A Rare Case of COVID Encephalitis in a Vaccinated Patient

Background and Purpose: SARS-CoV-2 infection is known to cause primarily respiratory symptoms, however, neurological disorders such as anosmia and stroke have been seen. Encephalitis is a rare complication of COVID-19 with a reported incidence of less than 1%¹. Most patients develop both COVID-19 symptoms and encephalitis symptoms during the same period¹. In addition, the majority of reports are from patients with no prior vaccination. Here, we present a case of encephalitis 2 weeks after mild COVID-19 in a fully vaccinated male. Case Presentation: A 68-year-old Hispanic male was brought to the ED due to new onset gaze deviation, generalized tonic posturing, facial drooping, and unresponsiveness. Days prior to his symptoms, family members reported he was found staring blankly, confused, disoriented, and experienced multiple falls. The patient had a positive COVID-19 PCR exam 2 weeks prior to developing the symptoms, despite completing two doses of the Moderna vaccine 6 months prior. His sole symptom at the time was a cough. At admission, SARS-CoV-2 PCR was negative. NIHSS was 15. He was intubated and CT head was negative for active bleeding. tPA was administered for suspected ischemic stroke, however brain perfusion CT and MRI ruled out large vessel occlusion. He was started on Levetiracetam for seizures; 6 days later, Valproate was added. He remained intubated due to an altered state of mind, airway protection, and continuous seizure activity. 24-hour cEEG showed: slower background with multiple sedating agents on. CSF analysis showed elevated: protein (73), glucose (116) and pleocytosis (WBC = 26; of which 87% lymphocytes); Panel was: negative for infectious encephalitis (e.g. CMV, HSV, N. Meningitidis, VZV, Cryptococcus), Anti-NMDA receptor Ab, Anti-LGI1 Ab. Serologies were negative for ANCA, ANA, dsDNA and Anti-Proteinase-3 Ab. Post-COVID encephalitis was suspected and plasmapheresis exchange (PLEX) therapy was started. He completed five treatments of PLEX with marked improvement after therapy. Given the significant clinical improvement, he was successfully extubated. Patient’s neurological status progressively improved, reaching closer to his baseline status. He was transferred to the medical floor and eventually to acute rehab. Conclusion: Post COVID-19 encephalitis should be in the differential for patients with new onset altered mental status (AMS) and prior history of recent SARS-CoV-2 infection. Patients presenting with encephalitis should be tested and questioned for COVID diagnosis, even in those fully vaccinated. The length of stay may be reduced with treatments targeted towards COVID encephalitis and shorter delay in presentation to treatment2. Though a COVID CSF PCR was not done in this case, to date, there are no definitive reports of SARS-CoV-2 detection in CSF3. Additionally, this case supports the use of PLEX therapy, as there are multiple other options that are still being studied for the limited cases reported

High-throughput analysis of tissue microarrays using automated desorption electrospray ionization mass spectrometry

Tissue microarrays (TMAs) are commonly used for the rapid analysis of large numbers of tissue samples, often in morphological assessments but increasingly in spectroscopic analysis, where specific molecular markers are targeted via immunostaining. Here we report the use of an automated high-throughput system based on desorption electrospray ionization (DESI) mass spectrometry (MS) for the rapid generation and online analysis of high-density (6144 samples/array) TMAs, at rates better than 1 sample/second. Direct open-air analysis of tissue samples (hundreds of nanograms) not subjected to prior preparation, plus the ability to provide molecular characterization by tandem mass spectrometry (MS/MS), make this experiment versatile and applicable to both targeted and untargeted analysis in a label-free manner. These capabilities are demonstrated in a proof-of-concept study of frozen brain tissue biopsies where we showcase (i) a targeted MS/MS application aimed at identification of isocitrate dehydrogenase mutation in glioma samples and (ii) an untargeted MS tissue type classification using lipid profiles and correlation with tumor cell percentage estimates from histopathology. The small sample sizes and large sample numbers accessible with this methodology make for a powerful analytical system that facilitates the identification of molecular markers for later use in intraoperative applications to guide precision surgeries and ultimately improve patient outcomes

5G-CLARITY: 5G-Advanced Private Networks Integrating 5GNR, WiFi, and LiFi

The future of the manufacturing industry highly depends on digital systems that transform existing production and monitoring systems into autonomous systems fulfilling stringent requirements in terms of availability, reliability, security, low latency, and positioning with high accuracy. In order to meet such requirements, private 5G networks are considered as a key enabling technology. In this article, we introduce the 5G-CLARITY system that integrates 5GNR, WiFi, and LiFi access networks, and develops novel management enablers to operate 5G-Advanced private networks. We describe three core features of 5G-CLARITY, including a multi-connectivity framework, a high-precision positioning server, and a management system to orchestrate private network slices. These features are evaluated by means of packet-level simulations and an experimental testbed demonstrating the ability of 5G-CLARITY to police access network traffic, to achieve centimeter-level positioning accuracy, and to provision private network slices in less than one minuteThis work is supported by the European Commission’s Horizon 2020 research and innovation program under grant agreement No 871428, 5G-CLARITY project

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

A Comparison of Evolutionary Computation Techniques for IIR Model Identification

System identification is a complex optimization problem which has recently attracted the attention in the field of science and engineering. In particular, the use of infinite impulse response (IIR) models for identification is preferred over their equivalent FIR (finite impulse response) models since the former yield more accurate models of physical plants for real world applications. However, IIR structures tend to produce multimodal error surfaces whose cost functions are significantly difficult to minimize. Evolutionary computation techniques (ECT) are used to estimate the solution to complex optimization problems. They are often designed to meet the requirements of particular problems because no single optimization algorithm can solve all problems competitively. Therefore, when new algorithms are proposed, their relative efficacies must be appropriately evaluated. Several comparisons among ECT have been reported in the literature. Nevertheless, they suffer from one limitation: their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments. This study presents the comparison of various evolutionary computation optimization techniques applied to IIR model identification. Results over several models are presented and statistically validated

