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We performed a retrospective cohort study of patients admitted to a novel, home-based COVID Virtual Observation Unit (CVOU) from an urban, university-affiliated emergency department with ∼112,000 annual visits. Telephone-based survey questions were administered by nursing staff working with the program. Of 402 patients enrolled in the CVOU, 221 (55%) were able to be contacted during the study period; 180 (45%) agreed to participate in the telephone interview. Overall, 95% (169 out of 177) of the surveyed patients reported 8 to 10 on the likelihood to recommend CVOU and 82% (100 out of 122) rated the quality of care as 10 out of 10. Over 90% of respondents reported that all role groups (nurses, paramedics, and physicians) treated them with courtesy and respect, explained things in an understandable way, and listened to them carefully. Over 80% of respondents reported that the program kept them at home. In summary, patient experiences with this novel home-based care program were highly positive. These data help underscore the importance of patient-centeredness in home-based care, and further support the concept of these innovative care models.

Abstract Background Mechanical power is a composite variable for energy transmitted to the respiratory system over time that may better capture risk for ventilator-induced lung injury than individual ventilator management components. We sought to evaluate if mechanical ventilation management with a high mechanical power is associated with fewer ventilator-free days (VFD) in children with pediatric acute respiratory distress syndrome (PARDS). Methods Retrospective analysis of a prospective observational international cohort study. Results There were 306 children from 55 pediatric intensive care units included. High mechanical power was associated with younger age, higher oxygenation index, a comorbid condition of bronchopulmonary dysplasia, higher tidal volume, higher delta pressure (peak inspiratory pressure—positive end-expiratory pressure), and higher respiratory rate. Higher mechanical power was associated with fewer 28-day VFD after controlling for confounding variables (per 0.1 J·min−1·Kg−1 Subdistribution Hazard Ratio (SHR) 0.93 (0.87, 0.98), p = 0.013). Higher mechanical power was not associated with higher intensive care unit mortality in multivariable analysis in the entire cohort (per 0.1 J·min−1·Kg−1 OR 1.12 [0.94, 1.32], p = 0.20). But was associated with higher mortality when excluding children who died due to neurologic reasons (per 0.1 J·min−1·Kg−1 OR 1.22 [1.01, 1.46], p = 0.036). In subgroup analyses by age, the association between higher mechanical power and fewer 28-day VFD remained only in children

Summary: Background: Neuroendocrine neoplasia (NEN) incidence is rising internationally. We aimed to evaluate the epidemiology of NEN in England and examine changes in survival over time. Methods: A retrospective, population-based study using nationally representative data between 1995 and 2018 from the National Cancer Registry and Analysis Service (NCRAS) in England was conducted on 63,949 tumours. Age-standardized incidence was calculated using Office for National Statistics (ONS) data. Overall survival (OS) was calculated using the Kaplan-Meier estimator. Multivariable analysis was performed using an accelerated failure time model. Findings: Of 63,949 cases, 50.5% (32,309) were female. Age-adjusted incidence increased 3.7-fold between 1995 and 2018 from 2.35 to 8.61 per 100,000. In 2018, highest incidence occurred in lung (1.47 per 100,000), small intestine (1.46 per 100,000), pancreas (1.00 per 100,000) and appendix (0.95 per 100,000). In multivariable analysis, age, sex, morphology, stage, site and deprivation were independent predictors of survival (p

