, the spatiotemporal organization of the T5 receptive field predicts the activity of T5 in response to motion stimuli. These findings demonstrate that direction selectivity emerges from the enhancement of responses to motion in the preferred direction, as well as the suppression of responses to motion in the null direction. Thus, remarkably, T5 incorporates the essential algorithmic strategies used by the Hassenstein-Reichardt correlator and the Barlow-Levick detector. Our model for T5 also provides an algorithmic explanation for the selectivity of T5 for moving dark edges: our model captures all two- and three-point spacetime correlations relevant to motion in this stimulus class. More broadly, our findings reveal the contribution of input pathway visual processing, specifically center-surround, temporally biphasic receptive fields, to the generation of direction selectivity in T5. As the spatiotemporal receptive field of T5 in Drosophila is common to the simple cell in vertebrate visual cortex, our stimulus-response model of T5 will inform efforts in an experimentally tractable context to identify more detailed, mechanistic models of a prevalent computation. SIGNIFICANCE STATEMENT: Feature selective neurons respond preferentially to astonishingly specific stimuli, providing the neurobiological basis for perception. Direction selectivity serves as a paradigmatic model of feature selectivity that has been examined in many species. While insect elementary motion detectors have served as premiere experimental models of direction selectivity for 60 years, the central question of their underlying algorithm remains unanswered. Using in vivo two-photon imaging of intracellular calcium signals, we measure the receptive fields of the first direction-selective cells in the Drosophila visual system, and define the algorithm used to compute the direction of motion. Computational modeling of these receptive fields predicts responses to motion and reveals how this circuit efficiently captures many useful correlations intrinsic to moving dark edges.

A Class of Visual Neurons with Wide-Field Properties Is Required for Local Motion Detection.

Visual motion cues are used by many animals to guide navigation across a wide range of environments. Long-standing theoretical models have made predictions about the computations that compare light signals across space and time to detect motion. Using connectomic and physiological approaches, candidate circuits that can implement various algorithmic steps have been proposed in the Drosophila visual system. These pathways connect photoreceptors, via interneurons in the lamina and the medulla, to direction-selective cells in the lobula and lobula plate. However, the functional architecture of these circuits remains incompletely understood. Here, we use a forward genetic approach to identify the medulla neuron Tm9 as critical for motion-evoked behavioral responses. Using in vivo calcium imaging combined with genetic silencing, we place Tm9 within motion-detecting circuitry. Tm9 receives functional inputs from the lamina neurons L3 and, unexpectedly, L1 and passes information onto the direction-selective T5 neuron. Whereas the morphology of Tm9 suggested that this cell would inform circuits about local points in space, we found that the Tm9 spatial receptive field is large. Thus, this circuit informs elementary motion detectors about a wide region of the visual scene. In addition, Tm9 exhibits sustained responses that provide a tonic signal about incoming light patterns. Silencing Tm9 dramatically reduces the response amplitude of T5 neurons under a broad range of different motion conditions. Thus, our data demonstrate that sustained and wide-field signals are essential for elementary motion processing.

Cardiovascular predictors of long-term outcomes after non-traumatic subarachnoid hemorrhage.

BACKGROUND AND PURPOSE: Cardiac injury is common after subarachnoid hemorrhage (SAH) and is associated with adverse early outcomes, but long-term effects are unknown. The first aim of this study was to compare the long-term rates of death, stroke, and cardiac events in SAH survivors versus a matched population without SAH. The second aim was to quantify the effects of cardiac injury on the outcome rates. METHODS: This was a retrospective cohort study of patients with and without non-traumatic SAH. For aim #1, the predictor variable was SAH and the outcome variables were all-cause and cerebrovascular mortality, stroke, cardiac mortality, acute coronary syndrome (ACS), and heart failure (HF) admission. A multivariable Cox proportional hazards analysis was performed. For aim #2, the predictor variables were cardiac injury (elevated serum cardiac enzymes or a diagnosis code for ACS) and dysfunction (pulmonary edema on X-Ray or a diagnosis code for HF). RESULTS: Compared with 4,695 members without SAH, the 910 SAH patients had higher rates of all-cause mortality (hazard ratio [HR 2.6], 95% confidence intervals [CI] 2.0-3.4), cerebrovascular mortality (HR 30.6, CI 13.5-69.4), and stroke (HR 10.2, CI 7.5-13.8). Compared with the non-SAH group, the SAH patients with cardiac injury had increased rates of all-cause mortality (HR 5.3, CI 3.0-9.3), cardiac mortality (HR 7.3, CI 1.7-31.6), and heart failure (HR 4.3, CI 1.53-11.88). CONCLUSIONS: SAH survivors have increased long-term mortality and stroke rates compared with a matched non-SAH population. SAH-induced cardiac injury is associated with an increased risk of death and heart failure hospitalization.

Diversity and wiring variability of olfactory local interneurons in the Drosophila antennal lobe.

Local interneurons are essential in information processing by neural circuits. Here we present a comprehensive genetic, anatomical and electrophysiological analysis of local interneurons (LNs) in the Drosophila melanogaster antennal lobe, the first olfactory processing center in the brain. We found LNs to be diverse in their neurotransmitter profiles, connectivity and physiological properties. Analysis of >1,500 individual LNs revealed principal morphological classes characterized by coarsely stereotyped glomerular innervation patterns. Some of these morphological classes showed distinct physiological properties. However, the finer-scale connectivity of an individual LN varied considerably across brains, and there was notable physiological variability within each morphological or genetic class. Finally, LN innervation required interaction with olfactory receptor neurons during development, and some individual variability also likely reflected LN-LN interactions. Our results reveal an unexpected degree of complexity and individual variation in an invertebrate neural circuit, a result that creates challenges for solving the Drosophila connectome.

Primate errors in transitive 'inference': a two-tier learning model.

Transitive performance (TP) is a learning-based behaviour exhibited by a wide range of species, where if a subject has been taught to prefer A when presented with the pair AB but to prefer B when presented with the pair BC, then the subject will also prefer A when presented with the novel pair AC. Most explanations of TP assume that subjects recognize and learn an underlying sequence from observing the training pairs. However, data from squirrel monkeys (Saimiri sciureus) and young children contradict this, showing that when three different items (a triad) are drawn from the sequence, subjects' performance degrades systematically (McGonigle and Chalmers, Nature 267:694-696, 1977; Chalmers and McGonigle, Journal of Experimental Child Psychology 37:355-377, 1984; Harris and McGonigle, The Quarterly Journal of Experimental Psychology 47B:319-348, 1994). We present here the two-tier model, the first learning model of TP which accounts for this systematic performance degradation. Our model assumes primate TP is based on a general-purpose task learning system rather than a special-purpose sequence-learning system. It supports the hypothesis of Heckers et al. (Hippocampus 14:153-162, 2004) that TP is an expression of two separate general learning elements: one for associating actions and contexts, another for prioritising associations when more than one context is present. The two-tier model also provides explanations for why phased training is important for helping subjects learn the initial training pairs and why some subjects fail to do so. It also supports the Harris and McGonigle (The Quarterly Journal of Experimental Psychology 47B:319-348, 1994) explanation of why, once the training pairs have been acquired, subjects perform transitive choice automatically on two-item diads, but not when exposed to triads from the same sequence.