An Improved Crow Search Algorithm Applied to Energy Problems

The efficient use of energy in electrical systems has become a relevant topic due to its environmental impact. Parameter identification in induction motors and capacitor allocation in distribution networks are two representative problems that have strong implications in the massive use of energy. From an optimization perspective, both problems are considered extremely complex due to their non-linearity, discontinuity, and high multi-modality. These characteristics make difficult to solve them by using standard optimization techniques. On the other hand, metaheuristic methods have been widely used as alternative optimization algorithms to solve complex engineering problems. The Crow Search Algorithm (CSA) is a recent metaheuristic method based on the intelligent group behavior of crows. Although CSA presents interesting characteristics, its search strategy presents great difficulties when it faces high multi-modal formulations. In this paper, an improved version of the CSA method is presented to solve complex optimization problems of energy. In the new algorithm, two features of the original CSA are modified: (I) the awareness probability (AP) and (II) the random perturbation. With such adaptations, the new approach preserves solution diversity and improves the convergence to difficult high multi-modal optima. In order to evaluate its performance, the proposed algorithm has been tested in a set of four optimization problems which involve induction motors and distribution networks. The results demonstrate the high performance of the proposed method when it is compared with other popular approaches

Andean roots and tubers crops as sources of functional foods

8 páginas.--5 figuras.-- 1 tabla.--129 referencias.-- Appendix A. Supplementary material to this article in https://doi.org/10.1016/j.jff.2018.10.007There are many valuable plant species improved by ancient cultures and cultivated locally but of very limited expansion worldwide. Some are considered neglected and underutilized species, such as the root and tuber crops from the Andes. They constitute traditional energy sources basic for the food security in the region but they also are great source of functional foods and there is a traditional associated knowledge on their properties. In this review, we focus on a few species (ahipa, arracacha, mashua, yacon) evaluated in the LATINCROP project which gathered information regarding their conservation status, cultivation practices and traditional uses and to promote new culinary uses. At the same time, this review covers the latest studies on their nutritional components and functional properties which may increase the public awareness to promote their adoption. It provides a view on the available facts and considers what is still to be doneThis work was funded by the FP7 from the European Union (Latincrop, FP7/2007-2013/ under grant agreement n° 613692).Peer reviewe

Assessing the Nutritional Value of Root and Tuber Crops from Bolivia and Peru

14 páginas.- 1 figura.- 9 tablas.- 71 referencias.- Suplementary material in https://www.mdpi.com/2304-8158/8/11/526#supplementaryAll over the world, there are species which may be considered as neglected or underutilized despite their nutritious properties. At present, such crops contribute to food security in isolated areas by providing energy and nutrients in a diversified diet. Such genetic heritage—improved by ancient cultures—is under threat of losing biodiversity as well as the traditional knowledge associated with their cultivation and usage. Among these species, the Andean root and tuber crops (ARTCs) constitute a valuable resource which should be preserved and popularized because of their food and functional properties. We studied three ARTC species (mashua, arracacha, and yacon) to provide data on their composition, essential for increasing their use globally. We compared their nutritional values with the values of more widely used crops. Important differences in nutrient composition among ARTC landraces were found. Mineral nutrients showed significant differences among species. Considerable variations in the contents of prebiotics like fructooligosaccharides or functional elements (antioxidants and glucosinolates) were found among species and intraspecific samples. Certainly, these species are important assets to complement human nutrition and to secure supply of functional elements for healthy dietsThis work was funded by the FP7 from the European Union (Latincrop, FP7/2007-2013/under grant agreement N◦ 613692).Peer reviewe

Three-Dimensionally Printed Surgical Simulation Tool for Brain Mapping Training and Preoperative Planning

Brain mapping is the most reliable intraoperative tool for identifying surrounding functional cortical and subcortical brain parenchyma. Brain mapping procedures are nuanced and require a multidisciplinary team and a well-trained neurosurgeon. Current training methodology involves real-time observation and operation, without widely available surgical simulation. To develop a patient-specific, anatomically accurate, and electrically responsive biomimetic 3D-printed model for simulating brain mapping. Imaging data were converted into a 2-piece inverse 3D-rendered polyvinyl acetate shell forming an anatomically accurate brain mold. Functional and diffusion tensor imaging data were used to guide wire placement to approximate the projection fibers from the arm and leg areas in the motor homunculus. Electrical parameters were generated, and data were collected and processed to differentiate between the 2 tracts. For validation, the relationship between the electrical signal and the distance between the probe and the tract was quantified. Neurosurgeons and trainees were interviewed to assess the validity of the model. Material testing of the brain component showed an elasticity modulus of 55 kPa (compared to 140 kPa of cadaveric brain), closely resembling the tactile feedback a live brain. The simulator's electrical properties approximated that of a live brain with a voltage-to-distance correlation coefficient of r2 = 0.86. Following 32 neurosurgeon interviews, ∼96% considered the model to be useful for training. The realistic neural properties of the simulator greatly improve representation of a live surgical environment. This proof-of-concept model can be further developed to contain more complicated tractography, blood and cerebrospinal fluid circulation, and more in-depth feedback mechanisms