BackgroundGoblet cell adenocarcinoma (GCA) of the appendix is a rare and aggressive tumour with varying nomenclature and classification systems. This has led to heterogeneity in published data, and there is a lack of consensus on incidence, survival, and management.MethodsWe provide an overview of GCA with a comprehensive systematic review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology and a retrospective analysis of all cases recorded in the English National Cancer Registration and Analysis Service database between 1995 and 2018. The Kaplan–Meier estimator was used to calculate overall survival, and Cox proportional hazards regression was used to identify prognostic factors.ResultsThe systematic review demonstrated an incidence of 0.05–0.3 per 100,000 per year among North American registry studies. The 1-, 3-, and 5-year survival rate was 95.5%, 85.9%–87.6%, and 76.0%–80.6%, respectively. Age, stage, and grade were identified as prognostic factors for survival. Our analysis included 1,225 cases. Age-standardised incidence was 0.0335 per year in 1995 and gradually rose to 0.158 per year in 2018. The 1-, 3-, and 5-year survival rate was 90.0% [95% confidence interval (95% CI): 85.4–94.0], 76.0% (95% CI: 73.8–80.9), and 68.6% (95% CI: 65.9–72.2), respectively. On univariate Cox regression analyses, female sex, stage, and grade were associated with worse overall survival. On multivariate analysis, only stage remained a statistically significant prognostic factor.ConclusionsGCA of the appendix is rare, but incidence is increasing. We report a lower incidence and survival than North American registry studies. Higher stage was associated with decreased survival. Further prospective studies are required to establish optimal management.

Fracture toughness, rather than strength, is often the limiting factor of structural materials. Developing new base materials with improved fracture toughness often takes more than a decade. Alternatively, topological design has recently been expanded by additive manufacturing. In the present study, architected planes of internal porosity mimicking a weak interface were found capable of arresting and deflecting a propagating crack, delaying fracture. This concept was demonstrated experimentally in solid beams of polymeric 3D printed material, and in gyroid metamaterials constructed from either a brittle polymer or stainless steel. Improvements in fracture toughness ranged from 22% to 300% depending on the material. Especially with topological optimization, toughening via designed porosity provides an avenue for cost-effective and simple toughening across a range of materials.

Identifying neural substrates of behavior requires defining actions in terms that map onto brain activity. Brain and muscle activity naturally correlate via the output of motor neurons, but apart from simple movements it has been difficult to define behavior in terms of muscle contractions. By mapping the musculature of the pupal fruit fly and comprehensively imaging muscle activation at single-cell resolution, we here describe a multiphasic behavioral sequence in Drosophila. Our characterization identifies a previously undescribed behavioral phase and permits extraction of major movements by a convolutional neural network. We deconstruct movements into a syllabary of co-active muscles and identify specific syllables that are sensitive to neuromodulatory manipulations. We find that muscle activity shows considerable variability, with sequential increases in stereotypy dependent upon neuromodulation. Our work provides a platform for studying whole-animal behavior, quantifying its variability across multiple spatiotemporal scales, and analyzing its neuromodulatory regulation at cellular resolution.

Drosophila larvae are able to perform visually-guided behaviours yet the molecular and circuit mechanisms for discriminating changes in light intensity are not known. Here, the authors report that ON versus OFF discrimination results from opposing cholinergic and glutamatergic mechanisms.

Metamaterials, otherwise known as architected or programmable materials, enable designers to tailor mesoscale topology and shape to achieve unique material properties that are not present in nature. Additionally, with the recent proliferation of additive manufacturing tools across industrial sectors, the ability to readily fabricate geometrically complex metamaterials is now possible. However, in many high-performance applications involving complex multi-physics interactions, design of novel lattice metamaterials is still difficult. Design is primarily guided by human intuition or gradient optimization for simple problems. In this work, we show how machine learning guides discovery of new unit cells that are Pareto optimal for multiple competing objectives; specifically, maximizing elastic stiffness during static loading and minimizing wave speed through the metamaterial during an impact event. Additionally, we show that our artificial intelligence approach works with relatively few (3500) simulation calls.

Emergency department (ED) crowding continues to be a major challenge and has important ramifications for patient care quality. One strategy to decrease ED crowding has been to implement alternative pathways to traditional hospital admission. Through a survey-based retrospective cohort study, we aimed to assess the patient experience for those who agreed to transfer and admission to an affiliated community hospital from a large, academic center’s ED. In all, 85% of participants rated their overall experience as either great or good, 92% did not find it hard to make the decision to be transferred, and 95% found the transfer process itself to be easy.

The diversity and dense interconnectivity of cells in the nervous system present a huge challenge to understanding how brains work. Recent progress toward such understanding, however, has been fuelled by the development of techniques for selectively monitoring and manipulating the function of distinct cell types—and even individual neurons—in the brains of living animals. These sophisticated techniques are fundamentally genetic and have found their greatest application in genetic model organisms, such as the fruit fly Drosophila melanogaster. Drosophila combines genetic tractability with a compact, but cell-type rich, nervous system and has been the incubator for a variety of methods of neuronal targeting. One such method, called Split Gal4, is playing an increasingly important role in mapping neural circuits in the fly. In conjunction with functional perturbations and behavioral screens, Split Gal4 has been used to characterize circuits governing such activities as grooming, aggression, and mating. It has also been leveraged to comprehensively map and functionally characterize cells composing important brain regions, such as the central complex, lateral horn, and the mushroom body—the latter being the insect seat of learning and memory. With connectomics data emerging for both the larval and adult brains of Drosophila, Split Gal4 is also poised to play an important role in characterizing neurons of interest based on their connectivity. We summarize the history and current state of the Split Gal4 method and indicate promising areas for further development or future application.

While lattice metamaterials can achieve exceptional energy absorption by tailoring periodically distributed heterogeneous unit cells, relatively little focus has been placed on engineering heterogeneity above the unit-cell level. In this work, the energy-absorption performance of lattice metamaterials with a heterogeneous spatial layout of different unit cell architectures was studied. Such multi-morphology lattices can harness the distinct mechanical properties of different unit cells while being composed out of a single base material. A rational design approach was developed to explore the design space of these lattices, inspiring a non-intuitive design which was evaluated alongside designs based on mixture rules. Fabrication was carried out using two different base materials: 316L stainless steel and Vero White photopolymer. Results show that multi-morphology lattices can be used to achieve higher specific energy absorption than homogeneous lattice metamaterials. Additionally, it is shown that a rational design approach can inspire multi-morphology lattices which exceed rule-of-mixtures expectations.

Summary: Eclosion hormone (EH) was originally identified as a brain-derived hormone capable of inducing the behavioral sequences required for molting across insect species. However, its role in this process (called ecdysis) has since been confounded by discrepancies in the effects of genetic and cellular manipulations of EH function in Drosophila. Although knock-out of the Eh gene results in severe ecdysis-associated deficits accompanied by nearly complete larval lethality, ablation of the only neurons known to express EH (i.e. Vm neurons) is only partially lethal and surviving adults emerge, albeit abnormally. Using new tools for sensitively detecting Eh gene expression, we show that EH is more widely expressed than previously thought, both within the nervous system and in somatic tissues, including trachea. Ablating all Eh-expressing cells has effects that closely match those of Eh gene knock-out; developmentally suppressing them severely disrupts eclosion. Our results thus clarify and extend the scope of EH action.

Existing genetic methods of neuronal targeting do not routinely achieve the resolution required for mapping brain circuits. New approaches are thus necessary. Here, we introduce a method for refined neuronal targeting that can be applied iteratively. Restriction achieved at the first step can be further refined in a second step, if necessary. The method relies on first isolating neurons within a targeted group (i.e. Gal4 pattern) according to their developmental lineages, and then intersectionally limiting the number of lineages by selecting only those in which two distinct neuroblast enhancers are active. The neuroblast enhancers drive expression of split Cre recombinase fragments. These are fused to non-interacting pairs of split inteins, which ensure reconstitution of active Cre when all fragments are expressed in the same neuroblast. Active Cre renders all neuroblast-derived cells in a lineage permissive for Gal4 activity. We demonstrate how this system can facilitate neural circuit-mapping in Drosophila.

Background: Patient-centered approaches in the evaluation of patient experience are increasingly important priorities for quality improvement in health-care delivery. Our objective was to investigate common themes in patient-reported data to better understand areas for improvement in the emergency department (ED) experience. Methods: A large urban, tertiary-care ED conducted phone interviews with 2607 patients who visited the ED during 2015. Patients were asked to identify one area that would have significantly improved their visit. Transcripts were analyzed using content analysis, and the results were summarized with descriptive statistics. Results: The most commonly cited themes for improvement in the patient experience were wait time (49.4%) and communication (14.6%). Related, but more nuanced, themes emerged around the perception of ED crowding and compassionate care as additional important contributors to the patient experience. Other frequently cited factors contributing to a negative experience were the discharge process and inability to complete follow-up plan (8.0%), environmental factors (7.9%), perceived competency of providers in the evaluation or treatment (7.4%), and pain management (7.4%). Conclusions: Wait times and perceptions of ED crowding, as well as provider communication and compassionate care, are significant factors identified by patients that affect their ED experience.

Summary: The neuromodulator dopamine (DA) plays a key role in motor control, motivated behaviors, and higher-order cognitive processes. Dissecting how these DA neural networks tune the activity of local neural circuits to regulate behavior requires tools for manipulating small groups of DA neurons. To address this need, we assembled a genetic toolkit that allows for an exquisite level of control over the DA neural network in Drosophila. To further refine targeting of specific DA neurons, we also created reagents that allow for the conversion of any existing GAL4 line into Split GAL4 or GAL80 lines. We demonstrated how this toolkit can be used with recently developed computational methods to rapidly generate additional reagents for manipulating small subsets or individual DA neurons. Finally, we used the toolkit to reveal a dynamic interaction between a small subset of DA neurons and rearing conditions in a social space behavioral assay. : The rapid analysis of how dopaminergic circuits regulate behavior is limited by the genetic tools available to target and manipulate small numbers of these neurons. Xie et al. present genetic tools in Drosophila that allow rational targeting of sparse dopaminergic neuronal subsets and selective knockdown of dopamine signaling. Keywords: dopamine, genetics, behavior, neural circuits, neuromodulation, Drosophila

Introduction: Patient experience with emergency department (ED) care is an expanding area of focus, and recent literature has demonstrated strong correlation between patient experience and meeting several ED and hospital goals. The objective of this study was to perform a systematic review of existing literature to identify specific factors most commonly identified as influencing ED patient experience. Methods: A literature search was performed, and articles were included if published in peer-reviewed journals, primarily focused on ED patient experience, employed observational or interventional methodology, and were available in English. After a structured screening process, 107 publications were included for data extraction. Result: Of the 107 included publications, 51 were published before 2011, 57% were conducted by American investigators, and 12% were published in nursing journals. The most commonly identified themes included staff-patient communication, ED wait times, and staff empathy and compassion. Conclusion: The most commonly identified drivers of ED patient experience include communication, wait times, and staff empathy; however, existing literature is limited. Additional investigation is necessary to further characterize ED patient experience themes and identify interventions that effectively improve these domains.

In Drosophila, long-term memory (LTM) requires the cAMP-dependent transcription factor CREBB, expressed in the mushroom bodies (MB) and phosphorylated by PKA. To identify other kinases required for memory formation, we integrated Trojan exons encoding T2A-GAL4 into genes encoding putative kinases and selected for genes expressed in MB. These lines were screened for learning/memory deficits using UAS-RNAi knockdown based on an olfactory aversive conditioning assay. We identified a novel, conserved kinase, Meng-Po (MP, CG11221, SBK1 in human), the loss of which severely affects 3 hr memory and 24 hr LTM, but not learning. Remarkably, memory is lost upon removal of the MP protein in adult MB but restored upon its reintroduction. Overexpression of MP in MB significantly increases LTM in wild-type flies showing that MP is a limiting factor for LTM. We show that PKA phosphorylates MP and that both proteins synergize in a feedforward loop to control CREBB levels and LTM. key words: Drosophila, Mushroom bodies, SBK1, deGradFP, T2A-GAL4, MiMIC

Genetically encoded effectors are important tools for probing cellular function in living animals, but improved methods for directing their expression to specific cell types are required. Here, we introduce a simple, versatile method for achieving cell-type-specific expression of transgenes that leverages the untapped potential of “coding introns” (i.e., introns between coding exons). Our method couples the expression of a transgene to that of a native gene expressed in the cells of interest using intronically inserted “plug-and-play” cassettes (called “Trojan exons”) that carry a splice acceptor site followed by the coding sequences of T2A peptide and an effector transgene. We demonstrate the efficacy of this approach in Drosophila using lines containing suitable MiMIC (Minos-mediated integration cassette) transposons and a palette of Trojan exons capable of expressing a range of commonly used transcription factors. We also introduce an exchangeable, MiMIC-like Trojan exon construct that can be targeted to coding introns using the Crispr/Cas system.

Neural networks are typically defined by their synaptic connectivity, yet synaptic wiring diagrams often provide limited insight into network function. This is due partly to the importance of non-synaptic communication by neuromodulators, which can dynamically reconfigure circuit activity to alter its output. Here, we systematically map the patterns of neuromodulatory connectivity in a network that governs a developmentally critical behavioral sequence in Drosophila. This sequence, which mediates pupal ecdysis, is governed by the serial release of several key factors, which act both somatically as hormones and within the brain as neuromodulators. By identifying and characterizing the functions of the neuronal targets of these factors, we find that they define hierarchically organized layers of the network controlling the pupal ecdysis sequence: a modular input layer, an intermediate central pattern generating layer, and a motor output layer. Mapping neuromodulatory connections in this system thus defines the functional architecture of the network.

In this review, we intend to highlight the progress which has been made in recent years around different types of smart activation nanosystems for cancer treatment. Conventional treatment methods, such as chemotherapy or radiotherapy, suffer from a lack of specific targeting and consequent off-target effects. This has led to the development of smart nanosystems which can effect specific regional and temporal activation. In this review, we will discuss the different methodologies which have been designed to permit activation at the tumour site. These can be divided into mechanisms which take advantage of the differences between healthy cells and cancer cells to trigger activation, and those which activate by a mechanism extrinsic to the cell or tumour environment.

Copulation is the goal of the courtship process, crucial to reproductive success and evolutionary fitness. Identifying the circuitry underlying copulation is a necessary step towards understanding universal principles of circuit operation, and how circuit elements are recruited into the production of ordered action sequences. Here, we identify key sex-specific neurons that mediate copulation in Drosophila, and define a sexually dimorphic motor circuit in the male abdominal ganglion that mediates the action sequence of initiating and terminating copulation. This sexually dimorphic circuit composed of three neuronal classes – motor neurons, interneurons and mechanosensory neurons – controls the mechanics of copulation. By correlating the connectivity, function and activity of these neurons we have determined the logic for how this circuitry is coordinated to generate this male-specific behavior, and sets the stage for a circuit-level dissection of active sensing and modulation of copulatory behavior.

More research is needed, across disciplines, to better understand the important and varied roles that animals play in the lives of people in refugee camps.

Here, we report, for what we believe to be the first time, on the modification of a low cost sensor, designed for the smartphone camera market, to develop an ultraviolet (UV) camera system. This was achieved via adaptation of Raspberry Pi cameras, which are based on back-illuminated complementary metal-oxide semiconductor (CMOS) sensors, and we demonstrated the utility of these devices for applications at wavelengths as low as 310 nm, by remotely sensing power station smokestack emissions in this spectral region. Given the very low cost of these units, ≈ USD 25, they are suitable for widespread proliferation in a variety of UV imaging applications, e.g., in atmospheric science, volcanology, forensics and surface smoothness measurements.

The availability of new tools for manipulating neuronal activity, coupled with the development of increasingly sophisticated techniques for targeting these tools to subsets of cells in living, behaving animals, is permitting neuroscientists to tease apart brain circuits by a method akin to classical mutagenesis. Just as mutagenesis can be used to introduce changes into an organism’s DNA to identify the genes required for a given biological process, changes in activity can be introduced into the nervous system to identify the cells required for a given behavior. If the changes are introduced randomly, the cells can be identified without any prior knowledge of their properties. This strategy, which we refer to here as “neurotrapping,” has been implemented most effectively in Drosophila, where transgenes capable of either suppressing or stimulating neuronal activity can be reproducibly targeted to arbitrary subsets of neurons using so-called “enhancer-trap” techniques. By screening large numbers of enhancer-trap lines, experimenters have been able to identify groups of neurons which, when suppressed (or, in some cases, activated), alter a specific behavior. Parsing these groups of neurons to identify the minimal subset required for generating a behavior has proved difficult, but emerging tools that permit refined transgene targeting are increasing the resolution of the screening techniques. Some of the most recent neurotrapping screens have identified physiological substrates of behavior at the single neuron level.